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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Contrasting Chemical Kinetic Parameters for Near In‐Service‐Temperature Aging and High‐Temperature Thermal Decomposition of Triaminotrinitrobenzene Formulations

Triaminotrinitrobenzene-based high explosives such as LX-17 offer high energy density and exceptional safety, yet their long-term aging behavior at low temperatures remains poorly understood. In this study, several legacy and new production lots of LX-17 were subjected to accelerated aging experiments below 100°C, during which the formation rate of the initial degradation product, monofurazan (F1), was monitored. Kinetic analysis was performed using a sample-age-aware computational approach, yielding activation energy estimates of 82–91 kJ mol −1 for the low-temperature initiation step—markedly lower than the ∼200 kJ mol −1 associated with high-temperature thermal decomposition. Extrapolation from established cookoff models supports the conclusion that the dominant degradation mechanism at low temperatures differs from that at high temperatures. In conclusion, our results provide a unified kinetic framework that bridges the gap between in-service conditions and high-temperature damage.

Chemistry - Chemical explosives↗
DOE OSTI2024

Laboratory Testing of the Temperature Sensor Qualification Device

The Temperature sensor Qualification Device (TQD) has been developed and tested under laboratory conditions to evaluate its thermal performance and the reliability of its retractable sensor system. The TQD is designed to provide an isothermal environment for temperature sensors in both test and reference zones during irradiation experiments. Initial testing revealed minimal radial and azimuthal temperature variations but identified a significant axial gradient. To address this, design modifications were implemented, including enhanced insulation and the addition of a small heater at the device's top. These changes are expected to produce a more uniform axial temperature profile, though further testing is recommended prior to irradiation. The retractable sensor mechanism was rigorously tested, achieving 1,350 cycles at room temperature and 332 cycles at 400°C before failure. The primary failure mechanism was the thermocouple becoming stuck in the wire guide or capillary tube. Based on these results, design improvements were proposed, such as incorporating a load cell for force monitoring and a stepper motor for precise sensor positioning.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

The Baltimore Community Weather Station Network: Filling the Urban Measurement Desert

Quantification and understanding of how heat, rainfall, and air quality vary within cities are needed to identify the area with the worst conditions, develop solutions to extreme weather, and assess the impact of proposed policies. However, neighborhood-level variability is not well quantified because there are few environmental measurement stations within cities. In Baltimore City, a community-based network of weather stations to address this issue has been developed through a partnership between universities, state agencies, and Baltimore residents. The weather stations are hosted by community partners, and the data collected are enabling the mapping of urban weather across the city and the testing of models and proposed mitigation strategies. In addition, the network provides direct community involvement, with resulting benefits of increased community engagement, education, and empowerment. Researchers have an opportunity to democratize the scientific process and ensure that local knowledge and lived experiences of city residents inform future decision-making. The approach could be used as a model for other cities that apply similar monitoring instruments for other environmental exposures.

community↗
DOE OSTI2025

Assessing the limitations of commercial sensors and models for supporting marine carbon dioxide removal monitoring: a case study

Several unknowns remain surrounding marine Carbon Dioxide Removal (mCDR) monitoring, reporting, and verification (MRV) practices and capabilities. Current in-situ sensor technology is limited (primarily pH and pCO 2 ), requiring calculations and assumptions to estimate changes in carbonate chemistry parameters, including total alkalinity (TA). Considering that cost, energy consumption, and accuracy of commercial sensors can vary by orders of magnitude, understanding how well existing sensors perform in an mCDR context is important for this emerging community. Likewise, documenting sensor limitations and how relatively simple models can optimize sensor deployments will improve MRV efforts and support protocol development. Here we (1) compare performance a variety of commercially available sensors in a blind mesocosm experiment simulating ocean alkalinity enhancement (OAE), and how sensor performance impacted carbonate chemistry estimates; (2) evaluate if sensors can distinguish the OAE signal from natural variability during a small scale OAE field test in Sequim Bay, WA, USA, and (3) use an idealized ocean biogeochemistry model to explore optimal sensor network design based on (1) and (2). Our mesocosm results indicate that correctly constraining pH uncertainty will be critical for accurate TA estimates with current sensor technology compared to the less impactful variation caused by uncertainty in pCO 2 (pH data that are presented throughout are reported on the total scale (pH T ) unless otherwise noted). Our pilot field test demonstrated that sensors were capable of distinguishing mCDR signatures from natural variability under optimal real-world conditions. Idealized modeling simulations of the field test showed that a range of sparse and dense (3 to 100) sensors sampling areas of detectable increases will underestimate the net change in surface pH by at least 35–55%, at both realistic and highly elevated alkalinity input levels. We also highlight the limitations of current sensing technology for MRV, and the importance of ocean biogeochemistry models as critical tools for predicting when and where mCDR signals will be detectable using available sensors. Overall, our findings suggest that commercially available pCO 2 sensors and some pH sensors will form an important backbone for mCDR MRV tasks, though complete MRV characterization will require these data to be used in combination with other tools.

