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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-camera imaging to characterize jet and liner uniformity on the Plasma Liner Experiment (PLX)

At Plasma Liner Experiment, a set of 36 coaxial plasma guns are deployed quasi-uniformly over a 9 ft diameter spherical chamber and are used to form a high-Z spherically compressive plasma liner. Simulations indicate that for the concept to ultimately achieve optimal target density and temperature, a high degree of timing uniformity is required between all guns. Therefore, to aid in quantifying and correcting gun-to-gun nonuniformities, a key diagnostic will consist of up to six fisheye-view CCD cameras positioned inside the main chamber such that each has all plasma guns within its view. The individual cameras can be triggered at different times to determine each plasma jet’s muzzle velocity and structure for different operating conditions. This camera array is currently under development, and the implementation needs and challenges for this camera array are discussed here. Additionally, we detail the analysis methodology for determining jet-to-jet uniformity deviations and how we can correct them, thereby improving overall liner uniformity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A glimpse of stars the size of dust particles

The Nuclear Imaging System (NIS) is an important diagnostic tool used to study nuclear fusion implosions at a research facility in California. There a capsule the size of a flea is compressed until it reaches the size of a speck of dust. As the capsule collapses on itself and ignites under extreme temperature and pressure, NIS detects particles emitted from that process at a scale that would correspond to watching a 32-inch TV screen from 100 miles away. My work involves taking snapshots of one of the most minuscule, fleeting and amazing experiments on Earth in order to ensure the safety and reliability of the US nuclear stockpile and get closer to developing a new form of clean energy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Nanocompression of 20 nm Silver Nanoparticles: In situ Aberration‐Corrected TEM and Atomistic Simulations

Single‐crystalline nanoparticles play an increasingly important role in a wide variety of fields including pharmaceuticals, advanced materials, catalysts for fuel cells, energy materials, as well as environmental detection and monitoring. Yet, the deformation mechanisms of very small nanoparticles are still poorly understood, in particular the role played by single dislocations and their interaction with surfaces. Here, in this work, silver nanoparticles with particularly small dimensions (≈20 nanometers in diameter) are compressed in situ in an aberration‐corrected transmission electron microscopy (TEM) and molecular dynamics (MD) simulations. During compression, the emergence of both dislocations and nanotwins are observed. However, these defects prove to be unstable and disappear upon removal of the indenter. Atomistic simulations confirm the role played by image stresses associated with the nearby surfaces and the reduction in dislocation line length as it approaches the free surface, thereby supporting the experimental observations. These results provide justification for the frequent observation of the absence of dislocations in nanoparticles of a few nanometers in size during in situ experiments, even after significant deformation. This phenomenon contributes to the self‐healing of samples through dislocation ejection toward the surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Bulk-scale stress–strain hysteresis in layered crystalline solids: A study of graphite and Ti 3 SiC 2

Polycrystalline graphite and the MAX phase Ti 3 SiC 2 are layered crystalline solids with similar deformation mechanisms, including basal slip, ripplocation boundaries (RBs), kink boundaries (KBs), and cracking. The interplay of these mechanisms, notably in energy dissipation, has been much discussed in the past twenty-five years. This study builds upon previous work, investigating deformation with a renewed emphasis on the bulk-scale and given recent findings concerning RBs. Our investigation compares the evolution of energy dissipation, nonlinear recoverable and irrecoverable strain, and damage upon increasing stress for graphite and Ti 3 SiC 2 . Benitez et al.’s (2016) methodology of compressive cyclic loading and post-mortem electron backscatter diffraction (EBSD) to assess the prevalence of kinking based on low-angle grain boundaries (LAGBs) was used. Strains were measured with digital image correlation and EBSD was conducted on Ti 3 SiC 2 leveraging dictionary indexing, which was necessary herein to identify LAGBs accurately. The stress–strain stages of Ti 3 SiC 2 agree with literature on Ti 2 AlC. Damage and energy dissipation were more accelerated in graphite. No significant difference was observed in the fraction of LAGBs between pristine and unloaded Ti 3 SiC 2 . Trends observed and EBSD evidence that KBs were not dominant suggest that RBs are the primary dissipator of energy in both materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Measurement of mix at the fuel–ablator interface in indirectly driven capsule implosions on the National Ignition Facility

