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Application of OpenFOAM to Plume Impingement in Space Environments

After 30 years of continuous human presence in low-earth orbit, NASA is returning to the moon and eventually will go to Mars. Travelling beyond low earth orbit requires NASA to learn how humans can live in Deep Space environments – beyond the protection of Earth’s magnetosphere and at distances from Earth that prevent a quick return in case of trouble. To this end, NASA is constructing the Lunar Gateway, an ISS-like space station to be put in orbit around the moon to act as a home base for Lunar exploration for NASA astronauts. The Gateway Lunar outpost will be built incrementally, via modules which will arrive at separate times and dock to the existing structure. The incremental addition of Gateway modules, and the docking of visiting vehicles, is achieved via a sequence of firings from the approaching body’s onboard reaction control system (RCS) thrusters to achieve the required approach trajectory. The typical hypergolic chemical RCS thrusters work by firing hot gases to produce adverse thrust and the needed change in velocity to safely finish the docking process. The exhaust gas from the RCS thrusters form plumes that expand into the vacuum of space and can impinge onto the outer surfaces of the Lunar Gateway, causing unwanted forces and moments, heat loads, sediment deposition, and in extreme cases, even surface erosion - all mechanisms that can damage the Lunar Gateway and must be minimized. Both permanent and visiting modules will have this RCS thruster exhaust impingement problem. This research aims to establish existing OpenFOAM solvers as a methodology for improving simulation techniques of rocket exhaust plume impingement in space environments. The flow structure of a plume in a space environment is complex; a plume that originates from a hypergolic chemical RCS thruster and expands into a vacuum will experience several regimes of rarefication. This range includes the continuum flow in the rocket nozzle through the fully rarefied free molecular flow further from the nozzle. The flow physics is different at these two extremes, and as such, the simulation approach for plumes is generally divided into a traditional computational fluid dynamics (CFD) simulation in and near the nozzle which is coupled to a subsequent direct simulation Monte Carlo (DSMC) simulation. At this time, the scope of this research is developing, verifying, and validating a method using existing solvers in the OpenFOAM framework for performing coupled CFD/DSMC calculations to determine the extent of plume impingement loading on generic space structures. This presentation will detail code-to-code comparisons between the hyStrath dsmcFoam+ solver, developed using OpenFOAM and available as open-source, and NASA’s in-house DSMC Analysis Code (DAC). Comparisons to several open-source publication findings using DAC [3,4] are presented, and advantages of using an OpenFOAM based solver are also discussed. The presentation concludes with a discussion of future work, and a plan for coupling the dsmcFoam+ solver with CFD simulations of chemical rocket engines for unified coupled plume simulation.

DSMC↗
NASA NTRS2022

Recommended Direct Simulation Monte Carlo Collision Model Parameters for Reacting Methane Flows

While hydrocarbon combustion and gas-surface interactions have been simulated for a variety of applications in continuum solvers, such processes have been rarely investigated in Direct Simulation Monte Carlo (DSMC). Thus Variable Hard/Soft Sphere (VHS/VSS)collision parameters are not available for most molecules of interest in the decomposition of methane, a significant pyrolysis gas product and potential atmospheric species for Titan re-entries. As these properties are essential for accurate modeling of gas transport and thermochemical effects, a method must be devised to compute them for use in DSMC. In this study, the methodology outlined in Stephani et al is utilized to compute the VHS/VSS parameters by fitting the Ω(1,1)and Ω(2,2) collision integrals [1]. These collision integrals are typically computed from intermolecular potentials and are used in CFD simulations to calculate transport properties such as viscosity, thermal conductivity, and diffusion. This approach ensures consistency between micro-scale collisions and macro-scale transport properties. To produce the necessary collision integrals needed for the fitting routine, we utilize the method described by Laricchiuta et al, where collision integrals are computed based on the constituent particles’ polarizability and effective electron number [2].Preliminary computations of pure-species Ω(1,1)and Ω(2,2)collision integrals produced from the coupled approach of Stephani et al and Laricchiuta et al for methane show good agreement with those computed via available ab-initio Potential Energy Surface Computations, as seen in Figure 1. Above 300K, no more than 12% deviation is observed between the two results over the temperature range of the fitted PES data [3].Current results of this study include full collision-specificVSS transport properties for a complex-species mixture involving major byproducts of pure methane decomposition. Targeted final results will include a comprehensive list of VSS parameters relevant toDSMC simulations of Titan atmospheric entry, based on the reduced kinetic model of Savajano et al [4].

