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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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557 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

Rogozenski, Paul [Carnegie Mellon U.; Arizona U.] ↗
DOE OSTI2022

A multistage distributionally robust optimization approach to water allocation under climate uncertainty

This paper investigates a Multistage Distributionally Robust Optimization (MDRO) approach to water allocation under climate uncertainty. The MDRO is formed by creating sets of conditional distributions (called conditional ambiguity sets) on a finite scenario tree. The distributions in the conditional ambiguity sets remain close to a nominal conditional distribution according a ø-divergence (e.g., Kullback-Leibler divergence, Hellinger distance, Burg entropy, etc.). Here, the paper discusses a decomposition algorithm to solve the resulting MDRO with ø-divergences, which uses the dual formulation and solves only linear subproblems instead of convex ones. Some properties of the algorithm such as generating feasible policies and valid upper/lower bounds are established. The paper then applies the modeling and solution techniques to allocate water in a rapidly-developing area of Tucson, Arizona. Tucson, like many arid and semi-arid regions around the world, faces considerable uncertainty in its ability to provide water for its citizens in the future. The primary sources of uncertainty in the Tucson region include (1) unpredictable population growth, (2) the availability of water from the Colorado River, and (3) the effects of climate variability on water consumption. This paper integrates forecasts for all these sources of uncertainty into a single optimization model for robust and sustainable water allocation. Then, it uses this model to analyze the value of constructing additional treatment facilities to reduce future water shortages. The results indicate that the MDRO approach can be very valuable for water managers by providing insights to minimize their risks and help them plan for the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Excitation-Dependent High-Lying Excitonic Exchange via Interlayer Energy Transfer from Lower - to - Higher Bandgap 2D Material

High light absorption (~15%) and strong photoluminescence (PL) emission in monolayer (1L) transition metal dichalcogenides (TMDs) make them ideal candidates for optoelectronic device applications. Competing interlayer charge transfer (CT) and energy transfer (ET) processes control the photocarrier relaxation pathways in TMD heterostructures (HSs). In TMDs, long-distance ET can survive up to several tens of nm, unlike the CT process. Our experiment shows that an efficient ET occurs from the 1Ls WSe 2 -to-MoS 2 with an interlayer hexagonal boron nitride (hBN), due to the resonant overlapping of the high-lying excitonic states between the two TMDs, resulting in enhanced HS MoS 2 PL emission. This type of unconventional ET from the lower-to-higher optical bandgap material is not typical in the TMD HSs. With increasing temperature, the ET process becomes weaker due to the increased electron–phonon scattering, destroying the enhanced MoS 2 emission. Our work provides new insight into the long-distance ET process and its effect on the photocarrier relaxation pathways.

2D material↗
DOE OSTI2024

Impact of Momentum Perturbation on Convective Boundary Layer Turbulence

Mesoscale-to-microscale coupling is an important tool for conducting turbulence-resolving multiscale simulations of realistic atmospheric flows, which are crucial for applications ranging from wind energy to wildfire spread studies. Different techniques are used to facilitate the development of realistic turbulence in the large-eddy simulation (LES) domain while minimizing computational cost. Here, we explore the impact of a simple and computationally efficient Stochastic Cell Perturbation method using momentum perturbation (SCPM-M) to accelerate turbulence generation in boundary-coupled LES simulations using the Weather Research and Forecasting model. We simulate a convective boundary layer (CBL) to characterize the production and dissipation of turbulent kinetic energy (TKE) and the variation of TKE budget terms. Furthermore, we evaluate the impact of applying momentum perturbations of three magnitudes below, up to, and above the CBL on the TKE budget terms. Momentum perturbations greatly reduce the fetch associated with turbulence generation. When applied to half the vertical extent of the boundary layer, momentum perturbations produce an adequate amount of turbulence. However, when applied above the CBL, additional structures are generated at the top of the CBL, near the inversion layer. The magnitudes of the TKE budgets produced by SCPM-M when applied at varying heights and with different perturbation amplitudes are always higher near the surface and inversion layer than those produced by No-SCPM, as are their contributions to the TKE. This study provides a better understanding of how SCPM-M reduces computational costs and how different budget terms contribute to TKE in a boundary-coupled LES simulation.

17 WIND ENERGY↗
DOE OSTI2020

Temperature dependence of electron-phonon interactions in vanadium

First-principles calculations were used to study the Fermi surface of body-centered cubic vanadium at elevated temperatures. Supercell calculations accounted for effects of thermal atom displacements on band energies, and band unfolding was used to project the spectral weight of the electron states into the Brillouin zone of a standard bcc unit cell. An electronic topological transition (ETT, or Lifshitz transition) occurred near the Γ point with increasing temperature, but the large thermal smearings from the atomic disorder and the Fermi-Dirac distribution reduced the effect of this ETT on the electron-phonon interactions. The phonon dispersions showed thermal stiffening of their Kohn anomalies near the Γ point and of the longitudinal N phonon mode. Finally, in general the effects of the ETT were overcome by the thermal smearing of the Fermi surface that reduces the spanning vector densities for anomalous phonon modes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Charge density wave with anomalous temperature dependence in UPt 2 Si 2

Using single-crystal neutron and x-ray diffraction, we discovered a charge density wave (CDW) below 320 K, which accounts for the long-sought origin of the heat capacity and resistivity anomalies in UPt 2 Si 2 . The modulation wave vector, Q mod , is intriguingly similar to the incommensurate wave vector of URu 2 Si 2 . Q mod shows an unusual temperature dependence, shifting from commensurate to incommensurate position upon cooling and becoming locked at aproximately (0.42 0 0) near 180 K. Furthermore, bulk measurements indicate a crossover toward a correlated coherent state around the same temperature, suggesting an interplay between the CDW and Kondo-lattice-like coherence before coexisting antiferromagnetic order sets in at T N =35 Κ.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Orbital selective spin waves in detwinned NaFeAs

