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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A lightweight Fe–Mn–Al–C austenitic steel with ultra-high strength and ductility fabricated via laser powder bed fusion

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (~9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, in this study, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Verification and Validation of a Magnetic Plasma Fluid Model Utilizing the MOOSE (Multiphysics Object Oriented Simulation Environment) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification, benchmarking, and validation studies have been conducted. Verification studies involved utilizing the method of manufactured solutions and comparing the convergence slope of a known solution to the theoretical slope. Benchmarking consists of comparisons to existing edge codes, namely BOUT++ and SOLEDGE3X. Validation efforts focused on comparisons against open-source data from the TCV tokamak.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Verification of a Fluid-Based Plasma-Edge Model Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. These models must incorporate the interconnected phenomena of these devices, including plasma physics, neutronics, first wall interactions, and tritium transport. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification studies have been conducted using newly developed magnetic plasma capabilities. These involved convergence analyses utilizing the method of manufactured solutions to verify new operators and case studies. A modular approach was taken here to demonstrate increasingly complicated simulation scenarios, which included a singular fluid with uniform magnetic field case, a singular fluid with spatially varying magnetic field case, and a coupled multifluid case.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Peak2Patch: High-Fidelity Functional Group Identification through Attention-Based Fusion of Infrared and Mass Spectra

Identifying molecular structure based on spectroscopic readings is a key task in a variety of chemical and biological applications. Common spectroscopy techniques, such as Infrared (IR) Spectroscopy and Mass Spectrometry (MS), provide detailed information on the structure of molecular compounds but nonetheless require expert-level knowledge to decode. Machine learning has emerged as a potential solution for automating structure prediction from chemical spectra; however, current approaches generally focus on single sensor modalities, neglecting to leverage the complementary information contained within differing spectra. In this paper, we introduce Peak2Patch, a novel approach to fusion-enhanced prediction of functional groups from IR and mass spectra. First, we perform a detailed comparison of backbone networks for encoding both sparse mass spectra and dense IR spectra and demonstrate the superior performance of transformer neural networks over current state-of-the-art convolutional neural networks. Second, we evaluate three broad categories of fusion: early (raw feature), middle (deep feature), and late (decision) fusion, demonstrating the potential of a deep feature fusion-based approach. Lastly, we present Peak2Patch, our attention-based fusion scheme, which leverages cross-attention to mix features between encoded tokens of the two modalities. We validate our approach on a publicly available multimodal spectroscopic data set of 790k simulated molecules, demonstrating a large improvement in functional group prediction over both the previous state-of-the-art and our own strong single-modal baselines.

Jacobson, Philip [Sandia National Laboratories (SN↗
DOE OSTI2025

Combining Observations and Models: A Review of the CARDAMOM Framework for Data‐Constrained Terrestrial Ecosystem Modeling

The rapid increase in the volume and variety of terrestrial biosphere observations (i.e., remote sensing data and in situ measurements) offers a unique opportunity to derive ecological insights, refine process‐based models, and improve forecasting for decision support. However, despite their potential, ecological observations have primarily been used to benchmark process‐based models, as many past and current models lack the capability to directly integrate observations and their associated uncertainties for parameterization. In contrast, data assimilation frameworks such as the CARbon DAta MOdel fraMework (CARDAMOM) and its suite of process‐based models, known as the Data Assimilation Linked Ecosystem Carbon Model (DALEC), are specifically designed for model‐data fusion. This review, motivated by a recent CARDAMOM community workshop, examines the development and applications of CARDAMOM, with an emphasis on its role in advancing ecosystem process understanding. CARDAMOM employs a Bayesian approach, using a Markov Chain Monte Carlo algorithm to enable data‐driven calibration of DALEC parameters and initial states (i.e., carbon pool sizes) through observation operators. CARDAMOM's unique ability to retrieve localized model process parameters from diverse datasets—ranging from in situ measurements to global satellite observations—makes it a highly flexible tool for analyzing spatially variable ecosystem responses to environmental change. However, assimilating these data also presents challenges, including data quality issues that propagate into model skill, as well as trade‐offs between model complexity, parameter equifinality, and predictive performance. We discuss potential solutions to these challenges, such as reducing parameter equifinality by incorporating new observations. This review also offers community recommendations for incorporating emerging datasets, integrating machine learning techniques, strengthening collaboration with remote sensing, field, and modeling communities, and expanding CARDAMOM's relevance for localized ecosystem monitoring and decision‐making. CARDAMOM enables a deep, mechanistic understanding of terrestrial ecosystem dynamics that cannot be achieved through empirical analyses of observational datasets or weakly constrained models alone.

