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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

A theoretical analysis of steady-state photocurrents in simple silicon diodes

A theoretical analysis solves for the steady-state photocurrents produced by a given photo-generation rate function with negligible recombination in simple silicon diodes, consisting of a uniformly doped quasi-neutral region (called 'substrate' below) adjacent to a p-n junction depletion region (DR). Special attention is given to conditions that produce 'funneling' (a term used by the single-eventeffects community) under steady-state conditions. Funneling occurs when carriers are generated so fast that the DR becomes flooded and partially or completely collapses. Some or nearly all of the applied voltage, plus built-in potential normally across the DR, is now across the substrate. This substrate voltage drop affects substrate currents. The steady-state problem can provide some qualitative insights into the more difficult transient problem. First, it was found that funneling can be induced from a distance, i.e., from carriers generated at locations outside of the DR. Secondly, it was found that the substrate can divide into two subregions, with one controlling substrate resistance and the other characterized by ambipolar diffusion. Finally, funneling was found to be more difficult to induce in the p(sup +)/n diode than in the n(sup +)/p diode. The carrier density exceeding the doping density in the substrate and at the DR boundary is not a sufficient condition to collapse a DR.

Edmonds, L.↗
NASA NTRS1948

Performance Investigations of a Large Centrifugal Compressor from an Experimental Turbojet Engine

An investigation was conducted on a large centrifugal compressor from an experimental turbojet engine to determine the performance of the compressor and to obtain fundamental information on the aerodynamic problems associated with large centrifugal-type compressors. The results of the research conducted on the compressor indicated that the compressor would not meet the desired engine-design air-flow requirements (78 lb/sec) because of an air-flow restriction in the vaned collector (diffuser). Revision of the vaned collector resulted in an increased air-flow capacity over the speed range and showed improved matching of the impeller and diffuser components. At maximum flow, the original compressor utilized approximately 90 percent of the available geometric throat area at the vaned-collector inlet and the revised compressor utilized approximately 94 percent, regardless of impeller speed. The ratio of the maximum weight flows of the revised and original compressors were less than the ratio of effective critical throat areas of the two compressors because of the large pressure losses in the impeller near the impeller inelt and the difference increased with an increase in impeller speed. In order to further increase the pressure ratio and maximum weight flow of the compressor, the impeller must be modified to eliminate the pressure losses therein.

Ginsburg, Ambrose↗
NASA NTRS2004

Transplanting Retinal Cells using Bucky Paper for Support

A novel treatment for retinal degenerative disorders involving transplantation of cells into the eye is currently under development at NASA Ames Research Center and Stanford University School of Medicine. The technique uses bucky paper as a support material for retinal pigment epithelial (RPE) cells, iris pigment epithelial (IPE) cells, and/or stem cells. This technology is envisioned as a treatment for age-related macular degeneration, which is the leading cause of blindness in persons over age 65 in Western nations. Additionally, patients with other retinal degenerative disorders, such as retinitis pigmentosa, may be treated by this strategy. Bucky paper is a mesh of carbon nanotubes (CNTs), as shown in Figure 1, that can be made from any of the commercial sources of CNTs. Bucky paper is biocompatible and capable of supporting the growth of biological cells. Because bucky paper is highly porous, nutrients, oxygen, carbon dioxide, and waste can readily diffuse through it. The thickness, density, and porosity of bucky paper can be tailored in manufacturing. For transplantation of cells into the retina, bucky paper serves simultaneously as a substrate for cell growth and as a barrier for new blood vessel formation, which can be a problem in the exudative type of macular degeneration. Bucky paper is easily handled during surgical implantation into the eye. Through appropriate choice of manufacturing processes, bucky paper can be made relatively rigid yet able to conform to the retina when the bucky paper is implanted. Bucky paper offers a distinct advantage over other materials that have been investigated for retinal cell transplantation - lens capsule and Descemet's membrane - which are difficult to handle during surgery because they are flimsy and do not stay flat.

