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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance Benchmark of Commercial and Developmental Fission Chambers in Elevated Temperatures

This report documents the testing of two in-core fission chamber technologies for high-temperature irradiation environments. This work is in collaboration with the French Alternative Energies and Atomic Energy Commission (CEA). The fission chamber evaluated by Idaho National Laboratory is the micro-pocket fission detector (MPFD). The fission chamber evaluated by the CEA are the 3 mm miniaturized fission chamber and the 7 mm high-temperature fission chamber. Demonstrations of the MPFD were performed at the Neutron Radiography Facility and the Massachusetts Institute of Technology Reactor. Demonstrations of the CEA fission chambers were performed at the Ohio State University Research Reactor. All demonstrations were conducted with a heated experiment rig up to 850°C.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

SERPENT 2 and TRIPOLI-4 neutronics benchmarking of the Jules Horowitz reactor

Jules Horowitz Reactor (JHR) is a future center for nuclear material testing in Europe, currently under construction at CEA Cadarache in southern France. It has been modelled extensively with CEA's HORUS3D/N neutron calculation package, that includes a Monte-Carlo neutron transport code TRIPOLI-4. In order to support the future computational analyses on the reactor core physics, VTT's Monte Carlo neutronics code SERPENT 2 has been used to create an alternative model of the JHR, taking advantage of the pre-existing Constructive Solid Geometry (CSG) structures on which the TRIPOLI-4 model was built. This work describes a benchmark, in which two JHR core configurations were analyzed using both of these models. The first configuration is a fresh fuel core at the beginning of life, in which aluminum based dummy-devices are installed in the reactor test positions. The second configuration represents the end-of-cycle equilibrium core with a heterogeneous burnup distribution, in which CALIPSO devices containing cladding material samples are installed at the in-core experimental positions, while the reflector positions are occupied by DEN-REP devices containing UO{sub 2} fuel. Neutron flux spectra and heat deposition are the parameters of interest in this study, due to their high importance in creating the desired experimental irradiation environment. The impact of delayed gamma energy deposition will be studied in detail, since the two models account for it with different methods. This work aims to establish a SERPENT 2 model of JHR, understanding its differences and agreements with TRIPOLI-4, and discussing its potential future applications. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

A New Shutdown Dose Rate Benchmark Problem for Representative Fusion Applications

Here, this work introduces a new benchmark problem for calculating shutdown dose rates (SDDRs) aimed at fusion reactor applications. The model is designed to represent a simplified version of a typical ITER port plug. The responses of interest include neutron flux, gamma flux, and gamma SDDR at 12 different locations scattered throughout the port. This article outlines the geometry specifications of the problem, provides material definitions for the components, specifies the required responses to be calculated, and presents the source definition information. The need for this benchmark arises from the limited availability of publicly accessible references, with only one benchmark representing the typical dimensions and materials found in fusion systems. This existing benchmark has been cited extensively, reflecting the demand within the scientific community to test both established and novel workflows for SDDR calculations. However, since its presentation at a conference in 2011, the results have become increasingly well known. Moreover, the absence of formal publication and peer review has led to the details of this benchmark being extracted from secondary sources, such as subsequent studies that reference it. As a result, analysts are left with significant flexibility in interpreting the key parameters, which can be adjusted to account for unknown systematic errors, ultimately reproducing the already well-known responses. This new benchmark serves as an updated version of that earlier work, with the aim of providing a more reliable description of the materials and their impurities, which is crucial for assessing activation and subsequent gamma emission. Additionally, it seeks to provide a geometry that more closely represents an ITER port plug. The improvements in the problem definition will lead to a more reproducible benchmark problem, while also presenting the radiation transport community with a completely new challenge. The results will be published in a future article to allow analysts adequate time to analyze this problem independently.

