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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

What Can Plastic Flow Fields Tell Us About Heat Sources in Deformation Processing?

We characterize primary (shape-change) and secondary (friction) deformation, and associated temperature fields, in metal cutting and forming processes, using in situ imaging and simulation. The experimental configurations enable access to the deformation zones and die contact-interfaces, for measuring deformation, temperature, and frictional drag. Infra-red thermography reveals that the plastic strain-rate field is an excellent proxy for the deformation-induced heat sources. Both spatially confined and diffuse strain-rate fields occur, depending on the initial workpiece deformation state. When the strain rate is confined, as in pre-hardened material, the temperature modeling is much simplified, as the heat source is also now localized. However complex, microstructure-driven deformation modes, like sinuous flow in annealed metals, result in spatially diffuse strain-rate and body heat sources, more challenging to analyze. Furthermore, our unified measurements should be of value for accurately estimating the fraction of plastic dissipation that is converted into heat in large-strain deformation processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dislocation half-loop control for optimal V-defect density in GaN-based light emitting diodes

V-defects are morphological defects that typically form on threading dislocations during epitaxial growth of $(0001)$-oriented GaN layers. A V-defect is a hexagonal pyramid-shaped depression with six {$10\bar{1}1$}-oriented sidewalls. These semipolar sidewalls have a lower polarization barrier than the polarization barriers present between the polar c-plane quantum wells and quantum barriers and can laterally inject carriers directly into quantum wells in GaN-based light emitting diodes (LEDs). This is especially important, as the high polarization field in c-plane GaN is a significant factor in the high forward voltage of GaN LEDs. The optimal V-defect density for efficient lateral carrier injection in a GaN LED (∼10 9 cm −2 ) is typically an order of magnitude higher than the threading dislocation density of GaN grown on patterned sapphire substrates (∼10 8 cm −2 ). Pure-edge dislocation loops have been known to exist in GaN, and their formation into large V-defects via low-temperature growth with high Si-doping has recently been studied. Here, in this work, we develop a method for pure-edge threading dislocation half-loop formation and density control via disilane flow, growth temperature, and thickness of the half-loop generation layer. We also develop a method of forming the threading dislocation half-loops into V-defects of comparable size to those originating from substrate threading dislocations.

Crystallographic defects↗
DOE OSTI2026

Time-dependent-bases with local CUR decomposition method for accelerating turbulent combustion simulations

Here, this study presents a novel reduced-order modeling framework, Time-Dependent Bases with Local CUR decomposition (TDB-L-CUR), designed to efficiently and accurately approximate the species transport equations in reacting flow simulations. The method extends the existing TDB-CUR approach for chemically reacting flows (Jung et al. Comput. Methods Appl. Mech. Engrg. 437 (2025) 117758), which leverages matrix decomposition techniques to form a global-in-space, time-dependent low-dimensional manifold. While TDB-CUR performs well in homogeneous systems, it may be less well-suited to spatially heterogeneous systems such as turbulent flames, where higher-rank approximations are typically required. The proposed TDB-L-CUR framework introduces two methodological extensions to the baseline approach. First, it applies unsupervised clustering to partition the physical domain into distinct regions, enabling spatially localized manifold construction, thereby reducing the rank required for the reduced-order representation. Second, it incorporates a computational singular perturbation (CSP)-based scheme for identifying and penalizing fast species, allowing for spatio-temporally adaptive mitigation of chemical stiffness. The proposed framework is validated on a hierarchy of test cases, including a one-dimensional premixed flame, a two-dimensional nonpremixed ignition case with vortex interaction, and a three-dimensional turbulent premixed flame. TDB-L-CUR significantly improves accuracy over TDB-CUR while further reducing computational cost. The fully on-the-fly formulation of TDB-L-CUR (i.e., requiring no offline training or prior knowledge) makes it a robust and scalable tool for reduced-order modeling of reactive flows.

