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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Moderate repetition rate ultra-intense laser targets and optics using variable thickness liquid crystal films

Liquid crystal films are variable thickness, planar targets for ultra-intense laser matter experiments such as ion acceleration. Their target qualities also make them ideal for high-power laser optics such as plasma mirrors and waveplates. By controlling parameters of film formation, thickness can be varied on-demand from 10 nm to above 50 μm, enabling real-time optimization of laser interactions. Presented here are results using a device that draws films from a bulk liquid crystal source volume with any thickness in the aforementioned range. Films form within 2 μm of the same location each time, well within the Rayleigh range of even tight F/# systems, thus removing the necessity for realignment between shots. As a result, the repetition rate of the device exceeds 0.1 Hz for sub-100nm films, facilitating higher repetition rate operation of modern laser facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Uncertainty Analysis in 3D Equilibrium Reconstruction

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the results of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dispersive X-ray absorption spectroscopy using independent grazing-incidence focusing and convexly bent Bragg-crystal dispersing optics

We present a modular instrument for dispersive X-ray absorption spectroscopy (DXAS) developed for the Advanced Spectroscopy Beamline at Sector 25 of the Advanced Photon Source. The setup employs a double-multilayer monochromator to provide X-rays with a broad energy bandwidth, Kirkpatrick–Baez mirrors for focusing, a convexly bent Bragg-crystal polychromator for energy dispersion, and a pixel-array detector to resolve all X-ray energies and collect their intensity simultaneously, thereby enabling acquisition of a full X-ray absorption spectrum in a single shot. The use of separate optics for X-ray focusing and energy dispersion provides high spatial resolution and avoids chromatic aberrations inherent in focusing bent-crystal optics, and a modular design makes implementation of the technique at other beamlines possible without requiring modifications to the upstream beamline configurations. Theoretical calculations are performed to determine optimal instrument operating parameters and demonstrate that an energy resolution better than the K-edge core-hole lifetime broadening can be maintained while providing a sufficient bandwidth for X-ray absorption near-edge structure spectroscopy through the full operating range of 5–11 keV. Additionally, instrument design, data analysis methods, and initial DXAS results on lithium–manganese–nickel oxide laminates are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

DeepAndes: A Self-Supervised Vision Foundation Model for Multispectral Remote Sensing Imagery of the Andes

By mapping sites at large scales usingremotely sensed data, archaeologists can generate unique insights into long-term demographic trends, interregional social networks, and human adaptations in the past. Remote sensing surveys complement field-based approaches, and their reach can be especially great when combined with deep learning and computer vision techniques. However, conventional supervised deep learning methods face challenges in annotating fine-grained archaeological features at scale. In addition, while recent vision foundation models have shown remarkable success in learning large-scale remote sensing data with minimal annotations, most off-the-shelf solutions are designed for RGB images rather than multispectral satellite imagery, such as the eight-band data used in our study. In this article, we introduce DeepAndes, a transformer-based vision foundation model trained on three million multispectral satellite images, specifically tailored for Andean archaeology. DeepAndes incorporates a customized DINOv2 self-supervised learning algorithm optimized for eight-band multispectral imagery, marking the first foundation model designed explicitly for the Andes region. We evaluate its image understanding performance through imbalanced image classification, image instance retrieval, and pixel-level semantic segmentation tasks. Our experiments show that DeepAndes achieves superior F1 scores, mean average precision, and Dice scores in few-shot learning scenarios, significantly outperforming models trained from scratch or pretrained on smaller datasets. This underscores the effectiveness of large-scale self-supervised pretraining in archaeological remote sensing.

