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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 OSTI2011

Target Diagnostics Supports NIF's Path to Ignition

The physics requirements derived from the National Ignition Facility (NIF) experimental campaigns are leading to a wide variety of target diagnostics. Software development for the control and analysis of these diagnostics is included in the NIF Integrated Computer Control System, Diagnostic Control System and Data Visualization. These projects implement the configuration, controls, data analysis and visual representation of most of these diagnostics. To date, over 40 target diagnostics have been developed to support NIF experiments. In 2011 diagnostics were developed or enhanced to measure Ignition performance in a high neutron yield environment. Performance is optimized around four key variables: Adiabat (a) which is the strength and timing of four shocks delivered to the target, Velocity (V) of the imploding target, Mix (M) is the uniformity of the burn, and the Shape (S) of the imploding Deuterium Tritium (DT) hot spot. The diagnostics used to measure each of these parameters is shown in figure 1. Adiabat is measured using the Velocity Interferometer System for Any Reflector (VISAR) diagnostic consisting of three streak cameras. To provide for more accurate adiabat measurements the VISAR streak cameras were enhanced in FY11 with a ten comb fiducial signal controller to allow for post shot correction of the streak camera sweep non-linearity. Mix is measured by the Neutron Time of Flight (NTOF) and Radiochemical Analysis of Gaseous Samples (RAGS) diagnostics. To accommodate high neutron yield shots, NTOF diagnostic controls are being modified to use Mach Zehnder interferometer signals to allow the digitizers to be moved from near the target chamber to the neutron shielded diagnostic mezzanine. In December 2011 the first phase of RAGS diagnostic commissioning will be completed. This diagnostic will analyze the tracers that are added to NIF target capsules that undergo nuclear reactions during the shot. These gases are collected and purified for nuclear counting by the RAGS system. Three new instrument controllers were developed and commissioned to support this diagnostic. A residual-gas analyzer (RGA) instrument measures the gas content at various points in the system. The Digital Gamma Spectrometer instrument measures the radiological spectrum of the decaying gas isotopes. A final instrument controller was developed to interface to a PLC based Gas collection system. In order to support the implosion velocity measurements an additional Gated X-ray Detector (GXD) diagnostic was tested and commissioned. This third GXD views the target through a slit contained in its snout and allows the other GXD diagnostics to be used for measuring the shape on the same shot. In order to measure the implosion shape in a high neutron environment, Actide Readout In A Neutron Environment (ARIANE) and Neutron Imaging (NI) diagnostics were commissioned. The controls for ARIANE, a fixed port gated x-ray imager, contain a neutron shielded camera and micro channel plate pulser with its neutron sensitive electronics located in the diagnostic mezzanine. The NI diagnostic is composed of two Spectral Instruments SI-1000 cameras located 20M from the target and provides neutron images of the DT hot spot for high yield shots. The development and commissioning of these new or enhanced diagnostics in FY11 have provided meaningful insight that facilitates the optimization of the four key Ignition variables. In FY12 they will be adding three new diagnostics and enhancing four existing diagnostics in support of the continuing optimization series of campaigns.

42 ENGINEERING↗
DOE OSTI2016

The LCLS variable-energy hard X-ray single-shot spectrometer

The engineering design, implementation, operation and performance of the new variable-energy hard X-ray single-shot spectrometer (HXSSS) for the LCLS free-electron laser (FEL) are reported. The HXSSS system is based on a cylindrically bent Si thin crystal for dispersing the incident polychromatic FEL beam. A spatially resolved detector system consisting of a Ce:YAG X-ray scintillator screen, an optical imaging system and a low-noise pixelated optical camera is used to record the spectrograph. The HXSSS provides single-shot spectrum measurements for users whose experiments depend critically on the knowledge of the self-amplified spontaneous emission FEL spectrum. It also helps accelerator physicists for the continuing studies and optimization of self-seeding, various improved mechanisms for lasing mechanisms, and FEL performance improvements. The designed operating energy range of the HXSSS is from 4 to 20 keV, with the spectral range of order larger than 2% and a spectral resolution of 2 × 10 -5 or better. Those performance goals have all been achieved during the commissioning of the HXSSS.

