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NASA NTRS1999

Horizontal vestibuloocular reflex evoked by high-acceleration rotations in the squirrel monkey. I. Normal responses

The horizontal angular vestibuloocular reflex (VOR) evoked by high-frequency, high-acceleration rotations was studied in five squirrel monkeys with intact vestibular function. The VOR evoked by steps of acceleration in darkness (3,000 degrees /s(2) reaching a velocity of 150 degrees /s) began after a latency of 7.3 +/- 1.5 ms (mean +/- SD). Gain of the reflex during the acceleration was 14.2 +/- 5.2% greater than that measured once the plateau head velocity had been reached. A polynomial regression was used to analyze the trajectory of the responses to steps of acceleration. A better representation of the data was obtained from a polynomial that included a cubic term in contrast to an exclusively linear fit. For sinusoidal rotations of 0.5-15 Hz with a peak velocity of 20 degrees /s, the VOR gain measured 0.83 +/- 0.06 and did not vary across frequencies or animals. The phase of these responses was close to compensatory except at 15 Hz where a lag of 5.0 +/- 0.9 degrees was noted. The VOR gain did not vary with head velocity at 0.5 Hz but increased with velocity for rotations at frequencies of >/=4 Hz (0. 85 +/- 0.04 at 4 Hz, 20 degrees /s; 1.01 +/- 0.05 at 100 degrees /s, P < 0.0001). No responses to these rotations were noted in two animals that had undergone bilateral labyrinthectomy indicating that inertia of the eye had a negligible effect for these stimuli. We developed a mathematical model of VOR dynamics to account for these findings. The inputs to the reflex come from linear and nonlinear pathways. The linear pathway is responsible for the constant gain across frequencies at peak head velocity of 20 degrees /s and also for the phase lag at higher frequencies being less than that expected based on the reflex delay. The frequency- and velocity-dependent nonlinearity in VOR gain is accounted for by the dynamics of the nonlinear pathway. A transfer function that increases the gain of this pathway with frequency and a term related to the third power of head velocity are used to represent the dynamics of this pathway. This model accounts for the experimental findings and provides a method for interpreting responses to these stimuli after vestibular lesions.

NASA Program Biomedical Research and Countermeasur↗

DOE OSTI2025

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER↗

NASA NTRS2018

On the 2018 Outburst of the Accreting Millisecond X-Ray Pulsar Swift J1756.9-2508 As Seen with NICER

We report on the coherent timing analysis of the 182 Hz accreting millisecond X-ray pulsar SwiftJ1756.92508during its 2018 outburst as observed with the Neutron Star Interior Composition Explorer (NICER). Combiningour NICER observations with Rossi X-ray Timing Explorer observations of the 2007 and 2009 outbursts, we alsostudied the long-term spin and orbital evolution of this source. We find that the binary system is well describedby a constant orbital period model, with an upper limit on the orbital period derivative of Pb < 7.4 Â´ 10-13 ss1.Additionally, we improve upon the source coordinates through astrometric analysis of the pulse arrival times,finding R.A.=17h56m57 18Â±0 08 and decl.=25Â°0627 8Â±3 5, while simultaneously measuring thelong-term spin frequency derivative as n = -7.3 Â´ 10-16 Hzs1. We briefly discuss the implications of thesemeasurements in the context of the wider population of accreting millisecond pulsars. We reported on the coherent timing analysis of the 2018 outburst of Swift J1756 as observed with NICER. Consistent with analyses of the previous outbursts (Krimm et al. 2007b; Patruno et al. 2010), we find that the X-ray pulsations have energy dependent amplitudes; the fractional amplitude of the fundamental increases with energy, whereas the fractional amplitude of the harmonic shows a slight decline with energy. This energy dependent behavior is not unusual in AMXPs (Patruno & Watts 2012) and can be interpreted in terms of the thermal emission from the stellar hotspot and reprocessing in the accretion column (e.g., Gierliński et al. 2002; Ibragimov & Poutanen 2009). The pulse arrival times of the 2018 outburst are well described by a timing model consisting of a circular orbit with a constant spin frequency. The pulse phases with respect to this model do not show spurious residuals with time or orbital phase, and no evidence is found that the pulse arrival times exhibit an additional delay associated with passing through the gravitational well of the companion star (Shapiro delay). We note, however, that the expected Shapiro delay is given as (Shapiro et al. 1971) Equation (5) where Φ is the orbital phase, G is the gravitational constant, c is the speed of light, and i is the inclination. Even for the maximum allowed companion mass, ${M}_{C}=0.030\,{M}_{\odot }$ (Krimm et al. 2007b, but see Section 4.2 for more details) and an inclination of 90°, the largest delay we can expect is only 4 μs. As this time-delay is smaller than the uncertainty on our phase residuals by nearly two orders of magnitude (see Figure 1), we are not sensitive to Shapiro delays in Swift J1756. Comparing our measurements for the 2018 outburst with those of the 2007 and 2009 outbursts as observed with RXTE, we analyzed the long-term evolution of this source. We found that the binary system is consistent with having a constant orbital period and that the pulsar shows a spin frequency derivative of $\dot{\nu }=-7.3\times {10}^{-16}\,\mathrm{Hz}\,{{\rm{s}}}^{-1}$. 4.1. Spin-down Evolution The long-term spin frequency derivative measured in Swift J1756 is of the same order as the spin frequency derivatives measured in other AMXPs (Hartman et al. 2008; Patruno 2010; Riggio et al. 2011). This frequency change is most likely driven by the neutron star's loss of rotational energy. If so, then the spin-down luminosity is given as Equation (6) where I represents the neutron star moment of inertia. The long-term spin-down of a neutron star is usually assumed to be dominated by the braking torque associated with a spinning magnetic field. Assuming this mechanism is responsible for the observed spin-down in Swift J1756, we can compute the magnetic dipole moment as (Spitkovsky 2006) Equation (7) where α is the misalignment angle between the rotational and magnetic poles. Considering α = 0°–90°, we then find a magnetic field strength of $B\simeq (4\mbox{--}6)\times {10}^{8}$ G at the stellar magnetic poles. This magnetic field strength estimate is in line with those obtained for other accreting millisecond pulsars (see Mukherjee et al. 2015 and references therein). 4.2. Orbit Evolution The observed long-term binary evolution of Swift J1756 is consistent with this source having a constant orbital period and a lower limit on the evolutionary timescale of Equation (8) Binary evolution theory predicts that systems of this type evolve due to angular momentum loss through gravitational radiation (Kraft et al. 1962; Rappaport et al. 1982; Verbunt 1993). For conservative mass transfer, the binary period derivative is given by di Salvo et al. (2008), Equation (9) where MNS is the neutron star mass, $q={M}_{C}/{M}_{\mathrm{NS}}$ is the binary mass ratio, and −1/3 < n < 1 is the mass–radius index of the companion star. Depending on the source inclination, Krimm et al. (2007b) derived a companion mass of ${M}_{C}\,=0.007\mbox{--}0.022\,{M}_{\odot }$ for a neutron star mass of 1.4 ${M}_{\odot }$. For a neutron star mass of 2.2 ${M}_{\odot }$, the allowed range increased to ${M}_{C}=0.009\mbox{--}0.030\,{M}_{\odot }$. In both cases, they assumed an upper limit on the inclination of i < 85°, motivated by the fact that Swift J1756 does not show eclipses in its light curve. Accounting for the extreme cases of stellar masses and n, the binary may either be contracting or expanding. In either case, however, the rate of change is limited to $| {\dot{P}}_{b}| \lesssim 7\times {10}^{-14}$ s s−1, which is well below the upper limit obtained in this work. Although the binary evolution timescale we obtain for Swift J1756 is consistent with theory, it is worth noting that this is not generally true for low-mass X-ray binaries (see Patruno et al. 2017, for a comprehensive discussion). The AMXP SAX J1808.4–3658, in particular, has been found to evolve on a much shorter timescale, with a first derivative on the orbital period of $3.5\times {10}^{-12}$ s s−1 (Hartman et al. 2008; Patruno et al. 2012; Sanna et al. 2017a). Two models have been proposed to explain this discrepancy: highly nonconservative mass transfer due to irradiation of the companion star by the pulsar (di Salvo et al. 2008; Burderi et al. 2009), and spin–orbit coupling in the companion star (Hartman et al. 2008, 2009). While the latter depends on the companion star, and may vary from source to source, the former should operate in all AMXPs (see also Patruno 2017; Sanna et al. 2017c), including Swift J1756. The spin-down luminosity impinging on the companion star can be estimated as Equation (10) where ${\dot{E}}_{\mathrm{abl}}$ is the ablation luminosity, RL2 is the Roche lobe radius of the companion (Eggleton 1983), and a the binary separation. The irradiation fraction is $f={\dot{E}}_{\mathrm{abl}}/{\dot{E}}_{\mathrm{sd}}$, which, accounting for the range of allowed neutron star and companion masses, evaluates to f = 0.15%–0.35%. The associated mass loss for the companion is given by Equation (11) such that, assuming an efficiency of η = 100%, ${\dot{M}}_{C}\,\sim -3\times {10}^{-10}\,{M}_{\odot }$ yr−1. The effect of this mass loss on the orbital period follows through the relation (Frank et al. 2002) Equation (12) giving a period derivative due to mass loss of ${\dot{P}}_{b,\mathrm{ML}}\,=5\times {10}^{-12}$ s s−1. This value is well above our limit on the period derivative. Hence, in order for this mechanism to be consistent with our observations of Swift J1756, the efficiency at which the companion star converts the incident luminosity into mass loss must be η < 15%. This value is very different from the 40% required in SAX J1808.4–3658 (Patruno et al. 2016) and is instead in line with the <5% efficiency determined for IGR J00291+5934 (Patruno 2017). This work was supported by NASA through the NICER mission and the Astrophysics Explorers Program, and made use of data and software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC). P.B. was supported by an NPP fellowship at NASA Goddard Space Flight Center. D.A. acknowledges support from the Royal Society.

