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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Analysis of an advanced ducted propeller subsonic inlet

A time marching Navier-Stokes code called PARC (PARC2D for 2-D/axisymmetric and PARC3D for 3-D flow simulations) was validated for an advanced ducted propeller (ADP) subsonic inlet. The code validation for an advanced ducted propeller (ADP) subsonic inlet. The code validation was implemented for a non-separated flow condition associated with the inlet operating at angles-of-attack of 0 and 25 degrees. The inlet test data were obtained in the 9 x 15 ft Low Speed Wind Tunnel at NASA Lewis Research Center as part of a cooperative study with Pratt and Whitney. The experimental study focused on the ADP inlet performance for take-off and approach conditions. The inlet was tested at a free stream Mach number of 0.2, at angles-of-attack between O and 35 degrees, and at a maximum propeller speed of 12,000 RPM which induced a corrected air flow rate of about 46 lb/sec based on standard day conditions. The computational grid and flow boundary conditions (BC) were based on the actual inlet geometry and the funnel flow conditions. At the propeller face, two types of BC's were applied: a mass flow BC and a fixed flow properties BC. The fixed flow properties BC was based on a combination of data obtained from the experiment and calculations using a potential flow code. Comparison of the computational results with the test data indicates that the PARC code with the propeller face fixed flow properties BC provided a better prediction of the inlet surface static pressures than the predictions when the mass flow BC was used. For an angle-of-attack of 0 degrees, the PARC2D code with the propeller face mass flow BC provided a good prediction of inlet static pressures except in the region of high pressure gradient. With the propeller face fixed flow properties BC, the PARC2D code provided a good prediction of the inlet static pressures. For an angle-of-attack of 25 degrees with the mass flow BC, the PARC3D code predicted statis pressures which deviated significantly from the test data; however, with the fixed flow properties BC, a good comparison with the test data was obtained.

Iek, Chanthy↗
NASA NTRS2011

Base Heating Sensitivity Study for a 4-Cluster Rocket Motor Configuration in Supersonic Freestream

In support of launch vehicle base heating and pressure prediction efforts using the Loci-CHEM Navier-Stokes computational fluid dynamics solver, 35 numerical simulations of the NASA TND-1093 wind tunnel test have been modeled and analyzed. This test article is composed of four JP-4/LOX 500 lbf rocket motors exhausting into a Mach 2 - 3.5 wind tunnel at various ambient pressure conditions. These water-cooled motors are attached to a base plate of a standard missile forebody. We explore the base heating profiles for fully coupled finite-rate chemistry simulations, one-way coupled RAMP (Reacting And Multiphase Program using Method of Characteristics)-BLIMPJ (Boundary Layer Integral Matrix Program - Jet Version) derived solutions and variable and constant specific heat ratio frozen flow simulations. Variations in turbulence models, temperature boundary conditions and thermodynamic properties of the plume have been investigated at two ambient pressure conditions: 255 lb/sq ft (simulated low altitude) and 35 lb/sq ft (simulated high altitude). It is observed that the convective base heat flux and base temperature are most sensitive to the nozzle inner wall thermal boundary layer profile which is dependent on the wall temperature, boundary layer s specific energy and chemical reactions. Recovery shock dynamics and afterburning significantly influences convective base heating. Turbulence models and external nozzle wall thermal boundary layer profiles show less sensitivity to base heating characteristics. Base heating rates are validated for the highest fidelity solutions which show an agreement within +/-10% with respect to test data.

Mehta, Manish↗
DOE OSTI2015

Sandia National Laboratories Environmental Fluid Dynamics Code V. 1 0.0 (Beta)

The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around MHK arrays while quantifying environmental responses. As an augmented version of US EPA's Environmental Fluid Dynamics Code (EFDC), SNL-EFDC includes: (1) a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate, (2) new, advanced sediment dynamics routines, and (3) augmented water quality modules.

Source record↗
DOE OSTI2021

Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media

Abstract The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ( $$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaView plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.

42 ENGINEERING↗
DOE OSTI2018

Analysis of Solids Flow Rate through Nonmechanical L-Valve in an Industrial-Scale Circulating Fluidized Bed Using Group B Particles

A series of statistically designed experiments were conducted using two different Geldart Group B particles in a 0.3 m diameter circulating fluidized bed (CFB) cold model to evaluate the nonmechanical L-valve for controlling the solids flow rate. The objective of this study was to investigate the effects of standpipe aeration, L-valve aeration, solids inventory, and superficial gas velocity through the riser on the solids flow rate. A stochastic correlation was developed for calculating the solid flow rate as a function of these variables. It was found that the solid flow rate increased directly proportional to each of these variables. Dimensional analysis was used to generate an expression for the solids turnover ratio. The model developed in the present study is intended to simulate flow in the present CFB loop. In conclusion, it is not intended for scale-up and will probably not apply for alternative CFB loops with different geometries/pressure balance conditions.

