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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Magnetized Target Fusion: Prospects for Low-Cost Fusion Energy

Magnetized Target Fusion (MTF) has attracted renewed interest in recent years because it has the potential to resolve one of the major problems with conventional fusion energy research - the high cost of facilities to do experiments and in general develop practical fusion energy. The requirement for costly facilities can be traced to fundamental constraints. The Lawson condition implies large system size in the case of conventional magnetic confinement, or large heating power in the case of conventional inertial confinement. The MTF approach is to use much higher fuel density than with conventional magnetic confinement (corresponding to megabar pressures), which results in a much-reduced system size to achieve Lawson conditions. Intrinsically the system must be pulsed because the pressures exceed the strength of any known material. To facilitate heating the fuel (or "target") to thermonuclear conditions with a high-power high-intensity source of energy, magnetic fields are used to insulate the high-pressure fuel from material surroundings (thus "magnetized target"). Because of magnetic insulation, the required heating power intensity is reduced by many orders of magnitude compared to conventional inertial fusion, even with relatively poor energy confinement in the magnetic field, such as that characterized by Bohm diffusion. In this paper we show semi-quantitatively why MTF-should allow fusion energy production without costly facilities within the same generally accepted physical constraints used for conventional magnetic and inertial fusion. We also briefly discuss potential applications of this technology ranging from nuclear rockets for space propulsion to a practical commercial energy system. Finally, we report on the exploratory research underway, and the interesting physics issues that arise in the MTF regime of parameters. Experiments at Los Alamos are focused on formation of a suitable plasma target for compression, utilizing the knowledge base for compact toroids called Field-Reversed Configurations. As reported earlier, it appears that the existing pulsed-power Shiva Star facility at the Air Force Research Laboratory in Albuquerque, NM can satisfy the heating requirements by means of imploding a thin metal cylinder (called a "liner") surrounding an FRC of the type presently being developed. The proposed next step is an integrated liner-on-plasma experiment in which an FRC would be heated to 10 keV by the imploding liner.

Siemon, Richard E.↗
NASA NTRS2018

Gradient Field Imploding Liner Fusion Propulsion System: NASA Innovative Advanced Concepts Phase I Final Report

The advancement of human deep space exploration requires the continued development of energetic in-space propulsion systems, from current chemical engines to nuclear thermal rockets to future high energy concepts such as nuclear fusion. As NASA embarks on a program to develop near-term nuclear thermal propulsion, this NASA Innovative Advanced Concepts (NIAC) Phase I activity was funded to investigate the feasibility of an innovative approach toward highly energetic pulsed fusion propulsion. Previous concept studies have proposed the conversion of fusion energy for in-space propulsion, ranging from laser-ignited fusion systems such as Gevaltig and VISTA, to the British Interplanetary Society's Daedalus concept and its more recent incarnation under Project Icarus, to steady-state spherical torus fusion systems. Recent NIAC studies have also evaluated several innovative fusion concepts, including the acceleration and compression of field reversed configuration plasmas in time-changing magnetic fields, magnetically driven liners imploding onto plasma targets, and high current z-pinch compression of material liners onto fission-fusion fuel targets. While each of these studies firmly established the potential benefits of fusion systems for interplanetary travel, they also identified significant challenges in successfully engineering such systems for spacecraft propulsion. The concept outlined in this Technical Publication (TP) builds on the lessons learned from these prior activities, approaching the quest for fusion-powered propulsion through an innovative variation of magneto-inertial fusion concepts developed for terrestrial power applications.

Lapointe, M. R.↗
DOE OSTI2025

Data-driven picosecond X-ray imaging for quantitative plasma-induced shock characterization

Imaging dynamic events, especially shockwave behavior, is key to advancing high-energy-density (HED) research. Recent advances in fourth- and fifth-generation X-ray light sources allow for high-resolution imaging of fast phenomena, but limited beam time necessitates maximizing data acquisition. We present a benchtop-scale pulsed plasma device submerged in liquid heptane, capable of generating dynamic events at rates exceeding 10 Hz, supporting the field’s data-driven goals by producing large, high-quality imaging datasets. Using X-ray phase contrast imaging (XPCI) at the Advanced Photon Source, we imaged weak shockwaves (Mach ~ 1.2) in heptane interacting with plasma-induced cavitation bubbles, causing deviation from Rankine-Hugoniot behavior; to our knowledge, this represents the first direct imaging of such interaction. Our quantitative analysis offers insight into weak shock phenomena and energy-focusing applications in pulsed plasmas. These results highlight the potential for large datasets to advance dynamic HED research at current light source facilities, and have implications for fields such as inertial confinement fusion, plasma-enhanced chemical processing, and biomedical applications.