Bult, Peter↗

DOE OSTI2021

AGR-5/6/7 Irradiation Test Final As-run Report

This document presents the as-run analysis of the Advanced Gas Reactor (AGR) 5/6/7 irradiation experiment. AGR-5/6/7 is the last of a series of experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of the development and qualification of tri-structural isotropic (TRISO) low enriched fuel for use in high-temperature gas-cooled reactors (HTGR). The test train contained five separate capsules that were independently controlled and monitored. Each capsule contained multiple 24.91-mm-long and 12.25-mm-dimeter compacts filled with low-enriched uranium carbide/oxide tri-structural isotropic fuel particles. The objectives of the AGR 5/6/7 experiment were to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel, beyond normal operating conditions. 3. Provide irradiated-fuel performance data and irradiated-fuel samples for post irradiation examination and safety testing. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) was to verify the successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures. Its primary objective is to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions, in support of plant design and licensing. AGR 5/6/7 will also provide irradiated-fuel performance data based on the fission gas release from particles during irradiation. To achieve the test objectives, the AGR-5/6/7 experiment was irradiated in the northeast (NE) flux trap of the ATR with a planned duration of 500 effective full-power days (EFPDs). The NE flux trap was selected because its larger diameter provided greater flexibility for test-train design compared to the Large B positions used for the AGR-1 and AGR-2 irradiations, significantly enhancing test capabilities for the combined irradiation campaigns. Due to delays in the ATR schedule, the AGR-5/6/7 irradiation was significantly shorter than the originally planned 13-cycle schedule. Irradiation began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles (162B?168A) over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of approximately 360.9 EFPDs. Final burnup values, on a per-compact basis, ranged from 5.66% to 15.26% fissions per initial heavy metal atom, while fast fluence values ranged from 1.62 to 5.55 × 1025 n/m2 (E >0.18 MeV). Time-averaged volume-averaged fuel temperatures on a capsule basis at the end of irradiation ranged from 756°C in Capsule 5 to 1313°C in Capsule 3 excluding days with significantly lower temperature during the two short powered axial locator mechanism cycles, 163A and 167A. By the end of irradiation, 48 out of 54 installed thermocouples (TC) had failed (the bottom three capsules lost all TCs). During the first five cycles (162B ? 165A), fission-gas isotope release-rate-to-birthrate (R/B) ratios were stable in the 10-8?10-6 range, and no in-pile particle failures were observed based on the gross gamma counts. During this time, the high exposed kernel fraction and high fuel particle temperatures in Capsule 1 led to the maximum R/B value of around 2 ? 10-6 for Kr-85m. The fission gas release in all capsules started to increase from the second half of Cycle 166A, when a large number of in-pile particle failures occurred in Capsule 1 and a gas line problem in this capsule caused fission gas leakage at various degrees into the other four capsules. This gas line problem also prevented fission gas release measurement for Capsule 1 during the last three cycles due to gas flow isolation. By the end of irradiation, it is estimated that approximately 15 particle failures in Capsule 3, which was considered possible at the start of the irradiation, since the experiment was designed to operate beyond the high-temperature gas-cooled reactor (HTGR) normal operating temperature range. A few hundred in-pile particle failures were estimated for Capsule 1 by the end of Cycle 166A, but the total number of failures is unknown due to lack of fission gas release data in the later cycles. Additionally, four potential in-pile failures were identified for Capsule 2 during the last cycle, 168A. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on absence of the typical spikes in gross gamma counts and low failure estimates using the AGR-3/4 R/B per exposed kernel model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

AGR-5/6/7 Irradiation Test Final As-run Report

This document presents the as-run analysis of the Advanced Gas Reactor (AGR)-5/6/7 irradiation experiment. AGR-5/6/7 is the last of a series of experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory in support of the development and qualification of tri-structural isotropic low-enriched fuel for use in high-temperature gas-cooled reactors. The test train contained five separate capsules that were independently controlled and monitored. Each capsule contained multiple 24.91-mm-long and 12.25-mm-dimeter compacts filled with low-enriched uranium carbide/oxide tri-structural isotropic fuel particles. The objectives of the AGR-5/6/7 experiment were to: • Irradiate reference-design fuel particles to support fuel qualification. • Establish operating margins for the fuel, beyond normal operating conditions. • Provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination and safety testing. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) was to verify the successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures. Its primary objective was to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions, in support of plant design and licensing. AGR-5/6/7 will also provide irradiated-fuel performance data based on the fission gas release from particles during irradiation. To achieve the test objectives, the AGR-5/6/7 experiment was irradiated in the northeast flux trap of the ATR with a planned duration of 500 effective full-power days. The northeast flux trap was selected because its larger diameter provided greater flexibility for test-train design compared to the Large B positions used for the AGR-1 and AGR-2 irradiations, significantly enhancing test capabilities for the combined irradiation campaigns. Due to delays in the ATR schedule, the AGR-5/6/7 irradiation was significantly shorter than the originally planned 13-cycle schedule. Irradiation began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles (162B–168A) over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of approximately 360.9 effective full-power days. Final burnup values, on a per-compact basis, ranged from 5.66 to 15.26% fissions per initial heavy metal atom, while fast fluence values ranged from 1.62 to 5.55 × 1025 n/m2 (E >0.18 MeV). Time-averaged volume-averaged fuel temperatures on a capsule basis at the end of irradiation ranged from 756°C in Capsule 5 to 1313°C in Capsule 3 excluding days with significantly lower temperature during the two short powered axial locator mechanism cycles, 163A and 167A. By the end of irradiation, 48 out of 54 installed thermocouples had failed (the bottom three capsules lost all thermocouples). During the first five cycles (162B – 165A), the fission-gas isotope release-rate-to-birthrate (R/B) ratios were stable in the 10-8–10-6 range, and no in-pile particle failures were observed based on the gross gamma counts. During this time, the high exposed kernel fraction and high fuel particle temperatures in Capsule 1 led to a maximum R/B value of around 2 ? 10-6 for Kr-85m. The fission gas release in all capsules started to increase from the second half of Cycle 166A, when a large number of in-pile particle failures occurred in Capsule 1 and a gas line problem in this capsule caused fission gas leakage at various degrees into the other four capsules. This gas line problem also prevented a fission gas release measurement for Capsule 1 during the last three cycles due to gas flow isolation. By the end of irradiation, it is estimated that approximately 15 particles failed in Capsule 3, which was considered possible because the experiment was designed to operate beyond the high-temperature gas-cooled reactor normal operating temperature range. A few hundred in-pile particle failures were estimated for Capsule 1 by the end of Cycle 166A, but the total number of failures is unknown due to the lack of fission gas release data in the later cycles. Additionally, four potential in-pile failures were identified for Capsule 2 during the last cycle, Cycle 168A. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on the absence of the typical spikes in gross gamma counts and low failure estimates using the AGR-3/4 R/B per exposed kernel model.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗

DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

High concentrations of ice: Investigations using polarimetric radar observations combined with in situ measurements and cloud modeling (Final Report)

This DOE-funded joint project had the over-arching goal of understanding the reasons for observed size distributions of ice particles in cold clouds. Its approach involves the use of cloud models and field observations by radar and aircraft of real storms. The project addresses three major research objectives: (1) Utilize a novel polarimetric radar technique to retrieve size distributions and amounts of ice from radar data collected during the previous DOE ARM field campaigns; (2) Evaluate the results of ice microphysical retrievals using available in situ aircraft measurements and other remote sensors (e.g., vertically pointing cloud radars and wind profilers); (3) Improve the treatment of microphysical processes leading to cloud glaciation and ice multiplication in numerical cloud models. The study was performed by three research organizations: University of Oklahoma, The Hebrew University of Jerusalem, Israel, and Lund University, Sweden. The Israel and Swedish partners were funded by the sub-awards from the University of Oklahoma. Cloud modeling studies have been performed by the research teams at The Hebrew University of Jerusalem (HUJ) and Lund University to identify the origins of high concentrations of cloud ice in areas of high ice water content (HIWC). The Hebrew University Cloud Model (HUCM) with full spectral bin microphysics and the Lund University aerosol-cloud (AC) model with a hybrid bin / bulk microphysics scheme complementing HUCM were utilized for simulations. Both research teams had particular focus on secondary ice production (SIP) as one of the possible sources of enhanced ice concentration. The HUJ group suggested a novel concept of ice multiplication during droplet freezing. It is assumed that splintering and droplet fragmentation during droplet freezing takes place because of dendritic growth within a supercooled drop. The resulting simulations of SIP generated small ice in concentrations exceeding hundreds per liter similar to what was observed in the HIWC regions of the tropical storms. The Lund team explored the SIP mechanisms such as breakup of ice particles due to ice-ice collisions and ice sublimation that are expected to dominate the continental storms. They also quantified the impact of homogeneous nucleation of cloud droplets on the total number concentration of ice at very low temperatures near the tops of the clouds. Additionally, the Lund AC model is able to simulate the effect of aerosols of various types (including biological) on the cloud life cycle and the corresponding ice production. The HUCM / AC model was used to simulate one of the “golden” cases of the DOE MC3E campaign on 20 May 2011. The model output was converted into the fields of polarimetric radar variables using the polarimetric radar forward operator developed at the University of Oklahoma and compared with radar observations and in situ microphysical measurements onboard research aircraft. It was demonstrated that specific differential phase KDP is the best radar parameter to identify the HIWC areas and quantify the corresponding ice parameters. For the first time, the shape of the vertical profile of KDP was realistically reproduced by the cloud model with the KDP maximum in the dendritic growth layer (DGL) centered at the -15°C isotherm. The University of Oklahoma team has developed a methodology for polarimetric radar retrievals of such microphysical parameters of ice as ice water content (IWC), mean volume diameter (Dm), and total number concentration (Nt) of ice particles. These retrievals have been validated using in situ aircraft measurements during 6 field campaigns and proved to be quite robust and reliable. This allowed to build the first climatology of the vertical profiles of polarimetric radar variables and retrieved microphysical parameters for the three types of weather systems: continental MCSs, maritime MCSs, and tropical cyclones / hurricanes (Hu and Ryzhkov 2022). The data were collected by a multitude of the WSR-88D radars in 13 continental and 10 maritime MCSs and 11 landfalling hurricanes. The HIWC areas were identified within the examined storms and the corresponding “HIWC statistics” was compared with the “background” one without HIWC. An overarching conclusion of the study is that maritime tropical storms (MCSs and hurricanes) are characterized by smaller size ice in higher concentration compared to the continental MCSs. High ice water content in the HIWC areas is primarily caused by a strong jump in a number concentration of ice particles rather than the increase of their size compared to the “background” environment. This may point to the homogeneous nucleation of excessive amounts of supercooled droplets and / or secondary ice production as the possible origins of HIWC. Such a climatology provides a good observational reference for the modelers to evaluate the performance of their models. As an example, the in-depth analysis of the 20 May 2011 MC3E case shows that the advanced cloud models developed in the course of this study still tend to underestimate the number concentration of ice in the HIWC areas although they succeed in reproducing realistically looking vertical profiles of IWC and Nt. The results of the project research are summarized in 13 journal papers.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

The Utilization Profiles of the CCSDS Unified Space Link Protocol (USLP)

