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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

Decay Curve Correction Analysis Report

The decay curve analysis that is done on the short-lived radionuclide gas samples is used to differentiate between gaseous radionuclides that have the same characteristic gamma decay energy, 511 kiloelectron-volts (keV). A sample of stack gas is isolated and the total counts in the 511 keV peak are counted repeatedly in 10-second intervals to evaluate the decay rate of the sample over time. Analysis of this decay data required a series of steps. First, a raw data report is generated by the gamma acquisition system, based on an analysis template within the acquisition software. The data report file was then loaded into Microsoft Word, and a macro was used to perform minor formatting (remove colons and insert tabs between data columns) to allow analysis within Excel. The file is then saved as a text file at this point. The text file is then uploaded into Excel and a series of macros are used to add labels, calculate radioactive decay constants, and analyze the gamma decay data using linear regression techniques. The analysis template has been used since 1998 for stack 53000303 (TA-53, building 0003, exhaust stack 03) and 2000 for stack 53000702. The overall process, including the gamma report format and the macros used in Word and Excel for processing the report, had remained unchanged until 2015. In October of 2015, staff made a change to the report template in the gamma acquisition software which resulted in an error in the calculations later performed by the Excel macro. This error was not caught until a more in-depth review of the analysis took place regarding 2020 data. This report covers a much more complete review of the issue that occurred regarding the decay curve analysis, a review of the calculations completed to correct the issue, a review of the updated decay curve analysis process, and recommendations for moving forward.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update: Preprint

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the Department of Energy's (DOE) Geothermal Technology Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and Levelized Cost of Energy (LCOE) of hydrothermal geothermal systems and EGS, and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and O&G, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Though drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves as of now.

API↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the U.S. Department of Energy's (DOE) Geothermal Technologies Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and levelized cost of energy (LCOE) of hydrothermal geothermal systems and enhanced geothermal systems (EGS), and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) to weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and the O&G sector, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Although drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves at this time.

API↗
DOE OSTI2021

Lowering post‐construction yield assessment uncertainty through better wind plant power curves

Abstract Many operational analyses of wind power plants require a statistical relationship, which can be called the wind plant power curve, to be developed between wind plant energy production and concurrent atmospheric variables. Currently, a univariate linear regression at monthly resolution is the industry standard for post‐construction yield assessments. Here, we evaluate the benefits in augmenting this conventional approach by testing alternative regressions performed with multiple inputs, at a finer time resolution, and using nonlinear machine‐learning algorithms. We utilize the National Renewable Energy Laboratory's open‐source software package OpenOA to assess wind plant power curves for 10 wind plants. When a univariate generalized additive model at daily or hourly resolution is used, regression uncertainty is reduced, in absolute terms, by up to 1.0 % and 1.2 % (corresponding to a −59 % and −80 % relative change), respectively, compared to a univariate linear regression at monthly resolution; also, a more accurate assessment of the mean long‐term wind plant production is achieved. Additional input variables also reduce the regression uncertainty: when temperature is added as an input to the conventional monthly linear regression, the operational analysis uncertainty connected to regression is reduced, in absolute terms, by up to 0.5 % (−43 % relative change) for wind power plants with strong seasonal variability. Adding input variables to the machine‐learning model at daily resolution can further reduce regression uncertainty, with up to a −10 % relative change. Based on these results, we conclude that a multivariate nonlinear regression at daily or hourly resolution should be recommended for assessing wind plant power curves.

17 WIND ENERGY↗
DOE OSTI2022

Demonstration of low-level biogenic fuel content using quench curve and direct liquid scintillation counting (LSC) methods

In this work, an investigation into the direct method for liquid scintillation counting (LSC) quantification of biogenic fuel content in fuel blendstock is presented. This method development intentionally used a colored matrix (~99 wt%), fossil diesel fraction, and low-level biogenic fractions (~1 wt%) to determine the applicability of the LSC technique in colored blend mixtures. LSC procedures for quench correction, including the use of an instrument internal standard (Quantulus SQP values), color quench curves, and an internal 14 C standard spike on samples containing low-level amounts of biogenic gasoline, jet, and diesel mixed with fossil fuel, were compared. Samples were analyzed on both Perkin-Elmer Quantulus and Tri-Carb instruments, and the 14 C contents were compared with those determined by accelerator mass spectrometry (AMS). Results from the Tri-Carb instrument showed that percent differences of <10 % compared to AMS-reported values are achievable at 5-hour count times despite colored samples. A comparison between the impact of chemical and color quenching in the fuel samples showed that color quenching in highly colored samples reduces efficiency significantly more than chemical quenching, indicating that chemical quench curves are not appropriate for highly colored biofuel/fossil-fuel blended samples. Results indicate that both the direct method with internal spike quench correction and the use of a color-quench curve provide accurate results for 1 % biogenic fuel blends. Additionally, we have explored the use of Fourier transform infrared (FTIR) spectroscopy in measuring the biogenic content of the colored blended fuel samples. Preliminary results show the presence of biogenic carbon-derived fingerprints that are absent in fossil-derived sample. However, further work is needed to develop an FTIR-based quantitative method.

