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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

On the numerical accuracy in finite-volume methods to accurately capture turbulence in compressible flows

The goal of the present article is to understand the impact of numerical schemes for the reconstruction of data at cell faces in finite-volume methods, and to assess their interaction with the quadrature rule used to compute the average over the cell volume. Here, third-, fifth- and seventh-order WENO-Z schemes are investigated. On a problem with a smooth solution, the theoretical order of convergence rate for each method is retrieved, and changing the order of the reconstruction at cell faces does not impact the results, whereas for a shock-driven problem all the methods collapse to first-order. Here, study of the decay of compressible homogeneous isotropic turbulence reveals that using a high-order quadrature rule to compute the average over a finite-volume cell does not improve the spectral accuracy and that all methods present a second-order convergence rate. However the choice of the numerical method to reconstruct data at cell faces is found to be critical to correctly capture turbulent spectra. In the context of simulations with finite-volume methods of practical flows encountered in engineering applications, it becomes apparent that an efficient strategy is to perform the average integration with a low-order quadrature rule on a fine mesh resolution, whereas high-order schemes should be used to reconstruct data at cell faces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Revisiting group contribution theory for estimating fractional free volume of microporous polymer membranes

Fractional free volume (FFV) is a commonly used metric for the development of structure–property relationships for polymer membranes. The most common method to calculate FFV uses Bondi's group contribution method, first introduced in 1964. While updated in 1997, there has not been a significant compilation of new structural motifs since the advent of linear microporous polymers. Here, in this study, we critically examined the assumptions in Bondi's original method and provide four recommendations to streamline and improve the accuracy of calculating van der Waals volume (V W ) for any group. Using these recommendations, we created an updated list of (V W ) values for structural groups commonly present in microporous polymers. The (V W ) and FFV values were then calculated for a database of 123 microporous and high free volume polymers from the literature, showing an average 7% decrease in (V W ) and corresponding increase in FFV by a factor of 24% when compared to prior group contribution correlations in the literature. The significant apparent increase in estimated FFV provides a new perspective to understand and interpret the role of free volume on the separation performance of linear microporous polymers. Additionally, standardization of the group contribution method allows for the direct comparison of FFV values across studies.

42 ENGINEERING↗
DOE OSTI2022

Biases associated with a particular image volume metric

Image analysis area and volume metrics A 80 and V 80 , used by others, are studied as a function of image morphology, a 3D feature, and Monte Carlo noise in simulated images. The A 80 area metric is found to be stable, with consistent results (and meaning) obtainable without a detailed understanding of 3D features and/or simulation noise levels. However, the V 80 volume metric varies significantly with image morphology, 3D features, and simulation noise. If an experimental image set gives A 80 area inferences that are consistent with 2D image simulations, but V 80 volume inferences that are significantly larger than those corresponding to simulated images, then issues related to 3D features and simulation noise should be explored before conclusions are drawn related to a possible mismatch in the real physical size of experimental and simulated source volumes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Low‐Volume Cores for Fabrication of Compact, Versatile, and Intelligent Soft Systems

Abstract This study introduces the low‐volume core (LVC) fabrication method, which enables the monolithic molding of compact, complex, versatile, and intelligent soft robotic systems. This method uses thin and flexible thermoplastic sheets to mold internal chambers in soft fluidic actuators, valves, and circuits. The LVC fabrication method creates low‐volume networks in soft actuators (LV‐net actuators) that can be made with compact and complex geometries, enabling both low actuation volume input and multi‐degree‐of‐freedom actuators. LVC fabrication can also be used for compact, completely soft, and monolithic logic components (valves with low‐volume core, also called as LV valves) to provide directional resistance as well as a switching mechanism that enables fluidic logic in soft systems. The compatibility of the fabrication methods for both soft actuators and valves facilitates the creation of compact, integrated, and versatile soft robotic systems with embodied intelligence. This study introduces two examples of such intelligent soft robotic systems that integrate both LV‐net actuators and LV valves to demonstrate capability for complex system fabrication.

