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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Source localization for neutron imaging systems using convolutional neural networks

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for determining the geometry of inertial confinement fusion implosions. The geometry is reconstructed from a neutron aperture image via a set of reconstruction algorithms using an iterative Bayesian inference approach. An important step in these reconstruction algorithms is finding the fusion source location within the camera field-of-view. Currently, source localization is achieved via an iterative optimization algorithm. In this paper, we introduce a machine learning approach for source localization. Specifically, we train a convolutional neural network to predict source locations given a neutron aperture image. We show that this approach decreases computation time by several orders of magnitude compared to the current optimization-based source localization while achieving similar accuracy on both synthetic data and a collection of recent NIF deuterium–tritium shots.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗
DOE OSTI2019

Optimizing galaxy samples for clustering measurements in photometric surveys

When analysing galaxy clustering in multiband imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-$z$) precision, which generally includes only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third-year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range $z$ = 0.2–0.95. We quantify the cosmological constraints using a figure of merit (FoM) that measures the combined constraints on $Ωm$ and $σ_8$ in the context of Λ cold dark matter ($Λ$CDM) cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to (1) whether cross-correlations between redshift bins are included or not, and (2) the ratio of the redshift bin width $δz$ to the photo-$z$ precision $σ_z$. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when $δz$ ~ $σ_z$. We find that for the typical case of 5-10 redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher $σ_z$, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Characterization and automated optimization of laser-driven proton beams from converging liquid sheet jet targets

Compact, stable, and versatile laser-driven ion sources hold great promise for applications ranging from medicine to materials science and fundamental physics. While single-shot sources have demonstrated favorable beam properties, including the peak fluxes necessary for several applications, high-repetition-rate operation will be necessary to generate and sustain the high average flux needed for many of the most exciting applications of laser-driven ion sources. Further, to navigate through the high-dimensional space of laser and target parameters toward experimental optima, it is essential to develop ion acceleration platforms compatible with machine learning techniques and capable of autonomous real-time optimization. Here, we present a multi-Hz ion acceleration platform employing a liquid sheet jet target. We characterize the laser-plasma interaction and the laser-driven proton beam across a variety of key parameters governing the interaction using an extensive suite of online diagnostics. We also demonstrate real-time, closed-loop optimization of the ion beam maximum energy by tuning the laser wave front using a Bayesian optimization scheme. This approach increased the maximum proton energy by 11% compared to a manually optimized wave front by enhancing the energy concentration within the laser focal spot, demonstrating the potential for closed-loop optimization schemes to tune future ion accelerators for robust high-repetition-rate operation.

Glenn, G. D. [SLAC National Accelerator Laboratory↗
DOE OSTI2022

An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules

The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.

McKeon, Caroline A. (ORCID:0000000217373503)↗
DOE OSTI2014

Propagation And Damping Of High Harmonic Fast Waves And Electron Cyclotron Waves In The Nstx-U-Device

For the spherical torus and for conventional tokamaks to be viable means of producing fusion energy there are two important requirements. The first is to heat the plasma in the experimental devices to high temperatures; preferably, to fusion relevant temperatures. The second is to drive a current in the plasma so that the fusion device operates in a steady-state mode. A pulsed fusion reactor for energy production is not desirable. A favored means to achieve both of these requirements is through the use of microwaves, commonly referred to as radio frequency waves. This proposal was to understand observations from the National Spherical Torus Experiment Upgrade (NSTX-U) device on radio frequency wave heating of the confined plasma during operations with high harmonic fast waves. The proposed research was also directed toward assisting in the optimization of the experimental modes of operation so as to maximize the heating efficiency. A detailed analysis of the experiments has shown that about one-third of the input radio frequency power does not make it into the core region of the plasma where heating is required. The losses are believed to occur primarily in the edge region where the radio frequency power is initially coupled into the plasma. Using sophisticated computational codes and theoretical models, that have been developed for the NSTX-U experimental program, this research quantified the physical processes which occur in the edge plasma and lead to a decrease in the heating efficiency. The effect of edge turbulence on the scattering of radio frequency waves was studied for waves in the ion cyclotron and electron cyclotron range of frequencies. For high harmonic fast waves in the ion cyclotron range of frequencies, simulations were carried out using a full-wave solver that was extended to the vacuum vessel wall. These simulations successfully reproduced trends that were observed experimentally. This simulation capability was also used to study the interaction of high harmonic fast waves with the scrape-off layer plasma. More recently, a new technique has been developed for the calculation of radio frequency waves in toroidal geometry that enables the simultaneous incorporation of antenna geometry, plasma facing components, the scrape off-layer, and core propagation in the high harmonic fast wave regime. The effect of turbulent plasmas on the mode conversion of extraordinary electromagnetic waves in the electron cyclotron range of frequencies in the NSTX-U plasma has been studied theoretically. In the over-dense plasmas of NSTX-U, the traditional electromagnetic waves are not effective for delivering energy and momentum to the core plasma. However, electron Bernstein waves generated by mode conversion are efficient carriers of wave energy and momentum to the core. The mode conversion occurs in the turbulent edge region. A theory for mode conversion in such plasmas has been developed. The parameters that can optimize the mode conversion can be readily determined. Also, the model is useful for experimentalists to analyze observation on a shot-to-shot basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Propagation And Damping Of High Harmonic Fast Waves And Electron Cyclotron Waves In The Nstx-U-Device