Benchmark↗
DOE OSTI2026

A large-scale benchmarking of deterministic and stochastic derivative-free optimization algorithms

This presentation summarizes our work in the PrOMMiS project on benchmarking of data-driven optimization algorithms and their applications in self-driving laboratories. This work supports the broader project goal of accelerating the identification of promising separation methods and operating conditions for critical minerals separation processes. We present a systematic benchmarking study of 42 data-driven optimization algorithms on a broad collection of 502 test problems. The results identify BAM, GLCCLUSTER, and MULTIMIN as the most effective optimization solvers, with BAM showing the highest overall performance and solving more than 80% of the benchmark problems. The study also shows that no single solver consistently outperforms the others across all problem types, indicating that our future laboratory applications may benefit from using a small set of strong solvers rather than relying on a single method. The presentation also illustrates an in-silico chemical reactor case study showing that data-driven optimization methods can guide autonomous experimentation in a self-driving laboratory and identify optimal operating conditions within a small number of experiments. Overall, the results provide a basis for selecting efficient optimization methods and demonstrate the practical use of data-driven optimization in self-driving laboratory workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Algorithm-guided experimentation for autonomous AI systems in self-driving laboratories

This presentation summarizes our work in the PrOMMiS project on benchmarking of data-driven optimization algorithms and their applications in self-driving laboratories. This work supports the broader project goal of accelerating the identification of promising separation methods and operating conditions for critical minerals separation processes. We present a systematic benchmarking study of 42 data-driven optimization algorithms on a broad collection of 502 test problems. The results identify BAM, GLCCLUSTER, and MULTIMIN as the most effective optimization solvers, with BAM showing the highest overall performance and solving more than 80% of the benchmark problems. The study also shows that no single solver consistently outperforms the others across all problem types, indicating that our future laboratory applications may benefit from using a small set of strong solvers rather than relying on a single method. The presentation also illustrates an in-silico chemical reactor case study showing that data-driven optimization methods can guide autonomous experimentation in a self-driving laboratory and identify optimal operating conditions within a small number of experiments. Overall, the results provide a basis for selecting efficient optimization methods and demonstrate the practical use of data-driven optimization in self-driving laboratory workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GPU-accelerated kinetic Hall thruster simulations in WarpX

Abstract Two-dimensional (axial-azimuthal) simulations of a Hall thruster are performed using the open-source particle-in-cell code WarpX. The simulation conditions are chosen to match those of the axial-azimuthal benchmark first reported by Charoy et al. in 2019. A range of numerical and solver parameters is investigated in order to find those which yield the best performance. It is found that WarpX completes the benchmark case in 3.8 days on an Nvidia V100 GPU, and in as low as 1.5 days on a more recent Nvidia H100 GPU. Of the numerical parameters investigated, it is determined that the field-solve tolerance and particle resampling thresholds have the largest effect on the simulation wall time and that particle resampling may artificially widen electron velocity distribution functions, leading to unphysical heating. A semi-implicit scheme for the electrostatic field solve is tested and is found to produce results consistent to within 10% of the benchmark in less than twelve hours. The scaling properties of the electrostatic solver to multiple GPUs are also assessed on a uniform plasma test problem. The results of this work are discussed in the context of advancements in GPU hardware and the suitability of kinetic Hall thruster simulations for engineering applications.

Marks, Thomas A.↗
DOE OSTI2020

Availability of Shielding Benchmark Experiment Data in the ICSBEP Handbook

The International Criticality Safety Benchmark Evaluation Projects (ICSBEP) has over two decades of experience under the auspices of the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) to identify, evaluate, and compile a comprehensive data set of criticality safety benchmark data [1]. The activities of the ICSBEP have led to the continued success of the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) [2]. The contents of the ICSBEP Handbook include benchmark specifications derived from nuclear facilities around the world, which have been utilized to support criticality safety efforts and also integral testing of nuclear data [3]. The 2020 edition of the ICSBEP Handbook will include data from 582 evaluations containing benchmark specifications for 5,053 critical, subcritical, or near-critical configurations. There are seven criticality-alarm-placement/shielding evaluations containing a total of 45 benchmark configurations, and ten fundamental physics evaluations containing a total of 237 measurements relevant to criticality safety applications. The purpose of this paper is to summarize those benchmarks relative to validation needs in shielding applications currently found within the ICSBEP Handbook. The current and future plans of shielding benchmarks with regards to the ICSBEP will also be discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Radiochronometric analysis of an historic Cs-137 activity standard

