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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Depressurization-Induced Fines Migration in Sediments Containing Methane Hydrate: X-Ray Computed Tomography Imaging Experiments

Depressurization of hydrate-bearing sediments (HBS) can cause the movement of fine particles, and in turn, such fines migration affects fluid flow and mechanical behavior of sediments, ultimately affecting long-term hydrocarbon production and wellbore stability. In this work, we investigate how and to what extent depressurization of HBS causes fines migration using X-ray computed tomography (CT) imaging. Methane hydrate was synthesized in sediments with 10% fines content (FC), composed of sands with silt and/or clay, and the hydrate-bearing samples were stepwisely depressurized while acquiring CT images. The CT images were analyzed to quantify the spatial changes in FC in the host sediment and thus to capture the fines migration during depressurization. It was found that the FC changes began occurring from the hydrate dissociation regions. This confirms that the multiphase flow caused by depressurization accompanies fines migration. Depressurization of HBS with a hydrate saturation of ~20–40% caused FC reduction from ~10% to ~6–9%, and the extent of fines migration differed with the particle sizes of the host sands and the types of fines. It was found that fines migration was more pronounced with coarse sands and with silty fines. Such observed level of FC reduction is estimated to increase sediment permeability by several factors based on the Kozeny-type permeability model. In conclusion, our results support the notion that the extent of fines migration and its effect on fluid flow behavior need to be assessed in consideration of physical properties of host sediment and fine particles to identify optimum depressurization strategies.

42 ENGINEERING↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2020

Critique on “A Revisit of Navier-Stokes Equation”

In a recently published work (Sheng, 2020), Sheng identified inconsistencies in the concepts and principles leading to the Navier–Stokes equations and proposed a new asymmetric “friction tensor” to resolve these inconsistencies. We show that this friction tensor can be interpreted as the non-isotropic part of a vorticity-influenced viscous stress tensor following the analysis in Berdahl and Strang (1986). The asymmetric stress tensor however violates the principles of mechanical equilibrium in fluid flows that are free of external or body couples and is therefore non-physical in classical continuum hydrodynamics. We refute the arguments in favour of the asymmetric stress tensor in Sheng (2020) whilst also demonstrating that the friction tensor leads to the incorrect form of the Navier–Stokes equations in non-Cartesian co-ordinates and its ability to recover the correct governing equations in Cartesian co-ordinates is fortuitous.

asymmetric↗
DOE OSTI2022

Evaluation of accuracy and convergence of numerical coupling approaches for poroelasticity benchmark problems

Accurate modeling of subsurface flow and transport processes is vital as the prevalence of subsurface activities such as carbon sequestration, geothermal recovery, and nuclear waste disposal increases. Computational modeling of these problems leverages poroelasticity theory, which describes coupled fluid flow and mechanical deformation. Although fully coupled monolithic schemes are accurate for coupled problems, they can demand significant computational resources for large problems. In this work, a fixed stress scheme is implemented into the Sandia Sierra Multiphysics toolkit. Two implementation methods, along with the fully coupled method, are verified with one-dimensional (1D) Terzaghi, 2D Mandel, and 3D Cryer sphere benchmark problems. The impact of a range of material parameters and convergence tolerances on numerical accuracy and efficiency was evaluated. Overall the fixed stress schemes achieved acceptable numerical accuracy and efficiency compared to the fully coupled scheme. However, the accuracy of the fixed stress scheme tends to decrease with low permeable cases, requiring the finer tolerance to achieve a desired numerical accuracy. For the fully coupled scheme, high numerical accuracy was observed in most of cases except a low permeability case where an order of magnitude finer tolerance was required for accurate results. Finally, a two-layer Terzaghi problem and an injection–production well system were used to demonstrate the applicability of findings from the benchmark problems for more realistic conditions over a range of permeability. Simulation results suggest that the fixed stress scheme provides accurate solutions for all cases considered with the proper adjustment of the tolerance. Furthermore, this work clearly demonstrates the robustness of the fixed stress scheme for coupled poroelastic problems, while a cautious selection of numerical tolerance may be required under certain conditions with low permeable materials.