Loftus, David J.↗
DOE OSTI2015

Influence of string-like cooperative atomic motion on surface diffusion in the (110) interfacial region of crystalline Ni

Although we often think about crystalline materials in terms of highly organized arrays of atoms, molecules, or even colloidal particles, many of the important properties of this diverse class of materials relating to their catalytic behavior, thermodynamic stability, and mechanical properties derive from the dynamics and thermodynamics of their interfacial regions, which we find they have a dynamics more like glass-forming (GF) liquids than crystals at elevated temperatures. This is a general problem arising in any attempt to model the properties of naturally occurring crystalline materials since many aspects of the dynamics of glass-forming liquids remain mysterious. We examine the nature of this phenomenon in the “simple” case of the (110) interface of crystalline Ni, based on a standard embedded-atom model potential, and we then quantify the collective dynamics in this interfacial region using newly developed methods for characterizing the cooperative dynamics of glass-forming liquids. As in our former studies of the interfacial dynamics of grain-boundaries and the interfacial dynamics of crystalline Ni nanoparticles (NPs), we find that the interface of bulk crystalline Ni exhibits all the characteristics of glass-forming materials, even at temperatures well below the equilibrium crystal melting temperature, T{sub m}. This perspective offers a new approach to modeling and engineering the properties of crystalline materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

A finite element method for diffusion dominated unsteady viscous flows

A general conforming finite element scheme for computing viscous flows is presented which is of second-order accuracy in space and time. Viscous terms are treated implicitly and advection terms are treated explicitly in the time marching segment of the algorithm. A method for solving the algebraic equations at each time step is given. The method is demonstrated on two test problems, one of them being a plane vortex flow for which asymptotic methods are used to obtain suitable numerical boundary conditions at each time step.

Gunzburger, M. D.↗
DOE OSTI2017

Anderson acceleration and application to the three-temperature energy equations

The Anderson acceleration method is an algorithm for accelerating the convergence of fixed-point iterations, including the Picard method. Anderson acceleration was first proposed in 1965 and, for some years, has been used successfully to accelerate the convergence of self-consistent field iterations in electronic-structure computations. Recently, the method has attracted growing attention in other application areas and among numerical analysts. Compared with a Newton-like method, an advantage of Anderson acceleration is that there is no need to form the Jacobian matrix. Thus the method is easy to implement. In this paper, an Anderson-accelerated Picard method is employed to solve the three-temperature energy equations, which are a type of strong nonlinear radiation-diffusion equations. Two strategies are used to improve the robustness of the Anderson acceleration method. One strategy is to adjust the iterates when necessary to satisfy the physical constraint. Another strategy is to monitor and, if necessary, reduce the matrix condition number of the least-squares problem in the Anderson-acceleration implementation so that numerical stability can be guaranteed. Numerical results show that the Anderson-accelerated Picard method can solve the three-temperature energy equations efficiently. Compared with the Picard method without acceleration, Anderson acceleration can reduce the number of iterations by at least half. A comparison between a Jacobian-free Newton–Krylov method, the Picard method, and the Anderson-accelerated Picard method is conducted in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Cluster dynamics models of irradiation damage accumulation in ferritic iron. II. Effects of reaction dimensionality

The black dot damage features which develop in iron at low temperatures exhibit significant mobility during in situ irradiation experiments via a series of discrete, intermittent, long range hops. By incorporating this mobility into cluster dynamics models, the temperature dependence of such damage structures can be explained with a surprising degree of accuracy. Such motion, however, is one dimensional in nature. This aspect of the physics has not been fully considered in prior models. This article describes one dimensional reaction kinetics in the context of cluster dynamics and applies them to the black dot problem. This allows both a more detailed description of the mechanisms by which defects execute irradiation-induced hops while allowing a full examination of the importance of kinetic assumptions in accurately assessing the development of this irradiation microstructure. Results are presented to demonstrate whether one dimensional diffusion alters the dependence of the defect population on factors such as temperature and defect hop length. Finally, the size of interstitial loops that develop is shown to depend on the extent of the reaction volumes between interstitial clusters, as well as the dimensionality of these interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Understanding NBI heating and fueling in LTX-β tokamak

