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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Implementation of an extensible property modeling framework in ESPEI with applications to molar volume and elastic stiffness models

Property models are becoming more widely adopted by commercial Calphad databases, but they are not nearly as common in non-commercial or traditional academic Calphad databases. A primary driver is that user-friendly Calphad modeling tools that support property models are not widely available. Here we present new property modeling capabilities that have been implemented in ESPEI (the Extensible, Self-optimizing Phase Equilibrium Infrastructure). These capabilities include both generating property model parameters from data and improvements to the algorithmic selection of the most appropriate model from a series of candidates. Additionally, two illustrative examples are given that use ESPEI to fit different property models. First, we generate molar volume model parameters for Group IV, V, and VI refractory BCC alloys based on the model by Lu et al. (2005). Second, we demonstrate the extensibility of ESPEI’s property modeling capabilities by implementing a custom PyCalphad model for BCC elastic stiffness parameters to generate and compare parameters to the ones assessed by Marker et al. (2018) using the same data. Property models generated by ESPEI can be used in PyCalphad or further optimized with uncertainty quantification using ESPEI.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2021

Prospective Single-Arm Phase 1 and 2 Study: Ipilimumab and Nivolumab With Thoracic Radiation Therapy After Platinum Chemotherapy in Extensive-Stage Small Cell Lung Cancer

Consolidative thoracic radiation therapy (TRT) has been shown to improve outcomes for patients with extensive stage small cell lung cancer. We hypothesized that the addition of ipilimumab (IPI) and nivolumab (NIVO) after TRT would improve outcomes for patients with extensive stage small cell lung cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Dynamic flow stress of pure polycrystalline aluminum: Pressure-shear plate impact experiments and extension of dislocation-based modeling to large strains

The dynamic thermo-mechanical behavior of pure aluminum has attracted renewed interest lately due to experimental observations of an anomalous increase in Hugoniot Elastic Limit (HEL) at incipient plasticity and elevated temperatures in polycrystalline pure metals. In context of current dislocation-mediated plasticity models for metals, this increase in dynamic strength is indicative of a transition in the rate controlling mechanism for dislocation glide from being thermally assisted to phonon-drag restricted due to increase in phonon viscosity at elevated temperatures. Though these studies have helped to shed light on these important mechanisms operative in FCC metals at incipient plasticity, the extent to which they contribute to flow stress, particularly at larger strains, remains unclear. Here, we address these questions through a combined experimental and modeling effort focused on investigating the evolution of dynamic flow stress in polycrystalline aluminum using experimental data gathered from a series of combined pressure-and-shear plate impact (PSPI) experiments designed to reveal the flow stress of pure aluminum at strain rates ~ 10 5 /s, plastic strains of up to 40% and temperatures ranging from room to 866 K. In all cases, the flow stress of aluminum, as inferred from the measured transverse particle velocity histories at the free surface of an elastic tungsten carbide target plate, reveals saturation with increasing plastic strains at stress levels that decrease with increasing test temperatures. Numerical simulations are performed to correlate the experimentally observed temperature and strain rate dependence of flow stress at small and large plastic strains using the Austin-McDowell dislocation-mediated plasticity model parametrized to normal plate impact experiments conducted in an earlier study by Zaretsky and Kanel (2012). Extensions to the model are made to better represent dynamic behavior of pure aluminum at larger plastic strains as observed in elevated temperature split Hopkinson Pressure bar (SPHB) experiments of Samanta (1971) and Lindholm and Yeakly (1965), and the combined pressure-and-shear plate-impact experiments conducted in the present study. The main theoretical extension to the Austin-McDowell model made in this paper is the introduction of a new rate- and temperature- dependent dynamic recovery function, which can potentially allow for an effective reduction in the rate of accumulation of dislocations at large plastic strains. The numerical predictions of the revised and re-calibrated plasticity model are brought into agreement with the experimental observations, correlating sufficiently well with dynamic yield stress at incipient plasticity and the flow stress levels at larger plastic strains, plastic strain rates in the range 10 3 – 10 6 /s, and elevated temperatures up to near melt. The model, in concert with the experimental measurements, suggests that at incipient plasticity the rate governing mechanism for plastic flow is phonon-drag restricted dislocation glide, whereas, at higher magnitudes of plastic strain, it transitions to stress-assisted thermally activated glide. The transition between these two rate governing mechanisms is controlled by the evolution of dislocations throughout the deformation process.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The small-angle neutron scattering extension in MCNPX and the SANS cross section for nanodiamonds