09 BIOMASS FUELS↗
DOE OSTI2022

Surface fluctuating hydrodynamics methods for the drift-diffusion dynamics of particles and microstructures within curved fluid interfaces

Here we introduce fluctuating hydrodynamics approaches on surfaces for capturing the drift-diffusion dynamics of particles and microstructures immersed within curved fluid interfaces of spherical shape. We take into account the interfacial hydrodynamic coupling, traction coupling with the surrounding bulk fluid, and thermal fluctuations. For fluid-structure interactions, we introduce Immersed Boundary Methods (IBM) and related Stochastic Eulerian-Lagrangian Methods (SELM) for curved surfaces. We use these approaches to investigate the statistics of surface fluctuating hydrodynamics and microstructures. For velocity autocorrelations, we find characteristic power-law scalings $τ^{-1}, τ^{-2}$, and plateaus can emerge. This depends on the physical regime associated with the geometry, surface viscosity, and bulk viscosity. This differs from the characteristic $τ^{-3/2}$ scaling for bulk three dimensional fluids. We develop theory explaining these observed power-laws associated with time-scales for dissipation within the fluid interface and coupling to the surrounding fluid. We then use our introduced methods to investigate a few example systems and roles of hydrodynamic coupling and thermal fluctuations including for the kinetics of passive particles and active microswimmers in curved fluid interfaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-pitch nano-accuracy surface profiler for strongly curved X-ray mirror metrology

We present our recent research and development effort on the Multi-Pitch Nano-accuracy Surface Profiler (MPNSP). This metrology instrument is developed to characterize strongly curved X-ray mirrors proposed to achieve diffraction-limited soft X-ray focusing for scientific applications at the synchrotron beamlines. The measurement process consists of forward-and-backward scans on the test mirror surface along its tangential direction at multiple pitch angles. Our research and development in this work aim to take the challenge of measuring strongly curved X-ray mirrors with a typical total slope range ≳10 mrad, while maintaining the Root Mean Square (RMS) value of measurement repeatability and self-consistency at 50 nrad RMS level. We first introduce the mechanical design, followed by a brief review of the mathematical model and the optimization algorithm for the MPNSP technique. By detecting the rotation axis of the mirror pitch with a machine vision approach, we can determine and then reduce the vertical distance between the pitch rotation axis and the test mirror surface to a sub-mm level. In addition, we describe a practical data acquisition procedure for strongly curved X-ray mirrors with a total slope range larger than the slope measuring range of the autocollimator used in the instrument. As a result, the proposed MPNSP measurements with different mirror orientations achieve remarkable self-consistency and reproducibility of < 50 nrad RMS in slope and < 0.5 nm RMS in height.

42 ENGINEERING↗
DOE OSTI2020

The 1 H T 1 dispersion curve of fentanyl citrate to identify NQR parameters

We report the 1 H T 1 dispersion curve between 0 and 5 MHz for the synthetic opioid fentanyl citrate (C 28 H 36 N 2 O 8 ). The structures in the curve can be used to estimate the 14 N nuclear quadrupole resonance (NQR) frequencies of the material. Density functional theory predictions of the NQR parameters of several fentanyl citrate compounds are also reported. The predictions for the aniline nitrogen are consistent with structures in the observed T 1 data. To help interpret the fentanyl citrate results the T 1 dispersion curve for the explosive ammonium nitrate is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The effect of entrance flow development on vortex formation and wall shear stress in a curved artery model

In this work, we numerically investigate the effect of entrance condition on the spatial and temporal evolution of multiple three-dimensional vortex pairs and the wall shear stress distribution in a curved artery model. We perform this study using a Newtonian blood-analog fluid subjected to a pulsatile flow with two inflow conditions. The first flow condition is fully developed while the second condition is undeveloped (i.e., uniform). We discuss the connection along the axial direction between regions of organized vorticity observed at various cross sections of the model and compare results between the different entrance conditions. We model a human artery with a simple, rigid 180° curved pipe with a circular cross section and constant curvature, neglecting the effects of taper, torsion, and elasticity. Numerical results are computed from a discontinuous high-order spectral element flow solver. The flow rate used in this study is physiological. We observe differences in secondary flow patterns, especially during the deceleration phase of the physiological waveform where multiple vortical structures of both Dean-type and Lyne-type coexist. The results indicate that decreased axial velocities under an undeveloped condition produce smaller secondary flows that ultimately inhibit growth of any interior flow vortices. We highlight the effect of the entrance condition on the formation of these structures and subsequent appearance of abnormal inner wall shear stresses, which suggest there may be a lower prevalence of cardiovascular disease in curved arteries where the flow is rather undeveloped—a potentially physiologically significant result to help understand the influence of blood flow development on disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Noise-specific beating in the higher-level Ramsey curves of a transmon qubit

