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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting the X-ray Absorption Spectrum of Ozone with Single Configuration State Functions

X-ray absorption spectra (XAS) of biradicaloid species are often thought to represent a challenge to theoretical methods. This has led to the testing of recently developed multireference techniques on the XAS of ozone, but reproduction of the experimental spectral profile has proven difficult. We utilize a minimal model consisting of a single configuration state function (CSF) per excited state to model core-level excitations of ozone, with the orbitals of each CSF optimized using the restricted open-shell Kohn–Sham (ROKS) method. This protocol leads to semiquantitative agreement with experimental XAS. In fact, we find that low-lying core-hole excited states in biradicaloids can be approximated with individual CSFs, despite the presence of multireference character in the ground state. Here, we also report that the 1s → π* and 1s → σ* transitions have quite distinct widths for O 3 . This reveals the importance of sampling over a representative range of geometries from the vibrational ground state for properly assessing the accuracy of electronic structure methods against experiments instead of the popular procedure of uniformly broadening stick spectra at the equilibrium geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. As a result, the utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Investigations on the heat flux and impurity for the HL-2M divertor

The controllability of the heat load and impurity in the divertor is very important, which could be one of the critical problems to be solved in order to ensure the success for a steady state tokamak. HL-2M has the advantage of the poloidal field (PF) coils placed inside the demountable toroidal field (TF) coils and close to the main plasma. As a result, it is possible to make highly accurate configuration control of the advanced divertor for HL-2M. The divertor target geometry of HL-2M has been designed to be compatible with different divertor configurations to study the divertor physics and support the high performance plasma operations. In this paper, the heat loads and impurities with different divertor configurations, including the standard X-point divertor, the snowflake-minus divertor and two tripod divertor configurations for HL-2M, are investigated by numerical simulations with the SOLPS5.0 code under the current design of the HL-2M divertor geometry. The plasmas with different conditions, such as the low discharge parameters with ${{I}_{\text{p}}}$ = 0.5 MA at the first stage of HL-2M and the high parameters with ${{I}_{\text{p}}}$ = 2.0 MA during the normal operations, are simulated. The heat load profiles and the impurity distributions are obtained, and the control of the peak heat load and the effect of impurity on the core plasma are discussed. The compatibility of different divertor configurations for HL-2M is also evaluated. It is seen that the excellent compatibility of different divertor configurations with the current divertor geometry has been verified. Here, the results show that the snowflake-minus divertor and the tripod divertor with ${{d}_{x}}=30\,\text{cm}$ present good performance in terms of the heat load profiles and the impurity distributions under different conditions, which may not have a big effect on the core plasma. In addition, it is possible to optimize the distance between the two X-points, ${{d}_{x}}$ , to achieve a better performance in terms of the parameters of discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quasiaperiodic grain boundary phases of Σ⁢5 tilt grain boundaries in refractory metals

We report ground-state structures and phase transitions in Σ⁢5⁢[001] tilt grain boundaries (GBs) in body-centered-cubic (bcc) refractory metals Nb, Ta, Mo, and W. Σ⁢5 tilt GBs have been extensively investigated over the past several decades, with their ground-state structure—composed of kite-shaped structural units—previously thought to be well understood. By performing a rigorous GB structure search that optimizes the number of atoms in the boundary core, we predict different quasiaperiodic “split kite” phases analogous to those previously found in GBs in face-centered-cubic metals. Furthermore, our results suggest that complex aperiodic phases of GBs appear to be a general phenomenon, as validated through density functional theory calculations. Moreover, the atoms in the split kite phase demonstrate distinct collective diffusion dynamics. Phase-contrast image simulations of split kites show better agreement with experimental observations, offering an alternative explanation for previous microscopy results and motivating future atomically resolved imaging of the GB structure.

