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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
DOE OSTI2021

P3A

Portably Performant Physical Algebra (P3A) is a C++ library that provides classes representing variables in a physical algebra equation. These equations are the fundamental way that physics models are written ("f = ma" for example). P3A provides a way to write in the C++ programming language similar to how one would do math on paper. P3A provides support tools for rapidly solving equations in a way that is common in scientific computing. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3183 O

Ibanez-Granados, Daniel↗
NASA NTRS2019

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D for Axisymmetric Jet Flow

Two full seven-equation turbulence models available in the FUN3D code are evaluated for their ability to improve the computation of challenging mixing flows encountered in aerospace propulsion. These models are the SSG/LRR and Wilcox full second-moment Reynolds stress models. They solve equations for the six components of the Reynolds stress and a seventh equation for the turbulent length scale. Two standard eddy viscosity models are also evaluated for comparison, the Spalart-Allmaras (SA) one-equation model and the Menter Shear Stress Transport (SST-V) two-equation turbulence model. Flow through an axisymmetric reference nozzle is examined at three flow conditions: subsonic unheated, subsonic heated, and near sonic unheated. Centerline profiles of velocity and turbulent kinetic energy and radial profiles of velocity, turbulent kinetic energy and turbulent stresses are examined. Results showed that the SA model did well at predicting the jet potential core length, but over-mixed the downstream flow, whereas the SST-V model over-predicted the potential core length. The Wilcox-model significantly over-predicted the potential core length and under-predicted the mixing and was not well-suited for the jet flows evaluated, however the SSG/LRR Reynolds stress model did well at predicting the mixing rate and mean velocity for all cases examined.

mixing layers↗
NASA NTRS2019

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D for Axisymmetric Jet Flow

Two full seven-equation turbulence models have been implemented into the FUN3D code to evaluate their ability to improve the computation of challenging flows encountered in aerospace propulsion, including mixing flows. These models are the SSG/LRR and Wilcox full second-moment Reynolds stress models. They solve equations for the six components of the Reynolds stress and a seventh equation for the mixing length. Two standard eddy viscosity models are also evaluated for comparison, the Spalart-Allmaras (SA) one-equation model and the Menter Shear Stress Transport (SST-V) two-equation turbulence model. Flow through an axisymmetric reference nozzle is examined at three flow conditions: subsonic unheated, subsonic heated, and near sonic unheated. Centerline profiles of velocity and turbulent kinetic energy and radial profiles of velocity, turbulent kinetic energy and turbulent stresses are examined. characteristics, no significant changes in the downstream flow behavior compared to the baseline case are observed. Furthermore, the total power consumed by the fans for different incoming flow conditions also remain marginally the same. It is hoped that the results, albeit obtained at very low speeds. would serve as a database for this technologically interesting flow field that has not been explored adequately before.

computational fluid dynamics↗
DOE OSTI2022

Adaptive workflow for simulation of RF heaters

Accurate RF (Radio Frequency) simulations of fusion systems like ITER require the definition of high-fidelity analysis geometries that include detailed antenna, reactor wall, and physics regions. Here, this paper will describe a workflow for the execution of adaptive high-performance simulations of RF fusion systems. In this workflow, the simulation input consists of a CAD model attributed with the needed analysis attributes. The analysis mesh is automatically generated and the analysis steps are executed using the time-harmonic Maxwell's equations solved using high-order Nédélec finite elements. A patch recovery-based error estimator is used to drive a conforming mesh adaptation procedure.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Loci-STREAM Version 0.9

Loci-STREAM is an evolving computational fluid dynamics (CFD) software tool for simulating possibly chemically reacting, possibly unsteady flows in diverse settings, including rocket engines, turbomachines, oil refineries, etc. Loci-STREAM implements a pressure- based flow-solving algorithm that utilizes unstructured grids. (The benefit of low memory usage by pressure-based algorithms is well recognized by experts in the field.) The algorithm is robust for flows at all speeds from zero to hypersonic. The flexibility of arbitrary polyhedral grids enables accurate, efficient simulation of flows in complex geometries, including those of plume-impingement problems. The present version - Loci-STREAM version 0.9 - includes an interface with the Portable, Extensible Toolkit for Scientific Computation (PETSc) library for access to enhanced linear-equation-solving programs therein that accelerate convergence toward a solution. The name "Loci" reflects the creation of this software within the Loci computational framework, which was developed at Mississippi State University for the primary purpose of simplifying the writing of complex multidisciplinary application programs to run in distributed-memory computing environments including clusters of personal computers. Loci has been designed to relieve application programmers of the details of programming for distributed-memory computers.