The purpose of this paper is to identify the utilization profiles for interfacing the Data Protocol Sublayer using the Unified Space Link Protocols (USLP) (reference 1) with the space link coding procedures as specified in the CCSDS Coding & Synchronization Blue Books (references 2 through 5), used in both telecommand and telemetry applications. This paper describes how the USLP Protocol utilizes the coding and synchronization sublayer to support: a. Direct to Earth (DTE) telemetry links for engineering and science data b. Direct to Earth (DTE) telemetry links for very high rate science data c. Direct from Earth (DFE) command, sequencing and flight software loads d. Space to Space Links (Proximity) utilized by orbiters for data exchange to/from surface bound assets. The CCSDS has divided the functions of the Data Link Layer into two sublayers: the Data Link Protocol Sublayer (DLP-SL) and the Coding and Synchronization Sublayer (CS-SL). The Data Link Protocol Sublayer (DLP-SL) interfaces to the users, accepting the data that is to be transported, on the sending side of the link, and delivering that data on the receiving end. The Transfer Frame is the data unit that is transferred across the Data Link Protocol Sublayer and the Coding and Synchronization Sublayer boundary. The Coding and Synchronization Sublayer (CS-SL) provides the encoding, randomization, and frame synchronization functions that prepares the USLP Transfer Frame for transport across the space link. The CS-SL is divided into 2 processes: 1) The Frame Interface Processes (FIP) performs the interface functions required to prepare the data for delivery to the Coding/Decoding Process (CDP). This process includes prepending a Frame Start Marker to the provided frame, when management has designated that the frame is not to be aligned to the codeblock or when there is no block code used. 2) The Coding/Decoding Process (CDP) performs the forward error correction processes that are used to optimize the performance of the link and minimize the error rate. The CDP creates the symbol stream that is delivered to the Physical Layer. The transfer of the USLP transfer frames across different types of space links is the focus of this paper. The Protocol Data Unit (PDU) that is passed in both directions between the Data Link Protocol Sublayer (DLP-SL) and Coding and Synchronization Sublayer (CS-SL) is the transfer frame. The USLP frame structure provides flexibility that can be constrained by the functions utilized within the CS-SL that prepare the transfer frame for transit. For example, the USLP transfer frame contains a length field that enables the frame to be of variable length but CS-SL under certain conditions may constrain the frame to be fixed in length. This paper describes 5 operational modes available for use by the Data Link Layer to provide data exchange across the USLP space link. These modes are different because different operational requirements apply to vastly different types of space links and thus the communications implementation requirements differ. The environmental issues include the power or energy available, the distance between the end points of the link, the complexity of the equipment available at those end points, the atmospheric conditions and radiometric frequency selection. The CS-SL utilizes different forward error correcting codes supported by specific operational modes to configure the data for transit. This paper describes all of the operational modes in a series of data models which decompose the functionality between the Data Link Protocol Sublayer and the Coding and Synchronization sublayer. The operational modes described are: 1. Uncoded Mode: has been used for short links that contain significant available power to provide an acceptable frame error rate. The frames in this mode can be variable in length and typically use an error detection algorithm (i.e., CRC) to determine if there are errors in the received frame. 2. Convolutional Only Mode: is currently the prime forward error correction coding used for the proximity links. The frames in this mode can be variable in length and typically use an error detection algorithm (i.e., CRC) to determine if there are errors in the received frame. 3. Variable Length Frame Aligned to Variable Length Codeblock (TC): is used for Direct from Earth links were power levels are high and the simple, least complex code i.e., the BCH code is used. This mode has been in use since the early 1970s. The BCH code is a short code and the decoder is easy to implement. 4. Fixed Length Frame Aligned to Fixed Length Codeblock (AOS/TM): was introduced when the concatenated Convolutional and Reed-Solomon Code was formulated to provide significant reduction in link data error rate and the ability to determine if there was an error in the decoded codeblock. The frame is aligned to the codeblock so that there is a one to one relationship of frame errors to codeblock errors without additional error detection coding being added. This mode requires the protocol frames to be the exact size of the message portion of the codeblock. 5. Frames Unaligned to Fixed Length Codeblocks (Currently used for very high rates and space to space links): This mode is currently used for missions that have a very high data rate that can be controlled adaptively as the environment changes and as the next generation operating mode for the proximity link. This mode from a coded data stream point of view is exactly like that described in 4. above, except that the frame need not be aligned to the codeblock. There is no requirement on frame length when using this mode. Thus when using USLP it can be used to support links that require short or long frames. There is also no mandatory requirement that frames cannot be separated by idle data reducing the tight data rate connection requirements between the data link protocol sublayer and the coding & synchronization sublayer. In conclusion, how these operational modes can be put to use in mission operational scenarios is described for Direct from Earth links (DFE), Direct to Earth links (DTE), and Proximity links.

Greenberg, E.↗

NASA NTRS1996

Saccades to remembered targets: the effects of smooth pursuit and illusory stimulus motion

1. Measurements were made in four normal human subjects of the accuracy of saccades to remembered locations of targets that were flashed on a 20 x 30 deg random dot display that was either stationary or moving horizontally and sinusoidally at +/-9 deg at 0.3 Hz. During the interval between the target flash and the memory-guided saccade, the "memory period" (1.4 s), subjects either fixated a stationary spot or pursued a spot moving vertically sinusoidally at +/-9 deg at 0.3 Hz. 2. When saccades were made toward the location of targets previously flashed on a stationary background as subjects fixated the stationary spot, median saccadic error was 0.93 deg horizontally and 1.1 deg vertically. These errors were greater than for saccades to visible targets, which had median values of 0.59 deg horizontally and 0.60 deg vertically. 3. When targets were flashed as subjects smoothly pursued a spot that moved vertically across the stationary background, median saccadic error was 1.1 deg horizontally and 1.2 deg vertically, thus being of similar accuracy to when targets were flashed during fixation. In addition, the vertical component of the memory-guided saccade was much more closely correlated with the "spatial error" than with the "retinal error"; this indicated that, when programming the saccade, the brain had taken into account eye movements that occurred during the memory period. 4. When saccades were made to targets flashed during attempted fixation of a stationary spot on a horizontally moving background, a condition that produces a weak Duncker-type illusion of horizontal movement of the primary target, median saccadic error increased horizontally to 3.2 deg but was 1.1 deg vertically. 5. When targets were flashed as subjects smoothly pursued a spot that moved vertically on the horizontally moving background, a condition that induces a strong illusion of diagonal target motion, median saccadic error was 4.0 deg horizontally and 1.5 deg vertically; thus the horizontal error was greater than under any other experimental condition. 6. In most trials, the initial saccade to the remembered target was followed by additional saccades while the subject was still in darkness. These secondary saccades, which were executed in the absence of visual feedback, brought the eye closer to the target location. During paradigms involving horizontal background movement, these corrections were more prominent horizontally than vertically. 7. Further measurements were made in two subjects to determine whether inaccuracy of memory-guided saccades, in the horizontal plane, was due to mislocalization at the time that the target flashed, misrepresentation of the trajectory of the pursuit eye movement during the memory period, or both. 8. The magnitude of the saccadic error, both with and without corrections made in darkness, was mislocalized by approximately 30% of the displacement of the background at the time that the target flashed. The magnitude of the saccadic error also was influenced by net movement of the background during the memory period, corresponding to approximately 25% of net background movement for the initial saccade and approximately 13% for the final eye position achieved in darkness. 9. We formulated simple linear models to test specific hypotheses about which combinations of signals best describe the observed saccadic amplitudes. We tested the possibilities that the brain made an accurate memory of target location and a reliable representation of the eye movement during the memory period, or that one or both of these was corrupted by the illusory visual stimulus. Our data were best accounted for by a model in which both the working memory of target location and the internal representation of the horizontal eye movements were corrupted by the illusory visual stimulus. We conclude that extraretinal signals played only a minor role, in comparison with visual estimates of the direction of gaze, in planning eye movements to remembered targ.