Guo, Junlin [Vanderbilt Univ., Nashville, TN (Unit↗
DOE OSTI2023

Sampling frequency thresholds for the quantum advantage of the quantum approximate optimization algorithm

We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers Gurobi and MQLib to solve the MaxCut problem on 3-regular graphs. We identify the minimum noiseless sampling frequency and depth p required for a quantum device to outperform classical algorithms. There is potential for quantum advantage on hundreds of qubits and moderate depth with a sampling frequency of 10 kHz. We observe, however, that classical heuristic solvers are capable of producing high-quality approximate solutions in linear time complexity. In order to match this quality for large graph sizes N, a quantum device must support depth p > 11. Additionally, multi-shot QAOA is not efficient on large graphs, indicating that QAOA p ≤ 11 does not scale with N. These results limit achieving quantum advantage for QAOA MaxCut on 3-regular graphs. Other problems, such as different graphs, weighted MaxCut, and 3-SAT, may be better suited for achieving quantum advantage on near-term quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Choppers to optimise the repetition rate multiplication technique on a direct geometry neutron chopper spectrometer

In recent years the use of repetition rate multiplication (RRM) on direct geometry neutron spectrometers has been established and is the common mode of operation on a growing number of instruments. However, the chopper configurations are not ideally optimised for RRM with a resultant 100 fold flux difference across a broad wavelength band. This paper presents chopper configurations that will produce a relative constant (RC) energy resolution and a relative variable (RV) energy resolution for optimised use of RRM. The RC configuration provides an almost uniform ΔE/E for all incident wavelengths and enables an efficient use of time as the entire dynamic range is probed with equivalent statistics, ideal for single shot measurements of transient phenomena. The RV energy configuration provides an almost uniform opening time at the sample for all incident wavelengths with three orders of magnitude in time resolution probed for a single European Spallation Source (ESS) period, which is ideal to probe complex relaxational behaviour. These two chopper configurations have been simulated for the Versatile Optimal Resolution direct geometry spectrometer, VOR, that will be built at ESS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Iterative reconstruction excursions for Baryon Acoustic Oscillations and beyond

ABSTRACT The density field reconstruction technique has been widely used for recovering the baryon acoustic oscillation (BAO) feature in galaxy surveys that has been degraded due to non-linearities. Recent studies advocated adopting iterative steps to improve the recovery much beyond that of the standard technique. In this paper, we investigate the performance of a few selected iterative reconstruction techniques focusing on the BAO and the broad-band shape of the two-point clustering. We include redshift-space distortions, halo bias, and shot noise and inspect the components of the reconstructed field in Fourier space and in configuration space using both density field-based reconstruction and displacement field-based reconstruction. We find that the displacement field reconstruction becomes quickly challenging in the presence of non-negligible shot noise and therefore present surrogate methods that can be practically applied to a much more sparse field such as galaxies. For a galaxy field, implementing a debiasing step to remove the Lagrangian bias appears crucial for the displacement field reconstruction. We show that the iterative reconstruction does not substantially improve the BAO feature beyond an aggressively optimized standard reconstruction with a small smoothing kernel. However, we find taking iterative steps allows us to use a small smoothing kernel more ‘stably’, i.e. without causing a substantial deviation from the linear power spectrum on large scales. In one specific example we studied, we find that a deviation of 13 per cent in $P(k\sim 0.1\, h{\rm \,\,Mpc^{-1}})$ with an aggressive standard reconstruction can reduce to 3–4 per cent with iterative steps.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

A new Fabry-Perot spectrometer for observations of diffuse near-infrared line emission

We describe a new Fabry-Perot spectrometer that is optimized for the detection of extended, low-surface-brightness line emission from 1.4 to 2.4 microns. The instrument combines high throughput and high sensitivity, yet limits the background radiation falling on the detector. The instrument has a single 20 sec - 200 sec beam and a resolving power lambda/delta(lambda) approximately 2500. The system is background shot-noise limited in the K window and limited by a combination of read noise, dark-current shot noise, and fluctuations in the OH airglow lines in the H window. We present sample data of some of the lowest-surface-brightness H2 line emission in the near infrared obtained to date.