We report: in the higher levels of superconducting transmon devices and more generally charge sensitive devices, T 2 * measurements made in the presence of low-frequency time-correlated 1/f charge noise and quasiparticle-induced parity flips can give an underestimation of the total dephasing time. The charge variations manifest as beating patterns observed in the overlay of several Ramsey fringe curves and are reproduced with a phenomenological Ramsey curve model, which accounts for the charge variations. T 2 * dephasing times, which more accurately represent the total dephasing time, are obtained. The phenomenological model is compared with a Lindblad master equation model. Both models are found to be in agreement with one another and the experimental data. Finally, the phenomenological formulation enables a simple method in which the power spectral density for the low-frequency noise can be inferred from the overlay of several Ramsey curves.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The EBLM project – VIII. First results for M-dwarf mass, radius, and effective temperature measurements using CHEOPS light curves

ABSTRACT The accuracy of theoretical mass, radius, and effective temperature values for M-dwarf stars is an active topic of debate. Differences between observed and theoretical values have raised the possibility that current theoretical stellar structure and evolution models are inaccurate towards the low-mass end of the main sequence. To explore this issue, we use the CHEOPS satellite to obtain high-precision light curves of eclipsing binaries with low-mass stellar companions. We use these light curves combined with the spectroscopic orbit for the solar-type companion to measure the mass, radius, and effective temperature of the M-dwarf star. Here, we present the analysis of three eclipsing binaries. We use the pycheops data analysis software to fit the observed transit and eclipse events of each system. Two of our systems were also observed by the TESS satellite – we similarly analyse these light curves for comparison. We find consistent results between CHEOPS and TESS, presenting three stellar radii and two stellar effective temperature values of low-mass stellar objects. These initial results from our on-going observing programme with CHEOPS show that we can expect to have ∼24 new mass, radius, and effective temperature measurements for very low-mass stars within the next few years.

Swayne, M. I.↗
DOE OSTI2021

Rotation curves and scaling relations of extremely massive spiral galaxies

We study the kinematics and scaling relations of a sample of 43 giant spiral galaxies that have stellar masses exceeding $10^{11} \, {\rm M}_\odot$ and optical discs up to 80 kpc in radius. We use a hybrid 3D–1D approach to fit 3D kinematic models to long-slit observations of the H α-$\rm{[N\, \small {II}]}$ emission lines and we obtain robust rotation curves of these massive systems. We find that all galaxies in our sample seem to reach a flat part of the rotation curve within the outermost optical radius. We use the derived kinematics to study the high-mass end of the two most important scaling relations for spiral galaxies: the stellar/baryonic mass Tully–Fisher relation and the Fall (mass-angular momentum) relation. All galaxies in our sample, with the possible exception of the two fastest rotators, lie comfortably on both these scaling relations determined at lower masses, without any evident break or bend at the high-mass regime. When we combine our high-mass sample with low-mass data from the Spitzer Photometry & Accurate Rotation Curves catalogue, we find a slope of α = 4.25 ± 0.19 for the stellar Tully–Fisher relation and a slope of γ = 0.64 ± 0.11 for the Fall relation. Our results indicate that most, if not all, of these rare, giant spiral galaxies are scaled up versions of less massive discs and that spiral galaxies are a self-similar population of objects up to the very high-mass end.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Optical variability of quasars with 20-yr photometric light curves

ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Deep learning unresolved lensed light curves

ABSTRACT Gravitationally lensed sources may have unresolved or blended multiple images, and for time varying sources, the light curves from individual images can overlap. We use convolutional neural nets to both classify the light curves as due to unlensed, double, or quad lensed sources and fit for the time delays. Focusing on lensed supernova systems with time delays Δt ≳ 6 d, we achieve 100 per cent precision and recall in identifying the number of images and then estimating the time delays to σΔt ≈ 1 d, with a 1000× speedup relative to our previous Monte Carlo technique. This also succeeds for flux noise levels $\sim 10{{\ \rm per\ cent}}$. For Δt ∈ [2, 6] d, we obtain 94–98 per cent accuracy, depending on image configuration. We also explore using partial light curves where observations only start near maximum light, without the rise time data, and quantify the success.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Rotation curves and dynamical masses of MaNGA barred galaxies