In this work, a 137 Cs activity standard discovered during routine inventory was analyzed to determine its model age using radiochronometry. The aqueous activity standard was separated using an established separation method that employs commercially available Sr resin. The method was also tested against a nuclear forensics reference material developed specifically for benchmarking 137 Cs radiochronometry methods. Results of the analyses showed good agreement between the results and the certified values of the reference material. Analysis of the discovered activity standard were also in good agreement with the activity certification date, though uncertainty was higher due to natural Ba contaminating the sample and the stable 133 Cs used as a carrier during the standard’s production.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for inverse problems: Determining material properties for heterogeneous systems

Here, we determine spatially varying discontinuous material properties using a domain-decomposition based physics-informed neural networks (PINNs) framework named the Adaptive Interface-PINNs or AdaI-PINNs (Roy et al., 2024). We propose the use of distinct neural networks for the field variables and material properties within each material, utilizing adaptive activation functions. While the neural networks across different materials share the same weights and biases, their activation functions are uniquely tailored using a hyperparameter that influences the slope of the activation function. The proposed framework is tested on several one-dimensional and two-dimensional benchmark examples, and its performance is compared with conventional PINNs and existing domain-decomposition PINNs frameworks, namely, the Multi-domain physics-informed neural network (M-PINN), and the eXtended physics-informed neural networks (XPINNs). The results demonstrate that the proposed approach can determine randomly distributed discontinuous material properties with an L 2 error of $\mathscr{O}$ (10 -3 ) for the material property and the root-mean-square error of $\mathscr{O}$ (10 -3 ) for the primary variable while the other approaches yield errors that are approximately two orders of magnitude larger (that is, $\mathscr{O}$ (10 -1 )). Moreover, the spatial distribution of material properties obtained using the proposed framework is in close agreement with the true distribution, whereas the other approaches fare much worse. Additionally, the proposed approach is approximately 40% faster than its competitors, indicating its potential as a robust alternative for solving inverse problems in heterogeneous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Divertor heat flux challenge and mitigation in SPARC

Owing to its high magnetic field, high power, and compact size, the SPARC experiment will operate with divertor conditions at or above those expected in reactor-class tokamaks. Power exhaust at this scale remains one of the key challenges for practical fusion energy. Based on empirical scalings, the peak unmitigated divertor parallel heat flux is projected to be greater than 10 GW m -2 . This is nearly an order of magnitude higher than has been demonstrated to date. Furthermore, the divertor parallel Edge-Localized Mode (ELM) energy fluence projections (~11–34 MJ m -2 ) are comparable with those for ITER. However, the relatively short pulse length (~25 s pulse, with a ~10 s flat top) provides the opportunity to consider mitigation schemes unsuited to long-pulse devices including ITER and reactors. The baseline scenario for SPARC employs a ~1 Hz strike point sweep to spread the heat flux over a large divertor target surface area to keep tile surface temperatures within tolerable levels without the use of active divertor cooling systems. In addition, SPARC operation presents a unique opportunity to study divertor heat exhaust mitigation at reactor-level plasma densities and power fluxes. Not only will SPARC test the limits of current experimental scalings and serve for benchmarking theoretical models in reactor regimes, it is also being designed to enable the assessment of long-legged and X-point target advanced divertor magnetic configurations. Experimental results from SPARC will be crucial to reducing risk for a fusion pilot plant divertor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

New Nonreactive Force Field for Accurate Molecular Dynamics Simulations of TATB at Extreme Conditions