Body-centered cubic↗
DOE OSTI2020

LCOE Design Optimization Using Genetic Algorithm with Improved Component Models for Medium-Voltage Transformerless PV Inverters

For real-world installations of photovoltaic and other renewable energy resources, the critical design metric is the levelized cost of energy (LCOE); however, many power electronics design optimizations are performed with efficiency and power density as the primary design goals. Recent work has shown that a new LCOE-focused optimization approach can yield improved system designs balancing cost and energy generation. This paper expands the LCOE optimization approach by considering comprehensive optimization parameters, adding new modeling of inductor cost, extending the semiconductor model to include effects of losses on housing cost, and implementing a genetic algorithm to improve computation efficiency.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

A Benchmark Suite for Evaluating Scientific AI Workloads on GPUs

AI applications have been steadily increasing in the allocation portfolio among leadership computing facilities. These applications depend on deep learning frameworks with hardware acceleration and underlying software systems. With the rapid development of applications, software stacks, and hardware devices, it is essential to evaluate the performance of core operations in AI workloads for direction of optimizations and procurement of next-generation high-performance computing (HPC) infrastructures. Currently, most benchmarks lack scientific AI workloads. So, we present DeepKernelBench and the experimental results of evaluating the benchmark suite for early observations and performance comparisons on datacenter GPUs using representative workloads for scientific AI, including Attentions, General matrix multiplications, Geometrics and Fourier neural operations.

Jin, Zheming [Advanced Micro Devices (AMD)]↗
DOE OSTI2016

Biaxially strained PtPb/Pt core/shell nanoplate boosts oxygen reduction catalysis

Compressive surface strains have been necessary to boost oxygen reduction reaction (ORR) activity in core/shell M/Pt catalysts (where M can be Ni, Co, Fe). We report a class of PtPb/Pt core/shell nanoplate catalysts that exhibit large biaxial tensile strains. The stable Pt (110) facets of the nanoplates have high ORR specific and mass activities that reach 7.8 milliampere per centimeter square and 4.3 ampere per milligram of platinum at 0.9 volts versus the reversible hydrogen electrode (RHE), respectively. Density functional theory calculations revealed that the edge-­Pt and top (bottom)-Pt (110) facets undergo large tensile strains that help optimize the Pt-­O bond strength. The intermetallic core and uniform 4 layers of Pt shell of the PtPb/Pt nanoplates appear to underlie the high endurance of these catalysts, which can undergo 50,000 voltage cycles with negligible activity decay and no apparent structure and composition changes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Characteristics of TRU Fueled SFR Core during the Transition with Partially Loaded LEU Assemblies

The fast reactor (FR) fuels typically require higher fissile content than the thermal reactor fuels because the cross sections of the fissile isotopes are smaller relative to the fertile isotopes and higher neutron leakage from the reactor core. The medium-sized high-burnup sodium-cooled fast reactors (SFRs) in the framework of uranium-plutonium/transuranic (U/Pu or U/TRU) fuel-cycle can be optimized to operate with less than 17 % of Pu/TRU content in the driver fuel while having higher TRU conversion ratios (CR~1.0) [1]. However, possible shortage or inaccessibility to TRU based fuel could be accommodated by the use of uranium-based fuels on demand such as low enriched uranium (LEU) having significantly higher 235U content than used in the commercial light water reactors (LWRs), which is defined as high-assay LEU. The reactor systems having low TRU conversion ratio are commonly categorized as burner reactors, which include LWRs and even can be achieved by FRs with designed to utilize higher TRU fractions (e.g., increased neutron leakage and lower fuel volume fractions). Such reactor systems need to be initially loaded with high excess reactivity, which decreases toward the end of cycle, in order to achieve target burnup conditions. Therefore, in order to offset the excess reactivity, neutron absorbing materials need to be inserted into the core to compensate (e.g., control rods). By reducing the neutron leakage (e.g., increasing the fuel volume fraction or thicker blankets), the TRU conversion ratio in the FR can be increased. If the TRU conversion ratio becomes 1.0 (technically slightly greater than 1.0 to account for process losses during recycle), the reactor is in the condition known as “breakeven”, in which fuel contains the same amount of fissile material after recycling that was used to fuel the reactor. In such a condition, combined with the fact that fission products do not have strong poisoning effects in FRs, the reactivity swing becomes smaller than that of burner type reactors. For breeders, the reactivity can increase toward the end of the cycle because more fissile material is produced than consumed. In this regard, the breakeven FR core is implicitly optimized in a sense by eliminating the large insertion of control elements to offset the reactivity during the normal operation. However, the breakeven condition here is assumed to be achieved only by the TRU based fuel. Possible lack of TRU based fuel needs to be compensated by available LEU resources containing equivalent amount of fissile (i.e., 235U). The use of LEU will have some impact on important safety parameters that need to be evaluated. U-235 has a higher effective delayed neutron fraction than Pu-239. Also, the number of neutrons produced by fissions per neutron absorption (i.e. ?) of 235U in the fast energy range (>1e4 eV) is lower than that of 239Pu, which may lead to the poor fissile conversion when LEU is used as a high-conversion FR fuel. The full-paper presents the study of the impact of partially loaded LEU fuels within TRU fueled breakeven SFR on the transition of nuclide evolutions and core characteristics particularly focusing on the burnup reactivity swing. The full paper analyzes how the large reactivity swing occurs during the LEU loading and addresses possible options to reduce it to the level equivalent to that of the TRU fueled SFR core.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Development and Validation of a SiC Based 50 kW Grid-Connected PV Inverter: Preprint