OAE↗
DOE OSTI2021

Use Attainability Analysis for Upper Sandia Canyon

This document presents a use attainability analysis (UAA) for the perennial segment of Upper Sandia Canyon, which is located within the Los Alamos National Laboratory (LANL) property near Los Alamos, New Mexico.1 This UAA is consistent with 20.6.4.15 New Mexico Administrative Code (NMAC) (New Mexico Environment Department [NMED] 2011c), which describes the perennial segment as “Sandia Canyon from Sigma Canyon upstream to LANL [National Pollutant Discharge Elimination System] NPDES outfall 001.” The perennial segment’s designated uses are coldwater aquatic life, livestock watering, wildlife habitat, and secondary contact. 40 Code of Federal Regulations (CFR) § 131.10(g) permits a state to remove a designated use that is not an existing use (as defined in 40 CFR §131.3), if a UAA demonstrates that naturally occurring pollutant concentrations prevent the attainment of the use or if physical conditions related to the natural features of the water body preclude the attainment of the aquatic life protection use. This UAA considers whether natural physical conditions in Upper Sandia Canyon, specifically air and/or water temperatures, prevent the designated aquatic life use water temperature limits (i.e., coldwater) from being attained in the perennial segment. The weight of evidence presented in this UAA supports the conclusion that, based on air-water temperature modeling and instream thermograph data, the coolwater aquatic life designated use is currently the attainable use. Accordingly, it is recommended that the coolwater aquatic life designated use replace the coldwater aquatic life designated use in the Upper Sandia Canyon assessment unit (AU).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Smart Adhesive Joint with High-Definition Fiber-Optic Sensing for Automotive Applications

Structural health monitoring of fiber-reinforced composite-based joints for automotive applications during their manufacturing and on-demand assessment for its durability in working environments is critically needed. High-definition fiber-optic sensing is an effective method to measure internal strain/stress development using minimally invasive continuous sensors. The sensing fiber diameters are in the same order of magnitude when compared to reinforcement (glass, basalt, or carbon fibers) used in polymer composites. They also offer a unique ability to monitor the evolution of residual stresses after repeated thermal exposure with varying temperatures for automotive components/joints during painting using an electrophoretic painting process. In this paper, a high-definition fiber-optic sensor utilizing Rayleigh scattering is embedded within an adhesive joint between a carbon fiber-reinforced thermoset composite panel and an aluminum panel to measure spatially resolved strain development, residual strain, and thermal expansion properties during the electrophoretic paint process-simulated conditions. The strain measured by the continuous fiber-optic sensor was compared with an alternate technique using thermal digital image correlation. The fiber-optic sensor was able to identify the spatial variation of residual strains for a discontinuous carbon fiber-reinforced composite with varying local fiber orientations and resin content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Effect of Fe on Co-Based SiO2Al2O3 Mixed Support Catalyst for Fischer–Tropsch Synthesis in 3D-Printed SS Microchannel Microreactor

This research explores the effect of a composite support of SiO2 and Al2O3 with Fe and Co incorporated as catalysts for Fischer–Tropsch synthesis (FTS) using a 3D-printed stainless steel (SS) microchannel microreactor. Two mesoporous catalysts, FeCo/SiO2Al2O3 and Co/SiO2Al2O3, were synthesized via a one-pot (OP) method and extensively characterized using N2 physisorption, XRD, SEM, TEM, H2-TPR, TGA-DSC, FTIR, and XPS. H2-TPR results revealed that the synthesis method significantly affected the reducibility of metal oxides, thereby influencing the formation of active FTS sites. SEM-EDS and TEM further revealed a well-defined hexagonal matrix with a porous surface morphology and uniform metal ion distribution. FTS reactions, carried out in the 200–350 °C temperature range at 20 bar with a H2/CO molar ratio of 2:1, exhibited the highest activity for FeCo/SiO2Al2O3, with up to 80% CO conversion. Long-term stability was evaluated by monitoring the catalyst performance for 30 h on stream at 320 °C under identical reaction conditions. The catalyst was initially active for the methanation reaction for up to 15 h, after which the selectivity for CH4 declined. Correspondingly, the C4+ selectivity increased after 15 h of time-on-stream, indicating a shift in the product distribution toward longer-chain hydrocarbons. This trend suggests that the catalyst undergoes gradual activation or restructuring under reaction conditions, which enhances chain growth over time. The increase in C4+ products may be attributed to the stabilization of the active sites and suppression of methane or light hydrocarbon formation.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Structural Characterization of a Toppling Rock Slab From Array-Based Ambient Vibration Measurements and Numerical Modal Analysis