Local manifold↗
DOE OSTI2022

Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

Abstract Identification of a heterogeneous conductivity field and reconstruction of a contaminant release history are key aspects of subsurface remediation. These two goals are achieved by combining model predictions with sparse and noisy hydraulic head and concentration measurements. Solution of this inverse problem is notoriously difficult due to, in part, high dimensionality of the parameter space and high computational cost of repeated forward solves. We use a convolutional adversarial autoencoder (CAAE) to parameterize a heterogeneous non‐Gaussian conductivity field via a low‐dimensional latent representation. A three‐dimensional dense convolutional encoder‐decoder (DenseED) network serves as a forward surrogate of the flow and transport model. The CAAE‐DenseED surrogate is fed into the ensemble smoother with multiple data assimilation (ESMDA) algorithm to sample from the Bayesian posterior distribution of the unknown parameters, forming a CAAE‐DenseED‐ESMDA inversion framework. The resulting CAAE‐DenseED‐ESMDA inversion strategy is used to identify a three‐dimensional contaminant source and conductivity field. A comparison of the inversion results from CAAE‐ESMDA with physical flow and transport simulator and from CAAE‐DenseED‐ESMDA shows that the latter yields accurate reconstruction results at the fraction of the computational cost of the former.

Zhou, Zitong↗
DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗
DOE OSTI2023

Appealing sheath‐core spun high‐performance composite carbon molecular sieve membranes

Abstract Carbon molecular sieve (CMS) membranes are attractive candidates to meet requirements for challenging gas separations. The added ability to maintain such intrinsic properties in an asymmetric morphology with a structure that we term a “Pseudo Wheel+Hub & Spoke” asymmetric form offers new opportunities. For CMS membrane, specifically, the structure provides both selective layer support and low flow resistance even for high feed pressures and fluxes in CO 2 removal from natural gas. This capability is unavailable to even rigid glassy polymers due to the much higher modulus of CMS materials. Combining precursor asymmetric hollow fiber formation and optimized pyrolysis creates a defect free CMS proof‐of‐concept membrane for this application. Facile formation of the sheath‐core spun precursor with a 6FDA‐DAM sheath and Matrimid® core also avoids the need to seal defects before or after the carbonization of the precursors. The composite CMS membrane shows CO 2 /CH 4 (50 : 50) mixed gas feed with an attractive CO 2 /CH 4 selectivity of 64.3 and CO 2 permeance of 232 GPU at 35 °C. A key additional benefit of the approach is reduction in use of the more costly high performance 6FDA‐DAM in a composite sheath‐core CMS membrane with the “Pseudo Wheel+Hub & Spoke” structure.

Cao, Yuhe↗
DOE OSTI2023

Appealing sheath-core spun high-performance composite carbon molecular sieve membranes

Carbon molecular sieve (CMS) membranes are attractive candidates to meet requirements for challenging gas separations. The added ability to maintain such intrinsic properties in an asymmetric morphology with a structure that we term a “Pseudo Wheel+Hub & Spoke” asymmetric form offers new opportunities. For CMS membrane, specifically, the structure provides both selective layer support and low flow resistance even for high feed pressures and fluxes in CO 2 removal from natural gas. Further, this capability is unavailable to even rigid glassy polymers due to the much higher modulus of CMS materials. Combining precursor asymmetric hollow fiber formation and optimized pyrolysis creates a defect free CMS proof-of-concept membrane for this application. Facile formation of the sheath-core spun precursor with a 6FDA-DAM sheath and Matrimid® core also avoids the need to seal defects before or after the carbonization of the precursors. The composite CMS membrane shows CO 2 /CH 4 (50 : 50) mixed gas feed with an attractive CO 2 /CH 4 selectivity of 64.3 and CO 2 permeance of 232 GPU at 35 °C. A key additional benefit of the approach is reduction in use of the more costly high performance 6FDA-DAM in a composite sheath-core CMS membrane with the “Pseudo Wheel+Hub & Spoke” structure.