In this digest a 50kW string PV inverter formed using all SiC semiconductor devices is presented. The inverter design includes additively manufactured power block, symmetrical Y-core inductors for ac side filter, and advanced inverter functionality for grid support. This inverter utilizes the conventional three-phase Voltage Source Inverter topology and optimizes the design for SiC based devices. This paper presents the full functional validation of the designed inverter along with quantification of the efficiency and power density. The performance of the inverter for high dc-bus voltage without multi-level topology to exploit SiC advantages is also presented in this digest. The full paper will include details of inverter design, optimization and further experimental validation.

14 SOLAR ENERGY↗
DOE OSTI2022

Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale

We introduce an ensemble of artificial intelligence models for gravitational wave detection that we trained in the Summit supercomputer using 32 nodes, equivalent to 192 NVIDIA V100 GPUs, within 2 h. Once fully trained, we optimized these models for accelerated inference using NVIDIA TensorRT. We deployed our inference-optimized AI ensemble in the ThetaGPU supercomputer at Argonne Leadership Computer Facility to conduct distributed inference. Using the entire ThetaGPU supercomputer, consisting of 20 nodes each of which has 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, our NVIDIA TensorRT-optimized AI ensemble processed an entire month of advanced LIGO data (including Hanford and Livingston data streams) within 50 s. Our inference-optimized AI ensemble retains the same sensitivity of traditional AI models, namely, it identifies all known binary black hole mergers previously identified in this advanced LIGO dataset and reports no misclassifications, while also providing a 3X inference speedup compared to traditional artificial intelligence models. We used time slides to quantify the performance of our AI ensemble to process up to 5 years worth of advanced LIGO data. In this synthetically enhanced dataset, our AI ensemble reports an average of one misclassification for every month of searched advanced LIGO data. We also present the receiver operating characteristic curve of our AI ensemble using this 5 year long advanced LIGO dataset. This approach provides the required tools to conduct accelerated, AI-driven gravitational wave detection at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Polymer large core optical splitter 1 × 2 Y for high-temperature operation

The design, fabrication and measurement of the properties of the large core 1 × 2 Y optical planar splitters for high-temperature operation are demonstrated. The splitters were designed by the beam propagation method optimized for operation wavelengths 650 nm and for assembling with optical fibre having core diameter 600 µm and cladding 630 µm. The splitters consisted of optical glue core and cladding layers made of Cyclo Olefin Polymer. The applied materials allowed for higher operating temperatures (up to 120 °C) than standard splitters made of acrylate plastic (up to 80 °C). The splitters show optical losses lower than 4.0 dB at 532 nm/650 nm, 2.6 dB at 850 nm, 3.4 dB at 1300 nm and 5.1 dB at 1550 nm at room temperature. The optical losses measured in the thermal shock test chamber at temperatures up to 120 °C showed that the best sample had losses lower than 4.2 dB at 850/1300 nm, 4.6 dB at 532 nm and 7.6 dB at 650 nm. Such splitters would be very useful in places with elevated temperatures, for instance in engine parts where the expected temperature can reach as high as 120 °C.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Extending Orbital-Optimized Density Functional Theory to L-Edge XPS and Beyond: Spin–Orbit Coupling via Nonorthogonal Quasi-Degenerate Perturbation Theory

