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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Block-Structured Operator Inference for Coupled Multiphysics Model Reduction

This work presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the governing equation structure for each physics component and the structure of the coupling terms. Once the multiphysics structure is specified, the reduced-order model is learned from snapshot data following the nonintrusive Operator Inference methodology. In addition to preserving physical system structure, which in turn permits preservation of system properties such as stability and second-order structure, the block-structured approach has the advantages of reducing the overall dimensionality of the learning problem and admitting tailored regularization for each physics component. The numerical advantages of the block-structured formulation over a monolithic Operator Inference formulation are demonstrated for aeroelastic analysis, which couples aerodynamic and structural models. For the benchmark test case of the AGARD 445.6 wing, block-structured Operator Inference provides an average 20% online prediction speedup over monolithic Operator Inference across subsonic and supersonic flow conditions in both the stable and fluttering parameter regimes while preserving the accuracy achieved with monolithic Operator Inference.

42 ENGINEERING↗
DOE OSTI2025

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often require thousands of rollouts to learn new tasks. We argue that the interpretable nature of language often provides a much richer learning medium for LLMs, compared to policy gradients derived from sparse, scalar rewards. To test this, we introduce GEPA (Genetic-Pareto), a prompt optimizer that thoroughly incorporates natural language reflection to learn high-level rules from trial and error. Given any AI system containing one or more LLM prompts, GEPA samples trajectories (e.g., reasoning, tool calls, and tool outputs) and reflects on them in natural language to diagnose problems, propose and test prompt updates, and combine complementary lessons from the Pareto frontier of its own attempts. As a result of GEPA's design, it can often turn even just a few rollouts into a large quality gain. Across six tasks, GEPA outperforms GRPO by 6% on average and by up to 20%, while using up to 35x fewer rollouts. GEPA also outperforms the leading prompt optimizer, MIPROv2, by over 10% (e.g., +12% accuracy on AIME-2025), and demonstrates promising results as an inference-time search strategy for code optimization. We release our code at https://github.com/gepa-ai/gepa.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Diffuse back-illumination temperature imaging (DBI-TI), a novel soot thermometry technique

To meet stringent emissions regulations on soot emissions, it is critical to further advance the fundamental understanding of in-cylinder soot formation and oxidation processes. Among several optical techniques for soot quantification, diffuse back-illumination extinction imaging (DBI-EI) has recently gained traction mainly due to its ability to compensate for beam steering, which if not addressed, can cause unacceptably high measurement uncertainty. Until now, DBI-EI has only been used to measure the amount of soot along the line of sight, and here, we extend the capabilities of a DBI-EI setup to also measure in-cylinder soot temperature. This proof of concept of diffuse back-illumination temperature imaging (DBI-TI) as a soot thermometry technique is presented by implementing DBI-TI in a single cylinder, heavy-duty, optical diesel engine to provide 2-D line-of-sight integrated soot temperature maps. The potential of DBI-TI to be an accurate thermometry technique for use in optical engines is analyzed. The achievable accuracy is due in part to simultaneous measurement of the soot extinction, which circumvents the uncertainty in dispersion coefficients that depend on the optical properties of soot and the wavelength of light utilized. Analysis shows that DBI-TI provides temperature estimates that are closer to the mass-averaged soot temperature when compared to other thermometry techniques that are more sensitive to soot temperature closer to the detector. Furthermore, uncertainty analysis and Monte Carlo (MC) simulations provide estimates of the temperature measurement errors associated with this technique. The MC simulations reveal that for the light intensities and optical densities encountered in these experiments, the accuracy of the DBI-TI technique is comparable or even better than other established optical thermometry techniques. Thus, DBI-TI promises to be an easily implementable extension to the existing DBI-EI technique, thereby extending its ability to provide comprehensive line-of-sight integrated information on soot.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

SALSAA: a statistical approach to line shapes from an average atom

Ion-Stark line broadening is a key density diagnostic for hot dense plasmas relevant to inertial fusion and astrophysics. It is caused by interactions of a radiating ion with nearby perturbing ions, whose electric microfields lead to changes in bound-bound transition energies. Ion-Stark broadening becomes increasingly difficult to compute for complex, many-electron ions with myriad transitions. In this paper, we propose a simplified approach to ion-Stark broadening based on self-consistent ion distributions and electronic structure from an average-atom model. We find that this approach reproduces the line shape predictions of one traditional method for high-n K-shell emission lines in aluminum ions with accuracy sufficient for density diagnostics in thermal plasmas with equal ion and electron temperatures. We expect that this approach can be extended to provide a reasonable picture of ion-Stark broadening in many-electron ions, enabling rapid calculations of line profiles in complex spectra.