Yu, Qifan↗
DOE OSTI2025

Exascale granular microstructure reconstruction in 3D volumes of arbitrary geometries with generative learning

Reconstructing 3D granular microstructures within volumes of arbitrary geometries from limited 2D image data is crucial for predicting the material properties, as well as performances of structural components accounting for material microstructural effects. We present a novel generative learning framework that enables exascale reconstruction of granular microstructures within complex 3D geometric volumes. Building upon existing transfer learning techniques using pre-trained convolutional neural networks (CNN), we introduce several key innovations to overcome the difficulties inherent in arbitrary geometries. Our framework incorporates periodic boundary conditions using circular padding techniques, ensuring continuity and representativeness of the reconstructed microstructures. We also introduce a novel seamless transition reconstruction (STR) method that creates statistically equivalent transition zones to integrate multiple pre-existing 3D microstructure volumes. Based on STR, we propose a cost-effective strategy for reconstructing microstructures within complex geometric volumes, minimizing computational waste. Validation through numerical experiments using kinetic Monte Carlo simulations demonstrates accurate reproduction of grain statistics, including grain size distributions and morphology. A case study involving the reconstruction of a 4-blade propeller microstructure illustrates the method’s capability to efficiently handle complex geometries. In conclusion, the proposed framework significantly reduces computational demands while maintaining high reconstruction quality, paving the way for scalable microstructure reconstruction in materials design and analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗
DOE OSTI2023

Assessment of Combustion Residual Leachate Volume, Composition, and Treatment Costs

Combustion residuals and the resulting leachate from storage sites represent a large volume of wastewater in the United States (U.S.) that has not been quantified. Here this work estimates the constituents present, volume of wastewater, and costs of treatment for both combustion residual landfill leachate and the leachate from surface impoundment closures. Combustion residual landfill leachate produced from contact with bituminous coal combustion byproducts is generally predicted to be higher in lithium and manganese, whereas landfill leachate produced from contact with subbituminous coal combustion byproducts is generally predicted to be higher in mercury and vanadium. The annual volume of a single landfill with combustion residual leachate can reach more than 800,000 cubic meters. This leachate represents an annual volume of 26.8–42.8 million cubic meters nationally. Closing surface impoundments can yield between 830 and 1040 cubic meters of leachate nationally for a three-year closure period. Costs as low as $1.5/m 3 or as high as $95/m 3 are observed. Treatment trains will need to remove 72% of total suspended solids (TSS), 87% of arsenic, and 64% of mercury from landfill leachate. When applied to impoundments, these treatment trains would need to remove 97% of arsenic.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

A high-volume resonator for L-band DNP-NMR

DNP-NMR and EPR experiments that operate at or greater than L-band (i.e., ν 0 (e – ) = 1–2 GHz) are typically limited to maximum sample volumes of several hundred µL. These experiments rely on well-known resonator designs for DNP/EPR irradiation such as the loop-gap resonator and Alderman-Grant coil, where their maximum volumes limit further application to imaging experiments and high-throughput screening beyond L-band. Herein, we demonstrate a birdcage (BC) resonator design that can accommodate several mL of sample while operating around 1.5 GHz. The sample volume is maximized by using two identical BC resonators in a stacked configuration. Simulations are used to optimize the BC design and the performance is validated experimentally with liquid-state Overhauser-DNP-NMR experiments. This BC design exploits just the parasitic capacitance of conductive rings and features no fixed tuning capacitors. An enhancement of –77 is achieved on a 10 mM 4-Amino-TEMPO in H 2 O sample for a 5 mL sample volume. Finally, the associated sample heating is minimal due to the low-E-fields generated and the large sample mass with +3.4 K when driving 100 W for several seconds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Manufacturing porous U-10Zr metallic fuels with controllable microstructure by volume control spark plasma sintering

In this paper, the volume control spark plasma sintering tool has been designed and applied to sinter porous U-10Zr metallic fuels, by which the sintered sample volume can be precisely controlled. Ethanol and NH 4 HCO 3 are used to control the powder compact or as pore formers to control the pore size and pore structure. Without pore formers, the fuel pellet displays an inhomogeneous microstructure consisting of highly porous and highly densified areas. Uneven powder stacking in the green body results in a non-uniform microstructure, and in the closed-packed area, Joule heating accelerates the neck formation and densification. The addition of ethanol reduces the friction between the powders, resulting in isolated pores formed by the stacking of powders during the sintering. By adding NH 4 HCO 3 , the pore size, and structure can be well controlled, and an interconnected pore structure can be obtained upon the decomposition of the NH 4 HCO 3 . Further, a uniform microstructure and pore distributions can be achieved through the U-10Zr fuel pellets by controlling current flow during the volume control SPS sintering. The microstructure and phase characterization of the sintered porous U-10Zr pellets show major phases of α-U and α-Zr for the sample with short dwelling. For the sample with long dwelling (30 min), the ω UZr 2 in the Zr-enriched area has been observed. The strategy of volume control SPS sintering with the assistance of pore formers could be used to fabricate porous U-10Zr metallic fuels to mimic the microstructure evolution of irradiated metallic fuels (including porosity) and could enable a possible solution for the design of new sodium-free metallic fuels for high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Shear-induced lift force on spheres in a viscous linear shear flow at finite volume fractions