Bayesian inference↗
DOE OSTI2026

Advancing extreme pulsed lasers through measurements: summary of the pulsed laser metrology workshop

In this report we present consensus findings produced during the pulsed laser metrology (PLM) workshop (Boulder, CO, USA, August 2025). The workshop was a meeting of 35 scientists from private industry, academia, and U.S. government to compile a list of the metrology needs to support extreme pulsed laser development and implementation. We define ‘extreme pulsed lasers’ loosely as those with peak powers above 1 TW or multi-Joule pulse energies. Such lasers are being increasingly used and investigated for use in high energy particle acceleration, short wavelength radiation generation, laser-based fusion, etc. The rapid growth of these fields and the proliferation of extreme lasers for these applications, coupled with the extreme electric fields they generate and relative scarcity of such lasers, presents unique challenges to accuracy in their measurement. The PLM workshop was a two-day event designed to hear from users, developers, and researchers on the current state of optical metrology associated with these extreme pulsed lasers. The goal was to identify the most important measurement challenges limiting development and implementation of these lasers in practical applications. We report here the conclusions and recommendations of this workshop. The hope is that this document will become the first of many iterations which track the status of measurement needs supporting extreme pulsed lasers.

Lasers↗
NASA NTRS2018

Preliminary Analysis of the Gradient Field Imploding Liner Fusion Propulsion Concept

The advancement of human deep space exploration requires the continued development of energetic in-space propulsion systems, advancing from current chemical engines to nuclear thermal rockets to future high energy concepts such as nuclear fusion. This paper presents the initial results of a NASA Innovative Advanced Concepts (NIAC) Phase I study funded to investigate the feasibility of a new pulsed fusion propulsion concept based on the rapid implosion of a fuel target injected at high velocity into a strong stationary magnetic field. The proposed concept takes advantage of the significant advances in terrestrial magneto-inertial fusion designs while attempting to mitigate the most common engineering impediments to in-space propulsion applications. A semi-analytic numerical model used to estimate target compression physics and energy release is presented, leading to estimates for engine performance. A preliminary vehicle design concept is outlined, and representative trajectory analyses for rapid Mars and Saturn missions are provided. The paper concludes with an overview of proposed next steps for theoretical and experimental validation of the concept.

Propulsion↗
DOE OSTI2021

Uranium integral fission product yields for a spectrally-shaped 14.1 MeV neutron source at the National Ignition Facility

This paper describes the experimental results for an energy tuning assembly created to modify the National Ignition Facility deuterium–tritium fusion neutron source into a notional thermonuclear and prompt fission neutron spectrum, which has applications in integral measurements, nuclear data benchmarks, and radiation effects on microelectronics. The Monte Carlo neutron transport utilized MCNP5 to estimate the ETA-modified fluence using the ENDF-B/VIII.0 and IRDFF-II continuous energy nuclear data libraries, and SCALE Sampler was used to estimate the systematic nuclear data covariance using ENDF-B/VII.1 and IRDFF-II in a 252-group structure. The experiment fielded eight activation foils and a highly enriched uranium sample. This provided fifteen reaction channels that were used in a forward-fit comparison to the modeled results and to unfold the neutron spectrum using STAYSL. Gamma-ray spectrometry was performed on the activation and highly enriched uranium foils, and the reduced Χ 2 between the modeled and experimental values was 1.21. The results from the STAYSL unfold, reduced Χ 2 = 1.62, indicated that the modeled neutron spectrum was achieved and the systematic nuclear data uncertainty associated with the neutron transport and activation product cross sections was representative of the experiment. Integral cumulative fission product yield data were collected for 37 mass chains with a combination of gamma-ray spectrometry and radiochemical analysis. Fission product analysis was generally in agreement with two models using a semi-empirical fit and the General Observables of Fission code, with the exception of mass chains 88, 109, 111, 112, 113, 129, 139, 142, 144, 151, and 156.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Cold Spray Deposition of 304L Stainless Steel to Mitigate Chloride-Induced Stress Corrosion Cracking in Canisters for Used Nuclear Fuel Storage

A feasibility study of the cold spray deposition process of 304L stainless steel on 304L stainless steel substrates as a mitigation method for chloride-induced stress corrosion cracking (CISCC) has been investigated under various substrate conditions. The study is aimed at the application of this technology to mitigate CISCC that may potentially occur in or nearthe fusion welded regions of stainless steel canisters in Dry Cask Storage System (DCSS) for used nuclear fuels. Spherical gas-atomized 304L stainless steel powder, in the size range of 25 µm to 44 µm, was used as a feedstock powder for the cold spray process. The powder was deposited on four types of 304L substrates with various surface conditions: as-polished, oxidized, cold-rolled, plates with prototypical CISCC. The effects of cold spray parameters on quality of cold spray coatings were investigated. Thickness, porosity, and phases in the as-deposited materials were evaluated using scanning electron microscopy (SEM) and X-ray diffraction (XRD), and correlated with microhardness and adhesion strength measured via micro-indentation and ASTM C633 pulling test, respectively. XRD analysis of the coatings was also conducted to examine the effects of cold spray condition on residual stress state in the coating. Detailed cross-sectional examination of coating/substrate interfaces was performed with transmission electron microscopy (TEM) equipped with energy dispersive spectroscopy (EDS). Dense and continuous coatings with good adhesion strength and hardness were produced for the various substrate conditions by adjusting cold spray parameters. The results demonstrate that cold spray stainless steel coating is a viable option to provide a physical barrier against CISCC in fusion weld regions of stainless steel in corrosive chloride salt-bearing environments.

