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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Machine Learning Models of Plastic Flow Based on Representation Theory

We use machine learning (ML) to infer stress and plastic flow rules using data from representative polycrystalline simulations. In particular, we use so-called deep (multilayer) neural networks (NN) to represent the two response functions. The ML process does not choose appropriate inputs or outputs, rather it is trained on selected inputs and output. Likewise, its discrimination of features is crucially connected to the chosen input-output map. Furthermore, we draw upon classical constitutive modeling to select inputs and enforce well-accepted symmetries and other properties. With these developments, we enable rapid model building in real-time with experiments, and guide data collection and feature discovery.

42 ENGINEERING↗
NASA NTRS1995

Instantaneous 2D Velocity and Temperature Measurements in High Speed Flows Based on Spectrally Resolved Molecular Rayleigh Scattering

A Rayleigh scattering diagnostic for high speed flows is described for the simultaneous, instantaneous measurement of gas temperature and velocity at a number (up to about one hundred) of locations in a plane illuminated by an injection-seeded, frequency doubled Nd:YAG laser. Molecular Rayleigh scattered light is collected and passed through a planar mirror Fabry-Perot interferometer. The resulting image is analyzed to determine the gas temperature and bulk velocity at each of the regions. The Cramer Rao lower bound for measurement uncertainty is calculated. Experimental data is presented for a free jet and for preliminary measurements in the Lewis 4 inch by 10 inch supersonic wind tunnel.

Seasholtz, Richard G.↗
DOE OSTI2023

Topological Relationship-Based Flow Direction Modeling: Stream Burning and Depression Filling

Flow direction modeling consists of (a) an accurate representation of the river network and (b) digital elevation model (DEM) processing to preserve characteristics with hydrological significance. In part 1 of our study, we presented a mesh-independent approach to representing river networks on different types of meshes. This follow-up part 2 study presents a novel DEM processing approach for flow direction modeling. This approach consists of (a) a topological relationship-based hybrid breaching-filling method to conduct stream burning for the river network and (b) a modified depression removal method for rivers and hillslopes. Our methods reduce modifications to surface elevations and provide a robust two-step procedure to remove local depressions in DEM. They are mesh-independent and can be applied to both structured and unstructured meshes. We applied our new methods with different model configurations to the Susquehanna River Basin. The results show that topological relationship-based stream burning, and depression-filling methods can reproduce the correct river networks, providing high-quality flow direction and other characteristics for hydrologic and Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Topological Relationship–Based Flow Direction Modeling: Mesh–Independent River Networks Representation

River networks are important features in surface hydrology. However, accurately representing river networks in spatially distributed hydrologic and Earth system models is often sensitive to the model's spatial resolution. Specifically, river networks are often misrepresented because of the mismatch between the model's spatial resolution and river network details, resulting in significant uncertainty in the projected flow direction. In this study, we developed a topological relationship-based river network representation method for spatially distributed hydrologic models. This novel method uses (a) graph theory algorithms to simplify real-world vector-based river networks and assist in mesh generation; and (b) a topological relationship-based method to reconstruct conceptual river networks. The main advantages of our method are that (a) it combines the strengths of vector-based and DEM raster-based river network extraction methods; and (b) it is mesh-independent and can be applied to both structured and unstructured meshes. This method paves a path for advanced terrain analysis and hydrologic modeling across different scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A higher‐order unsplit 2D direct Eulerian finite volume method for two‐material compressible flows based on the MOOD paradigms

SUMMARY A higher‐order unsplit multi‐dimensional discretization of the diffuse interface model for two‐material compressible flows proposed by R. Saurel, F. Petitpas and R. A. Berry in 2009 is developed. The proposed higher‐order method is based on the concepts of the Multidimensional Optimal Order Detection (MOOD) method introduced in three recent papers for single‐material flows. The first‐order unsplit multi‐dimensional Finite Volume discretization presented by SPB serves as foundation for the development of the higher‐order unlimited schemes. Specific detection criteria along with a novel decrementing algorithm for the MOOD method are designed in order to deal with the complexity of multi‐material flows. Numerically, we compare errors and computational times on several 1D problems (stringent shock tube and cavitation problems) computed on 2D meshes with the second‐ and fourth‐order MOOD methods using a classical MUSCL method as reference. Several simulations of a 2D shocked R22 bubble in the air are also presented on Cartesian and unstructured meshes with the second‐ and fourth‐order MOOD methods, and qualitative comparisons confirm the conclusions obtained with 1D problems. These numerical results demonstrate the robustness of the MOOD approach and the interest of using more than second‐order methods even for locally singular solutions of complex physics models. Copyright © 2014 John Wiley & Sons, Ltd.