M R Gosma↗
DOE OSTI2020

Efficient discontinuous Galerkin implementations and preconditioners for implicit unsteady compressible flow simulations

This work presents and compares efficient implementations of high-order discontinuous Galerkin methods: a modal matrix-free discontinuous Galerkin (DG) method, a hybridizable discontinuous Galerkin (HDG) method, and a primal formulation of HDG, applied to the implicit solution of unsteady compressible flows. The matrix-free implementation allows for a reduction of the memory footprint of the solver when dealing with implicit time-accurate discretizations. HDG reduces the number of globally-coupled degrees of freedom relative to DG, at high order, by statically condensing element-interior degrees of freedom from the system in favor of face unknowns. The primal formulation further reduces the element-interior degrees of freedom by eliminating the gradient as a separate unknown. This paper introduces a p-multigrid preconditioner implementation for these discretizations and presents results for various flow problems. Benefits of the p-multigrid strategy relative to simpler, less expensive, preconditioners are observed for stiff systems, such as those arising from low-Mach number flows at high-order approximation. The p-multigrid preconditioner also shows excellent scalability for parallel computations. Finally, additional savings in both speed and memory occur with a matrix-free/reduced version of the preconditioner.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Computational fluid mechanics

Two papers are included in this progress report. In the first, the compressible Navier-Stokes equations have been used to compute leading edge receptivity of boundary layers over parabolic cylinders. Natural receptivity at the leading edge was simulated and Tollmien-Schlichting waves were observed to develop in response to an acoustic disturbance, applied through the farfield boundary conditions. To facilitate comparison with previous work, all computations were carried out at a free stream Mach number of 0.3. The spatial and temporal behavior of the flowfields are calculated through the use of finite volume algorithms and Runge-Kutta integration. The results are dominated by strong decay of the Tollmien-Schlichting wave due to the presence of the mean flow favorable pressure gradient. The effects of numerical dissipation, forcing frequency, and nose radius are studied. The Strouhal number is shown to have the greatest effect on the unsteady results. In the second paper, a transition model for low-speed flows, previously developed by Young et al., which incorporates first-mode (Tollmien-Schlichting) disturbance information from linear stability theory has been extended to high-speed flow by incorporating the effects of second mode disturbances. The transition model is incorporated into a Reynolds-averaged Navier-Stokes solver with a one-equation turbulence model. Results using a variable turbulent Prandtl number approach demonstrate that the current model accurately reproduces available experimental data for first and second-mode dominated transitional flows. The performance of the present model shows significant improvement over previous transition modeling attempts.

Hassan, H. A.↗
NASA NTRS1989

CFD analysis for high speed inlets

The increased national interest in high speed flight has increased research for high speed propulsion components. The highly 3-D flows present in supersonic/hypersonic inlets are currently being studied at NASA-Lewis both experimentally and computationally using a family of steady Parabolized Navier-Stokes (PNS) and Navier-Stokes (NS) solvers and unsteady NS solvers. Some of the results of these efforts are presented with an emphasis on the comparison of the computational and experimental results. The flow in high speed inlets typically involves the interaction of compression shock waves and boundary layers on the internal surfaces. The fundamentals of these interactions have been studied experimentally for many years, while more recently, computations have been used to study these complex 3-D flow fields. Attempts to control the flow through boundary layer bleed are being investigated computationally prior to wind tunnel experiments. The ultimate goal is the higher performing inlets required for high speed flight.

Benson, Tom↗
NASA NTRS2024

Experimental and Computational Study of Convective Heating on the Aeroshell Back Side and Payload of the LOFTID Vehicle

A wind tunnel test program was conducted to obtain experimental convective heating data on models of the Low Earth Orbital Flight Test of an Inflatable Decelerator (LOFTID) vehicle in support of the flight test program. Wind tunnel testing was conducted at Mach 6 and Mach 10 at unit Reynolds numbers from 0.5×106/ft to 4.0×106/ft on 6.0inch diameter aeroshell models. Global heating data were obtained through phosphor thermography measurements on the front and back of the aeroshell and on the payload. For all test conditions, attached, laminar flow was definitively produced on the front of the aeroshell, while in the wake the flow was separated, unsteady and possibly transitional or turbulent. A complementary computational study was performed to assess the accuracy of heating predictions for LOFTID wake flow environments. A new grid topology was developed for the study to allow the use of structured grid solvers for complex, open-backed geometries such as that of LOFTID. Close agreement between measurements and predictions was obtained on the front of the aeroshell. Comparisons were more challenging in the wake because of both the extremely low heating rates and the accompanying high uncertainties and the unsteady nature of the separated wake flow simulations. While the differences between heating predictions and measurements for the wake flow were higher than for the forebody flow, these differences were used to assist in the definition of conservative uncertainty margins for predictions of the flight environments for the successful flight test of the LOFTID vehicle in November 2022.