The interface between the capsule ablator and fuel ice layer is susceptible to hydrodynamic instabilities. The subsequent mixing of hot ablator material into the ice reduces fuel compression at stagnation and is a candidate for reduced capsule performance. The ability to diagnose ice–ablator mix is critical to understanding and improving stability at this interface. Combining the crystal backlighter imager with the single line of sight camera on the National Ignition Facility (NIF) allows direct measurement of ice–ablator mix by providing multiple quasi-monochromatic radiographs of layered capsule implosions per experiment with high spatial (∼12 μm) and temporal (∼35 ps) resolution. The narrow bandwidth of this diagnostic platform allows radiography of the inner edge of the capsule limb close to stagnation without capsule self-emission contaminating the data and removes opacity uncertainties typically associated with the spectral content of the radiograph. Analysis of radiographic data via a parameterized forward-fitting Abel inversion technique provides measurements of the distribution of mix mass inwards from the ice–ablator interface. The sensitivity of this mix measurement technique was demonstrated by applying it to layered experiments in which the stability of the ice–ablator interface was expected to vary significantly. Additional experiments suggest that high-density carbon capsules that employ a buried-layer dopant profile suffer from mixing at the innermost doped–undoped interface. Data from these experiments suggest that opacity models used in hydrodynamic simulations of NIF experiments can potentially over-predict the opacity of doped capsules. LLNL-JRNL-850535-DRAFT.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗
DOE OSTI2025

Dynamic Strength and Equation of State of Epon 828 and Diethanolamine (DEA) Polymer Epoxy Under Shock Loading

Polymers are increasingly utilized in engineering applications that can experience high loading rates, necessitating increased understanding of their response under such conditions. The tamped Richtmyer-Meshkov Instability (RMI) method was used to characterize the equation of state and dynamic strength of the polymer Epon 828 cured with Diethanolamine (DEA). Plate impact experiments that drove a uniaxial shock compression wave across a sinusoidally corrugated metal-polymer interface were performed to generate shock stresses from 4-12 GPa and strain rates of approximately 1/s in the polymer. X-ray phase contrast imaging recorded the shock motion in the polymer and subsequent interface evolution. Analysis of this data yielded the polymer equation of state and, in conjunction with numerical modeling, the dynamic strength. The equation of state was validated against one-dimensional plate impact experiments from existing literature. The dynamic strength was compared to prior data for Epon 828 and related polymers at lower strain rates and found to exhibit significant strain rate and pressure-hardening effects. The strength of the Epon 828 polymer at 10 6 1/s was found to be approximately 1.5 GPa, suggesting that it is comparable to the strength of high strength metals at these dynamic conditions.

Equation of state↗
DOE OSTI2022

PLA Renewable Bio Polymer Based Solid-State Gamma Radiation Detector-Dosimeter for Biomedical and Nuclear Industry Applications

Polylactic acid (PLA) as a “green,” renewable corn-soy based polymer resin was assessed as a novel solid-state detector for rapid-turnaround gamma radiation dosimetry in the 1–100 kGy range–of significant interest in biomedical and general nuclear industry applications. Co-60 was used as the source of gamma photons. It was found that PLA resin responds well in terms of rheology and porosity metrics with an absorbed gamma dose (Dg). In this work, rheological changes were ascertained via measuring the differential mass loss ratio (MLR) of irradiated PLA placed within PTFE-framed (40 mm × 20 mm × 0.77 mm) cavities bearing ~0.9 g of PLA resin and pressed for 12–16 min in a controlled force hot press under ~6.6 kN loading and platens heated to 227 °C for the low Dg range: 0–11 kGy; and to 193 °C for the extended Dg range: 11–120 kGy. MLR varied quadratically from 0.05 to ~0.2 (1σ ~ 0.007) in the 0–11 kGy experiments, and from 0.05 to ~0.5 (1σ ~0.01) in the 0–120 kGy experiments. Rheological changes from gamma irradiation were modeled and simultaneously correlated with void-pocket formations, which increase with Dg. A single PLA resin bead (~0.04 g) was compressed 5 min at 216 °C in 0–16 kGy experiments, and compressed 2 min at 232 °C in the 16–110 kGy experiments, to form sturdy ~100 µm thick wafers in the same press. Aggregate coupon porosity was then readily measurable with conventional optical microscope imaging and analyzed with standard image processing; this provided complementary data to MLR. Average porosity vs. dose varied quadratically from ~0 to ~15% in the 0–16 kGy range and from ~0 to ~18% over the 16–114 kGy range. These results provide evidence for utilizing “green”/renewable (under $0.01) PLA resin beads for rapid and accurate (+/-5–10%) gamma dosimetry over a wide 0–120 kGy range, using simple to deploy mass and void measuring techniques using common laboratory equipment.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

