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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Semi-Analytic Reconstruction of Flux in Finite Volume Formulations

Semi-analytic reconstruction uses the analytic solution to a second-order, steady, ordinary differential equation (ODE) to simultaneously evaluate the convective and diffusive flux at all interfaces of a finite volume formulation. The second-order ODE is itself a linearized approximation to the governing first- and second- order partial differential equation conservation laws. Thus, semi-analytic reconstruction defines a family of formulations for finite volume interface fluxes using analytic solutions to approximating equations. Limiters are not applied in a conventional sense; rather, diffusivity is adjusted in the vicinity of changes in sign of eigenvalues in order to achieve a sufficiently small cell Reynolds number in the analytic formulation across critical points. Several approaches for application of semi-analytic reconstruction for the solution of one-dimensional scalar equations are introduced. Results are compared with exact analytic solutions to Burger s Equation as well as a conventional, upwind discretization using Roe s method. One approach, the end-point wave speed (EPWS) approximation, is further developed for more complex applications. One-dimensional vector equations are tested on a quasi one-dimensional nozzle application. The EPWS algorithm has a more compact difference stencil than Roe s algorithm but reconstruction time is approximately a factor of four larger than for Roe. Though both are second-order accurate schemes, Roe s method approaches a grid converged solution with fewer grid points. Reconstruction of flux in the context of multi-dimensional, vector conservation laws including effects of thermochemical nonequilibrium in the Navier-Stokes equations is developed.

Gnoffo, Peter A.↗
DOE OSTI2024

Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning

The deep operator network (DeepONet) has shown remarkable potential in solving partial differential equations (PDEs) by mapping between infinite-dimensional function spaces using labeled datasets. However, in scenarios lacking labeled data, the physics-informed DeepONet (PI-DeepONet) approach, which utilizes the residual loss of the governing PDE to optimize the network parameters, faces significant computational challenges, particularly due to the curse of dimensionality. This limitation has hindered its application to high-dimensional problems, making even standard 3D spatial with 1D temporal problems computationally prohibitive. Additionally, the computational requirement increases exponentially with the discretization density of the domain. Here, to address these challenges and enhance scalability for high-dimensional PDEs, we introduce the Separable physics-informed DeepONet (Sep-PI-DeepONet). This framework employs a factorization technique, utilizing sub-networks for individual one-dimensional coordinates, thereby reducing the number of forward passes and the size of the Jacobian matrix required for gradient computations. By incorporating forward-mode automatic differentiation (AD), we further optimize computational efficiency, achieving linear scaling of computational cost with discretization density and dimensionality, making our approach highly suitable for high-dimensional PDEs. We demonstrate the effectiveness of Sep-PI-DeepONet through three benchmark PDE models: the viscous Burgers’ equation, Biot’s consolidation theory, and a parameterized heat equation. Our framework maintains accuracy comparable to the conventional PI-DeepONet while reducing training time by two orders of magnitude. Notably, for the heat equation solved as a 4D problem, the conventional PI-DeepONet was computationally infeasible (estimated 289.35 h), while the Sep-PI-DeepONet completed training in just 2.5 h. These results underscore the potential of Sep-PI-DeepONet in efficiently solving complex, high-dimensional PDEs, marking a significant advancement in physics-informed machine learning.

Neural operator↗
NASA NTRS1988

Autonomous control systems - Architecture and fundamental issues

A hierarchical functional autonomous controller architecture is introduced. In particular, the architecture for the control of future space vehicles is described in detail; it is designed to ensure the autonomous operation of the control system and it allows interaction with the pilot and crew/ground station, and the systems on board the autonomous vehicle. The fundamental issues in autonomous control system modeling and analysis are discussed. It is proposed to utilize a hybrid approach to modeling and analysis of autonomous systems. This will incorporate conventional control methods based on differential equations and techniques for the analysis of systems described with a symbolic formalism. In this way, the theory of conventional control can be fully utilized. It is stressed that autonomy is the design requirement and intelligent control methods appear at present, to offer some of the necessary tools to achieve autonomy. A conventional approach may evolve and replace some or all of the `intelligent' functions. It is shown that in addition to conventional controllers, the autonomous control system incorporates planning, learning, and FDI (fault detection and identification).