Insensitive high explosives based on TATB (1,3,5-triamino-2,4,6-trinitrobenzene) are needed in applications when safety is of paramount importance, but the basic material properties that give rise to its insensitivity are not fully understood. Molecular dynamics modeling using empirical force fields (FFs) has been the main route to characterize many complicated dynamical properties of TATB single crystal, but these FFs have not been comprehensively tested at extreme conditions typical of detonation. We collect a benchmark data set of (quasi)static TATB physical properties as determined by experiments and electronic structure calculations and apply this data set to validate four existing TATB FFs along with a new TATB FF that we develop here and denote as the CEA-LLNL-Missouri (CLM) FF. Benchmark data include vibrational spectra, the TATB crystal temperature–pressure–volume equation of state and lattice parameters, properties of TATB crystal polymorphs and transitions to the gaseous and liquid states, dimer energy landscapes, the pressure-dependent elastic tensor, and the energy landscape for inelastic deformation via sliding of TATB crystal layers. As a general assessment, we find that the two existing nonreactive FFs are more accurate in describing TATB’s physical properties compared to the two variants of the ReaxFF reactive FF considered. The new CLM FF is found to consistently yield similar or better agreement with experiments and electronic structure theory than any of the existing FF models, and it presents a distinct improvement in accurately modeling TATB elasticity and equation of state. So this work is expected to help improve the accuracy of FF-based modeling of complicated dynamic responses that ultimately govern the safety and performance characteristics of this material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

SFCOMPO Database of Spent Nuclear Fuel Assay Data – the Next Frontier

SFCOMPO is the world’s largest database for measured spent nuclear fuel assay data. An international effort coordinated by the Nuclear Energy Agency (NEA) resulted in a significant expansion of the database and its release online in 2017 as a downloadable application. The SFCOMPO Technical Review Group (TRG) was recently formed under the direction of NEA’s Nuclear Science Committee/Working Party on Nuclear Criticality Safety and was mandated to maintain and further coordinate the development of SFCOMPO. This TRG is currently focused on (1) critical evaluation of the experimental assay data by independent experts and (2) development of benchmarks and benchmark models that can be applied to validate burnup codes. This will improve the quality and documentation of the experimental datasets and enable their use by the international community to support code validation for design and safety analysis of spent nuclear fuel transportation, storage, and repository applications. It follows the precedent and draws on the experience gained from similar NEA efforts in the International Reactor Physics Experiment Evaluation Project and the International Criticality Safety Benchmark Experiment Project. Ongoing SFCOMPO evaluations have served as a test bed to develop templates for documenting evaluations, develop review guidance, improve approaches for a global uncertainty analysis, and devise a strategy focused on providing practical information of highest value to the user community. The current effort, status, and associated challenges are discussed.

Ilas, Germina↗
DOE OSTI2025

Physical patterning of high-Q superconducting niobium resonators via ion beam etching

The development of superconducting quantum circuits increasingly involves the exploration of chemically distinct materials and complex multilayered structures. Accelerating this trend may benefit from low-damage, materials-agnostic patterning techniques that are compatible with a broad range of materials. Here, in this work, we investigate the utility of low-energy ion beam etching (IBE), a physical patterning technique, as an alternative to reactive ion etching for fabricating low-loss superconducting resonators. We use niobium (Nb) resonators as a test platform, leveraging their well-characterized performance metrics for benchmarking. To address IBE-induced surface redeposition, we introduce an in situ aluminum capping layer combined with targeted post-fabrication chemical treatment. This strategy yields resonators with internal quality factors as high as 6 × 10 5 in the single-photon regime at 50 mK. These results establish low-energy IBE as a promising patterning technique for superconducting devices, with the potential to accelerate development across chemically diverse and multilayered material platforms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A neural network for determination of latent dimensionality in Nonnegative Matrix Factorization

Non-negative Matrix Factorization (NMF) has proven to be a powerful unsupervised learning method for uncovering hidden features in complex and noisy datasets with applications in data mining, text recognition, dimension reduction, face recognition, anomaly detection, blind source separation, and many other fields. An important input for NMF is the latent dimensionality of the data, that is, the number of hidden features, K, present in the explored dataset. Unfortunately, and this quantity is rarely known a priori. The existing methods for determining latent dimensionality, such as Automatic Relevance Determination (ARD), are mostly heuristic and utilize different characteristics to estimate the number of hidden features. However, all of them require human presence to make a final determination of K. Here we utilize a supervised machine learning approach in combination with a recent method for model determination, called NMFk, to determine the number of hidden features automatically. NMFk performs a set of NMF simulations on an ensemble of matrices, obtained by bootstrapping the initial dataset, and estimates which K produces stable groups of latent features that reconstruct the initial dataset well. We then train a Multi-Layter Perceptron (MLP) classifier network to determine the correct number of latent features utilizing the statistics and characteristics of the NMF solution, obtained from NMFk. In order to train the MLP classifier, a training set of 58,660 matrices with predetermined latent features were factorized with NMFk. The MLP classifier in conjunction with NMFk maintains a greater than 95% success rate when applied to a held out test set. Additionally, when applied to two well-known benchmark datasets, the swimmer and MIT face data, NMFk/MLP correctly recovers the established number of hidden features. Finally, we compare the accuracy of our method to the ARD, AIC and Stability-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Capturing multireference excited states by constrained-density-functional theory