Dry Cask Storage Systems, cold spray, 304L stainle↗
DOE OSTI2022

First-principles theory of the rate of magnetic reconnection in magnetospheric and solar plasmas

Abstract The rate of magnetic reconnection is of the utmost importance in a variety of processes because it controls, for example, the rate energy is released in solar flares, the speed of the Dungey convection cycle in Earth’s magnetosphere, and the energy release rate in harmful geomagnetic substorms. It is known from numerical simulations and satellite observations that the rate is approximately 0.1 in normalized units, but despite years of effort, a full theoretical prediction has not been obtained. Here, we present a first-principles theory for the reconnection rate in non-relativistic electron-ion collisionless plasmas, and show that the same prediction explains why Sweet-Parker reconnection is considerably slower. The key consideration of this analysis is the pressure at the reconnection site (i.e., the x-line). We show that the Hall electromagnetic fields in antiparallel reconnection cause an energy void, equivalently a pressure depletion, at the x-line, so the reconnection exhaust opens out, enabling the fast rate of 0.1. If the energy can reach the x-line to replenish the pressure, the exhaust does not open out. In addition to heliospheric applications, these results are expected to impact reconnection studies in planetary magnetospheres, magnetically confined fusion devices, and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Laser-heated capillary discharge waveguides as tunable structures for laser-plasma acceleration

Laser-heated capillary discharge waveguides are novel, low plasma density guiding structures able to guide intense laser pulses over many diffraction lengths and have recently enabled the acceleration of electrons to 7.8 GeV by using a laser-plasma accelerator (LPA). These devices represent an improvement over conventional capillary discharge waveguides, as the channel matched spot size and plasma density can be tuned independently of the capillary radius. This has allowed the guiding of petawatt-scale pulses focused to small spot sizes within large diameter capillaries, preventing laser damage of the capillary structure. High performance channel-guided LPAs require control of matched spot size and density, which experiments and simulations reported here show can be tuned over a wide range via initial discharge and laser parameters. In this paper, measurements of the matched spot size and plasma density in laser-heated capillary discharges are presented, which are found to be in excellent agreement with simulations performed using the MHD code MARPLE. Strategies for optimizing accelerator performance are identified based on these results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Quantification and visualization of uncertainties in reconstructed penumbral images of implosions at Omega

Penumbral imaging is a technique used in plasma diagnostics in which a radiation source shines through one or more large apertures onto a detector. To interpret a penumbral image, one must reconstruct it to recover the original source. The inferred source always has some error due to noise in the image and uncertainty in the instrument geometry. Interpreting the inferred source thus requires quantification of that inference’s uncertainty. Markov chain Monte Carlo algorithms have been used to quantify uncertainty for similar problems but have never been used for the inference of the shape of an image. Because of this, there are no commonly accepted ways of visualizing uncertainty in two-dimensional data. This paper demonstrates the application of the Hamiltonian Monte Carlo algorithm to the reconstruction of penumbral images of fusion implosions and presents ways to visualize the uncertainty in the reconstructed source. This methodology enables more rigorous analysis of penumbral images than has been done in the past.

Instruments & Instrumentation↗
DOE OSTI2020

Fast Computational Algorithms for Partial Differential Equations and Uncertainty Quantifications