Clinical Trial↗

DOE OSTI2020

Study of the Mu2e sensitivity to the $\mu^-\rightarrow e^+$ conversion process

The Mu2e experiment at Fermilab (Batavia, IL) will search for the coherent neutrinoless conversion of a muon into an electron in the electric field of an aluminum atom. The conversion process results in a monochromatic electron with energy slightly below the muon rest mass ($E_e= 104.97$ MeV). The experiment goal is to improve the previous measurement by four orders of magnitude and reach a single event sensitivity of $3 \times 10^{-17} $ on the conversion rate with respect to the muon capture rate. \\ The experiment will deliver a very intense pulsed negative muon beam to an aluminum target to achieve a total number of $10^{18}$ stopped muons in three years of running. Production and transport of the muons are accomplished with a sophisticated magnetic system comprised of a Production, a Transport and a Detector solenoid, with the last one hosting a Straw-tube Tracker and a Crystal Calorimeter. The entire detector region is surrounded by a Cosmic Ray Veto system. Mu2e is und er construction at the Muon Campus of Fermilab. \\ The INFN italian group is responsible for the design and construction of the crystal calorimeter, which plays a crucial role in the Mu2e measurement, providing particle identification capabilities fundamental for the rejection of the different background sources that can mimic a conversion electron. The calorimeter information allows also to improve the tracking performances it provides a fast standalone trigger for the experiment.\\ After a long R\&D phase, the final drawings see a calorimeter comprised of 1348 pure CsI crystals arranged in two annular disks. Each crystal is readout by two custom UV-extended Silicon Photomultipliers (SiPMs). Performances of the selected components were verified with an electron beam test, carried out in 2017 at the Beam Test Facility (BTF) at the National Laboratories of Frascati, on a large size prototype of 51 crystals and 102 SiPMs, confirming excellent energy ($\sigma_{E}/E = \mathcal{O }(10\%)$) and timing ($\sigma_{T} <500$ ps) resolutions in a! greement with the Mu2e specifications.\\ In the first chapters of this thesis, I describe my involvement in the calorimeter activities, with particular emphasis on the data analysis of the prototype energy response and resolution, that I was personally leading. Moreover, a description of the tuning of the simulation and the careful data-MC comparison is also reported.\\ An auxiliary measurement that can be performed with Mu2e is the search for a Lepton Number Violation (LNV) process where the negatively charged muon converts, without neutrinos, into a positron, $\mu ^{-} +N(A,Z) \rightarrow $ e$^+ +N(A,Z-2)$. At the moment of writing, Neutrinoless Double Beta Decay (0$\nu \beta \beta$) has set the most stringent limit on the LNV processes (T$^{0\nu \beta \beta}_{1/2} > 1.1 \times 10^{26} $ yr at 90$\%$ CL) with the GERDA experiment. In 0$\nu \beta \beta$ a pair of free electrons is created in the transformation from a nucleus $(A, Z)$ into its daughter $(A, Z + 2)$, namely: $(A,Z)\rightarrow (A, Z+2) =2 e^-$. Similar transitions could proceed through the emission of a pair of positrons, double electron capture (EC), or EC and single emission of a positron, with the nucleus changing from $(A, Z)$ to $(A, Z - 2)$. All these variations are equally interesting when discussing of new Physics, since they all manifest a non-conservation of the number of leptons.\\ Moreover, recent studies show that, because of flavor effect, off-diagonal processes, such as the $\mu^- -e^+$ conversion, can have their rate enhanced with respect to processes occurring in the $e-e$ sector.\\ Mu2e will search for $\mu^- + Al(27,13) \rightarrow e^+ +Na(27,11)$, only considering ground state transition, producing a conversion positron with energy $E_{e^+}= 92.32 $ MeV.\\ This thesis is focused on this search. In particular, I developed an algorithm to account for the radiative corrections to be applied to the conversion positrons that resulted in a few percent reduction in s ignal acceptance.\\ One of the most prominent background to ! this sear! ch is the Radiative Muon Capture (RMC) $ \mu+ N(Z,A)\rightarrow \gamma + \nu_{\mu} + N(Z-1,A)$. The produced photon can convert, virtually or in the detector materials (in the following referred as internal or external conversion respectively) in an electron-positron pair, producing positrons with energies approaching the expected conversion energy. Experimental results from previous experiments indicate the RMC endpoint ($\kmax$) to be of $\sim$ 90 MeV. A precise modeling of this background is relevant due to the proximity of the photon spectrum endpoint to the positron conversion energy. The calorimeter group is obviously interested to reconstruct the RMC distribution having also the opportunity to improve the current knowledge of the process. \\ A toy MC has been developed to evaluate the number of $e^+$ from external RMC background in the signal window. Knowing this value and ev...

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Commercial Building Technology Demonstration (Final Scientific/Technical Report)

The background for this project was a unique and innovative concept that had been proposed and demonstrated by enVerid Systems, reducing the energy consumption in HVAC systems in commercial and public buildings by up to 50% at peak loads. The concept involves selective scrubbing of gas contaminants from indoor air as a practical substitute for outside air ventilation, the latter being the conventional practice today. This scrubbing enables recycling of most of the indoor air and significantly decreasing the amount of outside air, resulting in a reduced HVAC load and commensurate energy savings for the facility. Key to our approach is low cost scrubbing of all gas contaminants from indoor air using novel, efficient and regenerable sorbent materials. The total solution, labeled HLR (HVAC Load Reduction) is implemented by means of compact modules that can be retrofitted onto virtually any building, and utilizes novel sorbents that have been developed and brought to scale production by enVerid. Although the technology had been deployed and demonstrated, the US commercial building and HVAC markets, famously conservative with respect to innovation and new technologies, had yet to embrace the idea or the product. The overarching goal of the project was to help overcome market hesitancy and enable widespread adoption, by creating a critical mass of success stories across different regions and building types, all under oversight and verification of the DOE and NREL, to ensure credibility and accuracy. The project, overall, was a resounding success. Several installations were deployed and tested comprehensively for the impact on both energy consumption and indoor air quality, and results were not only excellent, but quantitatively in line with expectations. A total number of eight (8) installations were attempted, with 2 aborted due to building issues. Of the six successful installations, however, complete M&V was performed by NREL on 2 (Miami and NYC) and partial analysis on a third site (ArcBest), and these three, along with their results, were therefore presented from a financial and reporting standpoint. Although the number of case studies fell short of the original target of 10, we nevertheless had excellent demonstrations in vastly different climate zones: Southeast, Northeast and Midwest, and in very different building types. This included a modern high-rise office building in New York City and a University Campus health center in Miami, and a mid-rise high-density office in Arkansas. The cooling load reduction was shown to be significant, averaging 37% during the final cooling season in the Miami site. In the NYC site, the cooling energy savings were generally less, at around 12%, as expected. While this is a lower number for average/total savings, two comments are important to note: (i) the outside airflow (OA) reduction was not consistent during the data collection period, at least in part understating the attainable savings through incorrect measurement of the “high energy” reference state; and (ii) the peak impact in NYC is almost certainly as high as Miami, with critical ramifications for peak load reduction and equipment downsizing ability. Importantly, the measured energy savings in all locations were related to the outdoor climate conditions and the actual achievable reduction in outside air, very much in line with models and calculations; this leaves us with increased confidence in our understanding of the interaction between the technology and the building, and our ability to project the impact of this innovation in the future, through broad adoption. Simply put: the energy savings and load reduction impact of the HLR solution has been confirmed quantitatively. The results also confirmed the air quality objective. This may be even more significant, in that air quality is more complex and harder to measure and quantify, and the performance of the HLR as an air scrubber is the linchpin of the entire solution. In all sites, indoor air quality met or exceeded the required parameters, in terms of achieving the target (low) levels of indoor pollutants. Furthermore, the concentrations of outdoor sourced pollutants were markedly lower, as expected, mostly due to the reduction in outside air intake although in part also due to the scrubbing. The success was not immediate nor easy, and early challenges with the systems, especially (but not only) around controls and communication, caused delays in commissioning and undermined some of our M&V schedules. The good news is no fundamental issues were encountered and the number of such glitches was declining quickly by the end of the project. Other challenges had to do with coordinating the control of the building OA dampers, which the HLR needs to have in order to deliver the load reduction, but which the facility manager controls regularly and independently. This is not necessarily a problem for normal HLR operation but interferes with accurate M&V, where switching OA settings back and forth on a precise timetable is essential for clean data. The project provided valuable experience in retrofitting buildings that had been originally designed to operate with less recirculation and more outside air, and some key learnings related to the cyclical regeneration of the sorbents in the operational environment of the building. Some of these learnings gave already been incorporated into ongoing improvements in the design of the HLR module as well as the software that is used to control its operation. The cost and time of retrofit installations is much better understood; so is the test and balance procedure of the building that determines the available range of outside air reduction, which in turn determines the amount of load reduced. We had also implemented at least one annual cycle of sorbent cartridge replacement in the field, after which we tested the used sorbent to assess the rate of degradation of sorbent potency – an important factor affecting the long-term economics of HLR deployments. A notable shortfall of the project, other than the fact that the number of sites was below target, was that we had not (yet) completed testing to measure and verify (M&V) the winter energy savings. This is primarily due to late start on the NYC sites (Miami does not portend any heating savings associated with reduced outside air), combined with the issues of OA damper control. It is by no means suggested that such savings cannot be captured, only that the M&V with respect to winter in NYC has been incomplete. The value of this project and its interest to the general public are hard to overstate. The case studies created from Miami and especially from NYC have, without a doubt, opened up the interest of the broad HVAC industry to HLR in the past year. Major manufacturer reps have signed up to represent and promote the product, and dozens of top tier engineering consultants have introduced HLR as a base of design in upcoming construction and renovation projects – precisely the overarching goal of this project. These would not have happened without the highly visible installation in NYC and its ultimately satisfied customer. Furthermore, the DOE itself issued a report in late 2017 analyzing hundreds of candidate technologies for reducing energy consumption in HVAC; remarkably, the budding HLR solution ranked among the top 3(!); no doubt, its status as a viable and significant contender on this list is informed by the success of these demonstrations. And furthermore, in the wake of these demos, several major energy utilities, led by ConEdison in NYC, have endorsed the HLR solution and now routinely provide substantial cash rebates for customers choosing to incorporate the HLR in their buildings and reap the benefit of the reduced peak load as well as reduced cumulative energy demand. Last but not least, in January of 2019, as this report was being written, the HLR module won the AHR Expo Innovation Award for Green Buildings and, remarkably, the prestigious and only Product of the Year 2019, being selected by an independent professional panel of judges from AHR and ASHRAE. Given the confirmation of the enormous energy saving potential of HLR in widescale deployment, as well as ancillary but significant benefits in terms of equipment downsizing and indoor air quality, the benefit of this effort to the public speaks for itself. Accelerating adoption of HLR, without dependence on subsidies and driven by the private sector, is well under way. There is still much work to be done in terms of educating the HVAC and construction ecosystems and improving the product’s robustness and simplicity, to further facilitate the adoption of this technology and the capture of its potential value. But the American public will greatly benefit both directly and indirectly in the immediate future and beyond.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Thermal and kinematic properties of ejecta in SN1987A revealed by XRISM