My work on the contract DE-SC=0023274 (July, 2022 - July, 2025) was focused on understanding the plasma fueling by NBI. On Dec. 1998 with Sergei Krasheninnikov (UCSD, San Diego, CA) we initiated the Li Wall Fusion (LiWFusion) as a new concept of magnetic fusion [1]. The new 1 2 plasma 3 4 5 6 2.1 Overview of rate coefficients, mean-free paths λH0 , and diffusions coefficients 6 2. GSV code for ⟨σv⟩ analysis of NBI fueling concept was a reaction of the lack of luck of tokamak fusion with QDT = 1 on TFTR and JET. We recognized the edge plasma cooling by recycling to be the route reason of the tokamak problems on the way to burning plasma. LiWFusion relies on plasma pumping by a lithium layer on the inner walls of the plasma chamber, combined with the plasma heating and fueling by the Neutral Beam Injection (NBI). These two innovations eliminate the route problem of the tokmak fusion. The concept became theoretically mature in 2006. In 2012, the technology of continuously Flowing Liquid Lithium (24/7-FLiLi) was invented by me for the future implementations of the LWFusion concept. At the same time, my every presentation on LiWFusion to International Symposium on Lithium Applications since 2010 was objected by some person with words “Everybody since the 1970s knows that plasma fueling by NBI is impossible”. I dropped the name of the author of this objection and ignored his views. My work on the current grant on NBI fueling of LTX-β not only clarified the issue but resolved it in an astonishing way. The NBI fueling was fully understood (thus humiliating the current dogmatic fusion community). The new future of LTX-β dedicated for decades to Li in tokamaks, as well as of the entire magnetic fusion program was envisioned, in sharp contrast with the fallure of OFES in the post-TFTR era of 21st century.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1977

The jet engine design that can drastically reduce oxides of nitrogen

The NOx pollution problem of hydrogen fueled turbojets and supersonic combustion ramjets (scramjets) was investigated to determine means of substantially alleviating the problem. Since the NOx reaction rates are much slower than the energy producing reactions, the NOx production depends mainly on the maximum local temperatures in the combustor and the NOx concentration is far from equilibrium at the end of a typical combustor (L approximately 1 ft). In diffusion flames, as used in present turbojets and scramjets combustor designs, the maximum local temperature occurs at the flame and is equal to the stoichiometric value. Whereas, in the heat conduction flames, wherein the flame propagates due to a heat conduction process away from the flame to the cooler oncoming premixed unburnt gases, the maximum temperature is lower than in the diffusion flame. Hence the corresponding pollution index is also lower.

Ferri, A.↗
NASA NTRS1991

Shape selection criterion for cellular array during constrained growth of binary alloys - Need for low gravity experiment

Development of steady-state periodic cellular array is one of the critical problems in the study of nonlinear pattern formation during directional solidification of binary alloys. The criterion which establishes the values of cell tip radius and spacing under given growth condition is not known. Theoretical models, such as marginal stability and microscopic solvability, have been developed for purely diffusive regime. However, the experimental conditions where cellular structures are stable are precisely the ones where the convection effects are predominant. Thus, the critical data for meaningful evaluation of cellular array growth models can only be obtained by partial directional solidification and quenching experiments carried out in the low gravity environment of space.

Tewari, Surendra N.↗
NASA NTRS2006

Fuel Cells Utilizing Oxygen From Air at Low Pressures

A fuel cell stack has been developed to supply power for a high-altitude aircraft with a minimum of air handling. The fuel cell is capable of utilizing oxygen from ambient air at low pressure with no need for compression. For such an application, it is advantageous to take oxygen from the air (in contradistinction to carrying a supply of oxygen onboard), but it is a challenging problem to design a fuel-cell stack of reasonable weight that can generate sufficient power while operating at reduced pressures. The present fuel-cell design is a response to this challenge. The design features a novel bipolar plate structure in combination with a gas-diffusion structure based on a conductive metal core and a carbon gas-diffusion matrix. This combination makes it possible for the flow fields in the stack to have a large open fraction (ratio between open volume and total volume) to permit large volumes of air to flow through with exceptionally low backpressure. Operations at reduced pressure require a corresponding increase in the volume of air that must be handled to deliver the same number of moles of oxygen to the anodes. Moreover, the increase in the open fraction, relative to that of a comparable prior fuel-cell design, reduces the mass of the stack. The fuel cell has been demonstrated to operate at a power density as high as 105 W/cm2 at an air pressure as low as 2 psia (absolute pressure 14 kPa), which is the atmospheric pressure at an altitude of about 50,000 ft ( 15.2 km). The improvements in the design of this fuel cell could be incorporated into designs of other fuel cells to make them lighter in weight and effective at altitudes higher than those of prior designs. Potential commercial applications for these improvements include most applications now under consideration for fuel cells.