Detonation nanodiamonds provide an intriguing prospect for the development of a very cold neutron (VCN) source or as a high albedo material for VCN reflection helping to control leakage of cold and very cold neutrons in a moderator. The investigation of source and reflector designs necessitates the development of new simulation tools for existing Monte Carlo codes that include small angle neutron scattering (SANS). The SANS extension in MCNPX 2.7 provides an analytical model of hard-sphere scattering with variable scattering particle sizes, size distributions, and packing fractions in order to supplement currently existing scattering kernels as well as the capability to read an experimentally determined small angle neutron scattering profile from a data file. The SANS extension is discussed and compared to nanodiamond SANS measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

An NCrystal extension for thermal neutron scattering in MCNP

A new extension for MCNP has been developed that incorporates the NCrystal thermal scattering package in the form of a Fortran to C++ wrapper, which adds the capability to describe thermal neutron scattering in the NCrystal formalism instead of the ACE tabular format. This can be used to described poly- or single-crystalline materials as well as liquids. In conclusion, the functionality of this extension to MCNP is illustrated using a layered crystal monochromator, leakage of neutrons from a moderating sphere of material, and by simulating criticality benchmarks.

MCNP↗
DOE OSTI2022

The FastEddy® Resident-GPU Accelerated Large-Eddy Simulation Framework: Moist Dynamics Extension, Validation and Sensitivities of Modeling Non-Precipitating Shallow Cumulus Clouds

Herein we describe the moist dynamics formulation implemented within the graphics processing unit-resident large-eddy simulation FastEddy® model, which includes a simple saturation adjustment scheme for condensation and evaporation processes. Two LES model intercomparison exercises for non-precipitating shallow cumulus clouds are simulated in order to validate this model extension, including a static forcing and a time-dependent forcing case. Overall, we find our dynamical, thermodynamical and microphysical quantities, along with turbulence variability and fluxes, to be commensurate with the corresponding model intercomparison results. In addition, sensitivities to specific model settings are investigated. Among these settings, it is shown that boundary layer and cloud layer structure and characteristics are sensitive to use of higher-order advection schemes impacting the vertical distribution of cloud content and associated turbulence statistics. Increasing the timescale of the saturation scheme leads to enhanced liquid water presence and decreases vertical velocity variance within the cloud deck. In some cases, these sensitivities agree with the model-to-model variability reported in the intercomparison exercises, highlighting the important role of specific model implementation choices in the context of shallow cumulus convection simulations. These analyses and findings also provide the basis for future extensions and applications of FastEddy® for modeling moist convection and precipitation scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Extensive hydrogen incorporation is not necessary for superconductivity in topotactically reduced nickelates

Abstract A key open question in the study of layered superconducting nickelate films is the role that hydrogen incorporation into the lattice plays in the appearance of the superconducting state. Due to the challenges of stabilizing highly crystalline square planar nickelate films, films are prepared by the deposition of a more stable parent compound which is then transformed into the target phaseviaa topotactic reaction with a strongly reducing agent such as CaH 2 . Recent studies, both experimental and theoretical, have introduced the possibility that the incorporation of hydrogen from the reducing agent into the nickelate lattice may be critical for the superconductivity. In this work, we use secondary ion mass spectrometry to examine superconducting La 1−x X x NiO 2 / SrTiO 3 (X= Ca and Sr) and Nd 6 Ni 5 O 12 / NdGaO 3 films, along with non-superconducting NdNiO 2 / SrTiO 3 and (Nd,Sr)NiO 2 / SrTiO 3 . We find no evidence for extensive hydrogen incorporation across a broad range of samples, including both superconducting and non-superconducting films. Theoretical calculations indicate that hydrogen incorporation is broadly energetically unfavorable in these systems, supporting our conclusion that extensive hydrogen incorporation is not generally required to achieve a superconducting state in layered square-planar nickelates.

