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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 613 records · Page 34

Simulating plasma wave propagation on a superconducting quantum chip

Quantum computers may one day enable the efficient simulation of strongly coupled plasmas that lie beyond the reach of classical computation in regimes where quantum effects are important and the scale separation is large. Here, in this article, we take a first step toward efficient simulation of quantum plasmas by demonstrating linear plasma wave propagation on a superconducting quantum chip. Using high-fidelity and highly expressive device-native gates, combined with an error-mitigation technique, we simulate the scattering of laser pulses from inhomogeneous plasmas. Our approach is made feasible by the identification of a suitable local spin model whose excitations mimic plasma waves, and whose circuit implementation requires a lower gate count than other proposed approaches that would require a future fault-tolerant quantum computer. This work opens avenues to study more complicated phenomena that cannot be simulated efficiently on classical computers, such as nonlinear quantum dynamics when strongly coupled plasmas are driven out of equilibrium.

general physics↗

Neural network implementations of data association algorithms for sensor fusion

The paper is concerned with locating a time varying set of entities in a fixed field when the entities are sensed at discrete time instances. At a given time instant a collection of bivariate Gaussian sensor reports is produced, and these reports estimate the location of a subset of the entities present in the field. A database of reports is maintained, which ideally should contain one report for each entity sensed. Whenever a collection of sensor reports is received, the database must be updated to reflect the new information. This updating requires association processing between the database reports and the new sensor reports to determine which pairs of sensor and database reports correspond to the same entity. Algorithms for performing this association processing are presented. Neural network implementation of the algorithms, along with simulation results comparing the approaches are provided.

Brown, Donald E.↗

Integrated Data Analysis to Improve Te and Zeff Measurement on NSTX-U

The multi-energy soft x-ray (ME-SXR) camera is a new concept for a fusion plasma diagnostic based on a pixelated detector with adjustable photon cutoff thresholds. It is a single, compact, solid-state detector which combines spatial and spectral sensitivity and can be configured remotely at run time, making it ideal for a fusion environment. The detector can be configured for application to a wide range of physics problems including impurity transport, electron temperature profiles, and non-thermal effects. The detector has been installed on the Madison Symmetric Torus (MST) as part of a collaboration between Princeton Plasma Physics Laboratory and the University of Wisconsin–Madison to develop the technology and analysis techniques. A full diagnostic forward model of the ME-SXR diagnostic has been developed to enable analysis of the raw photon count data. This model incorporates the atomic physics underlying the plasma emission, diagnostic geometry, and detector response characteristics. Employing this model, a Bayesian analysis approach is used to extract electron temperature from the raw data. This analysis approach uses all available information, clearly quantifies prior information, and handles uncertainties transparently. The ME-SXR camera is being used to study the 3D (helical, stellarator-like) state that forms in the MST device. This helical core structure has improved energy confinement. The transition to the helical state is accompanied by a rise in electron temperature in the central part of the helical structure, but then this enhancement fluctuates. The characteristics of this fluctuation are being compared to a magneto-hydrodynamics model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

Large Scale and Multi-Alloy Rocket Engine Component Development using Various Metal Additive Manufacturing Techniques

The NASA Marshall Space Flight Center (MSFC) has been involved with various forms of metallic additive manufacturing (AM) for use in liquid rocket engine component design, development, and testing since 2010. These AM techniques have been demonstrated to significantly reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing fabrication of designs not feasible by conventional means. The focus at the NASA MSFC for these metal additive manufacturing techniques include laser powder-bed fusion (L-PBF), blown powder directed energy deposition (DED), arc-based deposition, and Laser Wire Direct Closeout (LWDC). A variety of components have been evaluated and tested including thrust chamber injectors, injector components such as faceplates, regeneratively-cooled combustion chambers, regeneratively-cooled nozzles, gas generator and preburner hardware, and augmented spark igniters. To support these component applications in harsh environments, NASA has advanced a variety of “standard” additive manufacturing alloys such as those in the superalloy-family and also evolved new alloys including GRCop-84, GRCop-42, NASA HR-1, and JBK-75. The purpose of this presentation is to discuss the various component programs at the NASA MSFC using AM to develop, fabricate, and test combustion devices hardware and the evolution of the new additive alloys. One of these projects that will be highlighted is Rapid Analysis and Manufacturing Propulsion Technology (RAMPT), which includes new process development for large scale AM components, multi-metallic AM components, including unique component designs using additive manufacturing. Additional information will be provided on the development of other components, hot-fire testing, post-processing of AM techniques including surface enhancements (polishing) techniques, material and process characterization, future development programs, and dissemination of data to industry partners.