Diot, S.↗
DOE OSTI2022

Advances in hexagon mesh-based flow direction modeling

Watershed delineation and flow direction representation are the foundations of streamflow routing in spatially distributed hydrologic modeling. A recent study showed that hexagon-based watershed discretization has several advantages compared to the traditional Cartesian (latitude–longitude) discretization, such as uniform connectivity and compatibility with other Earth system model components based on unstructured mesh systems (e.g., oceanic models). Despite these advantages, hexagon-based discretization has not been widely adopted by the current generation of hydrologic models. One major reason is that there is no existing model that can delineate hexagon-based watersheds while maintaining accurate representations of flow direction across various spatial resolutions. In this study, we explored approaches such as spatial resampling and hybrid breaching-filling stream burning techniques to improve watershed delineation and flow direction representation using a newly developed hexagonal mesh watershed delineation model (HexWatershed). We applied these improvements to the Columbia River basin and performed 16 simulations with different configurations. The results show that (1) spatial resampling modulates flow direction around headwaters and provides an opportunity to extract subgrid information; and (2) stream burning corrects the flow directions in mountainous areas with complex terrain features.

58 GEOSCIENCES↗
DOE OSTI2013

Adding Complex Terrain and Stable Atmospheric Condition Capability to the OpenFOAM-based Flow Solver of the Simulator for On/Offshore Wind Farm Applications (SOWFA): Preprint

This paper describes changes made to NREL's OpenFOAM-based wind plant aerodynamics solver such that it can compute the stably stratified atmospheric boundary layer and flow over terrain. Background about the flow solver, the Simulator for Off/Onshore Wind Farm Applications (SOWFA) is given, followed by details of the stable stratification/complex terrain modifications to SOWFA, along with somepreliminary results calculations of a stable atmospheric boundary layer and flow over a simply set of hills.

17 WIND ENERGY↗
NASA NTRS2010

Base Flow and Heat Transfer Characteristics of a Four-Nozzle Clustered Rocket Engine: Effect of Nozzle Pressure Ratio

The base pressure and heating characteristics of a four-nozzle clustered rocket configuration is studied numerically with the aid of OVERFLOW Navier-Stokes code. A pressure ratio (chamber pressure to freestream static pressure) range of 990 to 5,920 and a freestream Mach number range of 2.5 to 3.5 are studied. The qualitative trends of decreasing base pressure with increasing pressure ratio and increasing base heat flux with increasing pressure ratio are correctly predicted. However, the predictions for base pressure and base heat flux show deviations from the wind tunnel data. The differences in absolute values between the computation and the data are attributed to factors such as perfect gas (thermally and calorically perfect) assumption, turbulence model inaccuracies in the simulation, and lack of grid adaptation.

Nallasamy, R.↗
NASA NTRS2011

Enthalpy Distributions of Arc Jet Flow Based on Measured Laser Induced Fluorescence, Heat Flux and Stagnation Pressure Distributions

The centerline total enthalpy of arc jet flow is determined using laser induced fluorescence of oxygen and nitrogen atoms. Each component of the energy, kinetic, thermal, and chemical can be determined from LIF measurements. Additionally, enthalpy distributions are inferred from heat flux and pressure probe distribution measurements using an engineering formula. Average enthalpies are determined by integration over the radius of the jet flow, assuming constant mass flux and a mass flux distribution estimated from computational fluid dynamics calculations at similar arc jet conditions. The trends show favorable agreement, but there is an uncertainty that relates to the multiple individual measurements and assumptions inherent in LIF measurements.

Suess, Leonard E.↗
NASA NTRS1973

Experimental study of supersonic laminar base flow with and without suction

Heat-transfer and pressure distributions in laminar separated flows downstream of rearward-facing steps with and without mass suction were investigated at Mach numbers around 4 for the conditions when the boundary-layer thickness was comparable to or larger than the step height. In both suction and no-suction cases, an increase of the step height resulted in a sharp drop of the base heating rates, which then gradually recovered to less than or near attached-flow values obtained with flat-plate configuration. Mass suction from the step base area increased the local heating rates; this effect, however, was relatively weak for laminar flows tested, and the competing effect of the step height clearly predominated. It was found that even removal of the entire incoming boundary layer was not sufficient to raise the poststep heating rates above the flat-plate values. The base pressure in the no-suction, solid-step case correlated reasonably well with the step height-to-boundary-layer thickness ratio and with the Reynolds number based on the step height.