Science & Technology - Other Topics↗
DOE OSTI2021

Extensive Genome-Wide Phylogenetic Discordance Is Due to Incomplete Lineage Sorting and Not Ongoing Introgression in a Rapidly Radiated Bryophyte Genus

The relative importance of introgression for diversification has long been a highly disputed topic in speciation research and remains an open question despite the great attention it has received over the past decade. Gene flow leaves traces in the genome similar to those created by incomplete lineage sorting (ILS), and identification and quantification of gene flow in the presence of ILS is challenging and requires knowledge about the true phylogenetic relationship among the species. We use whole nuclear, plastid, and organellar genomes from 12 species in the rapidly radiated, ecologically diverse, actively hybridizing genus of peatmoss (Sphagnum) to reconstruct the species phylogeny and quantify introgression using a suite of phylogenomic methods. We found extensive phylogenetic discordance among nuclear and organellar phylogenies, as well as across the nuclear genome and the nodes in the species tree, best explained by extensive ILS following the rapid radiation of the genus rather than by postspeciation introgression. Our analyses support the idea of ancient introgression among the ancestral lineages followed by ILS, whereas recent gene flow among the species is highly restricted despite widespread interspecific hybridization known in the group. Our results contribute to phylogenomic understanding of how speciation proceeds in rapidly radiated, actively hybridizing species groups, and demonstrate that employing a combination of diverse phylogenomic methods can facilitate untangling complex phylogenetic patterns created by ILS and introgression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Investigating the effect of Milky Way dwarf spheroidal galaxies extension on dark matter searches with Fermi-LAT data

Satellite galaxies of the Milky Way with high mass-to-light ratios and little baryon content, i.e., dwarf spheroidal galaxies (dSphs), are among the most promising targets to detect or constrain the nature of dark matter (DM) through its final annihilation products into high-energy photons. Previously, the assumption that DM emission from dSphs is pointlike has been used to set strong constraints on DM candidates using data from the Fermi Large Area Telescope (LAT). However, due to their high DM densities and proximity, dSphs actually have sufficient angular extension to be detected by the Fermi-LAT. Here, we perform a comprehensive analysis about the impact of accounting for angular extension in the search for gamma-ray DM signals toward known dSphs with Fermi-LAT. Further, we show that, depending on the dSph under consideration, limits on the DM cross section can be weakened by up to a factor of 2–2.5, while the impact on the stacked, i.e., combined, limits is at most 1.5–1.8 depending on the annihilation channel. This result is of relevance when comparing dSph limits to other multimessenger DM constraints and for testing the DM interpretation of anomalous “excesses.”

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Dark Energy Survey Year 3 results: Constraints on extensions to Λ CDM with weak lensing and galaxy clustering

We constrain six possible extensions to the Λ cold dark matter (CDM) model using measurements from the Dark Energy Survey’s first three years of observations, alone and in combination with external cosmological probes. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data vectors and blind analyses of real data to validate the robustness of our results to astrophysical and modeling systematic errors. In many cases, constraining power is limited by the absence of theoretical predictions beyond the linear regime that are reliable at our required precision. The Λ CDM extensions are dark energy with a time-dependent equation of state, nonzero spatial curvature, additional relativistic degrees of freedom, sterile neutrinos with eV-scale mass, modifications of gravitational physics, and a binned σ 8 ( z ) model which serves as a phenomenological probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find ( w p , w a ) = ( - 0.9 9 - 0.17 + 0.28 , - 0.9 ± 1.2 ) at 68% confidence with z p = 0.24 from the DES measurements alone, and ( w p , w a ) = ( - 1.0 3 - 0.03 + 0.04 , - 0. 4 - 0.3 + 0.4 ) with z p = 0.21 for the combination of all data considered. Curvature constraints of Ω k = 0.0009 ± 0.0017 and effective relativistic species N eff = 3.1 0 - 0.16 + 0.15 are dominated by external data, though adding DES information to external low-redshift probes tightens the Ω k constraints that can be made without cosmic microwave background observables by 20%. For massive sterile neutrinos, DES combined with external data improves the upper bound on the mass m eff by a factor of 3 compared to previous analyses, giving 95% limits of ( Δ N eff , m eff ) ≤ ( 0.28 , 0.20 eV ) when using priors matching a comparable Planck analysis. For modified gravity, we constrain changes to the lensing and Poisson equations controlled by functions Σ ( k , z ) = Σ 0 Ω Λ ( z ) / Ω Λ , 0 and μ ( k , z ) = μ 0 Ω Λ ( z ) / Ω Λ , 0 , respectively, to Σ 0 = 0. 6 - 0.5 + 0.4 from DES alone and ( Σ 0 , μ 0 ) = ( 0.04 ± 0.05 , 0.0 8 - 0.19 + 0.21 ) for the combination of all data, both at 68% confidence. Overall, we find no significant evidence for physics beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Performance of an Astrophysical Radiation Hydrodynamics Code under Scalable Vector Extension Optimization