This project concerned the construction, testing and analysis of computational algorithms for solving parameterized and stochastic partial differential equations. The study and understanding of equations of this type is of fundamental importance in numerous engineering and scientific applications. Examples include simulation of plasma dynamics in models of electric propulsion and nuclear fusion, simulation of multiphase flows, such as the flow of water, gas and oil in reservoirs, and structural analysis of the dependence of structures on materials. Parametrization is used in such settings when properties of the models such as viscosity of fluids or electric resistivity of materials are not precisely understood and instead are treated as random variables. The resulting solutions are themselves random, and having such solutions will enable engineers to use probabilistic methods to assess the likelihood of events, for example, whether a pollutant in a liquid will exceed a limit, and to use such analyses to develop ways to ensure positive outcomes. Construction of accurate (high resolution) computational solutions is expensive, requiring significant computer time and computational resources, and there is need to reduce computational cost to make simulation useful and effective. The aim of the project was to construct algorithms to efficiently compute surrogate solutions to parameterized problems to allow for efficient and accurate simulation. The technical approach used focused on two related strategies, based on rank-reduction methods and reduced-order models. These methods construct surrogate solutions of parameter-dependent models by projection or interpolation into low-dimensional approximation spaces. Cost savings are achieved if the low-dimensional spaces can be identified and constructed efficiently and if the resulting low-dimensional algebraic systems can be solved cheaply. Accomplishments include: Theoretical and empirical demonstration of the effectiveness of fast multigrid solution strategies for computing low-rank representations of parameter-dependent solutions to discrete partial differential equations, including the first proof establishing so-called textbook convergence properties for low-rank methods. Development of efficient solution algorithms for solving nonlinear parameter-dependent partial differential equations used in models of fluid dynamics. Developent of efficient algorithms for low-rank representation of solutions of time-dependent simulations of fluid dynamics using multi-dimensional tensor representations of solutions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

Thermal capacitator design rationale. Part 1: Thermal and mechanical property data for selected materials potentially useful in thermal capacitor design and construction

The thermal properties of paraffin hydrocarbons and hydrocarbon mixtures which may be used as the phase change material (PCM) in thermal capacitors are discussed. The paraffin hydrocarbons selected for consideration are those in the range from C11H24 (n-Undecane) to C20H42 (n-Eicosane). A limited amount of data is included concerning other properties of paraffin hydrocarbons and the thermal and mechanical properties of several aluminum alloys which may find application as constructional materials. Data concerning the melting temperature, transition temperature, latent heat of fusion, heat of transition, specific heat, and thermal conductivity of pure and commercial grades of paraffin hydrocarbons are given. An index of companies capable of producing paraffin hydrocarbons and information concerning the availability of various grades (purity levels) is provided.

Bailey, J. A.↗
NASA NTRS1984

Two-region analysis of interface shape in continuous casting with superheated liquid

A slab ingot is being formed as a continuous casting by withdrawal from a mold with parallel walls. The sides of the ingot below the mold are cooled to remove heat of fusion and energy transferred to the solidification interface by superheated liquid metal in the mold. A two-region analysis is made to determine the non-uniform heat conduction from the liquid metal to the interface, and then from the interface to the cooled ingot sides. The solidification interface shape is found that is compatible with the removal of fusion energy and nonuniform heating from the liquid. The solution is obtained by two applications of a Cauchy boundary value method.

Siegel, R.↗
NASA NTRS1987

Fluoride salts and container materials for thermal energy storage applications in the temperature range 973 - 1400 K

Multicomponent fluoride salt mixtures were characterized for use as latent heat of fusion heat storage materials in advanced solar dynamic space power systems with operating temperatures in the range of 973 to 1400 K. The melting points and eutectic composition for many systems with published phase diagrams were verified, and several new eutectic compositions were identified. Additionally, the heats of fusion of several binary and ternary eutectics and congruently melting intermediate compounds were measured by differential scanning calorimetry. The extent of corrosion of various metals by fluoride melts was estimated from thermodynamic considerations, and equilibrium conditions inside a containment vessel were calculated as functions of the initial moisture content of the salt and free volume above the molten salt. Preliminary experimental data on the corrosion of commercial, high-temperature alloys in LiF-19.5CaF2 and NaF-27CaF2-36MgF2 melts are presented and compared to the thermodynamic predictions.

Misra, Ajay K.↗
NASA NTRS1981

A Solution in Search of Problems

Ferrofluids offered vast-problem solving potential. Under license for the NASA technology, Dr. Ronald Moskowitz and Dr. Ronald Rosensweig formed Ferrofluids Corporation. First problem they found a solution for was related to the manufacture of semiconductor "chips" for use in electronic systems. They developed a magnetic seal composed of ferrofluid and a magnetic circuit. Magnetic field confines the ferrofluid in the regions between the stationary elements and the rotary shaft of the seal. Result is a series of liquid barriers that totally bar passage of contaminants. Seal is virtually wear-proof and has a lifetime measured in billions of shaft revolutions. It has reduced maintenance, minimizes "downtime" of production equipment, and reduces the cost of expensive materials that had previously been lost through seal failures. Products based on ferrofluid are exclusion seals for computer disc drives and inertia dampers for stepper motors. Uses are performance-improving, failure-reducing coolants for hi-fi loudspeakers. Other applications include analytical instrumentation, medical equipment, industrial processes, silicon crystal growing furnaces, plasma processes, fusion research, visual displays, and automated machine tools.

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