For the spherical torus and for conventional tokamaks to be viable means of producing fusion energy there are two important requirements. The first is to heat the plasma in the experimental devices to high temperatures; preferably, to fusion relevant temperatures. The second is to drive a current in the plasma so that the fusion device operates in a steady-state mode. A pulsed fusion reactor for energy production is not desirable. A favored means to achieve both of these requirements is through the use of microwaves, commonly referred to as radio frequency waves. This proposal was to understand observations from the National Spherical Torus Experiment Upgrade (NSTX-U) device on radio frequency wave heating of the confined plasma during operations with high harmonic fast waves. The proposed research was also directed toward assisting in the optimization of the experimental modes of operation so as to maximize the heating efficiency. A detailed analysis of the experiments has shown that about one-third of the input radio frequency power does not make it into the core region of the plasma where heating is required. The losses are believed to occur primarily in the edge region where the radio frequency power is initially coupled into the plasma. Using sophisticated computational codes and theoretical models, that have been developed for the NSTX-U experimental program, this research quantified the physical processes which occur in the edge plasma and lead to a decrease in the heating efficiency. The effect of edge turbulence on the scattering of radio frequency waves was studied for waves in the ion cyclotron and electron cyclotron range of frequencies. For high harmonic fast waves in the ion cyclotron range of frequencies, simulations were carried out using a full-wave solver that was extended to the vacuum vessel wall. These simulations successfully reproduced trends that were observed experimentally. This simulation capability was also used to study the interaction of high harmonic fast waves with the scrape-off layer plasma. More recently, a new technique has been developed for the calculation of radio frequency waves in toroidal geometry that enables the simultaneous incorporation of antenna geometry, plasma facing components, the scrape off-layer, and core propagation in the high harmonic fast wave regime. The effect of turbulent plasmas on the mode conversion of extraordinary electromagnetic waves in the electron cyclotron range of frequencies in the NSTX-U plasma has been studied theoretically. In the over-dense plasmas of NSTX-U, the traditional electromagnetic waves are not effective for delivering energy and momentum to the core plasma. However, electron Bernstein waves generated by mode conversion are efficient carriers of wave energy and momentum to the core. The mode conversion occurs in the turbulent edge region. A theory for mode conversion in such plasmas has been developed. The parameters that can optimize the mode conversion can be readily determined. Also, the model is useful for experimentalists to analyze observation on a shot-to-shot basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes

Abstract We propose an on-chip gyroscope based on nonlinear multiresonant optics in a thin film χ (2) resonator that combines high sensitivity, compact form factor, and low power consumption simultaneously. We theoretically analyze a novel holistic metric – Fisher Information capacity of a multiresonant nonlinear photonic cavity – to fully characterize the sensitivity of our gyroscope under fundamental quantum noise conditions. Leveraging Bayesian optimization techniques, we directly maximize the nonlinear multiresonant Fisher Information. Our holistic optimization approach orchestrates a harmonious convergence of multiple physical phenomena – including noise squeezing, nonlinear wave mixing, nonlinear critical coupling, and noninertial signals – all encapsulated within a single sensor-resonator, thereby significantly augmenting sensitivity. We show that ∼ 470 × $\sim 470{\times}$ improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.

42 ENGINEERING↗
DOE OSTI2024

Predicting ptychography probe positions using single-shot phase retrieval neural network

Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstructed ptychography image is highly dependent on the accuracy of the recorded probe positions which often contain errors. These errors are typically corrected jointly with phase retrieval through numerical optimization approaches. When the error accumulates along the scan path or when the error magnitude is large, these approaches may not converge with satisfactory result. We propose a fundamentally new approach for ptychography probe position prediction for data with large position errors, where a neural network is used to make single-shot phase retrieval on individual diffraction patterns, yielding the object image at each scan point. The pairwise offsets among these images are then found using a robust image registration method, and the results are combined to yield the complete scan path by constructing and solving a linear equation. We show that our method can achieve good position prediction accuracy for data with large and accumulating errors on the order of 10 2 pixels, a magnitude that often makes optimization-based algorithms fail to converge. For ptychography instruments without sophisticated position control equipment such as interferometers, our method is of significant practical potential.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Entanglement estimation in non-optimal qubit states