We present an analysis of high-resolution spectra from the shock-heated plasmas in SN 1987A, based on an observation using the Resolve instrument onboard the X-Ray Imaging and Spectroscopy Mission (XRISM). The 1.7–10 keV Resolve spectra are accurately represented by a single-component, plane-parallel shock plasma model, with a temperature of $2.84_{-0.08}^{+0.09}$ keV and an ionization parameter of $2.64_{-0.45}^{+0.58}$ × $10^{11}\,\,{\rm s\,\, cm}^{-3}$. The Resolve spectra are also well reproduced by the 3D magneto-hydrodynamic simulation presented by Orlando et al. (2020, A&A, 636, A22) suggesting substantial contribution from the ejecta. The metal abundances obtained with Resolve align with the Large Magellanic Cloud value, indicating that the X-rays in 2024 originate from “non-metal-rich” shock-heated ejecta and the reverse shock has not reached the inner metal-rich region of ejecta. Doppler widths of the atomic lines from Si, S, and Fe correspond to velocities of 1500–1700 km s$^{-1}$, where the thermal broadening effects in this non-metal-rich plasma are negligible. Therefore, the line broadening seen in Resolve spectra is determined by the large bulk motion of ejecta. For reference, we determined a $90\%$ upper limit on non-thermal emission from a pulsar wind nebula at $4.3 \times 10^{-13}$ erg cm$^{-2}$ s$^{-1}$ in the 2–10 keV range, aligning with NuSTAR findings by Greco et al. (2022, ApJ, 931, 132). Additionally, we searched for the $^{44}$Sc K line feature and found a $1\sigma$ upper limit of $1.0 \times 10^{-6}$ photons cm$^{-2}$ s$^{-1}$, which translates to an initial $^{44}$Ti mass of approximately $2 \times 10^{-4}\, M_{\odot }$, consistent with previous X-ray to soft gamma-ray observations (Boggs et al. 2015, Science, 348, 670; Grebenev et al. 2012, Nature, 490, 373; Leising 2006, ApJ, 651, 1019).

ISM: supernova remnants↗

DOE OSTI2018

Development of Thermoacoustic Sensors for Sodium-cooled Fast Reactors

This Final Report refers to the project “Development of Thermoacoustic Sensors for Sodium-cooled Fast Reactor Systems”, which was led by Westinghouse Electric Company (Westinghouse) and carried out in collaboration with Argonne National Laboratory (ANL) and University of Pittsburgh. Thermo-acoustic Power Sensors (TAPS) are self-powered, wireless sensors envisioned for measuring key parameters, such as local temperature and neutron flux, in a nuclear reactor core. This project was intended to specifically investigate their applicability to Sodium-cooled Fast Reactors (SFR). TAPS are non-invasive (wireless) and passive (self-powered) devices. The passivity derives from their ability to use conditions that “naturally” exist in a nuclear reactor, such as gamma and neutron flux, as power sources. They generate oscillating pressure waves (i.e., sound waves) which, with a frequency and amplitude dependent upon these conditions, can travel through the core and associated structures, and reach the outside of the reactor vessel where a properly designed network of receivers can detect and interpret them. These receivers require a very small amount of power which, during loss of power events, can be provided for example by harvesting gamma radiation energy, thus resulting in a monitoring system that can function both during normal operation and during loss of power events. The project aimed at TAPS development through a series of tasks which are listed and briefly discussed as follows. TASK 1 – Sensor hardware design Subtask 1a: Assessment of sensor applications to SFRs Subtask 1b: Development of sensor functional requirements Subtask 1c: Definition of sensor hardware design specifications Task description: TAPS design was informed by considerations on their application (Subtask 1a), both the ultimate one in an SFR and the actual one in the ANL testing facilities that was intended to be used in support of the project. Considerations were made to identify optimum sensor design features that optimize the sensor size, materials, and output signal, for installation inside an SFR core. These considerations led to the development of Functional Requirements (Subtask 1b) and Design Requirements (Subtask 1c). TASK 2 – Sensor Hardware Manufacture Subtask 2a: Sensor hardware construction drawing development Subtask 2b: Sensor manufacture and assembly Task description: TAPS technical drawings were developed (Subtask 2a) using the Design Requirements established under Task 1. Subsequently, in spite of some problems which ultimately caused the program to be delayed, TAPS manufacturing was completed based on drawings (Subtask 2b). TASK 3 – Development of TAPS Signal Measurement System and TAPS Testing in Water Subtask 3a: Design, assembly and testing of signal measurement system, and TAPS testing in water Subtask 3b: Signal prediction-correction methodology development Task description: An assessment was performed on the techniques that can potentially be used to detect the signals emitted by the TAPS, e.g. a fiber-optic based acoustic signal measurement system, a laser vibrometer system, or an accelerometer-based system. The most suited technology, i.e. the accelerometer-based system, was developed further, and tested in water (Subtask 3a). Moreover, efforts were made to develop the methodology required to determine the actual system temperature and neutron flux distribution using differences between the measured and predicted TAPS responses (Subtask 3b). TASK 4 – Sensor System Testing in Sodium Subtask 4a: Test plan development Subtask 4b: Design, assembly and testing in small-scale sodium facility Subtask 4c: Design, assembly and testing in large-scale sodium and structures facility Task description: Upon proper test plan development (Subtask 4a), the fabricated TAPS was planned to be tested in sodium, by using two sodium facilities at ANL having different size and different purpose. The Under Sodium Viewing (USV) small-scale facility was intended to be used to investigate the effect of sodium on the sensor and its performance (Subtask 4b). The Mechanism Engineering Test Loop (METL) large-scale facility was instead intended to be used to assess the additional effect of prototypical SFR structures, such as fuel assembly mockup or parts of the core restrain structure, on sensor performance (Subtask 4c). As discussed in Section 3.2.2.7, unexpected issues during the TAPS manufacturing process resulted in some activities being delayed, with the TAPS and USV facility developed to the point to be ready for testing in sodium, however without the possibility to actually perform such testing (including the testing in METL) due to the end of the program’s performance period. Overall, through the development and testing (in water only) of two TAPS devices (a First-Generation TAPS followed by an optimized Second-Generation TAPS), the project confirmed the capability of this technology to generate acoustic signals proportional to temperature, which can be detected through a network of accelerometers identified as the best-suited type of receivers for acoustic signal detection. Moreover, the project also developed a computational model to predict the characteristics of the acoustic signals being generated, which combines thermal analysis of the TAPS with Finite Element Modeling (FEM)-aided acoustic characterization of the system. This model was benchmarked against experimental data collected during the project and, although general agreement was obtained, some limitations of the modeling methods were identified, which require additional development. Additional testing is needed in order to assess the effect, on TAPS operation and performance, of environmental changes resulting from the transition from water to liquid sodium. Such testing, which is suggested to be performed in the future, should look specifically at 1) both the effect resulting from the different thermoacoustic behavior of sodium (relative to water) and the effects of higher temperature on TAPS performance, and 2) the performance of the sensor-receiver system when multiple TAPS are used simultaneously and prototypical reactor structures are positioned in the testing environment. The latter testing is needed to assess the effects that potential signal attenuation/ distortion phenomena, as well as potential interference between signals emitted simultaneously, have on the performance of the technology for ultimate application in a nuclear reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