58 GEOSCIENCES↗
DOE OSTI2020

A thermodynamic analysis of hypervelocity impacts on metals

Hypervelocity impacts on solid surfaces generate and propagate shock waves and create extreme density, pressure, and temperature conditions. Understanding hypervelocity impacts requires a multi-physics approach at the intersection of fluid dynamics, solid mechanics, and quantum theory, which has the capability of spanning multiple different dominating physics regimes. These strong shock conditions found in hypervelocity impacts are studied in the context of high-speed collisions between spacecraft and meteoroids and debris. We study the problem of hypervelocity impacts on metals with the lens of understanding the processes that lead to the creation of an impact generated plasma. In order to characterize the impacting particle as well as its threat to spacecraft from the subsequent radiating plasma an analysis was performed that highlights how the kinetic energy of the impactor is deposited into a target, how the shock wave and shocked material in the target evolve, and how these effects can lead towards the creation of an impact plasma through heating. The analysis suggests that at low velocities the majority of the energy from a hypervelocity impact is stored in reversible elastic energy and does not contribute to strong heating. At higher impact velocities, nucleus and electron thermal components dominate, increasing the energy available for ionization. Overall, this work provides the complete set of state variable initial conditions for any study of hypervelocity impact plasma expansion and its effects.

42 ENGINEERING↗
DOE OSTI2021

Ferromagnetic liquid droplets with adjustable magnetic properties

Significance Structured functional liquids combine mechanical versatility of fluids with solid-state properties, such as ferromagnetism, and offer a route to synthesize and control magnetic liquids for adaptive liquid robotics. Studies on these intriguing materials are only in their nascent state, and a profound understanding of the physical state is still lacking. We use hydrodynamics experiments to probe how the magnetization of ferromagnetic liquid droplets, governed by the assembly and jamming of magnetic nanoparticles at liquid–liquid interfaces, and their response to external stimuli can be tuned by chemical, structural, and magnetic means. Our results highlight the leading role of structural short-range order on magnetic properties, which provide a path toward nano-patterning structured liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Novel Multiphysics Multiscale Multiporosity Shale Gas Transport Model for Geomechanics/Flow Coupling in Steady and Transient States

Summary A novel multiphysics multiscale multiporosity shale gas transport (M3ST) model was developed to investigate shale gas transport in both transient and steady states. The microscale model component contains a kerogen domain and an inorganic matrix domain, and each domain has its own geomechanical and gas transport properties. Permeabilities of various shale cores were measured in the laboratory using a pulse decay permeameter (PDP) with different pore pressure and confining stress combinations. The PDP-measured apparent permeability as a function of pore pressure under two effective stresses was fitted using the microscale M3ST model component based on nonlinear least squares fitting (NLSF), and the fitted model parameters were able to provide accurate model predictions for another effective stress. The parameters and petrophysical properties determined in the steady state were then used in the transient-state, continuum-scale M3ST model component, which performed history matching of the evolutions of the upstream and downstream gas pressures. In addition, a double-exponential empirical model was developed as a powerful alternative to the M3ST model to fit laboratory-measured apparent permeability under various effective stresses and pore pressures. The developed M3ST model and the research findings in this study provided critical insights into the role of the multiphysics mechanisms, including geomechanics, fluid dynamics and transport, and the Klinkenberg effect on shale gas transport across different spatial scales in both steady and transient states.

Engineering↗
DOE OSTI2020

Compact Diffusion Bonded Heat Exchanger Fatigue Life Simulations (Final Report)

Compact diffusion bonded heat exchangers are essential for high pressure heat exchange, but they are subject to thermal fatigue and ramp rate limitations. Simulation of these geometries is challenging with a large range of length and time scales from thousands of mm-sized microchannels inside a m-sized heat exchanger. Multi-physics simulations including thermal, fluid, and solid mechanics components are being used to predict stress within the heat exchangers under these conditions. These predictions can then be used to understand thermal ramp rate limitations while keeping maximum stresses low as well as fatigue life predictions from well-known empirical models.