36 MATERIALS SCIENCE↗
NASA NTRS2018

The Land Surface Data Toolkit (LDT v7.2) - A Data Fusion Environment for Land Data Assimilation Systems

The effective applications of land surface models (LSMs) and hydrologic models pose a varied set of data input and processing needs, ranging from ensuring consistency checks to more derived data processing and analytics. This article describes the development of the Land surface Data Toolkit (LDT), which is an integrated framework designed specifically for processing input data to execute LSMs and hydrological models. LDT not only serves as a preprocessor to the NASA Land Information System (LIS), which is an integrated framework designed for multi-model LSM simulations and data assimilation (DA) integrations, but also as a land-surface-based observation and DA input processor. It offers a variety of user options and inputs to processing datasets for use within LIS and stand-alone models. The LDT design facilitates the use of common data formats and conventions. LDT is also capable of processing LSM initial conditions and meteorological boundary conditions and ensuring data quality for inputs to LSMs and DA routines. The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models. Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational datasets and data analytics algorithms to aid land surface modeling and data assimilation.

droughts and floods↗
DOE OSTI2021

Improving the characterization of fusion in a MuSIC detector by spatial localization

Multi-Sampling Ionization Chambers (MuSIC) provide an efficient means of measuring nuclear reactions with low beam rates (< 10 6 pps). However, in comparison to thin-target measurements, prior measurements using MuSIC detectors all manifest fusion excitation functions with wide error bars in the energy dimension. This uncertainty limits the applicability of these devices in measuring near and sub-barrier fusion cross-sections. Key to overcoming this limitation is spatial localization of the fusion in the detector. By comparing the measured ionization in the MuSIC detector with accurate energy loss calculations the position of the fusion in the detector is determined. The analysis not only provides the desired improvement in energy resolution, but it also allows extraction of the atomic number of the evaporation residues following fusion. Furthermore, the effectiveness of this approach is demonstrated for 18 O+ 12 C measured with MuSIC@Indiana.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion

Abstract. Rivers and river habitats around the world are under sustained pressure from human activities and the changing global environment. Our ability to quantify and manage the river states in a timely manner is critical for protecting the public safety and natural resources. In recent years, vector-based river network models have enabled modeling of large river basins at increasingly fine resolutions, but are computationally demanding. This work presents a multistage, physics-guided, graph neural network (GNN) approach for basin-scale river network learning and streamflow forecasting. During training, we train a GNN model to approximate outputs of a high-resolution vector-based river network model; we then fine-tune the pretrained GNN model with streamflow observations. We further apply a graph-based, data-fusion step to correct prediction biases. The GNN-based framework is first demonstrated over a snow-dominated watershed in the western United States. A series of experiments are performed to test different training and imputation strategies. Results show that the trained GNN model can effectively serve as a surrogate of the process-based model with high accuracy, with median Kling–Gupta efficiency (KGE) greater than 0.97. Application of the graph-based data fusion further reduces mismatch between the GNN model and observations, with as much as 50 % KGE improvement over some cross-validation gages. To improve scalability, a graph-coarsening procedure is introduced and is demonstrated over a much larger basin. Results show that graph coarsening achieves comparable prediction skills at only a fraction of training cost, thus providing important insights into the degree of physical realism needed for developing large-scale GNN-based river network models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials

In this report we summarize the work conducted by PI Perdikaris and his group under this Early Career project DE–SC0019116 during the period of 09/01/2018 – 08/31/2023. The central aim of the work was to introduce a new paradigm for scientific data analysis that can seamlessly synthesize rigorous mathematical modeling with data of variable fidelity (e.g., measurements at multiple scales/resolutions or predictions of variable fidelity models) and multiple modalities (e.g., images, time–series, or scattered measurements). The setting we are interested in involves complex systems that are partially observed and whose dynamical behavior could be hard to model or totally unknown. The inherent uncertainty associated with this setting necessitates a departure from the classical deterministic realm of modeling and scientific computation, and, consequently, our main building blocks can no longer be crisp deterministic numbers and governing laws, but instead we must operate with probabilistic models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Chiral catalysis of nuclear fusion in molecules