Accurate assessments of the internal structure and boundary conditions of unstable rock slopes are imperative for evaluating landslide hazard scenarios. However, instability characterization at depth remains challenging and is often limited by costly or invasive subsurface investigations. Here, we develop a new approach coupling array-based ambient vibration modal analysis and numerical modeling to improve structural characterization of rock slope instabilities at depth. We used ambient noise cross-correlation on 4 hr of seismic data recorded by an array of 30 nodal geophones at a 500-m-long toppling rock slab in Utah, USA to identify modal frequencies between 0.8 and 3.5 Hz and derive modal displacements. We show that transverse and longitudinal bending modes span the length of the instability, indicating an interconnected slab. Further, statistical comparison of field results with outputs from >1,000 finite element models with varying boundary conditions showed that the instability depth varies between 40–70 and 10–20 m in the middle and lateral regions, respectively. Our approach yields new information on the structural conditions of rock cliff and column instabilities at depth, which is not easily obtained by other means but is imperative for change detection monitoring and improved hazard assessments.

58 GEOSCIENCES↗
DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗
DOE OSTI2021

An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, we, in this paper, propose a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Satellite-based Investigation of Power-Line Vegetation Encroachment in the US (SILVANUS)

Rapid wide-area assessments of vegetation encroachment on transmission and distribution line rights-of-way (ROW) is a highly desirable capability for understanding risks to the power grid during severe weather and wildfire events. Conventional assessments are time-consuming and expensive due to the need for in-situ inspections and the use of aerial assets. Performing conventional assessments on a wide area would require immense resources and time that might not be available within the horizon of an expected adverse event. Developing a capability to accurately assess vegetation encroachment into ROWs will enable faster analysis of potential grid vulnerabilities in NAERM. This project sought to develop a prototype capability for rapid ROW vegetation encroachment assessments by using Puerto Rico as a test case. Puerto Rico is a heavily forested island territory frequently impacted by tropical cyclones that threaten the electric grid by downing trees across transmission and distribution lines. Multispectral satellite imagery (MSI) enable very high resolution (i.e., 0.5 - 2 meter) assessment of vegetation conditions at scale and with revisit times appropriate for regular monitoring (e.g., weekly to quarterly, depending on cloud cover) of the entire island. Synthetic aperture radar (SAR) data from satellites was also investigated as solution to the cloud-cover issue as they are active sensors that emit and receive a microwave signal rather than relying on solar illumination, and are therefore unaffected by cloud cover and can collect data during day or night. Finally, MSI-derived digital surface models (DSMs) map the height of objects relative to sea level, and were assessed for their ability to estimate the height of forest canopies relative to coincident transmission lines. The results of the mapping investigation are described in this report.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Optical tuning of the diamond Fermi level measured by correlated scanning probe microscopy and quantum defect spectroscopy

Quantum technologies based on quantum point defects in crystals require control over the defect charge state. Here we tune the charge state of shallow nitrogen-vacancy and silicon-vacancy centers by locally oxidizing a hydrogenated surface with moderate optical excitation and simultaneous spectral monitoring. The loss of conductivity and change in work function due to oxidation are measured in atmosphere using conductive atomic force microscopy and Kelvin probe force microscopy (KPFM). We correlate these scanning probe measurements with optical spectroscopy of the nitrogen-vacancy and silicon-vacancy centers created via implantation 15–25 nm beneath the diamond surface and annealing. The observed charge state of the defects as a function of optical exposure demonstrates that laser oxidation provides a way to precisely tune the Fermi level over a range of at least 2.00 eV. We also observe a significantly larger oxidation rate for implanted surfaces compared to unimplanted surfaces under ambient conditions. Here, combined with knowledge of the electron affinity of a surface, these results suggest KPFM is a powerful, high-spatial-resolution technique to advance surface Fermi level engineering for charge stabilization of quantum defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synchrotron-based techniques for characterizing STCH water-splitting materials