Several studies have shown a significant increase in drag on a distribution of solid spherical particles within a fluid with increasing particle volume fraction. As a result, many empirical drag laws accounting for the dependence on the Reynolds number and volume fraction can be found in the literature. This study investigates the possibility of a similar effect of the particle volume fraction on the mean hydrodynamic lift force on randomly distributed spherical particles in a linear shear flow. Particle-resolved direct numerical simulations are performed to evaluate the mean lift force, and the results are compared with the case of an isolated particle in a linear shear flow for the same Reynolds number and shear rate. The mean lift force acting on the particles appears to remain nearly the same as that on an isolated particle. However, due to the influence of neighboring particles, there is a substantial force variation in transverse directions on each individual particle, whose magnitude is comparable to the mean drag force. The distribution of drag force in a linear shear flow is shown to be nearly the same as in a uniform flow at the same volume fraction and Reynolds number. A simple stochastic model based on a Gaussian distribution is presented for the lift force variation, and its performance is compared to the prediction of the deterministic pairwise interaction extended point-particle model.

42 ENGINEERING↗
DOE OSTI2020

Large-volume centimeter-wave cavities for axion searches

The scan rate of an axion haloscope is proportional to the square of the cavity volume. In this paper, a new class of thin-shell cavities are proposed to search for axionic dark matter. These cavities feature active volume much larger (>20×) than that of a conventional cylindrical haloscope, comparable quality factor Q, and a similar frequency tuning range. Furthermore, full 3D numerical finite-element analyses have been used to show that the TM 010 eigenmodes are singly polarized throughout the volume of the cavity and can facilitate axion-photon conversion in uniform magnetic field produced by a superconducting solenoid. To mitigate spurious mode crowding and volume losses due to localization, a pre-amplification binary summing network will be used for coupling. Because of the favorable frequency-scaling, the new cavities are most suitable for centimeter-wavelength (~ 10–100 GHz), corresponding to the promising post-inflation axion production window. In this frequency range, the tight machining tolerances required for high-Q thin-shell cavities are achievable with standard machining techniques for near-infrared mirrors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Design and Characterization of an Extremely-Sensitive, Large-Volume Gamma-Ray Spectrometer for Environmental Samples

A large volume gamma spectrometer was designed and constructed to analyze foodstuffs and environmental samples having low radionuclide concentrations. This system uses eight 11-cm × 42.5-cm × 5.5-cm NaI(Tl) detectors, chosen due to their relatively high sensitivity and availability and arranged in an octagonal configuration. The sensitive volume of the system is ~28 cm in diameter and ~42 cm deep. Shielding consists of an 86-cm × 86-cm square, 64-cm-tall lead brick enclosure with 18-cm-thick lead walls lined by 0.3-cm-thick copper plates. An aluminum top was machined to suspend the detectors within this shield. The shielding reduces background counts by 72% at 100 keV and 42% at 1,000 keV. The positional variability in sensitivity of the well was determined by both simulation and experiment. A 2.1-L volume of nearly uniform sensitivity, varying less than 10%, exists in the well's center. Energy resolutions of 14.6% and 7.8% were measured for 241 Am and 137 Cs, respectively. Energy resolution shows a 0.2% variation for both 241 Am and 137 Cs as a function of position within all regions of the well’s central sensitive volume. Dead time was also determined to be less than 35% for all sources measured in the system, the largest of which had an activity of 1,760 kBq. Simulated results for various source geometries show higher counts for smaller samples, especially at lower energies due to less attenuation of low energy photons. In conclusion, minimum detectable activities were determined for all source energies used, less than 5.1 Bq kg -1 for reasonable background and sample counting times.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Temperature dependence of vacancy/self-interstitial recombination volumes in copper

