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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

The effect of temperature fluctuations of reaction rate constants in turbulent reacting flows

Current models of turbulent reacting flows frequently use Arrhenius reaction rate constants obtained from static or laminar flow theory and/or experiments, or from best fits of static, laminar, and turbulent data. By treating the reaction rate constant as a continuous random variable which is temperature-dependent, the present study assesses the effect of turbulent temperature fluctuations on the reaction rate constant. This model requires that a probability density function (PDF) describing the nature of the fluctuations be specified. Three PDFs are examined: the clipped Gaussian, the beta PDF, and the ramp model. All the models indicate that the reaction rate constant is greater in a turbulent flow field than in an equivalent laminar flow. In addition, an amplification ratio, which is the ratio of the turbulent rate constant to the laminar rate constant, is defined and its behavior as a function of the mean temperature fluctuations is described

Chinitz, W.↗
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗
NASA NTRS1989

Simulation of turbomachinery flows

Significant advancements have been made in the last five years in the ability to model turbomachinery flows of engineering interest. This advancement can be directly attributed to the second generation of supercomputers like the Cray XMP and Cray 2 and advanced instrumentation techniques. Early on, the National Aeronautics and Space Administration Lewis Research Center recognized the potential gains in turbomachinery performance and life that could be achieved by taking advantage of this technology and instituted a comprehensive research program in turbomachinery flow modeling. This activity combined the areas of fluid flow analysis, computational fluid dynamics, and experimental fluid mechanics. As a result of this activity, Lewis has become an internationally recognized leader in turbomachinery flow modeling. Many of the research activities conducted under this program are utilized by industry. The presentation gives an overview of this program and provides sample illustration of simulation performed to date.

Adamczyk, John J.↗
DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
NASA NTRS1992

Transition region modeling for compressible flow

The ongoing effort at NASA Langley Research Center aimed at developing transitional zone models for Reynolds-averaged Navier-Stokes calculations is described. Results from three models that we have examined - two zero-equation models and a two-equation model of the k-omega type - are presented for high-speed flows. The use of analytical and computational tools to provide guidance and to provide the transitional flow-field data bases necessary to develop such models is discussed. Some results from validation of these tools are given; qualitative comparisons between modeled and theoretical/computational representations of the transitional zone are provided.

Chang, C.-L.↗
DOE OSTI2022

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗
DOE OSTI2021

A two-dimensional analytical unit cell model for redox flow battery evaluation and optimization

Cell performance optimization is important for improving the overall system efficiency of a redox flow battery. To gain better insights into key controlling factors of system efficiency, this work first proposed a theoretical model for a unit flow battery cell by extending a two-dimensional analytic model to a full battery cell. Such a model is then used for cell performance optimization after validating it with experimental and numerical modeling data. With the model results, the activation, equilibrium, and pump energy losses are identified as the dominant sources of battery energy losses. Further, a guideline for reducing these sources is also proposed. Following the guideline, the mass transport coefficient is shown as a key control factor of the equilibrium energy loss and Coulombic efficiency (CE). Approaches are then proposed to improve CE and the overall system efficiency. The mass transport is also revealed as the mechanism of pump rate optimization where an optimal pump rate significantly reduces the equilibrium energy loss. With both low equilibrium and pump energy losses, an optimal electrode porosity or specific area design can further improve a battery's system efficiency based on an optimal porosity predicted by the present model. The model also demonstrates distinct behaviors and overestimation in the system efficiency when reduced to a zero-dimensional model with neglected mass transport resistance. With the new model, the guideline, and new insights, this work provides a reliable and efficient tool for the evaluation and optimization of redox flow battery design in practical applications.