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

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗
DOE OSTI2021

Scale-Dependent Bedform Migration and Deformation in the Physical and Spectral Domains

Multi-scale bathymetries observed in laboratory channels and natural rivers have posed several challenges to the description of bedform geometry and kinematics. To better quantify scale-dependent migration velocity, high resolution spatio-temporal bed evolution data are analyzed using three independent methods: (i) a bedform tracking method that identifies individual bedforms in longitudinal bed elevation profiles, (ii) a cross-correlation based, image matching technique in consecutive bathymetry scans similar to Particle Image Velocimetry, and (iii) two-dimensional frequency-wavenumber spectra marking a dispersion relation between bedform period and length, allowing estimation of Fourier-based, scale-dependent migration velocities. The comparative studies show that the spectral and bedform tracking methods present small differences in the migration velocity of medium-large bedforms. However, significant deviations occur in the small bedforms, mostly due to bedform sheltering or amplified exposure to the flow, which also contribute to their enhanced scale-dependent deformation. The analysis also shows that some form of scale separation is needed to extract the large and slowly migrating bedforms as they are masked by secondary features when several bedform orders coexist. Bathymetric Image Velocimetry reasonably estimates the averaged migration velocity and exhibits potential to study relations between spanwise bed surface velocity and local bedform kinematics.

58 GEOSCIENCES↗
DOE OSTI2022

Combining complex flow manifold with three dimensional woven lattices as a thermal management unit

The present invention is directed to a manifold for directing cooling fluid and/or gas to a heat exchanger in a flow configuration designed to optimize heat transfer from the heat exchanger. The manifold can take many different forms such as a layered construction with distributed inlet paths, local outlet paths, a central collection changer and a path for fluid removal. The manifold can be formed from a metal, plastic, rubber, ceramic, or other heat resistant material known to or conceivable by one of skill in the art. The manifold can also be combined with any type of heat exchanger known to or conceivable by one of skill in the art to form a thermal management unit. To optimize overall properties such as low pressure drop, high heat transfer, and excellent temperature uniformity of the thermal management unit, the manifold can be graded, expanded and scaled as needed.

Hemker, Kevin J.↗
DOE OSTI2022

Ultrasonic Testing of Mechanical Changes in a Water-Filled Pipe with Multi-Mode and Broadband Signals and Two-Level Compensation

Ultrasonic testing (UT) has been widely used for the Nondestructive Evaluation (NDE) of pipes due to its many favorable characteristics. However, one of the main challenges in the general use of UT for real-world pipelines is the sensitivity of this method to environmental and operational condition changes. This paper proposes a new UT method with enhanced compensation for environmental effects and operational condition changes. In particular, the effectiveness of the new method is tested in the presence of temperature variations, and changes in water flow rate inside a stainless-steel pipe. The proposed UT method uses multi-mode and broadband guided ultrasonic waves in the pipe walls, excited and received by single-element ultrasonic sensors that are spatially separated, forming a measurement zone between any pair of such transmit and receive sensors. Amplitude changes, time shifts, and frequency content variations in the ultrasonic signal due to temperature changes and water flow are evaluated and compensated for reliable UT of mechanical changes in the pipe. It is observed that spurious effects of water flow on ultrasonic response, if not properly compensated, can dominate over effects due to actual mechanical changes, but such liquid-boundary effects can be compensated effectively by the proposed time- and frequency-filtering method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Evolution of the age-included nearest pair distribution in disperse multiphase flows