At low energies, nuclear fusion is strongly affected by electron screening of the Coulomb repulsion among the fusing nuclei. It may thus be possible to catalyze nuclear fusion in molecules (i.e., to fuse specific nuclei in situ) through quantum control of electron wave functions in intense laser fields. The circularly polarized (chiral) laser field can effectively squeeze the electron wave functions, greatly enhancing the screening in the spatial region relevant for the fusion process. Here, we estimate the corresponding fusion probabilities, and find that the proposed chiral catalysis of nuclear fusion in molecules may be observable, potentially with important practical applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1999

Technical Considerations for Advanced Propulsion Systems

This presentation reviews concerns involving advanced propulsion systems. The problems involved with the use of Am-242m, is that it has a high "eta" plus an order of magnitude larger fission cross section than other fissionable materials, and that it is extremely rare. However other americium isotopes are much more common, but extremely effective isotopic separation is required. Deuterium-Tritium fusion is also not attractive for space propulsion applications. Because the pulsed systems cannot breed adequate amounts of tritium and it is difficult and expensive to bring tritium from Earth. The systems that do breed tritium have severely limited performance. However, other fusion processes should still be evaluated. Another problem with advanced propellants is that inefficiencies in converting the total energy generated into propellant energy can lead to tremendous heat rejection requirements. Therefore Many. advanced propulsion concepts benefit greatly from low-mass radiators.

Houts, Michael G.↗
NASA NTRS2001

The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

Maluf, David A.↗
DOE OSTI2020

Thermochemical Data Fusion Using Graph Representation Learning

Large databases are required for “Big Data” applications in catalysis and materials science. Thermochemical databases can be created by combining data from various sources and by correcting low-fidelity datasets to higher accuracy with minimal computation. To achieve this “data fusion”, thermochemical quantities of interest, calculated at various levels of density functional theory (DFT), need to be mapped to the same, high levels of theory. In this work, a graph theoretical, statistical framework is proposed for such tasks. Subgraph frequencies are shown to provide a natural representation for learning these fusion maps. The maps are linear and are learnt with automated descriptor selection. Using a dataset of as few as ~1% from the QM9 database of 133,885 molecules, these models can predict multiple thermochemical quantities at a higher level of theory with an accuracy of 1 kcal/mol. Here, the method is explainable, generalizable, and provides a diagnostic tool for outlier identification

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Characterization of laser-accelerated proton beams from a 0.5 kJ sub-picosecond laser for radiography applications

Laser-accelerated ion beams show promise for many applications, including high-resolution flash imaging of static or dynamic objects in next-generation radiography to probe materials and plasmas in extreme environments and inertial confinement fusion. To scale up ion beam production for radiography applications, we conducted experiments using sub-picosecond lasers up to 0.5 kJ at the OMEGA-EP facility to characterize proton beams from solid targets, primarily CH/CD sub-micron thin films from which ion beams were also used for static and dynamic radiography for the first time. For standalone sub-micron thin CH films, the highest detected proton energy is in the range of 72–97 MeV. Proton beams with highest energy near or above 60 MeV at full laser energy and similar beam profiles are also measured from low-density CD foams and flat CH foil target of micrometer-scale thickness. The ~ 700–800 nm CH/CD foils achieve the highest ion yield among the targets tested. For sub-micron thin films, the laser prepulse can expand the target and lead to complex interactions, which is simulated using coupled hydrodynamic and two-step kinetic models. Simulations suggest the presence of a micrometer-scale preplasma plateau with near-critical density and further indicate that target normal sheath acceleration, electron heating from Relativistic transparency in the preplasma plateau, and background proton reflection from carbon ion front at the rear side contribute to the resulting proton spectrum from these sub-micron thin targets at various stages. These proton beams show strong potential for radiography and for production of secondary sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Convolution-Based Numerical Solutions of Transient Temperature Fields during Powder Bed Fusion Additive Manufacturing: Theory, Accuracy, and Computational Cost

Powder bed fusion (PBF) additive manufacturing has found numerous applications in the aerospace domain. However, components fabricated via PBF have a complex time-temperature history that significantly impacts subsequent mechanical performance. This study examines convolution-based numerical solutions of transient temperature fields that support simulations involving arbitrary beam shapes and paths during PBF. The convolutional approach is verified through comparisons with analytical solutions of the temperature field. The computational speed and accuracy of the method are assessed through comparisons with other explicit and implicit numerical techniques. In addition, the straightforward translation of the approach from a CPU to a GPU implementation and the resultant performance improvement are presented. The role of the technique in predicting microstructure evolution during PBF (for a greater process-structure-property-performance framework) is also demonstrated. This work supports the development of computational materials methods for understanding and controlling the time-temperature history during PBF.