25 ENERGY STORAGE↗
NASA NTRS2000

Thermal-Flow Code for Modeling Gas Dynamics and Heat Transfer in Space Shuttle Solid Rocket Motor Joints

A new, thermal-flow simulation code, called SFLOW. has been developed to model the gas dynamics, heat transfer, as well as O-ring and flow path erosion inside the space shuttle solid rocket motor joints by combining SINDA/Glo, a commercial thermal analyzer. and SHARPO, a general-purpose CFD code developed at Thiokol Propulsion. SHARP was modified so that friction, heat transfer, mass addition, as well as minor losses in one-dimensional flow can be taken into account. The pressure, temperature and velocity of the combustion gas in the leak paths are calculated in SHARP by solving the time-dependent Navier-Stokes equations while the heat conduction in the solid is modeled by SINDA/G. The two codes are coupled by the heat flux at the solid-gas interface. A few test cases are presented and the results from SFLOW agree very well with the exact solutions or experimental data. These cases include Fanno flow where friction is important, Rayleigh flow where heat transfer between gas and solid is important, flow with mass addition due to the erosion of the solid wall, a transient volume venting process, as well as some transient one-dimensional flows with analytical solutions. In addition, SFLOW is applied to model the RSRM nozzle joint 4 subscale hot-flow tests and the predicted pressures, temperatures (both gas and solid), and O-ring erosions agree well with the experimental data. It was also found that the heat transfer between gas and solid has a major effect on the pressures and temperatures of the fill bottles in the RSRM nozzle joint 4 configuration No. 8 test.

Wang, Qunzhen↗
NASA NTRS1995

A source-sink model of the generation of plate tectonics from non-Newtonian mantle flow

A model of mantle convection which generates plate tectonics requires strain rate- or stress-dependent rheology in order to produce strong platelike flows with weak margins as well as strike-slip deformation and plate spin (i.e., toroidal motion). Here, we employ a simple model of source-sink driven surface flow to determine the form of such a rheology that is appropriate for Earth's present-day plate motions. In this model, lithospheric motion is treated as shallow layer flow driven by sources and sinks which correspond to spreading centers and subduction zones, respectively. Two plate motion models are used to derive the source sink field. As originally implied in the simpler Cartesian version of this model, the classical power law rheologies do not generate platelike flows as well as the hypothetical Whitehead-Gans stick-slip rheology (which incorporates a simple self-lubrication mechanism). None of the fluid rheologies examined, however, produce more than approximately 60% of the original maximum shear. For either plate model, the viscosity fields produced by the power law rheologies are diffuse, and the viscosity lows over strike-slip shear zones or pseudo-margins are not as small as over the prescribed convergent-divergent margins. In contrast, the stick-slip rheology generates very platelike viscosity fields, with sharp gradients at the plate boundaries, and margins with almost uniformly low viscosity. Power law rheologies with high viscosity contrasts, however, lead to almost equally favorable comparisons, though these also yield the least platelike viscosity fields. This implies that the magnitude of toroidal flow and platelike strength distributions are not necessarily related and thus may present independent constraints on the determination of a self-consistent plate-mantle rheology.

Bercovici, David↗
NASA NTRS1989

A one equation turbulence model for transonic airfoil flows

A one-equation turbulence model has been developed from available experimental observations on both attached and separated turbulence flows, and numerical results are presented for flows about NACA 0012 and RAE 2822 airfoils. The model is shown to duplicate the accurate results of the Baldwin-Lomax (1978) algebraic model for the case of attached flow. For cases of separated flow, the model is found to predict shock location and strength closer to the experimentally observed values than both the algebraic and the q-omega two-equation models.

Mitcheltree, R. A.↗
NASA NTRS1974

Combined Quadrupole-dipole Model for Inlet Flow Distortion Noise from a Subsonic Fan

A combined quadrupole-dipole model has been developed for the noise generated by inlet flow distortion in a subsonic fan. A formula is derived for the total upstream-radiated acoustic power in each tone as a function of the design parameters of the fan and the properties of the inlet flow distortion. Numerical results are obtained for values of the parameters corresponding to various quiet fans. The analysis is compared with noise measurements taken on a 51-cm (20-in.) diameter research fan as well as with those taken on a number of full-scale fan stages. Fairly good agreement was obtained. It should therefore be possible to use this model to study the noise-reduction potential of the various fan design parameters.