LOFTID↗
DOE OSTI2016

CASL VMA Milestone Report FY16 (L3:VMA.VUQ.P13.08): Westinghouse Mixing with STAR-CCM+

STAR-CCM+ (STAR) is a high-resolution computational fluid dynamics (CFD) code developed by CD-adapco. STAR includes validated physics models and a full suite of turbulence models including ones from the k-ε and k-ω families. STAR is currently being developed to be able to do two phase flows, but the current focus of the software is single phase flow. STAR can use imported meshes or use the built in meshing software to create computation domains for CFD. Since the solvers generally require a fine mesh for good computational results, the meshes used with STAR tend to number in the millions of cells, with that number growing with simulation and geometry complexity. The time required to model the flow of a full 5x5 Mixing Vane Grid Assembly (5x5MVG) in the current STAR configuration is on the order of hours, and can be very computationally expensive. COBRA-TF (CTF) is a low-resolution subchannel code that can be trained using high fidelity data from STAR. CTF does not have turbulence models and instead uses a turbulent mixing coefficient β. With a properly calibrated β, CTF can be used a low-computational cost alternative to expensive full CFD calculations performed with STAR. During the Hi2Lo work with CTF and STAR, STAR-CCM+ will be used to calibrate β and to provide high-resolution results that can be used in the place of and in addition to experimental results to reduce the uncertainty in the CTF results.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Addition of Improved Shock-Capturing Schemes to OVERFLOW 2.1

Existing approximate Riemann solvers do not perform well when the grid is not aligned with strong shocks in the flow field. Three new approximate Riemann algorithms are investigated to improve solution accuracy and stability in the vicinity of strong shocks. The new algorithms are compared to the existing upwind algorithms in OVERFLOW 2.1. The new algorithms use a multidimensional pressure gradient based switch to transition to a more numerically dissipative algorithm in the vicinity of strong shocks. One new algorithm also attempts to artificially thicken captured shocks in order to alleviate the errors in the solution introduced by "stair-stepping" of the shock resulting from the approximate Riemann solver. This algorithm performed well for all the example cases and produced results that were almost insensitive to the alignment of the grid and the shock.

Burning, Pieter G.↗
NASA NTRS2009

Introduction: Prediction of F-16XL Flight Flow Physics

This special section is the result of fruitful endeavors by an international group of researchers in industry, government laboratories and university-led efforts to improve the technology readiness level of their CFD solvers through comparisons with flight data collected on the F-16XL-1 aircraft at a variety of test conditions. These 1996 flight data were documented and detailed the flight-flow physics of this aircraft through surface tufts and pressures, boundary-layer rakes and skin-friction measurements. The flight project was called the Cranked Wing Aerodynamics Project (CAWAP), due to its leading-edge sweep crank (70 degrees inboard, 50 degrees outboard), and served as a basis for the International comparisons to be made, called CAWAPI. This highly focused effort was one of two vortical flow studies facilitated by the NATO Research and Technology Organization through its Applied Vehicle Panel with a title of Understanding and Modeling Vortical Flows to Improve the Technology Readiness Level for Military Aircraft. It was given a task group number of AVT-113 and had an official start date of Spring 2003. The companion part of this task group dealt with fundamentals of vortical flow from both an experimental and numerical perspective on an analytically describable 65 degree delta-wing model for which much surface pressure data had already been measured at NASA Langley Research Center at a variety of Mach and Reynolds numbers and is called the Vortex Flow Experiment - 2 (VFE-2). These two parts or facets helped one another in understanding the predictions and data that had been or were being collected.

Lamar, John E.↗
DOE OSTI2014

Brownian dynamics without Green's functions

We develop a Fluctuating Immersed Boundary (FIB) method for performing Brownian dynamics simulations of confined particle suspensions. Unlike traditional methods which employ analytical Green's functions for Stokes flow in the confined geometry, the FIB method uses a fluctuating finite-volume Stokes solver to generate the action of the response functions “on the fly.” Importantly, we demonstrate that both the deterministic terms necessary to capture the hydrodynamic interactions among the suspended particles, as well as the stochastic terms necessary to generate the hydrodynamically correlated Brownian motion, can be generated by solving the steady Stokes equations numerically only once per time step. This is accomplished by including a stochastic contribution to the stress tensor in the fluid equations consistent with fluctuating hydrodynamics. We develop novel temporal integrators that account for the multiplicative nature of the noise in the equations of Brownian dynamics and the strong dependence of the mobility on the configuration for confined systems. Notably, we propose a random finite difference approach to approximating the stochastic drift proportional to the divergence of the configuration-dependent mobility matrix. Through comparisons with analytical and existing computational results, we numerically demonstrate the ability of the FIB method to accurately capture both the static (equilibrium) and dynamic properties of interacting particles in flow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