Rich, David↗
DOE OSTI2017

Online Measurement of the Energy Spread of Multi-Turn Beam in the Fermilab Booster at Injection

We have developed a computer program interfaced with the ACNET environment of Fermilab accelerators to measure energy spread of the proton beam from the LINAC at an injection into the Booster. It uses a digitizing oscilloscope and provides users an ability to configure the scope settings for optimal data acquisition from a resistive wall current monitor. When the program is launched, a) a one shot timeline is generated to initiate beam injection into the Booster, b) a gap of about 40 ns is produced in the injected beam using a set of fast kickers, c) collects line charge distribution data from the wall current monitor for the first 200 μs from the injection and d) performs complete data analysis to extract full beam energy spread of the beam. The program also gives the option to store the data for offline analyses. We illustrate a case with an example. We also present results on beam energy spread as a function of beam intensity from recent measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Experimental and numerical investigations of beryllium strength models using the Rayleigh-Taylor instability

We present a set of high explosive driven Rayleigh-Taylor strength experiments for beryllium to produce data to distinguish predictions by various strength models. Design simulations using existing strength model parameterizations from Steinberg-Lund and Preston-Tonks-Wallace (PTW) suggested an optimal design that would delineate between not just different strength models, but different parameters sets of the PTW model. Application of the models to the post-shot results, however, suggests growth consistent with little material strength. We focus mostly on efforts to simulate the data using published strength models as well as the more recent RING relaxation model developed at VNIIEF. The results of the strength experiments indicate weak influence of strength in mitigating the growth with the RING model coming closest to predicting the material behavior. Finally, we present shock and ramp-loading recovery experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Analysis of Cygnus Electrical Signals

The United States initiated the Subcritical Experiment (SCE) program to support a stockpile stewardship mission shortly after the 1992 moratorium on underground nuclear testing was established. Many SCE’s are conducted at the Nevada National Security Site (NNSS) in Nevada. Cygnus is a high-energy radiation generating device (RGD) located and operated at the NNSS and is a primary diagnostic for the SCE program. The Cygnus Dual Beam Radiographic Facility consists of two identical radiographic sources, Cygnus 1 and Cygnus 2. From creation of the high power V-I drive to energy transport and X-ray conversion at the rod-pinch diode, the Cygnus machines utilize the following components: oil-filled Marx generator, water-filled pulse-forming line (PFL), water-filled coaxial transmission line (CTL), three-cell vacuum induction voltage adder (IVA), and rod-pinch diode. The diode pulse has the following electrical specifications: 2.25 MV, 60 kA, 60 ns. Each source has the following X-ray specifications: 1 mm diameter, 4 rad at 1 m, and 50 ns radiation pulse. SCEs are both single-event and high-value; therefore, a high level of performance in reliability and reproducibility are key issues of Cygnus. Prior to executing such a SCE, there are a formidable number of shots (e.g., each of the two Cygnus RGDs charging and discharging properly into the rod-pinch diode load) that must be executed to determine reliability and reproducibility of the Cygnus RGDs. For every shot on Cygnus, voltages and currents along the machine are recorded and analyzed. In this paper we summarize attributes of the voltage and current waveforms at different locations using distribution plots. These distribution plots are used to quantify the reliability and reproducibility for Cygnus. This analysis methodology will provide a standard to trouble shoot results of individual Cygnus shots, and also to monitor long term Cygnus performance. Accordingly, this type of extensive analysis will contribute to optimized Cygnus performance on SCEs.

42 ENGINEERING↗
DOE OSTI2021

Leading order corrections to the quantum extremal surface prescription

We show that a naïve application of the quantum extremal surface (QES) prescription can lead to paradoxical results and must be corrected at leading order. The corrections arise when there is a second QES (with strictly larger generalized entropy at leading order than the minimal QES), together with a large amount of highly incompressible bulk entropy between the two surfaces. We trace the source of the corrections to a failure of the assumptions used in the replica trick derivation of the QES prescription, and show that a more careful derivation correctly computes the corrections. Using tools from one-shot quantum Shannon theory (smooth min- and max-entropies), we generalize these results to a set of refined conditions that determine whether the QES prescription holds. We find similar refinements to the conditions needed for entanglement wedge reconstruction (EWR), and show how EWR can be reinterpreted as the task of one-shot quantum state merging (using zero-bits rather than classical bits), a task gravity is able to achieve optimally efficiently.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Ion heating dynamics in solid buried layer targets irradiated by ultra-short intense laser pulses