Goldstein, M. E.↗
DOE OSTI2020

Data-driven recovery of hidden physics in reduced order modeling of fluid flows

In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework is based on using first principles to model the known physics in conjunction with utilizing the data-driven machine learning tools to model the remaining residual that is hidden in data. This framework employs proper orthogonal decomposition as a compression tool to construct orthonormal bases and Galerkin projection (GP) as a model to build the dynamical core of the system. Our proposed methodology hence compensates structural or epistemic uncertainties in models and utilizes the observed data snapshots to compute true modal coefficients spanned by these bases. The GP model is then corrected at every time step with a data-driven rectification using a long short-term memory (LSTM) neural network architecture to incorporate hidden physics. A Grassmannian manifold approach is also adopted for interpolating basis functions to unseen parametric conditions. The control parameter governing the system's behavior is thus implicitly considered through true modal coefficients as input features to the LSTM network. The effectiveness of the HAM approach is then discussed through illustrative examples that are generated synthetically to take hidden physics into account. Furthermore, our approach thus provides insights addressing a fundamental limitation of the physics-based models when the governing equations are incomplete to represent underlying physical processes.

42 ENGINEERING↗
NASA NTRS1990

Flow measurements in a model of the mildly curved femoral artery of man

The effects of curvature on the flow rate near the wall in the vicinity of the mildly curved femoral artery of man, and on the pressure distributions along the curved segment, were investigated using glass and tygon flow models constructed to conform to the shape of the femoral angiogram of a human subject. The test fluid was 33 percent aqueous sucrose. Steady flow observations, made using a dye flow visualization system, revealed a flow pattern like that observed in coiled pipes. A double helical type flow was found to develop, with converging streamlines in the wall vicinity from the upper and lower plane of curvature merging asymptotically along the inner curvature in a stable manner. Pressure measurements for steady flow revealed progressively larger pressure drops with distance along the entrance region of the curved segment, relative to that for a straight lumen.

Back, L. H.↗
DOE OSTI2021

Design and analysis of a wake model for spatially heterogeneous flow

Abstract. Methods of turbine wake modeling are being developed to more accurately account for spatially variant atmospheric conditions within wind farms. Most current wake modeling utilities are designed to apply a uniform flow field to the entire domain of a wind farm. When this method is used, the accuracy of power prediction and wind farm controls can be compromised depending on the flow-field characteristics of a particular area. In an effort to improve strategies of wind farm wake modeling and power prediction, FLOw Redirection and Induction in Steady State (FLORIS) was developed to implement sophisticated methods of atmospheric characterization and power output calculation. In this paper, we describe an adapted FLORIS model that features spatial heterogeneity in flow-field characterization. This model approximates an observed flow field by interpolating from a set of atmospheric measurements that represent local weather conditions. The objective of this method is to capture heterogeneous atmospheric effects caused by site-specific terrain features, without explicitly modeling the geometry of the wind farm terrain. The implemented adaptations were validated by comparing the simulated power predictions generated from FLORIS to the actual recorded wind farm output from the supervisory control and data acquisition (SCADA) recordings and large eddy simulations (LESs). When comparing the performance of the proposed heterogeneous model to homogeneous FLORIS simulations, the results show a 14.6 % decrease for mean absolute error (MAE) in wind farm power output predictions for cases using wind farm SCADA data and a 18.9 % decrease in LES case studies. The results of these studies also indicate that the efficacy of the proposed modeling techniques may vary with differing site-specific operational conditions. This work quantifies the accuracy of wind plant power predictions under heterogeneous flow conditions and establishes best practices for atmospheric surveying for wake modeling.

17 WIND ENERGY↗
DOE OSTI2024

Modeling Grid Data Flows for Transmission and Distribution Operations: Review, Design, Next Steps

Operational scenarios of the power grids grow multifold to accommodate the diverse needs of both the utilities and end consumers, and the various other stakeholders in-between. To comprehensively model and apply analytics to support objectives and business functions of grid sectors, a reliable approach to characterize and design data flows is crucial. The flows bridge business functions with communications protocols, stakeholders such as the grid actors, and data interfaces comprising different data objects. Additionally, constraints applied to the flow such as cybersecurity, trust, privacy, and ownership among others intersect these entities, requiring the delineation of their interactions under different scenarios. This paper aims to not only highlight relevant research in the space of grid data flows, but also proposes, for the transmission-distribution sector, a novel modeling approach that marries the aforementioned entities: objectives, business functions, data interfaces, communication protocols, data stakeholders, and flow constraints. It elaborates on the design philosophy and the significance of each entity within the model and applies it to an example function of fault location, isolation and service restoration (FLISR). Finally, the next steps to extend the application of this data flow model for other practical operational scenarios are discussed.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗
DOE OSTI2022