Cisar, Alan↗
DOE OSTI2014

Two critical issues in Langevin simulation of gas flows

A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefied gas flows. Compared with the direct simulation Monte Carlo (DSMC) method, the Langevin method is more efficient in simulating small Knudsen number flows. While it is well-known that the cell sizes and time steps should be smaller than the mean free path and the mean collision time, respectively, in DSMC simulations, the Langevin equation uses a drift term and a diffusion term to describe molecule movements, so no direct molecular collisions have to be modeled. This enables the Langevin simulation to proceed with a much larger time step than that in the DSMC method. Two critical issues in Langevin simulation are addressed in this paper. The first issue is how to reproduce the transport properties as that described by kinetic theory. Transport coefficients predicted by Langevin equation are obtained by using Green-Kubo formulae. The second issue is numerical scheme with boundary conditions. We present two schemes corresponding to small time step and large time step, respectively. For small time step, the scheme is similar to DSMC method as the update of positions and velocities are uncoupled; for large time step, we present an analytical solution of the hitting time, which is the crucial factor for accurate simulation. Velocity-Couette flow, thermal-Couette flow, Rayleigh-Bénard flow and wall-confined problem are simulated by using these two schemes. Our study shows that Langevin simulation is a promising tool to investigate small Knudsen number flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems

Here we present the PI-CKL-NN method for parameter estimation in differential equation (DE) models given sparse measurements of the parameters and states. In the proposed approach, the space- or time-dependent parameters are approximated by Karhunen-Loeve (KL) expansions that are conditioned on the parameters’ measurements, and the states are approximated by deep neural networks (DNNs). The unknown weights in the KL expansions and DNNs are found my minimizing the cost function that enforces the measurements of the states the DE constraint. Regularization is achieved by adding the l2 norm of the conditional KL coefficients into the loss function. Our approach assumes that the parameter fields are correlated in space or time and enforces the statistical knowledge (the mean and the covariance function) in addition to the DE constraints and measurements as opposed to the physics-informed neural network (PINN) and other similar physics-informed machine learning methods where only DE constraints and data are used for parameter estimation. We use the PI-CKL-NN method for parameter estimation in an ordinary differential equation with an unknown time-dependent parameter and the one- and two-dimensional partial differential diffusion equations with unknown space-dependent diffusion coefficients. We also demonstrate that PI-CKL-NN is more accurate than the PINN method, especially when the observations of the parameters are very sparse

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Use of Diffusion Bonded Cu Strap and Integrated MLI for Thermal Control of 100 K IR Detector on L’Ralph Instrument

Passive cooling of cryogenic instruments is one of the most challenging aspects of spaceflight thermal control systems. They are highly sensitive to parasitic heat leaks from their warmer environment, especially the spacecraft components. The L’Ralph instrument on the Lucy mission is an example of such a system, with its LEISA detector requiring passive cooling to temperatures below 112 K. MLI performance can be measured in terms of estar, and analysts apply bias between a high and low estar value. This approach works well for conventional MLI at room temperature, however, it can be dangerous when a mission goes through a wide range of temperatures during its lifetime, with estar values increasing exponentially as temperatures get colder. Various estar correlations are presented as well as how L’Ralph is approaching the MLI problem with the use of IMLI. IMLI uses discrete spacers to isolate each layer, and doesn’t require intermediate layers such as dacron netting. This results in estar performance that can be more precisely estimated, and yields valuesaround 0.004 at the 112K operating temperature. L’Ralph is using IMLI on the backside of the radiator, which permits a more effective use of increased radiator area, by minimizing the area dependent heat leak impact from the instrument backloading. The detector is thermally coupled to the radiator via a diffusion bonded Cu strap. The diffusion bonding process chemically bonds the Cu foil ends in order to maximize heat transfer effectiveness across the multiple foils used. Employing a pressure compensation design via the use of Ti blocks and a clamp at the strap ends ensures that as temperatures go colder, pre-load is maintained in order to minimize resistance at the strap ends. The use of both of these technologies, and how they work together are crucial to the success of the L’Ralph thermal control system.