average-atom↗
DOE OSTI2021

Broadband Stability of the Habitable Zone Planet Finder Fabry–Pérot Etalon Calibration System: Evidence for Chromatic Variation

The comblike spectrum of a white light–illuminated Fabry–Pérot etalon can serve as a cost-effective and stable reference for precise Doppler measurements. Understanding the stability of these devices across their broad (hundreds of nanometers) spectral bandwidths is essential to realizing their full potential as Doppler calibrators. However, published descriptions remain limited to small bandwidths or short time spans. We present an ∼6 month broadband stability monitoring campaign of the Fabry–Pérot etalon system deployed with the near-infrared Habitable Zone Planet Finder (HPF) spectrograph. We monitor the wavelengths of each of ∼3500 resonant modes measured in HPF spectra of this Fabry–Pérot etalon (free spectral range = 30 GHz, bandwidth = 820–1280 nm), leveraging the accuracy and precision of an electro-optic frequency comb reference. These results reveal chromatic structure in the Fabry–Pérot mode locations and their evolution with time. We measure an average drift on the order of 2 cm s{sup –1} day{sup −1}, with local departures up to ±5 cm s{sup –1} day{sup −1}. We discuss these behaviors in the context of the Fabry–Pérot etalon mirror dispersion and other optical properties of the system and the implications for the use of similar systems for precise Doppler measurements. Our results show that this system supports the wavelength calibration of HPF at the ≲10 cm s{sup −1} level over a night and the ≲30 cm s{sup −1} level over ∼10 days. Our results also highlight the need for long-term and spectrally resolved study of similar systems that will be deployed to support Doppler measurement precision approaching ∼10 cm s{sup −1}.

42 ENGINEERING↗
DOE OSTI2023

Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and –3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.

14 SOLAR ENERGY↗
DOE OSTI2022

The complex heavy-quark potential in an anisotropic quark-gluon plasma — Statics and dynamics

We generalize a complex heavy-quark potential model from an isotropic QCD plasma to an anisotropic one by replacing the Debye mass m> D with an anisotropic screening mass depending on the quark pair alignment with respect to the direction of anisotropy. Such an angle-dependent mass is determined by matching the perturbative contributions in the potential model to the exact result obtained in the Hard-Thermal-Loop resummed perturbation theory. An advantage of the resulting potential model is that its angular dependence can be effectively described by using a set of angle-averaged screening masses as proposed in our previous work. Consequently, one could solve a one-dimensional Schrödinger equation with a potential model built by changing the anisotropic screening masses into the corresponding angle-averaged ones, and reproduce the full three-dimensional results for the binding energies and decay widths of low-lying quarkonium bound states to very high accuracy. Finally, turning to dynamics, we demonstrate that the one-dimensional effective potential can accurately describe the time evolution of the vacuum overlaps obtained using the full three-dimensional anisotropic potential. This includes the splitting of different p-wave polarizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multi-species temperature and number density analysis of a laser-produced plasma using dual-comb spectroscopy

Dual-comb spectroscopy (DCS) represents a novel method of using absorption spectroscopy as a diagnostic tool for multispecies analysis of excitation temperatures and column densities in laser-produced plasmas (LPPs). DCS was performed on a LPP generated by ablating a multielement alloy containing Nd, Gd, and Fe. Transitions from all three elements were observed in absorption spectra measured from 530.08 to 535.19 nm at seven time-delays from 31 to 250 μs after ablation. The spectra were fit using a nonlinear regression algorithm to determine peak areas, and excitation temperatures and column densities were determined for the three atomic species separately using Boltzmann plots. The measured excitation temperatures of Nd I and Gd I showed good agreement at all time-delays, whereas the Fe I temperature was found to be higher, and the ratios between the column densities varied with delay. The observations are understood via effects of LPP spatial averaging, elemental fractionation, and molecular formation and are compared and contextualized with previous work studying LPPs using other spectroscopic techniques. A brief discussion of the precision and accuracy of the determined excitation temperatures and column densities is also presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Simulations of the nEDM@SNS light collection system efficiency

Here, a system for collecting the scintillation light produced by the capture of ultra-cold neutrons (UCN) on polarized 3 He is discussed and results from simulations of its performance are presented. This system will be implemented in nEDM@SNS, the experiment searching for the neutron electric dipole moment (nEDM) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. Simulation results show that the light collection system detects on average 17 photoelectrons per UCN- 3 He capture event (sufficient to generate a robust signal), reconstructs the event location in the beam direction to approximately 3 cm accuracy, detects capture events with a high and spatially uniform efficiency (0.95 with 1% variation), and rejects greater than 50% of beta decay background events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗
DOE OSTI2023