Antsaklis, P. J.↗
NASA NTRS1977

Theory of viscous transonic flow over airfoils at high Reynolds number

This paper considers viscous flows with unseparated turbulent boundary layers over two-dimensional airfoils at transonic speeds. Conventional theoretical methods are based on boundary layer formulations which do not account for the effect of the curved wake and static pressure variations across the boundary layer in the trailing edge region. In this investigation an extended viscous theory is developed that accounts for both effects. The theory is based on a rational analysis of the strong turbulent interaction at airfoil trailing edges. The method of matched asymptotic expansions is employed to develop formal series solutions of the full Reynolds equations in the limit of Reynolds numbers tending to infinity. Procedures are developed for combining the local trailing edge solution with numerical methods for solving the full potential flow and boundary layer equations. Theoretical results indicate that conventional boundary layer methods account for only about 50% of the viscous effect on lift, the remaining contribution arising from wake curvature and normal pressure gradient effects.

Melnik, R. E.↗
DOE OSTI2020

Modelling of nanometer scale dust grains in tokamak

Dust poses a serious threat to tokamak operation and safety. It is important to study the behaviour of dust grains under tokamak's discharge conditions, which depends heavily on their size and charge. Existing simulations mainly address issues on dust grains with radii larger than 1 μm, in which case, the drift effect due to electromagnetic fields can be safely ignored. For nanometer scale dust grains, however, the drift effect becomes significant and a new model based on guiding-centre system needs to be established. In this work, the NDS has been done under BOUT++ framework. The simulation contains two parts. Part one, NDS evaluates the charging and ablation processes of the dust grains. In the second part, the guiding-centre orbits of dust particles are tracked in tokamak plasmas, whose parameters are obtained from BOUT++, a highly desirable C++ code package for performing parallel plasma fluid simulations with an arbitrary number of equations in 3D curvilinear coordinates. The orbit of nanodust dynamics is described by guiding centre equations for simplicity, and these equations are numerically solved by conventional fourth-order Runge Kutta method. Simulations provide results such as trajectories and evolutions of dust particles with different sizes and velocities for different tokamak geometries. Results show tungsten dust grains with a radius of a few nanometers launched from outer midplane will oscillate before totally ablated in C-Mod. The oscillation in this case is driven by the ion drag force. Larger Nanodust with a radius of 100 nm, on the contrary, cannot be completely constrained by the electromagnetic field. In conclusion, the high plasma temperature and density in the seperatrix region causes severe dust ablation, resulting in total ablation within several ms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Integrating deep neural networks with full-waveform inversion: Reparameterization, regularization, and uncertainty quantification

Full-waveform inversion (FWI) is an accurate imaging approach for modeling the velocity structure by minimizing the misfit between recorded and predicted seismic waveforms. However, the strong nonlinearity of FWI resulting from fitting oscillatory waveforms can trap the optimization in local minima. We have adopted a neural-network-based full-waveform inversion (NNFWI) method that integrates deep neural networks with FWI by representing the velocity model with a generative neural network. Neural networks can naturally introduce spatial correlations as regularization to the generated velocity model, which suppresses noise in the gradients and mitigates local minima. Furthermore, the velocity model generated by neural networks is input to the same partial differential equation (PDE) solvers used in conventional FWI. The gradients of the neural networks and PDEs are calculated using automatic differentiation, which back propagates gradients through the acoustic PDEs and neural network layers to update the weights of the generative neural network. Experiments on 1D velocity models, the Marmousi model, and the 2004 BP model determine that NNFWI can mitigate local minima, especially for imaging high-contrast features such as salt bodies, and it significantly improves the inversion in the presence of noise. Adding dropout layers to the neural network model also allows analyzing the uncertainty of the inversion results through Monte Carlo dropout. NNFWI opens a new pathway to combine deep learning and FWI for exploiting the characteristics of deep neural networks and the high accuracy of PDE solvers. Because NNFWI does not require extra training data and optimization loops, it provides an attractive and straightforward alternative to conventional FWI.

58 GEOSCIENCES↗
NASA NTRS1974

Method for determining thermo-physical properties of specimens

The square root of the product of thermophysical properties q, c and k, where p is density, c is specific heat and k is thermal conductivity, is determined directly on a test specimen such as a wind tunnel model. The test specimen and a reference specimen of known specific heat are positioned at a given distance from a heat source. The specimens are provided with a coating, such as a phase change coating, to visually indicate that a given temperature was reached. A shutter interposed between the heat source and the specimens is opened and a motion picture camera is actuated to provide a time record of the heating step. The temperature of the reference specimen is recorded as a function of time. The heat rate to which both the test and reference specimens were subjected is determined from the temperature time response of the reference specimen by the conventional thin-skin calorimeter equation.