An experimental investigation of flame and autoignition behavior of propane

We report autoignition delay time data are one important means to develop, quantify, and validate fundamental understanding of combustion chemistry at low temperatures (T<1200 K). However, low-temperature chemistry often has higher uncertainties and scatter in the experimental data compared with high-temperature ignition data (T>1200 K). In this study, autoignition properties of propane and oxygen mixtures were investigated using the University of Michigan rapid compression facility in order to understand the effects of ignition regimes on low-temperature ignition data. For the first time for propane, autoignition delay times were determined from pressure histories, and autoignition characteristics were simultaneously recorded using highspeed imaging of the test section through a transparent end-wall. Propane mixtures with fuel-to-O 2 equivalence ratios of φ = 0.25 and φ = 0.5 and O 2 -to-inert gas molar ratios of 1:3.76 were studied over the pressure range of 8.9 to 11.3 atm and the temperature range of 930 – 1070 K. The results showed homogeneous or strong autoignition occurred for all φ = 0.25 experiments, and inhomogeneous or mixed autoignition occurred for all φ = 0.5 experiments. While a limited temperature range is covered in the study, importantly the data span predicted transitions in autoignition behavior, allowing validation of autoignition regime hypotheses. Specifically, the results agree well with strong-autoignition limits proposed based on the Sankaran Criterion. The autoignition delay time data at the strong-ignition conditions are in excellent agreement with predictions using a well-validated detailed reaction mechanism from the literature and a zerodimensional modeling assumption. However, the experimental data at the mixed autoignition conditions were systematically faster than the model predictions, particularly at lower temperatures (T< ~970 K). The results are an important addition to the growing body of data in the literature that show mixed autoignition phenomena are important sources of the higher scatter observed in the low-temperature autoignition data for propane and other fuels. The results are discussed in terms of different methods to capture the effects of pre-autoignition heat release associated with mixed autoignition conditions and thereby address some of the discrepancies between kinetic modeling and experimental measurements.

42 ENGINEERING↗
DOE OSTI2020

Experimental Evaluation of Geopolymer, Nano-Modified, and Neat Class H Cement by Using Diametrically Compressive Tests

Abstract Cement is the prime barrier material to maintain zonal isolation during wellbore life-cycle. Different types of the cement have different performances on sealability. The primary objective of this study is evaluation of three types of cement systems, neat Class H, nano-synthetic graphite, and rock-based geopolymer cements, on interfacial bond integrity. Diametrical compressive tests are used on casing–cement–formation systems. Cement performances are tested in a conventional configuration (Berea Sandstone). A universal testing system is utilized to analyze the relationship applied load–axial strain and the digital image correlation (DIC) technique is used to generate the strain field maps. Based on the relationship and DIC results, bond strengths in different cement systems are evaluated. Additionally, microscope images provide insight explanations of the bond from micro-view. Based on the experimental results, failures of all cases initiate and propagate from the casing–cement interface. Then, radial cracks develop through the formation. This is because the mechanical interlocking bonds are formed only at the cement–sandstone interface to enhance the bond strength. The comparison of geopolymer and nano-modified cements with the conventional cement (neat Class H) shows that the unconventional cements have a lower maximum load and higher axial strain before failure of the samples. It indicates that both the two kinds of cements are more ductile than conventional cement and can support more deformation before the initiation of cracks.

