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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
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 OSTI2022

Plasma facing components with capillary porous system and liquid metal coolant flow

Liquid metal can create a renewable protective surface on plasma facing components (PFC), with an additional advantage of deuterium pumping and the prospect of tritium extraction if liquid lithium (LL) is used and maintained below 450 °C, the temperature above which LL vapor pressure begins to contaminate the plasma. LM can also be utilized as an efficient coolant, driven by the Lorentz force created with the help of the magnetic field in fusion devices. Capillary porous systems can serve as a conduit of LM and simultaneously provide stabilization of the LM flow, protecting against spills into the plasma. Recently, a combination of a fast-flowing LM cooling system with a porous plasma facing wall (CPSF) was investigated [A. Khodak and R. Maingi, Nucl. Mater. Energy 26, 100935 (2021)]. The system takes an advantage of a magnetohydrodynamics velocity profile as well as attractive LM properties to promote efficient heat transfer from the plasma to the LL at low pumping energy cost, relative to the incident heat flux on the PFC. In the case of a disruption leading to excessive heat flux from the plasma to the LM PFCs, LL evaporation can stabilize the PFC surface temperature, due to high evaporation heat and apparent vapor shielding. The proposed CPSF was optimized analytically for the conditions of a fusion nuclear science facility [Kessel et al., Fusion Sci. Technol. 75, 886 (2019)]: 10 T toroidal field and 10 MW/m 2 peak incident heat flux. Finally, computational fluid dynamics analysis confirmed that a CPSF system with 2.5 mm square channels can pump enough LL so that no additional coolant is needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes

This paper proposes an online adaptive data-driven distributed energy resource (DER) dispatch optimization method for voltage control considering topology changes. By using a local sensitivity factor (LSF)-enabled voltage control, traditional DER control can be reformulated into a linear programming (LP) problem, leading to faster computation speeds. Power injection alteration and topology changes are two common operational changes in the distribution network that can affect the LSF and voltage control performance. To address this issue, a robust estimation method is developed to adjust the sensitivity matrix at each time step for the time-varying power injection changes. When topology changes occur, only the allocated predominant LSF submatrices are updated based on measurement data, allowing for a fast adaptation to the system reconfiguration. Results obtained from a real distribution feeder in Southern California demonstrate its robustness as compared to traditional volt-var control and constant LSF matrix dispatch control methods.

DERs↗
DOE OSTI2021

High-order algorithmic developments and optimizations for large-scale GPU-accelerated simulations (Milestone CEED-MS36)

The goal of this milestone was to improve the high-order software ecosystem for CEED-enabled ECP applications by making progress on efficient matrix-free kernels targeting forthcoming ECP architectures. These kernels included matrix-free preconditioning and the development of new set of CEED solver bake-off problems. As part of this milestone, we also released the next version of the CEED software stack, CEED-4.0, reported on results from several application collaborations, and documented the efforts of porting to AMD GPUs for Frontier and other modern architectures, such as Fugaku. The specific tasks addressed in this milestone were: (1) Port and run CEED benchmarks/miniapps on Frontier EA systems; (2) Demonstrate performant libCEED integration in MFEM, Nek and applications; (3) Matrix-free preconditioning of high-order operators; (4) Benchmark problems for fast high-order solvers on GPU platforms; and (5) Public release of CEED-4.0. The artifacts delivered include the next version of the CEED software stack, CEED-4.0, the next libCEED release, libCEED-0.8, and a number of developments integrated within applications to improve their GPU and CPU performance and capabilities. See the CEED website, https://ceed.exascaleproject.org and the CEED GitHub organization, https://github.com/ceed for more details.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Low-temperature sprayed SnO x nanocomposite films with enhanced hole blocking for efficient large area perovskite solar cells

Scalable fabrication of charge transport layers with high uniformity and compactness is essential for the commercialization of perovskite solar cells (PSCs). Cost-effective deposition of high-quality electron transport layers (ETLs) is a particularly important step to achieve low-cost, efficient and large-area PSCs. Here, an open-air (relative humidity of 40–50%) and low-temperature (≤100 °C) ultrasonic spray coating of tin oxide (SnO 2 ) nanocomposite films incorporating nanocrystalline SnO 2 nanoparticles in an amorphous SnO x matrix is demonstrated to fabricate large-area ETLs for planar PSCs. The optimized SnO 2 /SnO x nanocomposite exhibits significantly enhanced hole-blocking and high-power conversion efficiencies of 18% and 16% for planar PSCs with an active area of 0.2 cm 2 and 1 cm 2 , respectively. More importantly, the devices show little current–voltage hysteresis as well as good shelf-life stability by maintaining ~90% of the initial performance without encapsulation after 2500 hours storage under inert conditions. Additionally, high voltages of >6.0 V have been obtained for solar modules of 2.1 cm 2 aperture area comprising six sub-cells in series, suggesting that the low-temperature, open-air and fast spray coating is suitable and transferable to deposit large-area charge transport layers for scalable PSCs or other optoelectronic devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Time Resolution Characterization of 4H-SiC LGADs with a 90 Sr Source