The computation of excited electronic states with commonly employed (approximate) methods is challenging, typically yielding states of lower quality than the corresponding ground state for a higher computational cost. In this work, we present a mean-field method that extends the previously proposed excited constrained-density-functional theory (XCDFT) from single Slater determinants to ensemble one-body reduced density matrices for computing low-lying excited states. The method still retains an associated computational complexity comparable to a semilocal density functional theory (DFT) calculation while at the same time it is capable of approaching states with multireference character. Further, we benchmark the quality of this method on well-established test sets, finding good descriptions of the electronic structure of multireference states and maintaining an overall accuracy for the predicted excitation energies comparable to semilocal time-dependent DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Lattice phase shifts and mixing angles for an arbitrary number of coupled channels

We present a lattice method for determining scattering phase shifts and mixing angles for the case of an arbitrary number of coupled channels. The proposed method combines a spherical wall boundary condition and a channel-mixing auxiliary potential to extract the full-rank S-matrix from the radial wave functions. We consider the scattering problem of two spin-1 bosons interacting with a test potential involving up to four coupled channels. For this benchmark system, the phase shifts and mixing angles are shown to agree on the lattice and in the continuum. Our method should allow to extend previous two-channel nuclear lattice EFT simulations to mixing of more than two partial waves.

Bovermann, Lukas↗
DOE OSTI2024

Godiva 4 CAAS Shielding Benchmark: Pre CED-3A Overview [Slides]

Thiis presentation shows the character of an integral experiment. It covers the question why Godiva 4? Additionally, this presentation touches on the IER 498 benchmark quantity, activities facilitated by IER 498, proposed CED-2 test matrix, and what happened during the IER 498’s gap year.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Metal Scrap Upcycling with Shear Assisted Processing and Extrusion (ShAPE)

The overarching objective of this project is to convert metal scraps, such as aluminum, titanium, and other alloys provided by the industry, into extruded tubing, wires, and rods. Upcycling of scrap will be accomplished using Shear Assisted Processing and Extrusion (ShAPE). This approach is a new solution for recycling. The specific aims of this project are as follows: 1. Receive metal scrap under a Material Transfer Agreement (MTA), in the form of billets, from select industry partners that meet the following requirements: outer diameter of 1.245 inches (+/-0.003 inches), inner diameter drilled with a 0.404-inch drill bit, and a length of 4.0 inches (+/-0.01 inches). The billet must be cast or compacted to greater than 98% density. If the industry partner does not have the capabilities to prepare the billets, PNNL can make introductions to third-party entities as needed. Industry partners will also provide a composition analysis as weight percent. 2. Extrude metal scrap via the ShAPE process at PNNL. 3. Evaluate and benchmark the extrudate material properties per the ASTM B557-15 – Testing Tubulars Standard or similar wire and rod standards. 4. Characterize the extrudate microstructure for any of the following: grain size, second phase composition, and texture. Additional testing may include corrosion per the ASTM B117 standard and electro-potential. 5. Deliver specimens to industry partners under an MTA for additional third-party evaluations. Industry partners will, in return, provide a non-proprietary report on any testing, including testing per the ASTM B557-15, ASTM B117, and other industry standards. 6. PNNL will develop data and insights to support intellectual property capture, a published non-proprietary technical report, research collaborations, and commercialization opportunities.

36 MATERIALS SCIENCE↗