Energy & Fuels↗
DOE OSTI2026

Thermal images collected during 3D printing with Cincinnati BAAM

This data set contains images produced to test the performance of anomaly and fault detection methods in the context of additive manufacturing. A total of 10 print jobs were executed using a Cincinnati BAAM (model 606) with a Cincinnati medium compression screw. The material used was compounded polylactic acid (PLA) with wood flour as a filler produced by Jabil (80% NatureWorks Ingeo 6060D amorphous PLA, % 100 mesh pine flour from American Wood Fiber). Print sheets were 1/4in polycarbonate.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mitigation of mode-one asymmetry in laser-direct-drive inertial confinement fusion implosions

Nonuniformities present in the laser illumination and target in laser-driven inertial confinement fusion experiments lead to an asymmetric compression of the target, resulting in an inefficient conversion of shell kinetic energy to thermal energy of the hot-spot plasma. In this paper, the effects of asymmetric compression of cryogenic deuterium tritium laser-direct-drive implosions are examined using a suite of nuclear and x-ray diagnostics on the OMEGA laser. The neutron-averaged hot-spot velocity (~uhs) and apparent ion temperature (Ti) asymmetry are determined from neutron time-of-flight measurements of the primary deuterium tritium fusion neutron energy spectrum, while the areal density (rhoR) of the compressed fuel surrounding the hot spot is inferred from measurements of the scattered neutron energy spectrum. The low-mode perturbations of the hot-spot shape are characterized from x-ray self-emission images recorded along three quasi-orthogonal lines of sight. Implosions with significant mode-1 laser drive asymmetries show large hot-spot velocities (>100 km/s) in a direction consistent with the hot-spot elongation observed in x-ray images, measured Ti asymmetry, and rhoR asymmetry. Laser drive corrections have been applied through shifting the initial target location in order to mitigate the observed asymmetry. With the asymmetry corrected, a more-symmetric hot spot is observed with reduced ~uhs, Ti asymmetry, rhoR asymmetry, and a 30% increase in the fusion yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Evolution of tensile and shear cracking in crystalline rocks under compression

Here we performed laboratory-scale unconfined compression experiments on Barre granite specimen with a single pre-existing flaw to study the evolution of tensile and shear cracking that occurs during different stress levels. Moment tensor inversion of acoustic emission (AE) events in combination with the nonelastic strain component obtained through the 2D digital image correlation (DIC) technique are used to track the changes in the source mechanisms of the stress-induced cracks. The mode of deformation computed from the image based strain profiles, enables visual comparison of the nucleation, growth and interaction of the tensile and shear cracks with the microseismic source mechanism observed by moment tensor inversion of the AE events. Comparing the results obtained from the two techniques on the same dataset demonstrates a quantitative correlation between the acoustic and visual observations in terms of the cracking mechanisms obtained at different stages of cracking from crack initiation at the flaw tips to the failure of the rock specimen.

58 GEOSCIENCES↗
DOE OSTI2021

Mitigation of mode-one asymmetry in laser-direct-drive inertial confinement fusion implosions

Nonuniformities present in the laser illumination and target in laser-driven inertial confinement fusion experiments lead to an asymmetric compression of the target, resulting in an inefficient conversion of shell kinetic energy to thermal energy of the hot-spot plasma. In this paper, the effects of asymmetric compression of cryogenic deuterium tritium laser-direct-drive implosions are examined using a suite of nuclear and x-ray diagnostics on the OMEGA laser. The neutron-averaged hot-spot velocity (u → hs ) and apparent ion temperature (T i ) asymmetry are determined from neutron time-of-flight measurements of the primary deuterium tritium fusion neutron energy spectrum, while the areal density (ρR) of the compressed fuel surrounding the hot spot is inferred from measurements of the scattered neutron energy spectrum. Here, the low-mode perturbations of the hot-spot shape are characterized from x-ray self-emission images recorded along three quasi-orthogonal lines of sight. Implosions with significant mode-1 laser drive asymmetries show large hot-spot velocities (>100 km/s) in a direction consistent with the hot-spot elongation observed in x-ray images, measured T i asymmetry, and ρR asymmetry. Laser drive corrections have been applied through shifting the initial target location in order to mitigate the observed asymmetry. With the asymmetry corrected, a more-symmetric hot spot is observed with reduced u → hs , T i asymmetry, ρR asymmetry, and a 30% increase in the fusion yield.

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

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