This work presents timing measurements of 4H-SiC Low Gain Avalanche Detectors (4H-SiC LGADs) using beta particles from a 90Sr source. The 4H-SiC LGADs exhibit fast signal responses, and a time resolution of 61 ps was achieved, comparable to that of standard Si LGADs. The present limitation in the time resolution of 4H-SiC LGADs appears to stem from limited charge generation. Nevertheless, their higher voltage tolerance and faster carrier drift suggest that, with increased charge collection, their timing performance could approach or even surpass that of Si LGADs. Furthermore, these results demonstrate the strong potential of 4H-SiC LGADs as a robust platform for precision timing in future 4D tracking detectors, while also highlighting that signal charge is the dominant factor currently limiting their performance, indicating that further optimization of gain and drift structures will be essential for future development.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Reactivity Coefficient Measurements to Aid in Reducing Compensating Errors in Plutonium Nuclear Data

Compensating errors between several nuclear data observables in a nuclear data library can adversely impact application simulations. The primary goal of the EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) is to reduce compensating errors between fast (0.1–5 MeV) 239Pu nuclear data for prompt fission neutron spectra (PFNS), average prompt fission neutron multiplicities, and neutron induced fission, capture, elastic, and inelastic cross sections. This work will focus on the design and execution of void reactivity coefficient measurements in the EUCLID experiment, performed on the Planet vertical lift critical assembly machine at the National Criticality Experiments Research Center (NCERC). Two different base configurations were designed and measured, one with high neutron leakage, and one with low neutron leakage. Both were primarily made up of plutonium metal (Zero Power Physics Reactor plates) without interstitial moderators and reflected by half-inch aluminum. Design optimization showed that void reactivity coefficient measurements in three locations per configuration was most impactful to reduce nuclear data uncertainties due to the varying impacts from elastic and inelastic scattering, as well as fission and capture. The locations for measurements were chosen based on preliminary studies which balanced measurement uncertainty and measurement practicality. The measurements were also selected to have sensitivities maximally complementary to previous arrangements. Comparisons across nuclear data libraries highlight the potential impact.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electron density profile and associated fluctuation measurements using a microwave reflectometry diagnostic on Helically Symmetric eXperiment (HSX)

Abstract A dual-band frequency-modulated reflectometry is employed on the Helically Symmetric eXperiment (HSX) stellarator. This system equips a fast PIN switch to alternate the frequency source between two voltage-controlled oscillators, providing an operational frequency range from 14.5 GHz to 25.5 GHz. A monostatic antenna geometry and an ellipsoidal mirror are implemented in the vessel of HSX, where the polarization of the transmitted microwave can be switched between O- and X-mode to accommodate the magnetic field and plasma density. Although the original system was designed for density fluctuation measurement, significant efforts have been undertaken to improve the system performance and to realize the density profile inversion. Recent improvements of the system reported here include calibration of the dispersion in the transmission line, optimization of the waveform, and implementation of the Choi-Williams time–frequency distribution for spectral analysis. In this paper, we present the optimization of the reflectometry system along with first experimental measurements of the density profile and observations of fluctuations during gas puffing experiments.

Han, X. (ORCID:0000000184986433)↗
NASA NTRS1993

Real-time trajectory optimization on parallel processors

A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.