The existence of orbital-dependent electronic correlations has been recognized as an essential ingredient to describe the physics of iron-based superconductors. NaFeAs, a parent compound of iron-based superconductors, exhibits a tetragonal-to-orthorhombic lattice distortion below T s ≈ 60 K, forming an electronic nematic phase with two 90° rotated (twinned) domains, and orders antiferromagnetically below T N ≈ 42 K. We use inelastic neutron scattering to study spin waves in uniaxial pressure-detwinned NaFeAs. By comparing the data with combined density functional theory and dynamical mean-field theory calculations, we conclude that spin waves up to an energy scale of E crossover ≈ 100 meV are dominated by d yz -d yz intraorbital scattering processes, which have the twofold (C 2 ) rotational symmetry of the underlying lattice. On the other hand, the spin wave excitations above E crossover , which have approximately fourfold (C 4 ) rotational symmetry, arise from the d xy -d xy intraorbital scattering that controls the overall magnetic bandwidth in this material. In addition, we find that the low-energy (E ≈ 6 meV) spin excitations change from approximate C 4 to C 2 rotational symmetry below a temperature T* (>T s ), while spin excitations at energies above E crossover have approximate C 4 rotational symmetry and are weakly temperature dependent. Here, these results are consistent with angle-resolved photoemission spectroscopy measurements, where the presence of a uniaxial strain necessary to detwin NaFeAs also raises the onset temperature T* of observable orbital-dependent band splitting to above T s , thus supporting the notion of orbital selective spin waves in the nematic phase of iron-based superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electron-phonon coupling in M⁢n 1−𝑥 ⁢F⁡e 𝑥⁢ Si

We present a study of the lattice dynamical properties of M⁢n 1−𝑥⁢ F⁡e 𝑥 ⁢Si with 0≤𝑥≤0.22. Employing time-of-flight neutron spectroscopy and inelastic x-ray scattering, we investigate the doping dependence of phonon energies, 𝐸 ph , and linewidths, Γ ph . We find anomalous softening and broadening of a phonon mode propagating along the direction. Ab initio lattice dynamical calculations link this softening to an enhanced electron-phonon coupling due to the doping-dependent changes of the Fermi surface. In conclusion, we discuss an interplay of increased electron-phonon coupling and reduced ordered magnetic moments in M⁢n 1−𝑥⁢ F⁡e 𝑥 ⁢Si.

Density functional theory↗
DOE OSTI2021

Joint Modeling of Access Mode and Parking Choice of Air Travelers Using Revealed Preference Data

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Risk-Averse Approach for Distribution Grid Expansion Planning

Recent episodes of natural disasters have challenged the resilience of power grids. Adequate distribution grid planning that properly captures the risk aversion of the utility system planner is a key factor to increase the flexibility of distribution networks to circumvent these events. In this paper, we propose a methodology to determine the optimal portfolio of investments in lines and storage devices in order to minimize a convex combination between expected value and CVaR of operational costs, including energy not served, while taking into account the multistage nature of the energy storage management within this context. While the expected value of energy not served has been traditionally employed to tackle routine failures, we also minimize the CVaR of energy not served to address high-impact, low-probability (HILP) events. We illustrate the performance of the proposed methodology with a 54-Bus system test case.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The Intrinsic Shapes of Low Surface Brightness Galaxies (LSBGs): A Discriminant of LSBG Galaxy Formation Mechanisms

We use the low surface brightness galaxy (LSBG) samples created from the Hyper Suprime-Cam Subaru Strategic Program (781 galaxies), the Dark Energy Survey (20977 galaxies), and the Legacy Survey (selected via H ι detection in the Arecibo Legacy Fast ALFA Survey, 188 galaxies) to infer the intrinsic shape distribution of the LSBG population. To take into account the effect of the surface brightness cuts employed when constructing LSBG samples, we simultaneously model both the projected ellipticity and the apparent surface brightness in our shape inference. We find that the LSBG samples are well characterized by oblate spheroids, with no significant difference between red and blue LSBGs. This inferred shape distribution is in good agreement with similar inferences made for ultra-diffuse cluster galaxy samples, indicating that environment does not play a key role in determining the intrinsic shape of LSBGs. In this study, we also find some evidence that LSBGs are more thickened than similarly massive high surface brightness dwarfs. We compare our results to intrinsic shape measures from contemporary cosmological simulations, and find that the observed LSBG intrinsic shapes place considerable constraints on the formation path of such galaxies. In particular, LSBG production via the migration of star formation to large radii produces intrinsic shapes in good agreement with our observational findings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Spectra-to-exposure conversion using polynomial response models for gamma-ray field characterization

Accurate measurement of exposure rate from gamma-ray spectral data remains a critical challenge during radiological emergency response operations. Conventional methods rely on pre-defined static conversion factors derived from fixed geometries and isotopic compositions, which often fail to capture real-world environmental variability. This study presents a generalized approach as a "next-step" for converting gamma-ray spectral data into exposure rate using polynomial response models. The method introduces a flexible weighting scheme based on the in-situ detector response to distributed sources, enabling a pathway towards improved correspondence between measured spectra and "ground-truth" exposure rates. Experimental data from sodium iodide NaI(Tl) detectors were used to validate the approach as, at least equivalent to the current count-to-exposure method employed in emergency response CONOPS. Results show that the polynomial weighting model is sufficiently equal to the count-to-exposure method and may help improve accuracy given its adaptability to real-world conditions.

61 RADIATION PROTECTION AND DOSIMETRY↗