VERNE: Revealing the Mysteries and Histories of Venus

Introduction: The three Venus missions that were recently selected for upcoming flight (VERITAS, DAVINCI+, and EnVision) will be incredibly valuable to our understanding of Venus’ history, geology, and atmosphere. However, even once completed, key gaps in our knowledge of Venus, and more generally the formation and active processes on rocky, Earth-like planets, will still persist. Remaining questions include 1) how global intrinsic magnetic fields might be maintained on rocky worlds, and how they could then go extinct, and 2) what role atmospheric sulfur chemistry plays in climates of Earth-like planets, which is an increasingly timely subject as Earth’s own atmospheric sulfur content is climbing due to human activity. These questions require in-situ observations from Venus’ cloud deck, at the altitudes at which the UV absorber exists. The Venus Environment Research and Novel Exploration (VERNE) mission will address these questions with an aerial platform that will drift around the equatorial region of the planet for 9 days. VERNE will collect data to determine the identity of the mysterious UV absorber, while also taking magnetic field measurements over the tesserae, the regions on Venus that are most likely to retain remanent crustal magnetization, in order to understand the potential role of a past intrinsically-generated global magnetic field on Venus. Mission Objectives: The two major science objectives that drive the VERNE mission are: 1) Determine the identity of the Venusian unknown ultraviolet absorber(s). First observed approximately a century ago [1], the composition of Venus’ ultraviolet (UV) absorber is one of the oldest mysteries in Venus atmospheric chemistry [2,3]. While several candidate UV absorbers (mostly sulfur species) have been proposed, no consensus has been reached on its composition and its specific interactions with the atmosphere. Determining the identity of the UV absorber will aid climate models by showing how and where incident solar energy is absorbed by the atmosphere and make progress towards understanding the chemical and energetic processes taking place above Venus’ upper cloud deck [4]. 2) Determine if Venus retains evidence of a past, internally-generated magnetic field. While Venus does not currently have an intrinsically-generated magnetic field, evidence for the existence of a past field on Venus and a timeline of its decay will fill in a more holistic picture of the evolution of Venus’ geological record and atmosphere. As the oldest geologic units on the surface, Venus’ tesserae may still have remanent crustal magnetization signatures within the rocky composition [5]. In any case, the signatures detected will provide insight into Venus’ past geological and core dynamo activity. Mission Summary: VERNE includes a 3-part flight system made up of 1) an entry system with a HEEET (Heatshield for Extreme Entry Environment Technology) aeroshell, 2) an orbiter for data relay, and 3) an in-situ balloon and gondola. After entry into Venus’ atmosphere, the balloon will be deployed within the upper cloud deck, at an altitude of 62 km, over a tesserae region. The in-situ data collection will last for the duration of 2 full circumnavigations of the planet, which will take ~9 days. Instrumentation Suite: The four instruments that comprise VERNE’s instrument payload will enable the identification of the unknown UV absorber and the detection of remanent crustal magnetization if it exists in the tesserae. The proposed instrument suite cycle during mission operations is shown in Fig. 1. The four instruments are described below: 1) Adams (ion neutral mass spectrometer) has a range of 18-257 AMU and will detect and distinguish the mixing ratios of O₂, H₂O, H₂SO₄, S, S₂, S₃, S₄, S₅, S₆, S₇, S₈, SO, SO₂, OSSO, SO₃, Cl₂, FeCl₃ and other trace sulfur and organic species. The spatial (longitudinal) and temporal (day/night) variations will be observed throughout 2 circumnavigations with a sample cadence of 12 minutes. 2) Shelley (nephelometer) will determine the size distribution of the aerosols (0.4 to 36 um) in the atmosphere. With a size resolution of <0.7 um, it can determine which mode of H2SO4 is present and characterize the large (>30 um) organic particles previously detected by the Venera and Galileo missions [6,7]. 3) Herbert (UV imager) will measure UV radiance at 283 nm (the wavelength of SO2 absorption) and 365 nm (the unknown part of the absorber). UV images will be taken concurrently with the INMS and nephelometer to correlate UV absorption with abundances of the UV absorber species. 4) Vonnegut (magnetometer) has a range of >600 nT and a precision and accuracy of 1 nT. If magnetized by a past field, the crust may have retained a magnetization of up to 3 A/m2 [5]. With a noise floor of 10 nT, the magnetometer will be able to detect RCM from an altitude of 62 km, even if the thickness of the magnetized crust is just 1 km (Fig. 2). Mission Concept Design: VERNE will be launched with a mass of 3300 kg in an intermediate-high performance class vehicle with a 4-m fairing. The 475-day mission includes 466 days for the cruise, coasting, and orbit initialization phases before entry, descent, and balloon deployment. During the 9-day science phase, the aerial platform will make 2 circumnavigations of the planet at an altitude of 62 km. The INMS and the nephelometer will acquire data for 2 hours during the daytime and nighttime during each circumnavigation, while the UV imager will be on for the duration of the daytime, and the magnetometer will be operational throughout the entirety of the science phase. Data will be stored and processed with the JPL-designed Sphinx command and data handling system. Data will be sent from the balloon to the orbiter using an S-band relay link, stored on the orbiter, and then forwarded to Earth where it will be received by the DSN. Conclusion: VERNE will fill key gaps in our understanding of the history and ongoing processes related to the geology and atmosphere of Venus and rocky worlds in general. Even with adequate flight system contingencies and expected costs below the $900M New Frontiers cost cap, VERNE is not without its risks and challenges. Further trade spaces to explore include 1) using solely battery power vs. including solar panels to increase the mission duration and 2) investigating the use of lightweight materials and 3D-printed structures to reduce the gondola mass, among others. Acknowledgments: We would like to thank the JPL Planetary Science Summer School, especially our mentors Troy Hudson, Karl Mitchell, and Leslie Lowes, as well as our Team-X study lead Al Nash and the members of Team-X. We’d additionally like to thank our review panel for asking insightful questions and providing valuable feedback. References: [1] Ross, F. E. (1928) Astrophysical J., 68, 57-92. [2] Rossow, W. B. et al. (1980) J. Geophysical Research, 85, 8107-8128. [3] Pinto, J. P. et al. (2021) Nature Communications, 12, 175. [4] Titov, D. V. et al. (2007) Cosmic Research, 21, 401. [5] O’Rourke, J. et al. (2019) Geophysical Research Lett., 46, 5768–5777. [6] Limaye, S. S. et al. (2018) Astrobiology, 18(9), 1181-1198. [7] Grinspoon, D. H. et al. (2013) Planetary and Space Sci., 41(7), 515-542. [8] Parker, R. L. (2003) J. Geophysical Research, 108, 5006. *The cost information contained in this document is of a budgetary and planning nature and is intended for informational purposes only. It does not constitute a commitment on the part of JPL and/or Caltech.