Psiaki, Mark L.↗
DOE OSTI2025

Interligand Coupling Drives Fast Triplet Energy Transfer Routes in PbS/Tetracene Quantum Dot Hybrids

The binding of photoactive organic ligands to inorganic quantum dots (QDs) creates a versatile hybrid architecture that allows access to photophysical processes such as efficient triplet exciton generation with near-infrared radiation. Here we report the subnanosecond generation of a hybrid triplet state with mixed ligand-QD character by replacing native oleate ligands on small PbS QDs with 5,12-tetracenepropiolic acid, a bifunctional ligand with two carboxylic acids that tends to lie face-on with the QD surface at low loadings. The face-on geometry engenders a regime of strong electronic coupling that is evident in steady-state absorption and hastens triplet energy flow by several orders of magnitude compared with more typical tetracene-based ligands exhibiting weak coupling. We further determined via Fourier transform infrared (FTIR) and supported by density functional theory (DFT)-based geometry optimizations that high ligand loading causes a shift in QD-ligand mutual disposition toward an edge-on geometry that instigates the formation of intermolecular excited states characterized by triplet excimer-like features in photoluminescence and transient absorption. Our results demonstrate the ability to control strongly coupled ligand-QD systems toward ultrafast generation of photophysically relevant species such as triplets that are valuable for photon upconversion and catalysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

srlife: A Fast Tool for High Temperature Receiver Design and Analysis

This report describes a tool for estimating the structural service life of tubular, panel solar receivers operating at high temperatures. A complete version of the tool is available as open source software at https://github.com/Argonne-National-Laboratory/srlife and can be installed through the PyPi (https://pypi.org) package manager. Given the basic receiver geometry and the thermal loads on the receiver, the tool provides 1D, 2D, or 3D thermal and structural (single tube and simplified system) analysis and creep-fatigue service life prediction for six metallic alloys – 316H, 800H, Alloy 617, Alloy 740H, and Alloy 230. With the exception of Alloy 230 where the material data is preliminary, the software included a detailed set of models for the materials, well-supported by high temperature experimental test data. The tool is designed for easy integration with a software stack, including solar field and thermohydraulic simulations, for optimizing receiver designs to meet service life and economic targets. The report describes several heuristics that can be applied in srlife to reduce the analysis time by several orders of magnitude but with fairly accurate life estimation when compared with full analysis. The report provides several examples demonstrating the utility of srlife in receiver design. Finally, the report discusses high temperature tests on Alloy 282, collected as part of this project, used to develop and support the material model for that alloy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Overcoming Fundamental Limitations in Adsorbent Design: Alkene Adsorption by Non-porous Copper(I) Complexes

Purifying alkenes from alkanes requires cryogenic distillation. This consumes energy equivalent to countries of ca. 5 million people. Replacing distillation with adsorption processes would significantly increase energy efficiency. Trade-offs between kinetics, selectivity, capacity, and heat of adsorption have prevented production of an optimal adsorbent. Here, we report adsorbents that overcome these trade-offs. [Cu-Br] 3 and [Cu-H] 3 are air-stable trinuclear complexes that undergo reversible solid-state inter-molecular rearrangements to produce dinuclear [Cu-Br∙(alkene)] 2 and [Cu-H∙(alkene)] 2 . The reversible solid-state rearrangement, confirmed in situ using powder X-ray diffraction, allows adsorbent design trade-offs to be overcome, coupling low heat of adsorption (-10 to -17 kJ mol -1 alkene ), high alkene:alkane selectivity (47; 29), and uptake capacity (>2.5 molalkene mol -1 Cu3 ). Most remarkably, [Cu-H] 3 displays fast uptake and regenerates capacity within 10 minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigation on gate oxide reliability under gate bias screening for commercial SiC planar and trench MOSFETs

This paper evaluates the impact of the fast high gate-voltage screening technique on gate oxide reliability of commercial 1.2 kV 4H-SiC power metal-oxide-semiconductor field-effect transistors (MOSFETs) with planar and trench gate structures. The measurements are conducted on packaged devices with the intent that the results will be applicable to wafer-level screening. The threshold voltage (V th ) of SiC MOSFETs is measured before and after various screening treatments and recovery process. In addition, constant-voltage time-dependent dielectric breakdown (TDDB) measurements are performed on SiC MOSFETs to obtain the intrinsic lifetime of gate oxide. The objective of this study is to determine the optimal screening conditions and improve screening efficiency without degradation of gate oxide reliability, such as V th shift and reduced oxide intrinsic lifetime. Due to the differences in the gate oxidation process and structural design of SiC planar and trench MOSFETs, the two types of devices exhibit different oxide reliability in the screening process. The recommended screening conditions obtained in this paper reveal that SiC trench MOSFETs can accept higher screening voltages compared to SiC planar MOSFETs. Hence, it can be concluded that more efficient screening techniques can be adopted for SiC MOSFETs with thicker gate oxide to meet the requirements of industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improving reproducibility in synchrotron tomography using implementation-adapted filters

For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation-adapted filters for several open-source implementations and applying them to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