Additive Manufacturing↗

Extended X-ray absorption spectroscopy using an ultrashort pulse laboratory-scale laser-plasma accelerator

Laser-driven compact particle accelerators can provide ultrashort pulses of broadband X-rays, well suited for undertaking X-ray absorption spectroscopy measurements on a femtosecond timescale. Here the Extended X-ray Absorption Fine Structure (EXAFS) features of the K-edge of a copper sample have been observed over a 250 eV window in a single shot using a laser wakefield accelerator, providing information on both the electronic and ionic structure simultaneously. This capability will allow the investigation of ultrafast processes, and in particular, probing high-energy-density matter and physics far-from-equilibrium where the sample refresh rate is slow and shot number is limited. For example, states that replicate the tremendous pressures and temperatures of planetary bodies or the conditions inside nuclear fusion reactions. Using high-power lasers to pump these samples also has the advantage of being inherently synchronised to the laser-driven X-ray probe. A perspective on the additional strengths of a laboratory-based ultrafast X-ray absorption source is presented.

43 PARTICLE ACCELERATORS↗

In-process volumetric sensing of defects in multiple parts during powder bed fusion using ultrasound

This letter reports on the integration of eight ultrasonic transducers into a build substrate for individual in-process monitoring of eight parts fabricated using powder bed fusion additive manufacturing. Ultrasound is shown to be able to sense poor fusion of parts to the substrate and also sensitivity to porosity. This technique demonstrates the utility of ultrasound as one of a few techniques able to interrogate the volume of additively manufactured parts during the process. Additionally, the ability to measure several parts during a single build can be used for efficient process parameter development studies, as the ultrasonic measurements can offer rapid information about part quality and integrity.

Kizer, Nathan J.↗

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

L. Prinzel↗

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

Aviation Safety↗

Progress In Plasma Accelerator Development for Dynamic Formation of Plasma Liners

An experimental plasma accelerator for magnetic target fusion (MTF) applications under development at the NASA Marshall Space Flight Center is described. The accelerator is a coaxial pulsed plasma thruster (Figure 1). It has been tested experimentally and plasma jet velocities of approx.50 km/sec have been obtained. The plasma jet has been photographed with 10-ns exposure times to reveal a stable and repeatable plasma structure (Figure 2). Data for velocity profile information has been obtained using light pipes and magnetic probes embedded in the gun walls to record the plasma and current transit respectively at various barrel locations. Preliminary spatially resolved spectral data and magnetic field probe data are also presented. A high speed triggering system has been developed and tested as a means of reducing the gun "jitter". This jitter is being characterized and future work for second generation "ultra-low jitter" gun development is being identified.

Thio, Y. C. Francis↗

Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel

The long-term thermal stability of structural alloys is essential for ensuring the safe and reliable operation of nuclear reactors and other power plants. While extensive research has explored the effects of thermal aging on conventional stainless steels, the behavior of additively manufactured (AM) alloys remains less understood. This study examines the thermal aging response of laser powder bed fusion (LPBF) 316H stainless steel (SS) at temperatures ranging from 550 °C to 750 °C over durations of up to 10,000 h (approximately 1.14 years). Advanced characterization techniques, including electron microscopy and synchrotron X-ray diffraction, were used to investigate dislocation recovery and phase evolution. Based on these findings, a time-temperature-precipitation (TTP) diagram was developed for LPBF 316H SS, revealing a 10- to100-fold acceleration in precipitation kinetics compared to wrought 316H SS. A physics-informed model was calibrated using the short-term experimental data, enabling predictions of average precipitate sizes, volume fractions of M 23 C 6 and Laves phases, and changes in molybdenum solute concentration for aging up to 1 × 10⁶ h (114 years). These microstructural insights were further utilized to estimate yield strength and extrapolate strength reduction factors over the extended aging period. Despite the accelerated aging kinetics, LPBF 316H SS demonstrated superior yield strength retention compared to its wrought counterpart. In conclusion, this study establishes a framework for evaluating long-term performance using short-term experimental data and supports the accelerated qualification of AM materials for high-temperature structural applications.

Laser powder bed fusion↗

Reduced models for ETG transport in the tokamak pedestal

This paper reports on the development of reduced models for electron temperature gradient (ETG) driven transport in the pedestal. Model development is enabled by a set of 61 nonlinear gyrokinetic simulations with input parameters taken from pedestals in a broad range of experimental scenarios. The simulation data have been consolidated in a new database for gyrokinetic simulation data, the multiscale gyrokinetic database (MGKDB), facilitating the analysis. The modeling approach may be considered a generalization of the standard quasilinear mixing length procedure. The parameter η, the ratio of the density to temperature gradient scale length, emerges as the key parameter for formulating an effective saturation rule. With a single order-unity fitting coefficient, the model achieves an error of 15%. A similar model for ETG particle flux is also described. We also present simple algebraic expressions for the transport informed by an algorithm for symbolic regression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Equivariant Graph Attention Network - 3D Conformers & Feature Fusion