Quantum mechanical calculations of core electron binding energies (CEBEs) are relevant to interpreting X-ray photoelectron spectroscopy (XPS). Orbital-optimized density functional theory (OO-DFT) accurately predicts K-edge CEBEs but is challenged by the presence of significant spin–orbit coupling (SOC) at L- and higher edges involving inner-shell orbitals with nonzero angular momentum. Here, to extend OO-DFT to L-edges and higher, our method utilizes scalar-relativistic, spin-restricted open-shell OO-DFT to construct a minimal, quasi-degenerate basis of core-hole states corresponding to a chosen inner-shell (e.g., ionizing all six possible 2p spin orbitals). Nonorthogonal configuration interaction (NOCI) is then used to obtain the matrix elements of the full Hamiltonian including SOC in this quasi-degenerate model space of determinants. Using a screened 1-electron SOC operator parametrized with the Dirac-Coulomb-Breit (DCB) Hamiltonian results in doublet splitting (DS) values for third row elements that are nearly in quantitative agreement with experiment. The resulting NOCI eigenvalues are shifted by the average of the (scalar) OO-DFT CEBEs to yield CEBEs (split by SOC) corrected for dynamic correlation. Comparing calculations on gas phase molecules with experimental results establishes that NO-QDPT with the SCAN functional (NO-QDPT/SCAN), using the DCB screened 1-electron SOC operator is accurate to about 0.2 eV for L-edge CEBEs of molecules containing third row atoms. However, this NO-QDPT approach becomes less accurate for fourth-row elements starting in the middle of the 3d transition metal series, with errors increasing as atomic number increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Calculation of Higher Eigenpairs of the Transport Equation Using IRAM Based on Domain Decomposition

The higher eigenpairs of the neutron transport (or diffusion) equation are useful in core flux distribution reconstruction, transient analysis, stability analysis, and loading pattern optimization. There are various methods for the calculation of higher eigenpairs, such as the power iteration method with filtering technique, the Generalized Modified Power Method (GMPM), the power iteration method with innovative boundary conditions for symmetric cores, and Krylov subspace methods. In regard to Krylov subspace methods, the Implicitly Restarted Arnoldi Method (IRAM) and ORTHOMIN were implemented to calculate higher eigenpairs for both transport and diffusion equations. In Warsa's work, however, there was a significant drawback that problems with energy upscatter could not be treated efficiently. In Modak's work, the mode to which his method was likely to converge depended on the shape of initial guess flux, and only one mode could be computed each time, making it impractical for real use. Furthermore, the computational burden for higher eigenpairs is generally much larger than for only the first eigenpair, especially for neutron transport equations. Therefore, the implementation of parallel computation for higher eigenpairs is essential to improve the efficiency, and no such work has been reported in literature so far. In this summary, we propose an innovative method to calculate higher eigenpairs of the neutron transport equation based on high performance computation. In this method, 2D Matrix Method of Characteristic (MMOC) is used to discretize the neutron transport equation; IRAM is used to evaluate higher eigenpairs; spatial domain decomposition is used to realize parallel computation. The highlight of this method is using the MGMD PGMRES (Multi-Group and Multi-Domain coupled Parallel Generalized Minimal Residual Method) algorithm to simultaneously accelerate the upscatter iterations and the inner interface angular fluxes iterations, avoiding the drawback in Warsa's method and the efficiency problem of conventional Jacobi iteration. To the best of our knowledge, our work represents the first application of IRAM based on domain decomposition for higher eigenpairs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Bayesian and LASSO Regressions for Comparative Permeability Modeling of Sandstone Reservoirs