42 ENGINEERING↗
DOE OSTI2016

Delft3D turbine turbulence module

The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares’s, environmental hydrodynamics code, Delft3D, SNL-Delft3D includes a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate.

Chartrand, Chris↗
DOE OSTI2016

Delft3D turbine turbulence module

The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares’s, environmental hydrodynamics code, Delft3D, SNL-Delft3D includes a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate.

Chartrand, Chris↗
NASA NTRS1987

Relations between two-point correlations and pressure strain terms

The structure of the two-point spatial correlations (velocity-velocity, velocity-scalar, and scalar-scalar) were studied with a view to improve turbulence closure models. The linear model for the two-point correlations proposed by Naot provides a method of including the information about the turbulence structure in the turbulence models. The assumptions and adequacy of this model were tested against the homogeneous shear flow simulation data base. The model performs poorly in some details and it is suggested how it may be improved. The models were also tested for rapid pressure-strain terms in a variety of flows including axisymmetric expansion and contraction flows, homogeneous shear flow, channel flow, and boundary layer.

Wolfshtein, Micha↗
NASA NTRS1997

A Geometry Based Infra-structure for Computational Analysis and Design

The computational steps traditionally taken for most engineering analysis (CFD, structural analysis, and etc.) are: Surface Generation - usually by employing a CAD system; Grid Generation - preparing the volume for the simulation; Flow Solver - producing the results at the specified operational point; and Post-processing Visualization - interactively attempting to understand the results For structural analysis, integrated systems can be obtained from a number of commercial vendors. For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. Specifically the problems with this procedure are: (1) File based. Information flows from one step to the next via data files with formats specified for that procedure. (2) 'Good' Geometry. A bottleneck in getting results from a solver is the construction of proper geometry to be fed to the grid generator. With 'good' geometry a grid can be constructed in tens of minutes (even with a complex configuration) using unstructured techniques. (3) One-Way communication. All information travels on from one phase to the next. Until this process can be automated, more complex problems such as multi-disciplinary analysis or using the above procedure for design becomes prohibitive.

Haimes, Robert↗
DOE OSTI2014

An efficient particle Fokker–Planck algorithm for rarefied gas flows

This paper is devoted to the algorithmic improvement and careful analysis of the Fokker–Planck kinetic model derived by Jenny et al. [1] and Gorji et al. [2]. The motivation behind the Fokker–Planck based particle methods is to gain efficiency in low Knudsen rarefied gas flow simulations, where conventional direct simulation Monte Carlo (DSMC) becomes expensive. This can be achieved due to the fact that the resulting model equations are continuous stochastic differential equations in velocity space. Accordingly, the computational particles evolve along independent stochastic paths and thus no collision needs to be calculated. Therefore the computational cost of the solution algorithm becomes independent of the Knudsen number. In the present study, different computational improvements were persuaded in order to augment the method, including an accurate time integration scheme, local time stepping and noise reduction. For assessment of the performance, gas flow around a cylinder and lid driven cavity flow were studied. Convergence rates, accuracy and computational costs were compared with respect to DSMC for a range of Knudsen numbers (from hydrodynamic regime up to above one). In all the considered cases, the model together with the proposed scheme give rise to very efficient yet accurate solution algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

TOUGH-RFPA: Coupled thermal-hydraulic-mechanical Rock Failure Process Analysis with application to deep geothermal wells

This paper presents a coupled thermal-hydraulic-mechanical (THM) model for simulating failure processes in geological media. The coupling between stress/strain and heat transfer describing how thermal expansion affects stress is based on the theory of thermo-elasticity. Additionally, the coupling between stress/strain and fluid flow describing how pore-pressure affects stress is governed by Biot's consolidation theory. Stress/strain-dependent porosity/permeability/capillary-pressure defines the influence of stress on fluid flow and thermal fields. The THM model is implemented in the solver module that links the multiphase, multicomponent fluid flow simulator TOUGH2 with the geomechanical simulator RFPA (Rock Failure Process Analysis), which is based on the concept that heterogeneity leads to non-linearity and progressive failure behavior. Capability of TOUGH-RFPA simulator was verified by two benchmark problems related to hydraulic-mechanical and thermal-mechanical response in a hollow cylinder. Then the applicability of TOUGH-RFPA was demonstrated for modeling cooling-induced damage around a very deep geothermal well with mesoscopic heterogeneous properties, which showed complex damage evolution and fracturing during well cooling and fluid pressurization.