Jones, R. A.↗
NASA NTRS1974

Space and velocity focusing in time-of-flight mass spectrometers

A focusing equation is developed describing the relationship between space and velocity focusing for all one-dimensional time-of-flight mass spectrometers with constant electric fields. As a result of this equation, first-order double time focusing in one dimension is impossible. The possibility of large improvements in the resolving power of the time-of-flight mass spectrometers is discussed on this basis. The focusing equation also leads to an expression for the minimum time resolution obtainable. This second equation is applied to the conventional Wiley and McLaren (1955) two-field time-of-flight mass spectrometer with and without time-lag focusing, and to the mirror instrument of Karataev et al. (1972).

Stein, R.↗
NASA NTRS1982

Environmental solid particle effects on compressor cascade performance

The effect of suspended solid particles on the performance of the compressor cascade was investigated experimentally in a specially built cascade tunnel, using quartz sand particles. The cascades were made of NACA 65(10)10 airfoils. Three cascades were tested, one accelerating cascade and two diffusing cascades. The theoretical analysis assumes inviscid and incompressible two dimensional flow. The momentum exchange between the fluid and the particle is accounted for by the interphase force terms in the fluid momentum equation. The modified fluid phase momentum equations and the continuity equation are reduced to the conventional stream function vorticity formulation. The method treats the fluid phase in the Eulerian system and the particle phase in Lagrangian system. The experimental results indicate a small increase in the blade surface static pressures, while the theoretical results indicate a small decrease. The theoretical analysis, also predicts the loss in total pressure associated with the particulate flow through the cascade.

Tabakoff, W.↗
NASA NTRS1983

Effect of particle presence on the incompressible inviscid flow through a two dimensional compressor cascade

A computational model for calculating the flow field, in the presence of solid particles, through a two dimensional compressor cascade is presented. The method treats the particle phase in the Lagrangian system and the fluid phase in the Eulerian system. The equations of momentum of the fluid phase are modified to account for the momentum exchange between the two phases. The resulting modified momentum and continuity equations are reduced to the conventional stream function-vorticity formulation. The analysis yields the change in the blade surface pressure distribution, the total pressure and velocity in the flow field. Based on this, it is possible to predict the decrease in compressor performance under the presence of particles.

Balan, C.↗
NASA NTRS1986

Experiments on supersonic turbulent flow development in a square duct

The nature of supersonic, turbulent, adiabatic-wall flow in a square duct is investigated experimentally over a development length of x/D between 0 and 20 for a uniform flow, Mach 3.9 condition at the duct inlet. Initial discussion centers on the duct configuration itself, which was designed specifically to minimize wave effects and nozzle-induced distortion in the flow. Total pressure contours and local skin friction coefficient distributions are presented which show that the flow develops in a manner similar to that observed for the incompressible case. In particular, undulations exist in total pressure contours within the cross plane and in transverse skin friction coefficient distributions, which are indicative of the presence of a well-defined secondary flow superimposed upon the primary flow. The results are analyzed to show that local law-of-the-wall behavior extends well into the corner region, which implies that wall functions conventionally applied in two-equation type turbulence models, when suitably defined for compressible flow, may also be applied to supersonic streamwise corner flows.

Gessner, F. B.↗
NASA NTRS1993

Development of a gridless CFD method

The objective of this paper is to stimulate ideas concerning alternative approaches to discretizing fluid flow problems, i.e., the so-called gridless approach. The gridless approach uses only clouds of points and does not require that the points be connected to form a grid as is necessary in conventional CFD algorithms. The governing equations are solved directly by performing local least-squares curve fits in each cloud of points and then analytically differentiating the resulting curve fits to approximate the derivatives. A discussion of these topics is presented in viewgraph form.

John T Batina↗
NASA NTRS1994

Cluster Computation of Flight Reynolds Number Flows

The performance of a workstation cluster used for the solution of the Reynolds-averaged Navier-Stokes equations is compared with a conventional vector supercomputer architecture. The application simulation of the steady flowfield about a transonic transport was computed using an implicit diagonal scheme in an overset mesh framework. Static load balancing was used, while coarse grain decomposition was achieved by solution of a grid zone per processor. Price/performance ratios are estimated for several scenarios in which such clusters may be utilized.

Atwood, Christopher A.↗
NASA NTRS1978

Transitional Boundary-Layer Solutions Using a Mixing-Length and a Two-Equation Turbulence Model

Boundary-layer solutions were obtained using the conventional two-layer mixing-length turbulence model and the Wilcox-Traci two-equation model of turbulence. Both flatplate and blunt-body geometries were considered. The most significant result of the study is development of approximations for the two-equation model which permit streamwise stepsize comparable to that used in mixing-length computations. Additionally, a set of model-equation boundary conditions derived which apply equally well to both flat-plate and blunt-body geometries. Solutions obtained with the two-equations turbulence model are compared with experimental data and/or corresponding solutions obtained using the mixing-length model. Agreement is satisfactory for flat-plate boundary layers but not for blunt body boundary layers.