Thermal↗
DOE OSTI2026

Efficient data-driven regression for reduced-order modeling of spatial pattern formation

We present an efficient data-driven regression approach for constructing reduced-order models (ROMs) of reaction-diffusion systems exhibiting pattern formation. The ROMs are learned non-intrusively from available training data of physically accurate numerical simulations. The method can be applied to general nonlinear systems through the use of polynomial model form, while not requiring knowledge of the underlying physical model, governing equations, or numerical solvers. The process of learning ROMs is posed as a low-cost least-squares problem in a reduced-order subspace identified via Proper Orthogonal Decomposition (POD). Numerical experiments on classical pattern-forming systems–including the Schnakenberg and Mimura–Tsujikawa models–demonstrate that higher-order surrogate models significantly improve prediction accuracy while maintaining low computational cost. The proposed method provides a flexible, non-intrusive model reduction framework, well suited for the analysis of complex spatio-temporal pattern formation phenomena.

Data-driven modeling↗
NASA NTRS2017

Iterative Discrete Ordinates Solution of the Equation for the Surface-Reflected Radiance

This paper presents a new method of numerical solution of the integral equation for the radiance reflected from an anisotropic surface. The equation relates the radiance at the surface level with BRDF and solutions of the standard radiative transfer problems for a slab with no reflection on its surfaces. It is also shown that the kernel of the equation satisfies the condition of the existence of a unique solution and the convergence of the successive approximations to that solution. The developed method features two basic steps: discretization on a 2D quadrature, and solving the resulting system of algebraic equations with successive over-relaxation method based on the Gauss-Seidel iterative process. Presented numerical examples show good coincidence between the surface-reflected radiance obtained with DISORT and the proposed method. Analysis of contributions of the direct and diffuse (but not yet reflected) parts of the downward radiance to the total solution is performed. Together, they represent a very good initial guess for the iterative process. This fact ensures fast convergence. The numerical evidence is given that the fastest convergence occurs with the relaxation parameter of 1 (no relaxation). An integral equation for BRDF is derived as inversion of the original equation. The potential of this new equation for BRDF retrievals is analyzed. The approach is found not viable as the BRDF equation appears to be an ill-posed problem, and it requires knowledge the surface-reflected radiance on the entire domain of both Sun and viewing zenith angles.

Alexander Radkevich↗
DOE OSTI2022

A multi-resolution approach to hydraulic fracture simulation

Abstract We present a multi-resolution approach for constructing model-based simulations of hydraulic fracturing, wherein flow through porous media is coupled with fluid-driven fracture. The approach consists of a hybrid scheme that couples a discrete crack representation in a global domain to a phase-field representation in a local subdomain near the crack tip. The multi-resolution approach addresses issues such as the computational expense of accurate hydraulic fracture simulations and the difficulties associated with reconstructing crack apertures from diffuse fracture representations. In the global domain, a coupled system of equations for displacements and pressures is considered. The crack geometry is assumed to be fixed and the displacement field is enriched with discontinuous functions. Around the crack tips in the local subdomains, phase-field sub-problems are instantiated on the fly to propagate fractures in arbitrary, mesh independent directions. The governing equations and fields in the global and local domains are approximated using a combination of finite-volume and finite element discretizations. The efficacy of the method is illustrated through various benchmark problems in hydraulic fracturing, as well as a new study of fluid-driven crack growth around a stiff inclusion.

58 GEOSCIENCES↗
DOE OSTI2025

Joint state-parameter estimation for the reduced fracture model via the united filter

Here, in this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured porous media. Fluid flow and transport in fractured porous media are critical in subsurface hydrology, geophysics, and reservoir geomechanics. Reduced fracture models, which represent fractures as lower-dimensional interfaces, enable efficient multi-scale simulations. However, reduced fracture models also face accuracy challenges due to modeling errors and uncertainties in physical parameters such as permeability and fracture geometry. To address these challenges, we propose a United Filter method, which integrates the Ensemble Score Filter (EnSF) for state estimation with the Direct Filter for parameter estimation. EnSF, based on a score-based diffusion model framework, produces ensemble representations of the state distribution without deep learning. Meanwhile, the Direct Filter, a recursive Bayesian inference method, estimates parameters directly from state observations. The United Filter combines these methods iteratively: EnSF estimates are used to refine parameter values, which are then fed back to improve state estimation. Numerical experiments demonstrate that the United Filter method surpasses the state-of-the-art Augmented Ensemble Kalman Filter, delivering more accurate state and parameter estimation for reduced fracture models. This framework also provides a robust and efficient solution for PDE-constrained inverse problems with uncertainties and sparse observations.

Bayesian inference↗