The age of the nearest particle pair is introduced as the difference between the current time and the most recent time when the nearest particle pair was formed. The evolution equation for the age-included nearest pair distribution function is derived. With the assumption of random destruction of the nearest particle pairs, the evolution equation predicts the exponential probability distribution of the ages of the nearest particle pairs. Particle-resolved numerical simulations with moving particles are performed to verify this prediction. The equation is then used to derive the evolution equation for the particle–fluid–particle (PFP) stress, which is known to be related to hyperbolicity of the two-fluid equations. It is found that the relaxation time of the age probability distribution is also the relaxation time for the PFP stress. Guided by the closure terms in the PFP stress evolution equation, we study kinematics of the nearest particle pairs in the particle-resolved simulations for flows caused by sedimentation of the particles with initially isotropic and homogeneous particle distributions. At the steady states, the particle Reynolds numbers are around 20. Anisotropy and inhomogeneity of particle distributions are seen to develop in these flows. The mean distances to the nearest particles and evolution of the distribution of the Voronoi cell volumes are studied. We also found the PFP stress is closely related to the changes in these inter-particle scale quantities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Modification to the Hawking temperature of a dynamical black hole by a flow-induced supertranslation

One interesting proposal to solve the black hole information loss paradox without modifying either general relativity or quantum field theory, is the soft hair, a diffeomorphism charge that records the anisotropic radiation in the asymptotic region. This proposal, however, has been challenged, given that away from the source the soft hair behaves as a coordinate transformation that forms an Abelian group, thus unable to store any information. To maintain the spirit of the soft hair but circumvent these obstacles, we consider Hawking radiation as a probe sensitive to the entire history of the black hole evaporation, where the soft hairs on the horizon are induced by the absorption of a null anisotropic flow, generalizing the shock wave considered in [1, 2]. To do so we introduce two different time-dependent extensions of the diffeomorphism associated with the soft hair, where one is the backreaction of the anisotropic null flow, and the other is a coordinate transformation that produces the Unruh effect and a Doppler shift to the Hawking spectrum. Together, they form an exact BMS charge generator on the entire manifold that allows the nonperturbative analysis of the black hole horizon, whose surface gravity, i.e. the Hawking temperature, is found to be modified. The modification depends on an exponential average of the anisotropy of the null flow with a decay rate of 4M, suggesting the emergence of a new 2-D degree of freedom on the horizon, which could be a way out of the information loss paradox.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Observed volatilization behavior of silicon carbide in flowing hydrogen above 2000 K

In this work, the intrinsic compatibility of silicon carbide (SiC) and hydrogen (H 2 ) at high temperatures (2000-2473 K) and pressure near one atmosphere was evaluated through a combination of thermodynamic calculations and hot hydrogen exposure testing. Thermodynamic calculations predict the decomposition of SiC in a hydrogen environment to form free silicon (Si) and free carbon (C). Free Si is predicted to vaporize from the surface as a volatile species, while free C may interact with H 2 to form the hydrocarbons CH 4 (T < 2100 K) or C 2 H 2 (T > 2100 K). Coupons of high purity chemical vapor deposition (CVD) β-SiC were exposed to slowly flowing hydrogen at temperatures ranging between 2000 and 2473 K. SiC experienced active attack as the result of H 2 exposure, exhibiting linear weight loss kinetics and an Arrhenius dependence of weight loss on exposure temperature. The linear volatilization constant was experimentally evaluated to correspond with an activation energy of 370 ± 18 kJ/mol. Due to the dependence of observed corrosion rates on gas velocity, corrosion of SiC in flowing H 2 was determined to be governed by external mass transfer of volatile Si species through the boundary layer. Experimentally derived mass losses were in good agreement with mass losses predicted by a boundary layer limited gas diffusion model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evolution of Pore Structure in Organic-Lean and Organic-Rich Mudrocks

The pore structure of mudrocks is a key characteristic to evaluate flow behavior through these rocks. Although significant advances have been made to resolve pore characteristics, porosity evolution, or pore connectivity, there is still insufficient knowledge linking porosity evolution to flow and transport in mudrocks. To better understand these links, we conducted very small-angle (VSANS) and small-angle neutron scattering (SANS) experiments on 13 sets of mudrocks from global locations, characterized by differences in composition, maturity, and depositional environment. Our results indicate that a homogeneous pore structure reflects a stable and low-energy depositional environment. Organic-lean mudrocks mainly contain pores <10 nm, which restricts flow and is beneficial for, e.g., caprock seal integrity. Increasing maturity as a result of increasing burial depth, and therefore, temperature leads to porosity evolution. In organic-rich mudrocks (ORMs), this happens through the generation of organic matter pores and pore preservation around diagenetically formed carbonates. ORMs mainly contain macropores (>50 nm), favoring production from, e.g., unconventional reservoirs. SANS-derived pore size distributions will help to better understand fluid imbibition and flow properties in mudrocks through comprehensive quantitative characterization of the nano- to micron scale pore network conduits and their relationships to burial diagenesis.