In this research, Bayesian model averaging (BMA) and least absolute shrinkage and selection operator regression (LASSO) algorithms were adopted for the core permeability modeling as a function of well log and core measurements. More specifically, the core permeability (dependent factor) was modeled given the well log and core data (independent variables) and then predicted in non-cored intervals of a well in a sandstone formation. The BMA is a stochastic linear modeling and a Bayesian parameter selection. Among 50 linear models generated as a function of the independent variables and depicted in Occam’s window, the best model of the highest posterior probability is determined. The best model has the optimal subset parameters that most influences the response factor. The core permeability modeling was again conducted using the LASSO algorithm, which adopts a completely different way of modeling and subset selection by using the penalized least-squared equation. Both BMA and LASSO resulted in a very accurate prediction of the core permeability by achieving perfect measured and calculated permeability matching. Matches for the two algorithms were quantified by computing the adjusted R-squared and root-mean-squared prediction error. In addition, results of the BMA and LASSO were compared to the conventional multiple linear regression (LM). The LASSO algorithm led to an accurate matching similar to LM, but slightly better than BMA. Therefore, both BMA and LASSO represent integrated procedures for accurate permeability estimation similar to conventional regression analysis.

58 GEOSCIENCES↗
DOE OSTI2022

Genetic algorithm-based optimisation of the few-group structure for lead fast reactors analysis

The optimal choice of the few-group structure for full-core transient analyses is still an open issue in reactor physics, especially for fast system like the lead fast reactor. One possible approach to select the group boundaries is represented by heuristic search algorithms, such as evolutionary ones. In this paper, a genetic algorithm coupled with the SIMMER code is employed to determine optimized six-group boundaries for the analysis of the ALFRED reactor. The Serpent Monte Carlo code is adopted to produce both the fine-group cross section library and the fine-group flux, used as a figure of merit to drive the genetic optimisation. The results show that the algorithm is indeed able to find satisfactory solutions that comply with the set objectives and can be reasonably interpreted in light of the underlying physics of the considered core. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Discovery of Energy Storage Molecular Materials Using Quantum Chemistry-Guided Multiobjective Bayesian Optimization

Redox flow batteries (RFBs) are a promising technology for stationary energy storage applications due to their flexible design, scalability, and low cost. In RFBs, energy is carried in flowable redoxactive materials (redoxmers) which are stored externally and pumped to the cell during operation. Further improvements in the energy density of RFBs necessitates redoxmer designs with wider redox potential windows and higher solubility. Additionally, designing redoxmers with a fluorescence-enabled self-reporting functionality allows monitoring of the state of health of RFBs. To accelerate the discovery of redoxmers with desired properties, state-of-the- art machine learning ( ML) methods, such as multiobjective Bayesian optimization (MBO), are useful. Here, we first employed density functional theory calculations to generate a database of reduction potentials, solvation free energies, and absorption wavelengths for 1400 redoxmer molecules based on a 2,1,3-benzothiadiazole (BzNSN) core structure. From the computed properties, we identified 22 Pareto-optimal molecules that represent best trade-off among all of the desired properties. We further utilized these data to develop and benchmark an MBO approach to identify candidates quickly and efficiently with multiple targeted properties. With MBO, optimal candidates from the 1400-molecule data set can be identified at least 15 times more efficiently compared to the brute force or random selection approach. Importantly, we utilized this approach for discovering promising redoxmers from an unseen database of 1 million BzNSN-based molecules, where we discovered 16 new Pareto-optimal molecules with significant improvements in properties over the initial 1400 molecules. Furthermore, we anticipate that this active learning technique is general and can be utilized for the discovery of any class of functional materials that satisfies multiple desired property criteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy

A core goal of auditory neuroscience is to build quantitative models that predict cortical responses to natural sounds. Reasoning that a complete model of auditory cortex must solve ecologically relevant tasks, we optimized hierarchical neural networks for speech and music recognition. The best-performing network contained separate music and speech pathways following early shared processing, potentially replicating human cortical organization. The network performed both tasks as well as humans and exhibited human-like errors despite not being optimized to do so, suggesting common constraints on network and human performance. The network predicted fMRI voxel responses substantially better than traditional spectrotemporal filter models throughout auditory cortex. It also provided a quantitative signature of cortical representational hierarchy—primary and non-primary responses were best predicted by intermediate and late network layers, respectively. Here the results suggest that task optimization provides a powerful set of tools for modeling sensory systems.

59 BASIC BIOLOGICAL SCIENCES↗