We investigate bulk ion heating in solid buried layer targets irradiated by ultra-short laser pulses of relativistic intensities using particle-in-cell simulations. Our study focuses on a CD{sub 2}-Al-CD{sub 2} sandwich target geometry. We find enhanced deuteron ion heating in a layer compressed by the expanding aluminium layer. A pressure gradient created at the Al-CD{sub 2} interface pushes this layer of deuteron ions towards the outer regions of the target. During its passage through the target, deuteron ions are constantly injected into this layer. Our simulations suggest that the directed collective outward motion of the layer is converted into thermal motion inside the layer, leading to deuteron temperatures higher than those found in the rest of the target. This enhanced heating can already be observed at laser pulse durations as low as 100 fs. Thus, detailed experimental surveys at repetition rates of several ten laser shots per minute are in reach at current high-power laser systems, which would allow for probing and optimizing the heating dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Advancing a Low-Temperature, Low-Cost Direct Air Capture System Based on Organic Chemistry

Holocene Climate Corporation (Holocene) partnered with Oak Ridge National Laboratory (ORNL) to conduct bench-scale testing of a new optimized Direct Air Capture (DAC) process to assist the U.S. Department of Energy (DOE) in achieving the Carbon Negative Shot target of under $\$$100/net tonne CO₂ removed by 2031. Holocene’s DAC process for carbon dioxide (CO₂) removal uses amino acids and guanidine compounds, an ORNL-invented chemical process and licensed by Holocene. Holocene will use this novel chemistry to develop a new process and deploy the technology commercially.

36 MATERIALS SCIENCE↗
DOE OSTI2023

XploreNAS : Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars

Compute In-Memory platforms such as memristive crossbars are gaining focus as they facilitate acceleration of Deep Neural Networks (DNNs) with high area and compute efficiencies. However, the intrinsic non-idealities associated with the analog nature of computing in crossbars limits the performance of the deployed DNNs. Furthermore, DNNs are shown to be vulnerable to adversarial attacks leading to severe security threats in their large-scale deployment. Thus, finding adversarially robust DNN architectures for non-ideal crossbars is critical to the safe and secure deployment of DNNs on the edge. This work proposes a two-phase algorithm-hardware co-optimization approach called XploreNAS that searches for hardware efficient and adversarially robust neural architectures for non-ideal crossbar platforms. We use the one-shot Neural Architecture Search approach to train a large Supernet with crossbar-awareness and sample adversarially robust Subnets therefrom, maintaining competitive hardware efficiency. Our experiments on crossbars with benchmark datasets (SVHN, CIFAR10, CIFAR100) show up to ~8–16% improvement in the adversarial robustness of the searched Subnets against a baseline ResNet-18 model subjected to crossbar-aware adversarial training. We benchmark our robust Subnets for Energy-Delay-Area-Products (EDAPs) using the Neurosim tool and find that with additional hardware efficiency–driven optimizations, the Subnets attain ~1.5–1.6× lower EDAPs than ResNet-18 baseline.

97 MATHEMATICS AND COMPUTING↗
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.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A customizable data management framework for high-repetition-rate high-energy-density science

The high-energy-density (HED) physics community is moving toward a new paradigm of high-repetition-rate (HRR) operation. To fully leverage the scientific power of HRR HED facilities, all of the components of each subsystem (laser, targetry, and performance diagnostics) must be connected and synchronized in a reliable and robust manner while the data acquired are tagged and archived in real time. To this end, GA has begun developing a generalized NoSQL-database framework, the MongoDB repository for information and archiving. An organizational strategy has been developed that shifts HED data organization from a shot-based to a diagnostic-based approach in order to increase archival and retrieval efficiency that lends itself to optimization applications. This work is a first step in pushing HRR HED science toward data management solutions that emphasize machine actionability and aim to stimulate community engagement to define data standards in HED science.