HLPW-4/GMGW-3: High-Order Discretization Technology Focus Group Workshop Summary

This paper summarizes the High-Order Technical Focus Group (HO-TFG) submissions for the joint 4th AIAA High Lift Prediction (HLPW-4) and 3rd Geometry and Mesh Generation Workshop (GMGW-3). The goal of the workshop was to assess the state-of-the-art in mesh generation and computational fluid dynamics software. The Common Research Model High-Lift (CRM-HL) variant served as the primary focus of the workshop, and a two-dimensional airfoil section from the CRM-HL was used as a verification test case. Here, the HO-TFG was tasked with generating high-order curved meshes for both geometries, and computing high-order solutions using both Reynolds-averaged Navier–Stokes and scale-resolving formulations. While limited by computational resources, the final results demonstrate the potential of higher-order methods to increase solution accuracy with a lower degree-of-freedom count relative to second-order discretizations.

42 ENGINEERING↗
DOE OSTI2022

HLPW-4/GMGW-3: High Order Discretization Technology Focus Group Workshop Summary

This paper summarizes the High-Order Technical Focus Group (HO-TFG) submissions for the joint 4th AIAA High Lift Prediction and 3rd Geometry and Mesh Generation Workshop. The goal of the workshop was to assess the state-of-the-art in mesh generation and computational fluid dynamics software. The Common Research Model High-Lift (CRM-HL) variant served as the primary focus of the workshop, and a 2D airfoil section from the CRM-HL was used as a verification test case. The HO-TFG was tasked with generating high-order curved meshes for both geometries, and computing high-order solutions using both Reynolds Averaged Navier-Stokes and scale resolving formulations. While limited by computational resources, the final results demonstrate the potential of higher-order methods to increase solution accuracy with a lower degree of freedom count relative to second-order discretizations.

Galbraith, Marshall C.↗
DOE OSTI2022

Improved $^{95}\mathrm{Mo}$ neutron resonance parameters and astrophysical reaction rates

We report improved 95 Mo neutron resonance parameters and reaction rates are important for nuclear astrophysics, testing nuclear models, and nuclear criticality safety. However, despite many previous neutron-capture and total cross-section measurements on this nuclide, there still is much room for improvement as well as several discrepancies. For example, there are very few firm resonance spin and parity assignments; average resonance parameters are available only for each parity, the currently recommended astrophysical reaction rate results in disagreements between stellar models and meteoric isotopic anomalies, and there are substantial disagreements in the neutron-capture cross section at low energies important for nuclear criticality safety. To obtain an improved set of neutron resonance parameters and astrophysical reaction rates for 95 Mo. High-resolution neutron-capture and transmission data were measured at the Oak Ridge Electron Linear Accelerator (ORELA) using highly isotopically enriched 95 Mo samples. The neutron-capture apparatus, data reduction, and analysis were improved so that information contained in the γ-ray cascade following neutron capture were used to assign resonance J π values. Following this, simultaneous analysis of the new neutron-capture and transmission data was used to obtain resonance energies, gamma widths, and neutron widths and their uncertainties to a maximum energy of 10 keV. Accurate neutron-capture cross sections also were obtained for the unresolved resonance region to a maximum energy of 500 keV and, together with the new resonance parameters, used to calculate the astrophysical reaction rates in the temperature range from 5 to 30 keV. A vastly improved set of 95Mo neutron resonance parameters and an astrophysical reaction rate accurate to about 3% were obtained. Firm J π assignments were determined for 261 of the 314 observed resonances. This is a very large improvement over the previously published 32 firm J π assignments for 108 resonances. Also, the number of resonances having both firm J π assignments and Γ γ values was increased by almost a factor of 24—from 11 to 261. Neutron- and total-radiation-width distributions and average resonance spacings, average total radiation widths, and neutron strength functions were obtained for the six different s- and p-wave possibilities. Parameters for the lowest s-wave resonance, which is most important for criticality benchmarks, were obtained with high accuracy. Simple modification of the neutron-capture apparatus and expansion and improvement of data analysis techniques led to a large increase in firm J π assignments for 95 Mo neutron resonances. The resulting astrophysical reaction rate is 20%–30% larger than the currently recommended rate at s-process temperatures, which should lead to better agreement between stellar models and meteoric isotopic anomalies. The neutron-capture cross section at low energies is substantially larger than recommended in the latest evaluation, which is problematical for criticality benchmarks. The average resonance spacing as a function of spin and parity is significantly different from current models. The total-radiation-width distributions are significantly broader than predicted by theory and show significant departures from the expected Gaussian shapes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Residual estimation for grid modification in wall-modeled large eddy simulation using unstructured high-order methods