58 GEOSCIENCES↗
DOE OSTI2022

Bidisperse supension balance model

The suspension balance model (SBM) for viscous Stokes flow has been well studied for the case of identical, monodisperse spherical particles in a channel, however, more work remains to be done to explore the bidisperse and polydisperse SBM. Here, we present a simple extension of the SBM that allows for modeling of suspensions of particles of bidisperse size. The comparison with avaiable experiments and direct simulations is found to be good. Additionally, we present a range of simulations to justify the assumptions made in the polydisperse suspension balance model for non-Brownian, neutrally buoyant particles that vary in size with a bidisperse distribution. The aim is to study the effects of moderate size variation on the rheology of the suspension and the distribution of the particles across the flow, especially in the near-wall regions. It is shown that, at the size ratios considered, bidispersity in the particle size does not significantly affect rheological parameters including the particle volume fraction and relative viscosity in the bulk of a Couette flow. The particle phase stresses are distributed between small and large particles in proportion to the relative volume fractions of each species. In bidisperse suspensions, the large particles in the wall layer develop a spatial structure and form chains in the streamwise direction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Numerical calculation of the particle–fluid–particle stress in random arrays of fixed particles

Based on the nearest particle statistics [Zhang, J. Fluid Mech. 910, A16 (2021)], the phase interaction force in a multiphase flow is decomposed into a particle–mean-field force and the divergence of the particle–fluid–particle (PFP) stress. The PFP stress is proportional to the correlation product of the distance from a particle to its nearest neighbor and the force on the particle conditionally averaged on the nearest-neighbor location. In this work, a functional form of the stress is obtained corrected to the first order of the ratio between the interparticle distance and the macroscopic length scale of the flow. Particle-resolved numerical simulations are used to calculate the PFP stress in random arrays of fixed particles and to explore the physics represented by the stress. The numerical results show that the PFP stress is attractive along the direction of the flow and is repulsive in the directions perpendicular to the flow. In the flow regime simulated, this PFP stress can be considered as a macroscopic representation of the drafting–kissing–tumbling mechanism. Finally, the Reynolds stress for the fluid phase is also calculated and compared with the PFP stress.

42 ENGINEERING↗
DOE OSTI2025

Seedless nonresonant gas-flow velocimetry with single-shot coherent Rayleigh-Brillouin scattering

We demonstrate neutral gas-flow velocimetry by exploiting the optical dipole forces exerted by precisely tailored high-intensity laser fields on polarizable particles, in the form of single-shot coherent Rayleigh-Brillouin scattering (CRBS). This enables mapping of the velocity distribution function of the particles in a single laser shot of approximately 200 ns duration, allowing us to perform spectroscopic measurements in the time, rather than the frequency, domain. Importantly, CRBS results in a coherent signal beam, which renders the technique ideal for measurements in optically noisy environments. By correlating the time shift of the resulting spectrum to the Doppler shift caused by the bulk motion of particles, we perform neutral gas-flow velocimetry without the need to seed the flow, nondestructively, for a variety of gases, atomic or molecular. We demonstrate gas-flow velocimetry at flow velocities as low as 1 m ⁢s −1 , with similar velocity resolution, while temperature and gas density can also be estimated from the same single-shot spectra. To prove the effectiveness of the measurement technique, we benchmark it against Pitot tube measurements, which show excellent agreement.

Gerakis, Alexandros [Luxembourg Institute of Scien↗