Jakubowski, A. K.↗
DOE OSTI2024

Redox Activity Modulation in Extended Fluorenone-Based Flow Battery Electrolytes with π-π Stacking Effect

Redox flow battery shows promise for grid-scale energy storage. Aqueous organic redox flow batteries are particularly popular due to their potentially low material cost and safe water-based electrolyte. Commonly, redox active molecules used in this field feature aromatic rings, and increasing π-aromatic conjugation has been a popular strategy to achieve high energy density, high power density, and reduced crossover in new material design. However, this approach can inadvertently hinder redox activity depending on redox mechanism. This study reveals the underlying π-π stacking effect in extended aromatic redox active compounds, where aromatic radical intermediates are involved in the redox process. We report a molecular design strategy to mitigate the negative effect of π-π stacking by altering solvation dynamics and introducing molecular steric hindrance.

25 ENERGY STORAGE↗
DOE OSTI2018

Numerical Modeling of Gas-Liquid Compressible Pipe Flow Based on the Theory of Thermodynamically Compatible Systems

Based on the theory of thermodynamically compatible systems, we formulate the governing equations of a gas-liquid compressible pipe flow and develop the Runge–Kutta–TVD and Runge–Kutta–WENO high accuracy methods. The computational model is used to solve a series of test cases demonstrating its efficiency and capability to be applied to slug flows modeling.

42 ENGINEERING↗
DOE OSTI2018

Inverse Normalization Method for Cross-Sectional Imaging and Velocimetry of Two-Phase Flows Based on Electrical Capacitance Tomography

Proper normalization of the measured capacitance data is a prerequisite in electrical capacitance tomography (ECT). Conventional methods, such as parallel and series normalization, assume a higher permittivity perturbation in a homogeneous (lower) permittivity background. Although this is applicable to a number of cases, some two-phase flows are better modeled instead as a lower permittivity perturbation in a homogeneous (higher) permittivity background. A different normalization method is proposed for such cases, which provides similar image quality as conventional, but is particularly beneficial for velocimetry applications based on sensitivity gradient of ECT sensor. Furthermore, simulation and experimental results are provided to illustrate the advantages for the proposed normalization technique.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

2D velocity and temperature measurements in high speed flows based on spectrally resolved Rayleigh scattering

The use of molecular Rayleigh scattering for measurements of gas velocity and temperature is evaluated. Molecular scattering avoids problems associated with the seeding required by conventional laser anemometry and particle image velocimetry. The technique considered herein is based on the measurement of the spectrum of the scattered light. Planar imaging of Rayleigh scattering using a laser light sheet is evaluated for conditions at 30 km altitude (typical hypersonic flow conditions). The Cramer-Rao lower bounds for velocity and temperature measurement uncertainties are calculated for an ideal optical spectrum analyzer and for a planar mirror Fabry-Perot interferometer used in a static, imaging mode. With this technique, a single image of the Rayleigh scattered light from clean flows can be analyzed to obtain temperature and one component of velocity. Experimental results are presented for planar velocity measurements in a Mach 1.3 air jet.

Seasholtz, Richard G.↗
DOE OSTI2021

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2016

Space Launch System Base Heating Test: Environments and Base Flow Physics

The NASA Space Launch System (SLS) vehicle is composed of four RS-25 liquid oxygen- hydrogen rocket engines in the core-stage and two 5-segment solid rocket boosters and as a result six hot supersonic plumes interact within the aft section of the vehicle during ight. Due to the complex nature of rocket plume-induced ows within the launch vehicle base during ascent and a new vehicle con guration, sub-scale wind tunnel testing is required to reduce SLS base convective environment uncertainty and design risk levels. This hot- re test program was conducted at the CUBRC Large Energy National Shock (LENS) II short-duration test facility to simulate ight from altitudes of 50 kft to 210 kft. The test program is a challenging and innovative e ort that has not been attempted in 40+ years for a NASA vehicle. This presentation discusses the various trends of base convective heat ux and pressure as a function of altitude at various locations within the core-stage and booster base regions of the two-percent SLS wind tunnel model. In-depth understanding of the base ow physics is presented using the test data, infrared high-speed imaging and theory. The normalized test design environments are compared to various NASA semi- empirical numerical models to determine exceedance and conservatism of the ight scaled test-derived base design environments. Brief discussion of thermal impact to the launch vehicle base components is also presented.

Mehta, Manish↗
DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