Understanding the role of oxygen vacancy–induced atomic and electronic structural changes to complex metal oxides during water-splitting processes is paramount to advancing the field of solar thermochemical hydrogen production (STCH). The formulation and confirmation of a mechanism for these types of chemical reactions necessitate a multifaceted experimental approach, featuring advanced structural characterization methods. Synchrotron X-ray techniques are essential to the rapidly advancing field of STCH in part due to properties such as high brilliance, high coherence, and variable energy that provide sensitivity, resolution, and rapid data acquisition times required for the characterization of complex metal oxides during water-splitting cycles. X-ray diffraction (XRD) is commonly used for determining the structures and phase purity of new materials synthesized by solid-state techniques and monitoring the structural integrity of oxides during water-splitting processes (e.g., oxygen vacancy–induced lattice expansion). X-ray absorption spectroscopy (XAS) is an element-specific technique and is sensitive to local atomic and electronic changes encountered around metal coordination centers during redox. While in operando measurements are desirable, the experimental conditions required for such measurements (high temperatures, controlled oxygen partial pressures, and H 2 O) practically necessitate in situ measurements that do not meet all operating conditions or ex situ measurements. Here, we highlight the application of synchrotron X-ray scattering and spectroscopic techniques using both in situ and ex situ measurements, emphasizing the advantages and limitations of each method as they relate to water-splitting processes. The best practices are discussed for preparing quenched states of reduction and performing synchrotron measurements, which focus on XRD and XAS at soft (e.g., oxygen K-edge, transition metal L-edges, and lanthanide M-edges) and hard (e.g., transition metal K-edges and lanthanide L-edges) X-ray energies. The X-ray absorption spectra of these complex oxides are a convolution of multiple contributions with accurate interpretation being contingent on computational methods. The state-of-the-art methods are discussed that enable peak positions and intensities to be related to material electronic and structural properties. Through careful experimental design, these studies can elucidate complex structure–property relationships as they pertain to nonstoichiometric water splitting. A survey of modern approaches for the evaluation of water-splitting materials at synchrotron sources under various experimental conditions is provided, and available software for data analysis is discussed.

08 HYDROGEN↗
DOE OSTI2025

Thermochemical Properties of a Water-Soluble Zr(IV)-Flavonolate Complex for Fluoride Sensing

Detection of fluoride in water samples is critical for monitoring many chemical, environmental, and biological processes, however, these measurements often rely on costly instrumentation. Here, this situation has motivated the design of simple to use, fieldable fluoride sensors. Previously, a fluorometric sensor based on (EDTA)­Zr­(H 2 O) 2 (EDTA = ethylenediamine-N,N,N′,N′-tetraacetate) and 3-hydroxyflavone (FlvH) was reported for fluoride detection in ethanol-H 2 O mixtures. Herein, we report the synthesis and characterization of the previously proposed Zr­(IV)-flavonolate complex as the dimethylammonium salt, [(EDTA)­Zr­(Flv)]­[NMe 2 H 2 ] (Flv = 3-hydroxyflavonolate), and detail its utility for aqueous fluoride sensing. This species exhibits an intense blue fluorescence upon excitation with near-UV light (λ ex = 390 nm; λ em = 460 nm) that is quenched in the presence of NaF (100 mM acetate buffer, pH = 5) with good sensitivity (LOD = 20.9 nM; [F – ] from 10 –8 to 10 –4 M) under neat aqueous conditions. The equilibrium constant (K eq = 1.26 ± 0.00184 × 10 8 M –2 ) and free energy (Δ$G^°_{\textrm{rxn}}$ = –11.0 kcal mol –1 ) were determined under the conditions used for fluoride sensing, indicating a highly favorable reaction with F – in water. Finally, we developed paper-based sensing strips for qualitative fluoride sensing by immobilizing the sensor in a deposited gel enabling good selectivity and reduced interference due to slower ion diffusion.

aqueous chemistry↗
DOE OSTI2023

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗
DOE OSTI2024

Advanced Energy Scale Correction Techniques for the X-ray Transition Edge Sensors of the Athena mission

The X-ray Integral Field Unit (X-IFU) onboard the future European X-ray telescope Athena will be the first space instrument carrying an array of more than a thousand transition edge sensors. One of the key challenges of the X-IFU is the measurement of narrow X-ray atomic lines to determine velocity shifts at an unprecedented level of accuracy. For this reason, the energy scale of the instrument needs to be known with extreme accuracy, of 0.4 eV (1σ) up to 7 keV. The energy scale will be measured on the ground through a dedicated calibration campaign using fiducial X-ray sources. Though calibrated, the energy scale is extremely sensitive to the environmental conditions around the TES array, and drifts in the readout chain electronics. Uncorrected, the energy scale can naturally drift up to hundreds of eVs. Changes of the TES gain will be monitored via onboard X-ray calibration sources, and the energy scale will be corrected either per pixel, or within a small groups of pixels. Although simulations show that a 0.4 eV level can be achieved, the very high accuracy required by the X-IFU calls for experimental validation. A dedicated measurement campaign has been performed by NASA Goddard Space Flight Center to characterize the energy scale of a prototype kilo-pixel array of X-IFU-representative TESs. The analysis of the data demonstrated the ability to correct for various drifts using two fiducial lines to track the temporal gain variation. In this paper, we propose to extend this study on the same data set by investigating multi-parameter correction techniques based on both the pulse-height of the fiducial line and the prepulse baseline level, using the knowledge of the TES energy scale at reference temperature/magnetic field set points acquired on the ground. Investigations on the co-adding of pixels to perform a joint correction over pools of pixels is also explored.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