We use molecular dynamics to calculate rate coefficients for recombination of vacancies with self-interstitial atoms (SIAs) in Cu at temperatures from 300 to 700 K. From these results, we calculate vacancy/SIA recombination volumes and find that they decrease from around 290 (where is one atomic volume) at 300 K to 160 at 500 K and above. By counting the number of distinct pathways by which a stable SIA may migrate to a site of spontaneous recombination with a nearby vacancy, we find a lower bound estimate of 168 for the recombination volume. We furthermore rationalize its temperature dependence based on differences between the activation energies for recombination and SIA migration. Furthermore, our work sheds light on the fundamental nature of the recombination volume and provides information that may be incorporated into multiscale models of radiation response in solids.

36 MATERIALS SCIENCE↗
DOE OSTI2026

REV-INR: Regularized Evidential Implicit Neural Representation for Uncertainty-Aware Volume Visualization

Applications of Implicit Neural Representations (INRs) have emerged as a promising deep learning approach for compactly representing large volumetric datasets. These models can act as surrogates for volume data, enabling efficient storage and on-demand reconstruction via model predictions. However, conventional deterministic INRs only provide value predictions without insights into the model’s prediction uncertainty or the impact of inherent noisiness in the data. This limitation can lead to unreliable data interpretation and visualization due to prediction inaccuracies in the reconstructed volume. Identifying erroneous results extracted from model-predicted data may be infeasible, as raw data may be unavailable due to its large size. To address this challenge, we introduce REV-INR, Regularized Evidential Implicit Neural Representation, which learns to predict data values accurately along with the associated coordinate-level data uncertainty and model uncertainty using only a single forward pass of the trained REV-INR during inference. By comprehensively comparing and contrasting REV-INR with existing well-established deep uncertainty estimation methods, we show that REV-INR achieves the best volume reconstruction quality with robust data (aleatoric) and model (epistemic) uncertainty estimates using the fastest inference time. Consequently, we demonstrate that REV-INR facilitates assessment of the reliability and trustworthiness of the extracted isosurfaces and volume visualization results, enabling analyses to be solely driven by model-predicted data.

Saklani, Shanu [Indian Institute of Technology, Ka↗
DOE OSTI2023

Quasiparticle Generation-Recombination Noise in the Limit of Low Detector Volume

We have measured the quasiparticle generation-recombination (GR) noise in aluminium lumped element kinetic inductors with a wide range of detector volumes at various temperatures. The basic detector consists of meandering inductor and interdigitated capacitor fingers. The inductor volume is varied from 2 to 153 mu m(3) by changing the inductor width and length to maintain a constant inductance. We started with measuring the power spectrum density (PSD) of the detectors frequency noise which is a function of GR noise and we clearly observed the spectrum roll off at 10 kHz which corresponds to the quasiparticle lifetime. Using data from a temperature sweep of the resonator frequency we convert the frequency fluctuation to quasiparticle fluctuation and observe its strong dependence on detector volume: detectors with smaller volume display less quasiparticle noise amplitude. Meanwhile we observe a saturated quasiparticle density at low temperature from all detectors as the quasiparticle life time tqp approaches a constant value at low temperature.

Li, Juliang↗
DOE OSTI2025

IsoDAR@Yemilab: Preliminary design report—volume I (cyclotron driver)

This Preliminary Design Report (PDR) describes the IsoDAR electron-antineutrino source in two volumes which are mostly site-independent and describe the cyclotron driver providing a 10 mA/60 MeV proton beam (this Volume); and the medium energy beam transport line (MEBT) and target (Volume II). The IsoDAR driver and target will produce about 1.15 x 10 23 electron-antineutrinos over 5 years while operating with the anticipated 10 mA/60 MeV beam at an estimated 80% duty factor. Paired with a kton-scale liquid scintillator detector, it will enable a broad particle physics program including searches for new symmetries, new interactions and new particles. Here in Volume I, we describe the driver, which includes the ion source, low energy beam transport, and cyclotron. The latter features Radio-Frequency Quadrupole (RFQ) direct axial injection and represents the first accelerator purpose-built to make use of so-called vortex motion.

Winklehner, Daniel (ORCID:0000000207156310)↗
DOE OSTI2023

Quantifying Volume Change in Porous Electrodes via the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, the need for coupled electrochemical/mechanical models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary. In this study, we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions.

25 ENERGY STORAGE↗
DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