H Alpert↗

DOE OSTI2019

Size-resolved ice nucleating particle (INP) concentrations from the MOSAiC campaign

Sample collection: Ground-based immersion mode ice nucleation measurements were conducted on samples collected at the U.S. DOE ARM AMF2 onboard the R/V Polarstern P-deck during MOSAiC from 23 Oct 2019 to 01 Oct 2020. Samples were collected using a Davis Rotating-drum Unit for Monitoring (DRUM; DRUMAir, LLC) cascading impactor in 4 stages (i.e., size bins). Instrument information on the model used, the DA400, can be found at the DRUMAir website (http://www.drumair.com/). Stages A, B, C, and D had particle size cuts at 2.96, 1.21, 0.34, and 0.15 µm in particle diameter, respectively. Strips of sample substrate (PFA, perfluoroalkoxy; McMaster) were adhered to each disc in each stage and coated with petrolatum to enable particles to stick on impact. The discs move slowly over time, such that aerosol loading is streaked onto the PFA. Every 24 hours, a blank is created on the PFA to separate daily samples. During MOSAiC, the pump typically pulled 20 – 35 lpm (average of 32 lpm) at the inlet with all the discs in place in each stage. Daily samples were collected for each of the four stages, equaling 28,800 – 50,400 total L of air (average of 46,080 L total L of air) per sample. Discs rotated for approximately 24 days before the sampling per strip was complete and changed to a new disc. Discs were stored frozen after collection. Sample preparation for analysis: Following collection and transport from MOSAiC to the Kreidenweis/DeMott laboratory, care of PI Creamean, in Fort Collins, CO, strips were removed from the discs and cut up to separate daily samples. Each daily portion of the strip was stored in separate sterile 15-mL centrifuge tubes and stored in a standard commercial freezer until analysis (approximately 4 – 12 months after collection). Sample analysis: Drop freezing assays (DFAs) were conducted on one daily sample set every 3 – 4 days of the study for all four stages using the Colorado State University (CSU) cold plate (CP). Sample set days were chosen to cover the entire year of MOSAiC and avoiding days where the AOS purge system was activated. Immediately after removal from the freezer, 2 mL of 0.1-µm filtered deionized water was added with a single-use sterile syringe directly to the tubes, then mixed using a vortex mixer for at least 30 minutes at 500 rpm to resuspend particles from the PFA into the deionized water. Following sample preparation, another single-use syringe was used to create 100 aliquots on a 3-inch diameter copper plate, then covered with a transparent plastic dome. The drops were approximately the same volume (2.5 µL each), though careful inspection. The plate was cooled at approximately 3 – 10 K min-1 from room temperature until all drops froze on the plate. Temperature was measured by an Omega thermocouple probes and meter. Drop freezing was visually detected but recorded through monitoring software to provide the time frozen, channel of the meter used, temperature, and cooling rate for each drop. Not all 100 drops were always detected; the total number of rows in each data file equals the number of drops recorded, which typically was > 80 %. Each sample was tested three times (i.e., a new set of 100 drops was created for each test). Data provided are files containing these parameters. From the freezing temperatures recorded, the fraction frozen was and INP concentrations were calculated per L of air using the equation from Vali (1971): [INPs] = −(ln(f)/Valiquot)*(Vsuspension/Vair) where f is the proportion of droplets not frozen, Valiquot is the volume of each aliquot (i.e., 2.5e-6 L), Vsuspension is the volume of the suspension (i.e., 0.002 L), and Vair is the volume of air per sample (i.e., 36000 L). Data usage guidance: There are three files included with this dataset: (1) dumcp_inp_concentrations.csv which includes cumulative INP concentrations binned every 0.5 °C from 0 to –30 °C for all samples and size ranges (i.e., DRUM stages) processed via DFA using the CSU CP; (2) dumcp_inp_standard_deviation.csv which includes the standard deviations for all samples and temperatures in dumcp_inp_concentrations.csv; and (3) dumcp_blank_concentrations_standard_deviation.csv which includes the INP concentrations and standard deviations for the deionized water and PFA blanks binned every 0.5 °C from 0 to –30 °C. The first column in each file represents the freezing temperature in °C binned every 0.5 °C from 0 to –30 °C (first cell in this column = header = “temp”). The second column in each file represents the standard deviation of each temperature bin in °C (first cell in this column = header = “temperr”). For file (1) dumcp_inp_concentrations.csv, the remaining columns indicate the INP concentrations per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as “A_”, “B_”, “C_”, or “D_”) and date (“_yyyymmdd) of collection. For file (2) dumcp_inp_standard_deviation.csv, the remaining columns indicate the INP concentration standard deviation per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as “A_”, “B_”, “C_”, or “D_”) and date (“_yyyymmdd) of collection. For file (3) dumcp_blank_concentrations_standard_deviation.csv, the remaining columns indicate the INP concentrations and standard deviations for the deionized water blank (“di_0.1” and “di_0.1sd” for the concentrations and standard deviations, respectively) and PFA blank (“pfa” and “pfasd” for the concentrations and standard deviations, respectively). Please see Creamean et al. (2019a; 2018a; 2018b; 2019b) for additional details on DRUM sample collection and offline processing. For questions or help with data interpretation, contact Dr. Jessie Creamean (jessie.creamean@colostate.edu). References: Creamean, J. M., Mignani, C., Bukowiecki, N., and Conen, F.: Using spectra characteristics to identify ice nucleating particle populations during winter storms in the Alps, Atmos. Chem. Phys., 19, 8123–8140, 2019a. Creamean, J. M., Kirpes, R. M., Pratt, K. A., Spada, N. S., Maahn, M., de Boer, G., Schnell, R. C., and China, S.: Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location, Atmospheric Chemistry and Physics, 18, 18023-18042, 10.5194/acp-18-18023-2018, 2018a. Creamean, J. M., Primm, K. M., Tolbert, M. A., Hall, E. G., Wendell, J., Jordan, A., Sheridan, P. J., Smith, J., and Schnell, R. C.: HOVERCAT: A novel aerial system for evaluation of aerosol-cloud interactions, Atmospheric Measurement Techniques, 11, 3969-3985, 10.5194/amt-11-3969-2018, 2018b. Creamean, J. M., Cross, J. N., Pickart, R., McRaven, L., Lin, P., Pacini, A., Hanlon, R., Schmale, D. G., Ceniceros, J., Aydell, T., Colombi, N., Bolger, E., and DeMott, P. J.: Ice nucleating particles carried from below a phytoplankton bloom to the Arctic atmosphere, Geophys. Res. Lett., 46, 8572-8581, https://doi.org/10.1029/2019GL083039, 2019b. Vali, G.: Quantitative Evaluation of Experimental Results an the Heterogeneous Freezing Nucleation of Supercooled Liquids, Journal of the Atmospheric Sciences, 28, 402-409, 10.1175/1520-0469(1971)028<0402:qeoera>2.0.co;2, 1971.

4-stage DRUM aerosol collector (DA400),Ice nuclei,↗

DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