Highlights: • Quantum Fisher Information. • Entanglement Estimation. • Squeezed States. • Husimi Function. - Abstract: In the last years, a relationship has been established between the quantum Fisher information (QFI) and quantum entanglement. In the case of two-qubit systems, all pure entangled states can be made useful for sub-shot-noise interferometry while their QFI meets a necessary and sufficient condition (Hyllus et al., 2010). In M-qubit systems, the QFI provides just a sufficient condition in the task of detecting the degree of entanglement of a generic state (Pezzé and Smerzi, 2009). In our work, we show analytically that, for a large class of one-parameter non-optimal two-qubit states, the maximally entangled states are associated with stationary points of the QFI, as a function of such parameter. We show, via numerical simulations, that this scenario is maintained for the generalisation of this class of states to a generic M-qubit system. Furthermore, we suggest a scheme for an interferometer able to detect the entanglement in a large class of two-spin states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Detection limits for laser absorption spectroscopy of Li in laser ablation plumes

A high-sensitivity laser absorption spectroscopy (LAS) method is demonstrated for rapid and non-contact analysis of Li in solids. Glass samples with Li concentrations ranging from 1-500 ppm by mass are ablated in 5 Torr air, and time-resolved Li atomic absorption is measured using a tunable laser near 671 nm. Significant improvements in analytical performance over prior laser-induced breakdown techniques are demonstrated. Here, a single-shot limit of detection (LOD) of 180 ppb is shown for fixed wavelength operation, improving to 6 ppb with averaging over 1000 ablation shots (100 s acquisition time). Isotope-resolved Li absorption spectra are measured with a 17 ppb LOD in 40 s. Methods for optimizing LOD based on noise/averaging properties of LAS experiments in LA plumes are discussed.

(020.3260) Isotope shifts↗
DOE OSTI2015

Highly collimated monoenergetic target-surface electron acceleration in near-critical-density plasmas

Optimized-quality monoenergetic target surface electron beams at MeV level with low normalized emittance (0.03π mm mrad) and high charge (30 pC) per shot have been obtained from 3 TW laser-solid interactions at a grazing incidence. The 2-Dimension particle-in-cell simulations suggest that electrons are wake-field accelerated in a large-scale, near-critical-density preplasma. It reveals that a bubble-like structure as an accelerating cavity appears in the near-critical-density plasma region and travels along the target surface. A bunch of electrons are pinched transversely and accelerated longitudinally by the wake field in the bubble. The outstanding normalized emittance and monochromaticity of such highly collimated surface electron beams could make it an ideal beam for fast ignition or may serve as an injector in traditional accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Wavefront sensing at X-ray free-electron lasers

Here a direct comparison is made between various X-ray wavefront sensing methods with application to optics alignment and focus characterization at X-ray free-electron lasers (XFELs). Focus optimization at XFEL beamlines presents unique challenges due to high peak powers as well as beam pointing instability, meaning that techniques capable of single-shot measurement and that probe the wavefront at an out-of-focus location are desirable. The techniques chosen for the comparison include single-phase-grating Talbot interferometry (shearing interferometry), dual-grating Talbot interferometry (moiré deflectometry) and speckle tracking. All three methods were implemented during a single beam time at the Linac Coherent Light Source, at the X-ray Pump Probe beamline, in order to make a direct comparison. Each method was used to characterize the wavefront resulting from a stack of beryllium compound refractive lenses followed by a corrective phase plate. In addition, difference wavefront measurements with and without the phase plate agreed with its design to within λ/20, which enabled a direct quantitative comparison between methods. Finally, a path toward automated alignment at XFEL beamlines using a wavefront sensor to close the loop is presented.

42 ENGINEERING↗
DOE OSTI2012

X-Ray Emission Spectrometer Design with Single-Shot Pump-Probe and Resonant Excitation Capabilities