Wright, Jeffrey↗
DOE OSTI2023

Solving multiphysics-based inverse problems with learned surrogates and constraints

Abstract Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining computationally cheap learned surrogates with learned constraints. Not only does this combination lead to vastly improved inversions for the important fluid-flow property, permeability, it also provides a natural platform for inverting multimodal data including well measurements and active-source time-lapse seismic data. By adding a learned constraint, we arrive at a computationally feasible inversion approach that remains accurate. This is accomplished by including a trained deep neural network, known as a normalizing flow, which forces the model iterates to remain in-distribution, thereby safeguarding the accuracy of trained Fourier neural operators that act as surrogates for the computationally expensive multiphase flow simulations involving partial differential equation solves. By means of carefully selected experiments, centered around the problem of geological carbon storage, we demonstrate the efficacy of the proposed constrained optimization method on two different data modalities, namely time-lapse well and time-lapse seismic data. While permeability inversions from both these two modalities have their pluses and minuses, their joint inversion benefits from either, yielding valuable superior permeability inversions and CO 2 plume predictions near, and far away, from the monitoring wells.

Yin, Ziyi (ORCID:0000000250248771)↗
NASA NTRS1992

Upwind scheme for solving the Euler equations on unstructured tetrahedral meshes

An upwind scheme is presented for solving the three-dimensional Euler equations on unstructured tetrahedral meshes. Spatial discretization is accomplished by a cell-centered finite-volume formulation using flux-difference splitting. Higher-order differences are formed by a multidimensional linear reconstruction process. The solution gradients required for the higher-order differenes are computed by a novel approach that yields highly resolved solutions in regions of smooth flow while avoiding oscillations across shocks without explicitly applying a limiter. Solutions are advanced in time by a three-stage Runge-Kutta time-stepping scheme with convergence accelerated to steady state by local time stepping and implicit residual smoothing. Transonic solutions are presented for two meshes around the ONERA M6 wing and demonstrate substantial accuracy and insensitivity to mesh size.

Frink, Neal T.↗
DOE OSTI2023

Incremental Interval Assignment by Integer Linear Algebra with Improvements

Interval Assignment (IA) is the problem of selecting the number of mesh edges (intervals) for each curve for conforming quad and hex meshing. The intervals x is fundamentally integer-valued. Many other approaches perform numerical optimization then convert a floating-point solution into an integer solution, which is slow and error prone. We avoid such steps: we start integer, and stay integer. Incremental Interval Assignment (IIA) uses integer linear algebra (Hermite normal form) to find an initial solution to the meshing constraints, satisfying the integer matrix equation Solving for reduced row echelon form provides integer vectors spanning the nullspace of A. Here we add vectors from the nullspace to improve the initial solution, maintaining Ax = b Heuristics find good integer linear combinations of nullspace vectors that provide strict improvement towards variable bounds or goals. IIA always produces an integer solution if one exists. In practice we usually achieve solutions close to the user goals, but there is no guarantee that the solution is optimal, nor even satisfies variable bounds, e.g. has positive intervals. We describe several algorithmic changes since first publication that tend to improve the final solution. The software is freely available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Linear model decision trees as surrogates in optimization of engineering applications

Machine learning models are promising as surrogates in optimization when replacing difficult to solve equations or black-box type models. This work demonstrates the viability of linear model decision trees as piecewise-linear surrogates in decision-making problems. Linear model decision trees can be represented exactly in mixed-integer linear programming (MILP) and mixed-integer quadratic constrained programming (MIQCP) formulations. Furthermore, they can represent discontinuous functions, bringing advantages over neural networks in some cases. We present several formulations using transformations from Generalized Disjunctive Programming (GDP) formulations and modifications of MILP formulations for gradient boosted decision trees (GBDT). We then compare the computational performance of these different MILP and MIQCP representations in an optimization problem and illustrate their use on engineering applications. Importantly, we observe faster solution times for optimization problems with linear model decision tree surrogates when compared with GBDT surrogates using the Optimization and Machine Learning Toolkit (OMLT).