Luhman, M. L.↗
DOE OSTI2017

Computed Axial Lithography (CAL):Toward Single Step 3D Printing of Arbitrary Geometries

Most additive manufacturing processes today operate by printing voxels (3D pixels) serially point-by-point to build up a 3D part. In some more recently-developed techniques, for example optical printing methods such as projection stereolithography [Zheng et al. 2012], [Tumbleston et al. 2015], parts are printed layer-by-layer by curing full 2d (very thin in one dimension) layers of the 3d part in each print step. There does not yet exist a technique which is able to print arbitrarily-defined 3D geometries in a single print step. If such a technique existed, it could be used to expand the range of printable geometries in additive manufacturing and relax constraints on factors such as overhangs in topology optimization. It could also vastly increase print speed for 3D parts. In this work, we develop the principles for an approach for single exposure 3D printing of arbitrarily defined geometries. Our approach, termed Computed Axial Lithgography (CAL), is based on tomographic reconstruction, with mathematical optimization to generate a set of projections to optically define an arbitrary dose distribution within a target volume. We demonstrate the potential ability of the technique to print 3D parts using a prototype CAL system based on sequential illumination from many angles. Finally, we propose new hardware designs which will help us to realize true single-shot arbitrary-geometry 3D CAL.

42 ENGINEERING↗
DOE OSTI2022

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. Furthermore, while robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by implementing a few-shot learning (FSL) approach. A knowledge-based model originally developed for a HT-PEMFCs was used to generate simulated data (887,735 points) and used to pretrain a neural network source model tuned via a genetic algorithm-based AutoML. Then, experimental datasets from HT-PEMFCs with different materials and operating conditions (~50 points each) were used to train six target models via FSL. Models for the unseen data reached high accuracies in all cases (rRMSE < 10%).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Cr-Be Pushered Single Shell (PSS) Capsule Development

Pushered single shell (PSS) has emerged as an alternative platform of implosion to ease the stability issue at the ablation front. The design consists of a thin inner Be layer, a 50% Cr:Be plateau region, an S-curve gradient, a low Cr (1.5%) tamper layer, and followed by a pure Be outer layer. General Atomics has developed a way to fabricate the higher-Z Cr to lower-Z Be gradients on glow discharge polymer mandrels with a designed S-shape profile for optimal implosion stability using magnetron sputtering. Microstructure analysis of the gradient coating indicated that at lower Cr concentration a short order or amorphous structure was formed. Here, these fabricated PSS capsules were subsequently built into capsule fill tube assemblies, verified to be leak tight at both ambient and cryogenic conditions, and delivered to Lawrence Livermore National Laboratory for the shots. The capsule thermal stability was demonstrated by invariable Cr profiles before and after pyrolysis. However, cracking at inner Cr layers was observed, which has been attributed to thermal stress.

Capsule↗
NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
DOE OSTI2017

RCCI Combustion Regime Transitions in a Single-Cylinder Optical Engine and a Multi-Cylinder Metal Engine

We present that Reactivity Controlled Compression Ignition (RCCI) is an approach to increase engine efficiency and lower engine-out emissions by using in-cylinder stratification of fuels with differing reactivity (i.e., autoignition characteristics) to control combustion phasing. Stratification can be altered by varying the injection timing of the high-reactivity fuel, causing transitions across multiple regimes of combustion. When injection is sufficiently early, combustion approaches a highly-premixed autoignition regime, and when it is sufficiently late it approaches more mixing-controlled, diesel-like conditions. Engine performance, emissions, and control authority over combustion phasing with injection timing are most favorable in between, within the RCCI regime.To study charge preparation phenomena that dictate regime transitions, two different optical diagnostics are applied in a single-cylinder heavy-duty optical engine, and conventional engine diagnostics are applied in a multi-cylinder, light-duty all-metal engine. Both engines are operated with iso-octane and n-heptane as the low- and high-reactivity fuels, respectively. The iso-octane fuel fraction delivers 80% of the total fuel energy, the global equivalence ratio is 0.35, and no exhaust gas recirculation is used. In the optical engine, single-shot, band-pass infrared (IR) imaging of emission near 3.3 microns measures thermal C-H stretch-band emission of hot fuel vapor and intermediate combustion products, providing qualitative information about the fuel-vapor distribution and ignition locations during low-temperature heat release. Additionally, high-speed 7.2 kHz visible-light imaging of natural luminosity, optimized to detect chemiluminescence, indicates the spatial and temporal evolution of high-temperature heat release and combustion. Similar combustion regimes are observed for both engine platforms, allowing an opportunity for optical engine data to provide insight into fundamental phenomena affecting regime ranges and transitions in production engines. Key findings from imaging diagnostics indicate that at the late-injection limit of RCCI control authority, low-temperature ignition occurs when clearly identifiable jet structures are still intact, and during high-temperature combustion there is prevalent and persistent soot incandescence representative of locally mixing-limited (i.e., fuel-rich) combustion. Finally, at the early-injection limit of RCCI control, observed stratification during low-temperature ignition is subtle; however, high-temperature combustion still occurs sequentially from the bowl rim radially inwards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Lightweight jet reconstruction and identification as an object detection task