Equation‐Free Surrogate Modeling of Geophysical Flows at the Intersection of Machine Learning and Data Assimilation

Abstract There is a growing interest in developing data‐driven reduced‐order models for atmospheric and oceanic flows that are trained on data obtained either from high‐resolution simulations or satellite observations. The data‐driven models are non‐intrusive in nature and offer significant computational savings compared to large‐scale numerical models. These low‐dimensional models can be utilized to reduce the computational burden of generating forecasts and estimating model uncertainty without losing the key information needed for data assimilation (DA) to produce accurate state estimates. This paper aims at exploring an equation‐free surrogate modeling approach at the intersection of machine learning and DA in Earth system modeling. With this objective, we introduce an end‐to‐end non‐intrusive reduced‐order modeling (NIROM) framework equipped with contributions in modal decomposition, time series prediction, optimal sensor placement, and sequential DA. Specifically, we use proper orthogonal decomposition (POD) to identify the dominant structures of the flow, and a long short‐term memory network to model the dynamics of the POD modes. The NIROM is integrated within the deterministic ensemble Kalman filter (DEnKF) to incorporate sparse and noisy observations at optimal sensor locations obtained through QR pivoting. The feasibility and the benefit of the proposed framework are demonstrated for the NOAA Optimum Interpolation Sea Surface Temperature (SST) V2 data set. Our results indicate that the NIROM is stable for long‐term forecasting and can model dynamics of SST with a reasonable level of accuracy. Furthermore, the prediction accuracy of the NIROM gets improved by almost one order of magnitude by the DEnKF algorithm.

Pawar, Suraj↗
NASA NTRS1994

A fiber matrix model for fluid flow and streaming potentials in the canaliculi of an osteon

A theoretical model is developed to predict the fluid shear stress and streaming potential at the surface of osteocytic processes in the lacunar-canalicular porosity of an osteon when the osteon is subject to mechanical loads that are parallel or perpendicular to its axis. The theory developed in Weinbaum et al. (31) for the flow through a proteoglycan matrix in a canaliculus is employed in a poroelastic model for the osteon. Our formulation is a generalization of that of Petrov et al. (17). Our model predicts that, in order to satisfy the measured frequency dependence of the phase and magnitude of the SGP in macroscopic bone samples, the fiber spacing in the fluid annulus must lie in the narrow range 6-7 nm typical of the spacing of GAG sidechains along a protein monomer. The model predictions for the local SGP profiles in the osteon agree with the experimental observations of Starkebaum et al. (24). The theory predicts that the pore pressure relaxation time, tau d, for a 150-300 microns diameter osteon with the foregoing matrix structure is approximately 0.03-0.13 sec, and that the amplitude of the mean fluid shear stress on the membrane of the osteocytic process at the mean areal radius of the osteon has a maximum at 28 Hz if tau d = 0.06 sec. This maximum, which is independent of the magnitude of the loading, could be important in vivo since the recent experiments of Turner et al. (28) and McLeod et al. (15) have a peak in the strain frequency spectrum between 20 and 30 Hz that also appears to be independent of the type (magnitude) of loading. Numerical predictions for the amplitude of the average fluid shear stress on the osteocytic membrane at the mean areal radius of the osteon show that the fluid shear stress associated with the low amplitude 20-30 Hz spectral strain component is at least as large as the average fluid shear stress associated with the high amplitude 1 Hz stride component, although the latter loading is an order of magnitude larger, and has a magnitude that lies within the middle of the range, 6-30 dynes/cm2, where fluid shear stresses in tissue culture studies with osteoblast monolayers have elicited an intracellular Ca++ response (31). The implications of these results for intracellular electrical communication are discussed.

Non-NASA Center↗
NASA NTRS2005

The Lag Model Applied to High Speed Flows

The Lag model has shown great promise in prediction of low speed and transonic separations. The predictions of the model, along with other models (Spalart-Allmaras and Menter SST) are assessed for various high speed flowfields. In addition to skin friction and separation predictions, the prediction of heat transfer are compared among these models, and some fundamental building block flowfields, are investigated.

Olsen, Michael E.↗