Here, the accuracy and computational cost of a large eddy simulation are highly dependent on the computational grid. Building optimal grids manually from a priori knowledge is not feasible in most practical use cases; instead, solution-adaptive strategies can provide a robust and cost-efficient method to generate a grid with the desired accuracy. We adapt the residual estimation algorithm developed by Toosi and Larsson for Discontinuous Galerkin Spectral Elements Methods (DGSEM) to guide the grid-adaptation process. The core of the method is the computation of the estimated modeling residual using the polynomial basis functions used in DGSEM, and the averaging of the estimated residual over each element. The final method is assessed in multiple channel flow test cases and for the transonic flow over an airfoil, in both cases making use of mortar interfaces between elements with hanging nodes. The method is found to be robust and reliable, and to provide solutions on grids with significantly fewer elements at comparable accuracy compared to when using human-generated grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

OpenET: Filling a Critical Data Gap in Water Management for the Western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗
DOE OSTI2022

Reduced-Order Modeling Method for Phase-Change Thermal Energy Storage Heat Exchangers

Thermal energy storage can facilitate the effective utilization of renewable energy. To speed up the design process of thermal energy storage devices, it is critical to develop fast and accurate modeling methods for phase change material embedded heat exchangers (PCM HXs). This study developed and compared two approximation-assisted reduced-order PCM HX models for the simulation of thermal storage components and systems, which were verified against a validated finite-volume model. They are a pure black-box model, and a grey-box model based on the Number of Transfer Units (or effectiveness-NTU) approach. We used the reduced-order models to predict the performance of standalone PCM HX for 1000 cases with different fluid inlet conditions and HX designs. We also integrated the models with a vapor compression system to predict the compressor energy consumption and total charging time under various conditions. The results show that overall, the black-box model gave more accurate results than the grey-box model. On average, the mean absolute deviation in the PCM HX fluid outlet temperature was 0.05 K and 0.1 K for the black-box model and grey-box model, respectively. The grey-box model gave larger temperature deviation toward the end of the phase change process, due to the simplified two-node PCM representation. On the system level, the mean absolute deviation in compressor energy consumption was 0.2% and 0.3% for the black-box model and grey-box model, respectively. Their mean absolute deviation in total charging time was 1.1% and 2.6%, respectively. In terms of computation efficiency, the system simulation speedup ratio gained by using the reduced-order models was 11 to 57. System simulation time was decreased from an average of 1465 s to an average of 59 s. This shows that the proposed reduced-order modeling methods can be used to predict system performance of PCM HXs with less than 3% accuracy penalty, and 25 times less computational time than finite-volume models, enabling faster design and evaluation of PCM thermal storage devices.

25 ENERGY STORAGE↗
DOE OSTI2020

Comparison of total emitted solar-induced chlorophyll fluorescence (SIF) and top-of-canopy (TOC) SIF in estimating photosynthesis

We report many studies have shown that solar-induced fluorescence (SIF) has a good potential to predict gross primary production (GPP) of vegetation. What we measured by remote sensing or near-surface platforms is top-of-canopy (TOC) SIF (SIF toc ), which is not necessarily equal or proportional to total emitted SIF (SIF tot ) from the entire canopy due to the (re)absorption and scattering effects. However, photosynthesis, the process that plants use to fix carbon from the atmosphere, occurs at the entire vertical canopy. Here, by using the recollision theory, we calculated SIF tot at 760 nm from the measured SIF toc , hyperspectral reflectance (R), canopy interception (i) and leaf albedo (ω l ). Among them, both SIF toc and R can be obtained from concurrent TOC spectral measurements; i and ω l in the near-infrared region can be estimated from the open access datasets with a good accuracy. Our result confirms that the measured SIF toc only accounts for a small fraction of SIF tot : the above-the-canopy sensor can only “see” on average 22.9% of SIF tot at Harvard Forest. SIF tot has the following advantages over SIF toc in estimating GPP: (1) SIF tot improves the diurnal estimate of canopy GPP, especially capable to capture the midday depression of photosynthesis which may cause the large discrepancies between SIF toc and GPP on a diurnal basis, (2) SIF tot produces a stronger correlation with GPP from plants with complex canopy structure or under sky conditions with more diffuse irradiance, and (3) the SIF tot -GPP relationship shows a stronger resilience to environmental stresses. The fluorescence escape ratio (f esc ), the ratio between SIF toc multiplied by π and SIF tot , is mostly determined by the sun-canopy-sensor geometry and leaf inclination distribution. The effect of LAI and the leaf chlorophyll concentration on f esc is marginal at the 760 nm wavelength. Our results suggest that converting SIF toc into SIF tot provides a better tool to understand and estimate GPP.

54 ENVIRONMENTAL SCIENCES↗