powder bed fusion↗
NASA NTRS1986

Advances in cryogenic engineering. Volume 31; Proceedings of the Cryogenic Engineering Conference, MIT, Cambridge, MA, Aug. 12-16, 1985

The present conference on the applications of state-of-the-art cryogenic engineering technologies considers topics associated with the development status of the 'Superconducting SuperCollider', superconducting magnetic energy storage methods, large magnets for fusion and other physics researches, cryogenic hardware improvements, and phenomena and applications of superconducting magnet-employing acoustic emission test equipment. Also discussed are design criteria for superconducting magnet stability, heat exchangers and heat transfer to liquid He and N, heat and mass transfer characteristics of He II, refrigeration techniques for magnetic resonance imaging and other small systems, refrigeration for liquefaction and for superconducting fusion as well as for accelerator and generator systems, magnetic refrigeration, cryocooling and refrigeration for space applications, the storage and transfer of cryogenic fluids, the properties of cryogenic liquids, and air liquefaction equipment.

Fast, R. W.↗
NASA NTRS2012

Nuclear Propulsion through Direct Conversion of Fusion Energy: The Fusion Driven Rocket

The future of manned space exploration and development of space depends critically on the creation of a dramatically more proficient propulsion architecture for in-space transportation. A very persuasive reason for investigating the applicability of nuclear power in rockets is the vast energy density gain of nuclear fuel when compared to chemical combustion energy. Current nuclear fusion efforts have focused on the generation of electric grid power and are wholly inappropriate for space transportation as the application of a reactor based fusion-electric system creates a colossal mass and heat rejection problem for space application.

Propulsion↗
DOE OSTI2023

Compression of tokamak boundary plasma simulation data using a maximum volume algorithm for matrix skeleton decomposition

This report demonstrates satisfactory data compression of SOLPS-ITER simulation output ranging from 2D fields, 1D profiles, and 0D scalar variables with a novel matrix decomposition approach. The singular value decomposition (SVD) scales poorly for large matrix sizes and is unsuited to the application on high dimensional data common to fusion plasma physics simulation. In this work, we employ the columns-submatrix-rows (CUR) matrix factorization technique in order to compute a low-rank approximation up to two orders of magnitude faster than the SVD, but within a nominal L2-norm relative error of ε = 10 –2 . In addition, the CUR approach maintains the original format of the data, in its extracted columns and rows, allowing for interpretable data storage at the original resolution of the simulation. We utilize an iterative algorithm to compute the CUR decomposition of simulation output by maximizing the volume, or linearly independent information content, of a low-rank submatrix contained within the data. Experiments over $\textit{n} × \textit{n}$ randomized test matrices with embedded rank-deficient features show that this maximum volume implementation of CUR matrix approximation has reduced asymptotic computational complexity on the order of n compared to the SVD, which scales approximately as $n^3$. These results show that the CUR technique can be used to effectively select time step snapshots (columns) of over 140 SOLPS-ITER output variables and the associated discretized coordinate timeseries (rows) allowing for reconstruction of the complete simulation dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Effect of alloying on intrinsic ductility in WTaCrV high entropy alloys

Tungsten (W) exhibits desirable properties for extreme applications, such as the divertor in magnetic fusion reactors, but its practicality remains limited due to poor formability and insufficient irradiation resistance. In this work, we study the intrinsic ductility of body-centered cubic WTaCrV based high entropy alloys (HEAs), which are known to exhibit excellent irradiation resistance. The ductility evaluations are carried out using a criterion based on the competition between the critical stress intensity factors for emission (K Ie ) and cleavage (K Ic ) in the {110} slip planes and {110} crack planes, which are evaluated within the linear elastic fracture mechanics framework and computed using density functional theory. The results suggest that increasing the alloying concentrations of V and reducing the concentrations of W can significantly improve the ductility in these HEAs. The elastic anisotropy for these HEAs is analyzed using the Zener anisotropy ratio and its correlation with the concentration of W in the alloys is studied. Results indicate that these alloys tend to be fairly isotropic independently from the concentration of W in them. The computed data for the elastic constants of these HEAs is also compared against available experimental data. The results are in good agreement, validating the robustness and accuracy of the computational methods. Multiple phenomenological ductility metrics were also computed and analyzed against the analytical model. Some metrics, mainly the surrogate D parameter, show a good correlation with the Rice model. The potential of these empirical metrics to serve as surrogate screening models for optimizing the compositional space is also discussed.

Anisotropy↗