We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. Here, we performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a “deeper dive” into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗
DOE OSTI2020

An Extensible Software and Communication Platform for Distributed Energy Resource Management

This paper introduces a novel Distributed Extensible Grid Control (DEGC) software and communication platform to facilitate the control of distributed energy resources on electric grids. The DEGC software platform leverages state-of-the-art advances in secure, distributed communication and decentralized authorization and authentication. We discuss how these advances enable the kind of robust and secure communication required for a distributed grid control platform, and show how DEGC applies these technologies to the agile development and deployment of grid software through an extensible and flexible API. Here, we describe how DEGC can implement both Volt-VAR voltage magnitude control and Phasor-Based Control as sample applications and demonstrate the DEGC platform in hardware with the demanding Phasor-Based Control test case, and provide performance metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Dual activity of anthocyanidin reductase supports the dominant plant proanthocyanidin extension unit pathway

Proanthocyanidins (PAs) are plant natural products important for agriculture and human health. They are polymers of flavan-3-ol subunits, commonly (-)-epicatechin and/or (+)-catechin, but the source of the in planta extension unit that comprises the bulk of the polymer remains unclear, as does how PA composition is determined in different plant species. Anthocyanidin reductase (ANR) can generate 2,3-cis-epicatechin as a PA starter unit from cyanidin, which itself arises from 2,3-trans-leucocyanidin, but ANR proteins from different species produce mixtures of flavan-3-ols with different stereochemistries in vitro. Genetic and biochemical analyses here show that ANR has dual activity and is involved not only in the production of (-)-epicatechin starter units but also in the formation of 2,3-cis-leucocyanidin to serve as (-)-epicatechin extension units. Differences in the product specificities of ANRs account for the presence/absence of PA polymerization and the compositions of PAs across plant species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Extension of the bright high-harmonic photon energy range via nonadiabatic critical phase matching

The concept of critical ionization fraction has been essential for high-harmonic generation, because it dictates the maximum driving laser intensity while preserving the phase matching of harmonics. In this work, we reveal a second, nonadiabatic critical ionization fraction, which substantially extends the phase-matched harmonic energy, arising because of the strong reshaping of the intense laser field in a gas plasma. We validate this understanding through a systematic comparison between experiment and theory for a wide range of laser conditions. In particular, the properties of the high-harmonic spectrum versus the laser intensity undergoes three distinctive scenarios: (i) coincidence with the single-atom cutoff, (ii) strong spectral extension, and (iii) spectral energy saturation. We present an analytical model that predicts the spectral extension and reveals the increasing importance of the nonadiabatic effects for mid-infrared lasers. These findings are important for the development of high-brightness soft x-ray sources for applications in spectroscopy and imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Primordial nucleosynthesis with non-extensive statistics

The conventional Big Bang model successfully anticipates the initial abundances of 2 H(D), 3 He, and 4 He, aligning remarkably well with observational data. However, a persistent challenge arises in the case of 7 Li, where the predicted abundance exceeds observations by a factor of approximately three. Despite numerous efforts employing traditional nuclear physics to address this incongruity over the years, the enigma surrounding the lithium anomaly endures. In this context, we embark on an exploration of Big Bang nucleosynthesis (BBN) of light element abundances with the application of Tsallis non-extensive statistics. A comparison is made between the outcomes obtained by varying the non-extensive parameter q away from its unity value and both observational data and abundance predictions derived from the conventional big bang model. Here, a good agreement is found for the abundances of 4 He, 3 He and 7 Li, implying that the lithium abundance puzzle might be due to a subtle fine-tuning of the physics ingredients used to determine the BBN. However, the deuterium abundance deviates from observations.

Bertulani, Carlos A.↗
DOE OSTI2023

Extensions to the SENSEI In situ Framework for Heterogeneous Architectures

The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper memory hierarchies on these systems. In this work, we discuss challenges that arise in in situ code coupling on these heterogeneous architectures. In particular, we present data and execution model extensions to the SENSEI in situ framework that are targeted at the effective use of systems with heterogeneous architectures. We then use these new data and execution model extensions to investigate several in situ placement and execution configurations and to analyze the impact these choices have on overall performance.

Loring, Burlen↗