42 ENGINEERING↗
DOE OSTI2026

A Unified Workflow for Sensitivity-Based Kinetic Analysis in Microkinetic Models

Degrees of rate control (DRC), apparent activation energies, and apparent reaction orders are established local sensitivity diagnostics for interpreting microkinetic models, but applying them routinely to large mechanisms often requires substantial reaction-specific bookkeeping, perturbation design, and postprocessing. Here, in this study, we present a unified derivative-based workflow that evaluates these quantities from a single compiled reaction-network model and target-rate definition. For any user-provided microkinetic model, the workflow compiles the mechanism into stoichiometrically consistent mass-action rate equations, solves the surface dynamics, and uses automatic differentiation to compute sensitivities with respect to rate constants, temperature, and gas partial pressures. By combining their calculations in the same framework, the workflow clearly demonstrates the relationships between different DRCs and the apparent activation energy. Using existing examples of propylene partial oxidation and methane oxidation on Pd(100), we verify expected transient redistribution of rate control, distinguish net Campbell DRCs from one-sided directional sensitivities, and show how apparent activation energy can be reconstructed either from one-sided DRCs or from state-based DRCs while critical mechanistic insights are obtained consistently. In the methane oxidation case, a pathway-subset test further illustrates how a simplified mechanism preserves key kinetic signatures of a full model, showing the potential of our user-friendly tool for model construction beyond kinetic analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using Prompt Neutron Decay Constant Measurements to Obtain Additional Kinetics Information

Prompt neutron decay constant measurements are typically used to infer the prompt neutron lifetime in a chain-reacting system, but these measurements include much more information about the kinetics of the system. This work focuses specifically on the Rossi-α method of measuring the prompt neutron decay constant. The Rossi-α system of equations consists of five unknown parameters. With five unknowns and three equations, the system of equations solved by the Rossi-α measurement is under-determined. It has been postulated that a well posed problem can be formulated using independent measurement configurations on a single system. The external source strength, the effective delayed neutron fractions, and Diven’s parameter do not typically change for different configurations of a single experiment. If good detector geometry is chosen, the detector efficiency does not change for multiple measurements of a single experiment using Rossi-α measurements. By making these assumptions, there are only two unique variables. This knowledge can be used to solve for most of the unique parameters using two independent, unique Rossi-α measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

W7-X and the sawtooth instability: towards realistic simulations of current-driven magnetic reconnection

Magnetic reconnection in W7-X is studied by means of global numerical simulations in a series of models of increasing complexity. The magnetic geometry ranges from that of a cylinder to the full three-dimensional field of W7-X, and the equations solved range from ideal magnetohydrodynamics (MHD) to gyrokinetics. We simulate plasmas from the first operation phase with electron cyclotron current drive (ECCD). These are characterized by an equilibrium magnetic field featuring an ECCD-distorted 'humped' profile of the rotational transform ι, with ι = 1 in two radial locations. Such plasmas generally show sawtooth activity, hence motivating the present study. We pay particular attention to the role of equilibrium current density gradients in the destabilization of reconnecting modes. When the equilibrium temperature and density gradients are artificially suppressed (to eliminate the pressure gradient drive), the perturbed electrostatic potential is radially localized between the locations at which ι = 1. This is shown with a purely collisionless gyrokinetic model, in cylindrical geometry. In the real toroidal geometry of W7-X, for a non-ideal MHD model including a uniform resistivity, electron inertia and (numerical) viscosity, the same qualitative behaviour is observed. In particular, even if a resonant (m, n) = (1, -1) perturbation is initialized, the most unstable mode is the (m, n) = (-4, 4), where m and n are the poloidal and toroidal mode numbers, respectively. Other modes are destabilized due to geometric coupling. The growth rate of this instability scales as η 1/3 , where η is the plasma resistivity, thus suggesting that ECCD drives ideal MHD stable W7-X plasmas towards non-ideal marginality. An ideal magnetohydrodynamic analysis confirms the result. A fluid-kinetic hybrid version of the EUTERPE code shows that gyrokinetic ions have a stabilizing effect on these modes. For W7-X relevant collisionalities, the growth rate scales linearly with the electron skin depth, d e . Implications of our results for sawtoothing W7-X operation are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Error quantification and comparison of binary neutron star gravitational waveforms from numerical relativity codes

Future gravitational wave detections of merging binary neutron star systems have the possibility to tightly constrain the equation of state of dense nuclear matter. In order to extract such constraints, gravitational waveform models need to be calibrated to accurate numerical relativity simulations of the late inspiral and merger. In this work, we take an essential step toward classifying the error and potential systematics in current generation numerical relativity simulations of merging binary neutron stars. To this end, we perform a direct comparison of two codes (fil, spec), which differ in many aspects, including the numerical methods and discretizations used and equations solved. We find that despite these different approaches, the codes are—within current numerical resolution bounds—fully consistent, and broadly comparable in cost for a given accuracy level. Our results indicate that the error in the waveforms is primarily dominated by the hydrodynamic evolution, consistent with earlier findings in the literature. Finally, we also discuss current limitations and cost estimates for numerical relativity simulations to reach the accuracies required in the era of next-generation gravitational detectors.

gravitational waves↗
DOE OSTI2020

A Hybrid Lagrangian/Eulerian Collocated Velocity Advection and Projection Method for Fluid Simulation