Anderson, E. C.↗
NASA NTRS2000

NCC: A Physics-Based Design and Analysis Tool for Combustion Systems

The National Combustion Code (NCC) is an integrated system of computer codes for physics-based design and analysis of combustion systems. It uses unstructured meshes and runs on parallel computing platforms. The NCC is composed of a set of distinct yet closely related modules. They are: (1) a gaseous flow module solving 3-D Navier-Stokes equations; (2) a turbulence module containing the non-linear k-epsilon models; (3) a chemistry module using either the conventional reduced kinetics approach of solving species equations or the Intrinsic Low Dimensional Manifold (ILDM) kinetics approach of table looking up in conjunction with solving the equations of the progressive variables; (4) a turbulence-chemistry interaction module including the option of solving the joint probability density function (PDF) for species and enthalpy; and (5) a spray module for solving the liquid phase equations. In early 1995, an industry-government team was formed to develop the NCC. In July 1998, the baseline beta version was completed and presented in two NCC sessions at the 34th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, July 1998. An overview of this baseline beta version was presented at the NASA HPCCP/CAS Workshop 98, August 1998. Since then, the effort has been focused on the streamlining, validation, and enhancement of the th baseline beta version. The progress is presented in two NCC sessions at the AIAA 38 Aerospace Sciences Meeting & Exhibit, January 2000. At this NASA HPCCP/CAS Workshop 2000, an overview of the NCC papers presented at the AIAA 38 th Aerospace Sciences Meeting & Exhibit is presented, with emphasis on the reduction of analysis time of simulating the (gaseous) reacting flows in full combustors. In addition, results of NCC simulation of a modern turbofan combustor will also be reported.

Liu, Nan-Suey↗
DOE OSTI2020

An extended trajectory-mechanics approach for calculating two-phase flow paths

A technique originating in quantum dynamics is used to derive a trajectory-based, semi-analytical solution for two-phase flow. The partial differential equation governing the evolution of the aqueous phase is equivalent to a family of ordinary differential equations defined along a path through the porous medium. The trajectories may be found by solving the differential equations directly or by post-processing the output of a numerical solution to the full set of governing equations. The trajectories, which differ from conventional streamlines, are found to bend downward in response to gravitational forces. The curvature is more pronounced as the dip of the porous layer containing the flow increases. Subtle changes in the relative permeability curve can lead to significant variations in the trajectories. The ordinary differential equation for the trajectory provides an expression for the travel time along the path. The expression produces a semi-analytical approximation to the model parameter sensitivities, the partial derivatives of the travel times with respect to changes in the permeability model. The semi-analytical trajectory-based sensitivities generally agree with those computed using a numerical reservoir simulator and a perturbation approach. The sensitivities are useful in tomographic imaging algorithms designed to estimate the spatial variation in permeability within a porous medium using multiphase observations.

58 GEOSCIENCES↗
NASA NTRS1976

Differential absorption and scattering sensitivity predictions

A set of general equations for evaluating the sensitivity of the Differential Absorption and Scattering (DAS) technique based upon a conventional analysis of statistical errors is derived. The equations are put in a proper form for evaluating total column density and range resolved concentration measurements of a variety of atmospheric species. The derived equation are subsequently used to analyze the sensitivity of DAS in three specific applications assuming realistic parameters for the optical and electronic components of proposed DAS systems. The three DAS applications evaluated are: (1) measurement of nitrogen at ground levels over a horizontal path; (2) measurement of atmospheric ozone depletion in the wake of a jet engine at 20 km altitude; and (3) measurements of the ozone distribution in the atmosphere from an orbiting space platform, in a downward viewing mode. The results of this study have shown that with reasonable laser energy and telescope receiver dimensions, DAS is capable of meeting requirements for performing these measurements.

Thompson, R. T., Jr.↗
NASA NTRS1989

Vibration of beams and plate strips with three-dimensional flexibility

Studies making use of higher vibration modes and frequencies have indicated a need for a more accurate beam theory. Equations of motion are developed here that give a more accurate representation of the dynamic behavior of a beam than conventional beam theory. Results are obtained using these equations for the natural vibrations of simply-supported aluminum beams of rectangular cross-sections. These results are compared to results from conventional beam theory, and they are examined to identify where various effects are important.

Stein, Manuel↗