Instruments & Instrumentation↗
DOE OSTI2012

Automated treatment planning for a dedicated multi-source intracranial radiosurgery treatment unit using projected gradient and grassfire algorithms

Purpose: The purpose of this work is to develop a framework to the inverse problem for radiosurgery treatment planning on the Gamma Knife{sup Registered-Sign} Perfexion Trade-Mark-Sign (PFX) for intracranial targets. Methods: The approach taken in the present study consists of two parts. First, a hybrid grassfire and sphere-packing algorithm is used to obtain shot positions (isocenters) based on the geometry of the target to be treated. For the selected isocenters, a sector duration optimization (SDO) model is used to optimize the duration of radiation delivery from each collimator size from each individual source bank. The SDO model is solved using a projected gradient algorithm. This approach has been retrospectively tested on seven manually planned clinical cases (comprising 11 lesions) including acoustic neuromas and brain metastases. Results: In terms of conformity and organ-at-risk (OAR) sparing, the quality of plans achieved with the inverse planning approach were, on average, improved compared to the manually generated plans. The mean difference in conformity index between inverse and forward plans was -0.12 (range: -0.27 to +0.03) and +0.08 (range: 0.00-0.17) for classic and Paddick definitions, respectively, favoring the inverse plans. The mean difference in volume receiving the prescribed dose (V{sub 100}) between forward and inverse plans was 0.2% (range: -2.4% to +2.0%). After plan renormalization for equivalent coverage (i.e., V{sub 100}), the mean difference in dose to 1 mm{sup 3} of brainstem between forward and inverse plans was -0.24 Gy (range: -2.40 to +2.02 Gy) favoring the inverse plans. Beam-on time varied with the number of isocenters but for the most optimal plans was on average 33 min longer than manual plans (range: -17 to +91 min) when normalized to a calibration dose rate of 3.5 Gy/min. In terms of algorithm performance, the isocenter selection for all the presented plans was performed in less than 3 s, while the SDO was performed in an average of 215 min. Conclusions: PFX inverse planning can be performed using geometric isocenter selection and mathematical modeling and optimization techniques. The obtained treatment plans all meet or exceed clinical guidelines while displaying high conformity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Application of deep learning to single-shot gas-phase laser-induced breakdown spectroscopy

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has the potential to capture ns-scale electrode desorption phenomena in pulsed power fusion drivers. However, the successful implementation of the diagnostic for this purpose is challenging, as it requires interpreting single-shot measurements collected from low-density gas mixtures. In this work, we demonstrate the efficacy of a Bayesian-optimized convolutional neural network (CNN) to interpret these measurements. We generated 256 distinct measurement conditions at relevant gas pressures ranging from 80–530 mTorr by mixing 100–250 sccm H 2 and 50–200 sccm CH 4 in increments of 10 sccm. Despite the considerable overlap between signals separated by 20 sccm, the CNN is able to predict the H 2 flow rate with a root-mean-square error (RMSE) of 15.9 sccm and the CH 4 flow rate with an RMSE of 12.0 sccm. The average relative prediction error is <9% for each gas and largely remains below or near 10%.

Brown, Nathan Parnell [Sandia National Lab. (SNL-N↗
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 ↗
NASA NTRS1995

Carbon isotopic analysis of atmospheric methane by isotope-ratio-monitoring gas chromatography-mass spectrometry

Less than 15 min are required for the determination of delta C(sub PDB)-13 with a precision of 0.2 ppt(1 sigma, single measurement) in 5-mL samples of air containing CH4 at natural levels (1.7 ppm). An analytical system including a sample-introduction unit incorporating a preparative gas chromatograph (GC) column for separation of CH4 from N2, O2, and Ar is described. The 15-min procedure includes time for operation of that system, high-resolution chromatographic separation of the CH4, on-line combustion and purification of the products, and isotopic calibration. Analyses of standards demonstrate that systematic errors are absent and that there is no dependence of observed values of delta on sample size. For samples containing 100 ppm or more CH4, preconcentration is not required and the analysis time is less than 5 min. The system utilizes a commercially available, high-sensitivity isotope-ratio mass spectrometer. For optimal conditions of smaple handling and combustion, performance of the system is within a factor of 2 of the shot-noise limit. The potential exists therefore for analysis of samples as small as 15 pmol CH4 with a standard deviation of less than 1 ppt.

Merritt, Dawn A.↗
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↗
NASA NTRS1991

Clear line of sight (CLOS) statistics within cloudy regions and optimal sampling strategies for space-based lidars

Simulated cloud/hole fields as well as Landsat imagery are used in a computer model to evaluate several proposed sampling patterns and shot management schemes for pulsed space-based Doppler lidars. Emphasis is placed on two proposed sampling strategies - one obtained from a conically scanned single telescope and the other from four fixed telescopes that are sequentially used by one laser. The question of whether there are any sampling patterns that maximize the number of resolution areas with vertical soundings to the PBL is addressed.

Emmitt, G. D.↗