In this paper we analyse a sample of 46 barred galaxies of MaNGA. Our goal is to investigate the stellar kinematics of these galaxies and obtain their rotation curves. Additionally, we aim to derive the total stellar and dynamical masses, as well as the maximum rotation velocity, in order to examine their distributions and scaling relations. Using the Pipe3D dataproducts publicly available we obtained the rotation curves, which were fitted considering two components of an axisymmetric Miyamoto–Nagai gravitational potential. We found a wide range of the maximum rotation velocities (117–340 ${\rm km\, s^{-1}}$), with a mean value of 200 ${\rm km\, s^{-1}}$. In addition we found that the total stellar and dynamical masses are in the range of log(M star /M ⊙ ) = 10.1−11.5, with a mean value of log(M star /M ⊙ ) = 10.8, and log(M dyn /M ⊙ ) = 10.4−12.0, with a mean value of log(M dyn /M ⊙ ) = 11.1, respectively. We found a strong correlation between dynamical mass and maximum velocity, between maximum velocity and magnitude, and between stellar mass and maximum velocity. According to these results, barred galaxies exhibit similar behaviour to that of normal spiral galaxies with respect to these relations, as well as in terms of the distribution of their dynamical mass and maximum rotation velocity. However, we found that the distribution of stellar masses of barred galaxies is statistically different from other samples including non-barred galaxies. Finally, analysing the galaxies that show nuclear activity, we find no difference with the rotation curves of normal galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The dark matter profile of the Milky Way inferred from its circular velocity curve

ABSTRACT In this paper, we construct the circular velocity curve of the Milky Way out to ∼30 kpc, providing an updated model of the dark matter density profile. We derive precise parallaxes for 120 309 stars with a data-driven model, using APOGEE DR17 spectra combined with GaiaDR3, 2MASS, and WISE photometry. At outer galactic radii up to 30 kpc, we find a significantly faster decline in the circular velocity curve compared to the inner parts. This decline is better fit with a cored Einasto profile with a slope parameter $0.91^{+0.04}_{-0.05}$ than a generalized Navarro–Frenk–White (NFW) profile. The virial mass of the best-fitting dark matter halo profile is only $1.81^{+0.06}_{-0.05}\times 10^{11}$ M⊙, significantly lower than what a generalized NFW profile delivers. We present a study of the potential systematics, affecting mainly large radii. Such a low mass for the Galaxy is driven by the functional forms tested, given that it probes beyond our measurements. It is found to be in tension with mass measurements from globular clusters, dwarf satellites, and streams. Our best-fitting profile also lowers the expected dark matter annihilation signal flux from the galactic centre by more than an order of magnitude, compared to an NFW profile-fit. In future work, we will explore profiles with more flexible functional forms to more fully leverage the circular velocity curve and observationally constrain the properties of the Milky Way’s dark matter halo.

Ou, Xiaowei (ORCID:0000000246699967)↗
DOE OSTI2024

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗
DOE OSTI2025

Probing Curved Spacetime with a Distributed Atomic Processor Clock

Quantum dynamics on curved spacetime has never been directly probed beyond the Newtonian limit. Although we can describe such dynamics theoretically, experiments would provide empirical evidence that quantum theory holds even in this extreme limit. The practical challenge is the minute spacetime curvature difference over the length scale of the typical extent of quantum effects. Here, we propose a quantum network of alkaline earth (like) atomic processors for constructing a distributed quantum state that is sensitive to the differential proper time between its constituent atomic processor nodes, implementing a quantum observable that is affected by post-Newtonian curved spacetime. Conceptually, we propose to delocalize one clock between three locations by encoding the presence or absence of a clock into the state of the local atoms. By separating three atomic nodes over approximately kilometer-scale elevation differences and distributing one clock between them via a 𝑊 state, we demonstrate that the curvature of spacetime is manifest in the interference of the three different proper times that give rise to three distinct beat notes in our nonlocal observable. We further demonstrate that 𝑁-atom entanglement within each node enhances the interrogation bandwidth by a factor of 𝑁. We discuss how our proposed system can probe new facets of fundamental physics, such as the linearity, unitarity, and probabilistic nature of quantum theory on curved spacetime. Our protocol combines several recent advances with neutral atom and trapped ions to realize a novel quantum probe of gravity uniquely enabled by quantum networks.

Covey, Jacob P. [Univ. of Illinois at Urbana-Champ↗