Abstract We present a hybrid particle/grid approach for simulating incompressible fluids on collocated velocity grids. Our approach supports both particle‐based Lagrangian advection in very detailed regions of the flow and efficient Eulerian grid‐based advection in other regions of the flow. A novel Backward Semi‐Lagrangian method is derived to improve accuracy of grid based advection. Our approach utilizes the implicit formula associated with solutions of the inviscid Burgers’ equation. We solve this equation using Newton's method enabled by C 1 continuous grid interpolation. We enforce incompressibility over collocated, rather than staggered grids. Our projection technique is variational and designed for B‐spline interpolation over regular grids where multiquadratic interpolation is used for velocity and multilinear interpolation for pressure. Despite our use of regular grids, we extend the variational technique to allow for cut‐cell definition of irregular flow domains for both Dirichlet and free surface boundary conditions.

Gagniere, S.↗
DOE OSTI2022

Supersaturation Variability from Scalar Mixing: Evaluation of a New Subgrid-Scale Model Using Direct Numerical Simulations of Turbulent Rayleigh–Bénard Convection

We report that supersaturation fluctuations in the atmosphere are critical for cloud processes. A nonlinear dependence on two scalars - water vapor and temperature - leads to different behavior than single scalars in turbulent convection. For modeling such multiscalar processes at subgrid scales (SGS) in large-eddy simulations (LES) or convection-permitting models, a new SGS scheme is implemented in CM1 that solves equations for SGS water vapor and temperature fluctuations and their covariance. The SGS model is evaluated using benchmark direct-numerical simulations (DNS) of turbulent Rayleigh–Bénard convection with water vapor as in the Michigan Tech Pi Cloud Chamber. This idealized setup allows thorough evaluation of the SGS model without complications from other atmospheric processes. DNS results compare favorably with measurements from the chamber. Results from LES using the new SGS model compare well with DNS, including profiles of water vapor and temperature variances, their covariance, and supersaturation variance. SGS supersaturation fluctuations scale appropriately with changes to the LES grid spacing, with the magnitude of SGS fluctuations decreasing relative to those at the resolved scale as the grid spacing is decreased. Sensitivities of covariance and supersaturation statistics to changes in water vapor flux relative to thermal flux are also investigated by modifying the sidewall conditions. Relative changes in water vapor flux substantially decrease the covariance and increase supersaturation fluctuations even away from boundaries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Learning Forecasts of Rare Stratospheric Transitions from Short Simulations

Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Finkel, Justin↗
DOE OSTI2020

FY20 Verification of BISON Using Analytic and Manufactured Solutions

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution Modeling and Simulation (M&S) tools for modeling of Light Water Reactors (LWRs). This hub, Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including BISON, CTF, MPACT, and MAMBA. BISON is a fuel performance code which models the thermo-mechanical behavior of nuclear fuel using high performance M&S. It is capable of modeling traditional LWR fuel rods, fuel plates, and TRi-structural ISOtropic (TRISO) fuel particles. It can employ three-dimensional Cartesian, two-dimensional axisymmetric cylindrical, or one-dimensional radial spherical geometry. It includes empirical models for a large variety of fuel physics: temperature- and burnup-dependent thermal properties, fuel swelling and densification, fission gas production, cladding creep, fracture, cladding plasticity, and gap/plenum models. This document details a series of code verification test problems that are used to test BISON. These problems add confidence that the BISON code is a faithful representation of its underlying mathematical model. The suite of verification tests are mapped to the underlying conservation equations solved by the code: heat conduction, mechanics, and species conservation. Twenty-two problems are added for the heat conduction solution, two for the mechanics solution, and none for species conservation. Method of Manufactured Solutions (MMS) capability is demonstrated with three problems, and temperature drops across the fuel gap are tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Stacked networks improve physics-informed training: Applications to neural networks and deep operator networks

Physics-informed neural networks and operator networks have shown promise for effectively solving equations modeling physical systems. However, these networks can happen to be difficult or impossible to train accurately. Here, we present a novel multifidelity framework for stacking physics-informed neural networks and operator networks that facilitates training. We successively build a chain of networks, where the output at one step can act as a low-fidelity input for training a longer chain, gradually increasing the expressivity of the learnt model. The equations imposed at each step of the iterative process can be the same or different (akin to simulated annealing). The iterative (stacking) nature of the proposed method allows us to learn progressively features of a solution which could have been hard to learn directly. Through benchmark problems including a nonlinear pendulum, the wave equation, and the viscous Burgers equation, we show how stacking can be used to improve the accuracy and reduce the required size of physics-informed neural networks and operator networks.

97 MATHEMATICS AND COMPUTING↗