42 ENGINEERING↗
DOE OSTI2022

A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019

Abstract This article presents a hydrological reconstruction of the Upper Colorado River Basin with an hourly temporal resolution, and 1-km spatial resolution from October 1982 to September 2019. The validated dataset includes a suite of hydrologic variables including streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) simulated by an integrated hydrological model, ParFlow-CLM. The dataset was validated over the period with a combination of point observations and remotely sensed products. These datasets provide a long-term, natural-flow, simulation for one of the most over-allocated basins in the world.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Numerical simulations of the flow in the HYPULSE expansion tube

Axisymmetric numerical simulations with finite-rate chemistry are presented for two operating conditions in the HYPULSE expansion tube. The operating gas for these two cases is nitrogen and the computations are compared to experimental data. One test condition is at a total enthalpy of 15.2 MJ/Kg and a relatively low static pressure of 2 kPa. This case is characterized by a laminar boundary layer and significant chemical nonequilibrium in the acceleration gas. The second test condition is at a total enthalpy of 10.2 MJ/Kg and a static pressure of 38 kPa and is characterized by a turbulent boundary layer. For both cases, the time-varying test gas pressure predicted by the simulations is in good agreement with experimental data. The computations are also found to be in good agreement with Mirels' correlations for shock tube flow. It is shown that the nonuniformity of the test gas observed in the HYPULSE expansion tube is strongly linked to the boundary layer thickness. The turbulent flow investigated has a larger boundary layer and greater test gas nonuniformity. In order to investigate possibilities of improving expansion tube flow quality by reducing the boundary layer thickness, parametric studies showing the effect of density and turbulent transition point on the test conditions are also presented. Although an increase in the expansion tube operating pressure level would reduce the boundary layer thickness, the simulations indicate that the reduction would be less than what is predicted by flat plate boundary layer correlations.

Wilson, Gregory J.↗
DOE OSTI2024

Artificial Intelligence-Aided Wind Plant Optimization for Nationwide Evaluation of Land Use and Economic Benefits of Wake Steering

If clean energy pathways are to harness massive increases in wind power, innovations with broad geographic viability will be needed to support buildout in diverse locations. However, geodiversity in impact potential is seldom captured in technology assessment. Here we propose a scalable approach to plant-level optimization using artificial intelligence to evaluate land sparing and economic benefits of wake steering at more than 6,800 plausible onshore wind locations in the USA. This emerging controls strategy optimizes plant energy production by directing turbine wakes. On the basis of estimates from our artificial intelligence model trained on engineering wind flow simulations, co-optimizing plant layouts with wake steering can reduce land requirements by an average of 18% per plant (site-specific benefits range from 2% to 34%), subject to errors and uncertainties in the flow model, wind resource estimates, buildout scenario and geographic factors. According to model estimates, wake steering is predicted to increase power production during high-value (relatively low wind) periods, boosting the annual revenue of individual plants by up to US$3.7 million (equivalent to US$13,000 MW-1 yr-1) but producing negligible gains in some settings. Consideration of wake steering’s geographic potential reveals divergent nationwide prospects for improved economics and siting flexibility.

deployment↗
DOE OSTI2019

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time, however tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This work develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions and Gaussian injections in particular. Furthermore, our algorithm applies to the practical case of unbalanced three-phase power flow. The performance is validated on AC power flow simulations over three phase IEEE distribution grid test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Parallel Element Agglomeration Multilevel Monte Carlo Library (ParELAGMC)

ParELAGMC is a parallel distributed memory C++ library for multilevel Monte Carlo (MLMC) simulations with algebraically constructed coarse spaces for estimating statistical moments of a quantity of interest involving solutions of partial differential equations with uncertain coefficients. A primary focus of the library is the scalable generation of Gaussian random fields using a novel stochastic PDE (SPDE) sampling technique for large-scale simulations. A key feature in the SPDE sampling technique is a novel non-matching mesh embedding technique to mitigate artificial boundary artifacts that are inherent in the method. Example applications to uncertainty quantification of subsurface flow simulations in the mixed finite element setting are provided as well.

Osborn, SarahV.↗