42 ENGINEERING↗
DOE OSTI2024

Exploration of Binder Jet Additive Manufacturing for Automotive Heat Sink Component Fabrication

ORNL (Contractor) and Magna Services of America Inc. (Participant) collaborated to determine the feasibility of binder jet additive manufacturing (BJAM) for the fabrication of copper components for automotive heat sink applications. This Phase 1 collaboration focused on printing copper heat sinks that rely on capillary effect to move fluids rather than mechanical pumps in electric vehicles to extend the battery range and life. Partial sintering of copper powders deposited via BJAM was hypothesized to aid capillary effect to improve the heat transfer. Further, BJAM offers the potential for scalability at a production level.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solar Decarbonization of Paraffin Dehydrogenation Through Particle Heat Carriers (Final Technical Report)

This project focuses on solutions to decarbonize high-temperature catalytic processes using solar thermal heat. The primary project goal is to show the validity of a moving packed bed reactor for propane dehydrogenation using catalyst particles as the heat carrier for the reaction, which can be heated by concentrated solar energy in a particle receiver. This concept, if further developed, may provide a cost-effective pathway for converting lower value gases to important chemical precursors for industrial materials using only renewable energy. The project was divided into six tasks. In Task 1, DFT calculations were performed to understand the role of Pt and Sn in the catalytic dehydrogenation reaction. In Task 2 chemical kinetics measurements were made for several catalyst formulations at high temperatures. In Task 3, the solar absorptance of catalyst particles was compared to the absorptance of commonly used materials in particle receivers. In Task 4, numerical models were developed which could predict performance of the complete system and predict specific temperatures in the system. In Task 5, a prototype system was designed, fabricated, and tested to show the validity of the concept. Task 6 concerned project management activities. Experiments with the prototype showed repeatable thermal performance at temperatures targeted for the reaction. A limited set of tests were done with active catalyst and propane dehydrogenation, showing conversion of propane to propylene with a range of conversions and selectivities. The results are promising, and the prototype designed was reliable during testing, and the team expects that further development of the prototype would yield improved results. A numerical model framework based on coupled fluid and particle mechanics was developed with high computational efficiency using GPU calculations. The model may prove highly useful for evaluating other high-temperature particle systems. However, it was determined that simpler porous media models were good fits for the needs of the current moving packed bed concept. Data showing strong solar absorption of the particles validates the plan of using existing solar particle receivers with only a change in the particle type. Catalyst investigation showed that Pt 1 Sn 3 is the most viable candidate for developing PtSn catalysts for high temperature propane dehydrogenation, considering the balance of activity, selectivity, and deactivation. This project completed an initial study of various factors needed to incorporate a moving bed catalytic reactor for propane dehydrogenation into a concentrated solar thermal particle system. Future developments may allow this technology to be scaled up and help to use solar thermal energy to decarbonize not only the propane dehydrogenation reaction, but other gas-solid catalytic reactions at similar temperatures.

14 SOLAR ENERGY↗
DOE OSTI2021

Deep Learning Approaches to Surrogates for Solving the Diffusion Equation for Mechanistic Real-World Simulations