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN large hadron collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Single Shot Detection network. The algorithm, named PFJet-SSD performs simultaneous localization, classification and regression tasks to cluster jets and reconstruct their features. This all-in-one single feed-forward pass gives advantages in terms of execution time and an improved accuracy w.r.t. traditional rule-based methods. A further gain is obtained from network slimming, homogeneous quantization, and optimized runtime for meeting memory and latency constraints of a typical real-time processing environment. We experiment with 8-bit and ternary quantization, benchmarking their accuracy and inference latency against a single-precision floating-point. We show that the ternary network closely matches the performance of its full-precision equivalent and outperforms the state-of-the-art rule-based algorithm. Finally, we report the inference latency on different hardware platforms and discuss future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2008

Signal Analysis Algorithms for Optimized Fitting of Nonresonant Laser Induced Thermal Acoustics Damped Sinusoids

This study seeks a numerical algorithm which optimizes frequency precision for the damped sinusoids generated by the nonresonant LITA technique. It compares computed frequencies, frequency errors, and fit errors obtained using five primary signal analysis methods. Using variations on different algorithms within each primary method, results from 73 fits are presented. Best results are obtained using an AutoRegressive method. Compared to previous results using Prony s method, single shot waveform frequencies are reduced approx.0.4% and frequency errors are reduced by a factor of approx.20 at 303K to approx. 0.1%. We explore the advantages of high waveform sample rates and potential for measurements in low density gases.

Balla, R. Jeffrey↗
DOE OSTI2013

Optical characteristics of a HgBr excilamp

Optical characteristics of a coaxial HgBr excilamp on multicomponent mercury dibromide vapour mixtures with helium, nitrogen and sulfur hexafluoride are investigated under pumping by a pulse-periodic barrier discharge. Stable excilamp operation was demonstrated at a pump pulse repetition rate of 3 – 9 kHz. The component composition of the working system was determined, which provides a maximal average and pulsed specific radiation power of 48.8 mW cm{sup -3} and 40.6 W cm{sup -3}, respectively, at the efficiency of 7.3 % in the blue-green spectral range with the maximal radiation intensity at the wavelength of 502 nm. The reduction in the radiation power after 2.5 × 10{sup 6} shots is 5 %. Interpretation is given for the results of optimisation of excilamp characteristics. (optical radiation sources)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Molecular level structure in water-alcohol mixtures; from shots to pints: L’Chaim!

The two objectives of this work are to look at the molecular level mixing in water-alcohol liquid mixtures and to determine how well the Effective Fragment Potential (EFP) method performs at describing small, heterogenous water-alcohol mixtures. In this work we look both at small clusters, size 2 – 24 molecules, as well as bulk mixtures, 64 or more molecules. For small clusters (2 – 24 molecules), the molecular structure was studied using the EFP method and MP2. Extensive Monte Carlo/simulated annealing (MC/SA) global optimizations were used to locate low energy structures for all water, alcohol, and water-alcohol mixtures. The alcohols studied include the small, straight-chain, primary alcohols: methanol, ethanol, propanol, and 1-butanol as well as the secondary alcohol 2-butanol, and tertiary butanol. It is shown that a number of low energy mixed clusters retain the structural characteristics of the pure clusters. It is also shown that the EFP method performs well at describing small, heterogenous water-alcohol mixtures. The molecular structure in bulk water, alcohol, and water-alcohol mixtures is studied with the EFP method and molecular dynamics simulations. Radial distribution functions are used to analyze structure and to benchmark the EFP method against experimental results. The effect of alcohol concentration and alcohol chain length on the local structure of water is investigated. Preliminary results indicate that the EFP method can potentially model bulk water-alcohol systems well as compared to experiment. Results on the effects of alcohol chain length are forthcoming.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