EGAN-3F (Equivariant Graph Attention Network - 3D Conformers & Feature Fusion) presents an innovative approach for predicting binding affinity between small molecules and protein targets, a fundamental task in drug discovery. Traditional structure-based methods often depend on protein-ligand complex structures obtained from crystallography or molecular docking. In contrast, ligand-only machine learning models using 1D or 2D representations such as SMILES have been developed to predict binding affinity without structural information about the target; however, their accuracy is often limited due to the lack of 3D ligand information. EGAN-3F addresses this limitation by integrating spatially aware graph learning with traditional descriptor-based features. We systematically investigate how combining 2D and 3D molecular representations enhances binding affinity prediction from SMILES strings. This approach underscores the importance of modeling conformational diversity and incorporating chemically meaningful descriptors to improve predictive accuracy. The key innovation of EGAN-3F lies in its ability to achieve robust ligand-based binding affinity predictions without requiring protein-ligand complex structures, effectively bridging the gap between purely structural and ligand-only modeling paradigms.

Shim, Heesung [Lawrence Livermore National Laborat↗

Modeling the electron cyclotron emission radiation signature from suprathermal electrons in a tokamak

An Electron Cyclotron Emission (ECE) modeling code has been developed to model ECE radiation with an arbitrary electron momentum distribution, a small oblique angle, both ordinary (O-mode) and extraordinary polarizations (X-mode), and multiple cyclotron frequency harmonics. The emission and absorption coefficients are calculated using the Poynting theorem from the cold plasma dispersion and the electron–microwave interaction from the full anti-Hermitian tensor. The modeling shows several ECE radiation signatures that can be used to diagnose the population of suprathermal electrons in a tokamak. First, in an n = 2 X-mode (X2) optically thick plasma and oblique ECE view, the modeling shows that only suprathermal electrons, which reside in a finite region of the velocity and space domains, can effectively generate cyclotron emissions to the ECE receiver. The code also finds that the O1 mode is sensitive to suprathermal electrons of both a high v ⊥ and v || , while the X2 mode is dominantly sensitive to suprathermal electrons of a high v ⊥ . Finally, the modeling shows that an oblique ECE system with both X/O polarization and a broad frequency coverage can be used to effectively yield information of the suprathermal electron population in a tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transformation and gene editing in the bioenergy grass Miscanthus

Miscanthus, a C4 member of Poaceae, is a promising perennial crop for bioenergy, renewable bioproducts, and carbon sequestration. Species of interest include nothospecies M. x giganteus and its parental species M. sacchariflorus and M. sinensis. Use of biotechnology-based procedures to genetically improve Miscanthus, to date, have only included plant transformation procedures for introduction of exogenous genes into the host genome at random, non-targeted sites. We developed gene editing procedures for Miscanthus using CRISPR/Cas9 that enabled the mutation of a specific (targeted) endogenous gene to knock out its function. Classified as paleo-allopolyploids (duplicated ancient Sorghum-like DNA plus chromosome fusion event), design of guide RNAs (gRNAs) for Miscanthus needed to target both homeologs and their alleles to account for functional redundancy. Prior research in Zea mays demonstrated that editing the lemon white1 (lw1) gene, involved in chlorophyll and carotenoid biosynthesis, via CRISPR/Cas9 yielded pale green/yellow, striped or white leaf phenotypes making lw1 a promising target for visual confirmation of editing in other species. Using sequence information from both Miscanthus and sorghum, orthologs of maize lw1 were identified; a multi-step screening approach was used to select three gRNAs that could target homeologs of lw1. Embryogenic calli of M. sacchariflorus, M. sinensis and M. x giganteus were transformed via particle bombardment (biolistics) or Agrobacterium tumefaciens introducing the Cas9 gene and three gRNAs to edit lw1. Leaves on edited Miscanthus plants displayed the same phenotypes noted in maize. Sanger sequencing confirmed editing; deletions in lw1 ranged from 1 to 26 bp in length, and one deletion (433 bp) encompassed two target sites. Confocal microscopy verified lack of autofluorescence (chlorophyll) in edited leaves/sectors. We developed procedures for gene editing via CRISPR/Cas9 in Miscanthus and, to the best of our knowledge, are the first to do so. This included five genotypes representing three Miscanthus species. Designed gRNAs targeted all copies of lw1 (homeologous copies and their alleles); results also confirmed lw1 made a good editing target in species other than Z. mays. The ability to target specific loci to enable endogenous gene editing presents a new avenue for genetic improvement of this important biomass crop.

09 BIOMASS FUELS↗

Experience With Bayesian Image Based Surface Modeling

Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.

Stutz, John C.↗

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