In many mechanistic medical, biological, physical, and engineered spatiotemporal dynamic models the numerical solution of partial differential equations (PDEs), especially for diffusion, fluid flow and mechanical relaxation, can make simulations impractically slow. Biological models of tissues and organs often require the simultaneous calculation of the spatial variation of concentration of dozens of diffusing chemical species. One clinical example where rapid calculation of a diffusing field is of use is the estimation of oxygen gradients in the retina, based on imaging of the retinal vasculature, to guide surgical interventions in diabetic retinopathy. Furthermore, the ability to predict blood perfusion and oxygenation may one day guide clinical interventions in diverse settings, i.e., from stent placement in treating heart disease to BOLD fMRI interpretation in evaluating cognitive function (Xie et al., 2019; Lee et al., 2020). Since the quasi-steady-state solutions required for fast-diffusing chemical species like oxygen are particularly computationally costly, we consider the use of a neural network to provide an approximate solution to the steady-state diffusion equation. Machine learning surrogates, neural networks trained to provide approximate solutions to such complicated numerical problems, can often provide speed-ups of several orders of magnitude compared to direct calculation. Surrogates of PDEs could enable use of larger and more detailed models than are possible with direct calculation and can make including such simulations in real-time or near-real time workflows practical. Creating a surrogate requires running the direct calculation tens of thousands of times to generate training data and then training the neural network, both of which are computationally expensive. Often the practical applications of such models require thousands to millions of replica simulations, for example for parameter identification and uncertainty quantification, each of which gains speed from surrogate use and rapidly recovers the up-front costs of surrogate generation. We use a Convolutional Neural Network to approximate the stationary solution to the diffusion equation in the case of two equal-diameter, circular, constant-value sources located at random positions in a two-dimensional square domain with absorbing boundary conditions. Such a configuration caricatures the chemical concentration field of a fast-diffusing species like oxygen in a tissue with two parallel blood vessels in a cross section perpendicular to the two blood vessels. To improve convergence during training, we apply a training approach that uses roll-back to reject stochastic changes to the network that increase the loss function. The trained neural network approximation is about 1000 times faster than the direct calculation for individual replicas. Because different applications will have different criteria for acceptable approximation accuracy, we discuss a variety of loss functions and accuracy estimators that can help select the best network for a particular application. We briefly discuss some of the issues we encountered with overfitting, mismapping of the field values and the geometrical conditions that lead to large absolute and relative errors in the approximate solution.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1970

Investigation of positive shaft seals

Welded metal bellows secondary seals prevent secondary seal leakage with a minimum number of potential leak paths. High performance seal is obtained by controlling the potentially unstable seal-face movements induced by mechanical vibrations and fluid pressure pulsations.

Pfouts, J. O.↗
NASA NTRS1976

Metabolic and endocrine studies - The second manned Skylab mission

Complete metabolic collections were performed on the Skylab 3 crew in the preflight, inflight, and postflight phases of the mission. Changes in fluid and electrolyte balance have been correlated with weight loss, changes in the excretion of aldosterone, vasopressin, and fluid compartments. The initial changes observed were consistent with an increase in thoractic blood volume upon transition to a zero gravity environment, producing a net fluid loss. Compensatory mechanisms reestablished positive water balance. The indicators investigated returned to thin preflight levels during the recovery period postflight

Leach, C. S.↗
NASA NTRS1982

Welding Research

Welding fabrication and welding processes were studied. The following research projects are reported: (1) welding fabrication; (2) residual stresses and distortion in structural weldments in high strength steels; (3) improvement of reliability of welding by in process sensing and control (development of smart welding machines for girth welding of pipes); (4) development of fully automated and integrated welding systems for marine applications; (5) advancement of welding technology; (6) research on metal working by high power laser (7) flux development; (8) heat and fluid flow; (9) mechanical properties developments.

Source record↗
NASA NTRS1984

Thrust for interorbital propulsion - A question of lifetime

The most promising operational window for the use of magnetoplasmadynamic (MPD) thrusters is identified to be at megawatt power levels for orbital maneuvering. For such applications, the operation of a steady-state MPD thruster system imposes stringent requirements on the lifetime of thruster surfaces which will erode due to interactions with the plasma working fluid. Basic erosion mechanisms are presented and the problems associated with measuring the erosion rates are discussed. An experimental approach that would allow the development of a phenomenological model for erosion is proposed.

Gabriel, S. B.↗
NASA NTRS1985

An overview of the Space Station Technology/Advanced Development Program

The Advanced Technology Plan of the Fiscal Year (FY) 1986 is designed to focus on the most promising technology options applicable to the Space Station (SS), selected from the list of tasks identified by the FY 1984 Technology Program as the most critical technologies to be developed for the initial SS Initial Operating Capability. Most of the current activities are in the stages of manufacture and life tests of specific SS subsystems. Special attention is given to major technologies, which include power systems (PSs) (with emphasis on a Solar Dynamic PS concept); the thermal control system (with the focus on the 'thermal bus' concept); the environmental control and life support system; and the data management system; all are illustrated schematically. Other tasks, including dynamics, communications, extravehicular activities, mechanics, propulsion, and fluid, as well as the tasks of cost, maintainability, automation and robotics, and productivity are discussed.

Carlisle, R. F.↗