Core-level spectroscopy in the soft X-ray regime is a powerful tool for the study of chemical bonding processes. The ultrafast, ultrabright X-ray pulses generated by the Linac Coherent Light Source (LCLS) allow these reactions to be studied in greater detail than ever before. In this study, we investigated a conceptual design of a spectrometer for the LCLS with imaging in the non-dispersive direction. This would allow single-shot collection of X-ray emission spectroscopy (XES) measurements with varying laser pump X-ray probe delay or a variation of incoming X-ray energy over the illuminated area of the sample. Ray-tracing simulations were used to demonstrate how the components of the spectrometer affect its performance, allowing a determination of the optimal final design. These simulations showed that the spectrometer's non-dispersive focusing is extremely sensitive to the size of the sample footprint; the spectrometer is not able to image a footprint width larger than one millimeter with the required resolution. This is compatible with a single shot scheme that maps out the laser pump X-ray probe delay in the non-dispersive direction as well as resonant XES applications at normal incidence. However, the current capabilities of the Soft X-Ray (SXR) beamline at the LCLS do not produce the required energy range in a small enough sample footprint, hindering the single shot resonant XES application at SXR for chemical dynamics studies at surfaces. If an upgraded or future beamline at LCLS is developed with lower monochromator energy dispersion the width can be made small enough at the required energy range to be imaged by this spectrometer design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

High yield polar direct drive fusion neutron sources at the National Ignition Facility

Polar direct drive neutron source experiments were performed at the National Ignition Facility showing substantial improvement in total neutron yield and efficiency of conversion of laser energy to fusion output. Plastic capsules 3–4 mm in diameter were filled with 1.5 mg/cc of deuterium–tritium (DT) fuel and imploded with laser beam pointing and defocus designed to compensate for polar asymmetry introduced by the facility beam entrance angles. Radiation-hydrodynamics simulations were employed to optimize the multi-dimensional laser and target parameter space, within facility and target fabrication constraints. Ensembles of 1D simulations tuned to match the outputs of early shots in the series were used to design subsequent shots in the series. This allowed the later shots to be designed based on empirically motivated sensitivities to laser and target input parameters, while eliminating the need to explicitly model phenomena such as hydrodynamic instabilities and nonlinear laser–plasma interactions. Additionally, one experiment with a 3.0 mm diameter CH capsule produced 13.6 kJ (4.81 × 10 15 DT neutrons) from a laser input below the NIF optics damage threshold at 585 kJ, 328 TW. Two experiments with 4.0 mm capsules produced 31.3 and 33.6 kJ of fusion output (1.11 × 10 16 and 1.19 × 10 16 DT neutrons) with 1.10 MJ, 390 TW and 1.26 MJ, 425 TW of laser input, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
DOE OSTI2025

Evaluating Variable-Impedance Magnetically-Insulated Transmission Lines as a Risk-Mitigation Measure for Next-Generation Pulsed Power

This project has produced the first detailed characterizations of power flow resulting from applying the “variable-impedance MITL” concept to real-life systems in Sandia’s pulsed power program (Z and next-generation pulsed power (NGPP)). We present simulation results and analyses for constant-impedance versions of both Z and NGPP and survey the operational viability of several variable-impedance re-designs in the parameter space of linear tapers. Circuit modeling (SCREAMER/Bertha) was used to pinpoint promising candidate designs, and EM-PIC (Empire) simulations were used to evaluate these candidates more rigorously. This approach was particularly successful in the Z regime which resulted in the identification of several viable variable-impedance MITL designs for each level. The approach was more challenged in the operating space NGPP occupies, producing data points that speak to a more restrictive design space due to anode plasma turn-on. In the end, we were able to converge on one viable variable-impedance design for the highest inductance line (level “F”) and one for the highest current line (level “A”). Altogether, the body of simulation evidence presented in this report suggest there does exist flexibility in operating space for magnetically-insulated transmission lines (MITLs) having variable geometric impedance to be a potential enabling technology for safely increasing current delivery (and potentially lowering stack voltage) in pulsed-power drivers by manipulating electron losses; however, operating points for a particular design must be carefully screened. Circuit and EM-PIC modeling provided consistent verdicts in safe operating regimes for operational viability, but additional physics such as anode plasma turn-on which is included in Empire but not in SCREAMER/Bertha was found to be a critical factor affecting power flow that lead to different assessments between the codes. It is not always the case that the occurrence of anode plasma caused a design to fail (some designs turned on anode plasma yet still delivered load currents meeting design targets); the details matter such as how early in the pulse anode surfaces break down (and how large a region). However, in every case that it did fail it was found that the feedback from anode plasma was the cause (i.e., turning off the anode plasma model in Empire restored agreement with the circuit model prediction). As circuit simulations represent an efficient and practical means of surveying design space compared to more computationally-expensive approaches such as EM-PIC, it could be prudent to invest in the research and development of models to include the effects of anode plasma such as ion emission in circuit codes. The variable-impedance MITL design is a new concept that enables controlled manipulation of the initial electron losses in the outer MITL and can be tested on Z today. We encourage follow-on work to explore further optimization (including alternative variable-impedance profiles, e.g., having constant dZ/dR), and to confirm the major findings presented in this report by fielding test hardware on actual Z shots.

24 POWER TRANSMISSION AND DISTRIBUTION↗