A Class of High-Resolution Explicit and Implicit Shock-Capturing Methods

The development of shock-capturing finite difference methods for hyperbolic conservation laws has been a rapidly growing area for the last decade. Many of the fundamental concepts, state-of-the-art developments and applications to fluid dynamics problems can only be found in meeting proceedings, scientific journals and internal reports. This paper attempts to give a unified and generalized formulation of a class of high-resolution, explicit and implicit shock capturing methods, and to illustrate their versatility in various steady and unsteady complex shock waves, perfect gases, equilibrium real gases and nonequilibrium flow computations. These numerical methods are formulated for the purpose of ease and efficient implementation into a practical computer code. The various constructions of high-resolution shock-capturing methods fall nicely into the present framework and a computer code can be implemented with the various methods as separate modules. Included is a systematic overview of the basic design principle of the various related numerical methods. Special emphasis will be on the construction of the basic nonlinear, spatially second and third-order schemes for nonlinear scalar hyperbolic conservation laws and the methods of extending these nonlinear scalar schemes to nonlinear systems via the approximate Riemann solvers and flux-vector splitting approaches. Generalization of these methods to efficiently include real gases and large systems of nonequilibrium flows will be discussed. Some perbolic conservation laws to problems containing stiff source terms and terms and shock waves are also included. The performance of some of these schemes is illustrated by numerical examples for one-, two- and three-dimensional gas-dynamics problems. The use of the Lax-Friedrichs numerical flux to obtain high-resolution shock-capturing schemes is generalized. This method can be extended to nonlinear systems of equations without the use of Riemann solvers or flux-vector splitting approaches and thus provides a large savings for multidimensional, equilibrium real gases and nonequilibrium flow computations.

Yee, H. C.↗
DOE OSTI2018

A non-intrusive parallel-in-time adjoint solver with the XBraid library

In this paper, an adjoint solver for the multigrid-in-time software library XBraid is presented. XBraid provides a non-intrusive approach for simulating unsteady dynamics on multiple processors while parallelizing not only in space but also in the time domain (XBraid: Parallel multigrid in time, http://llnl.gov/casc/xbraid). It applies an iterative multigrid reduction in time algorithm to existing spatially parallel classical time propagators and computes the unsteady solution parallel in time. Techniques from Automatic Differentiation are used to develop a consistent discrete adjoint solver which provides sensitivity information of output quantities with respect to design parameter changes. The adjoint code runs backwards through the primal XBraid actions and accumulates gradient information parallel in time. It is highly non-intrusive as existing adjoint time propagators can easily be integrated through the adjoint interface. The adjoint code is validated on advection-dominated flow with periodic upstream boundary condition. We report it provides similar strong scaling results as the primal XBraid solver and offers great potential for speeding up the overall computational costs for sensitivity analysis using multiple processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Enhancing high-fidelity nonlinear solver with reduced order model

Abstract We propose the use of reduced order modeling (ROM) to reduce the computational cost and improve the convergence rate of nonlinear solvers of full order models (FOM) for solving partial differential equations. In this study, a novel ROM-assisted approach is developed to improve the computational efficiency of FOM nonlinear solvers by using ROM’s prediction as an initial guess. We hypothesize that the nonlinear solver will take fewer steps to the converged solutions with an initial guess that is closer to the real solutions. To evaluate our approach, four physical problems with varying degrees of nonlinearity in flow and mechanics have been tested: Richards’ equation of water flow in heterogeneous porous media, a contact problem in a hyperelastic material, two-phase flow in layered porous media, and fracture propagation in a homogeneous material. Overall, our approach maintains the FOM’s accuracy while speeding up nonlinear solver by 18–73% (through suitable ROM-assisted FOMs). More importantly, the proximity of ROM’s prediction to the solution space leads to the improved convergence of FOMs that would have otherwise diverged with default initial guesses. We demonstrate that the ROM’s accuracy can impact the computational efficiency with more accurate ROM solutions, resulting in a better cost reduction. We also illustrate that this approach could be used in many FOM discretizations (e.g., finite volume, finite element, or a combination of those). Since our ROMs are data-driven and non-intrusive, the proposed procedure can easily lend itself to any nonlinear physics-based problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Linear optimal power flow system and method

An electric power system or power grid is optimized using a computer-implemented tool the represents in computer memory the optimization function and at least one constraint, which the processor operates upon using a linear programming solver algorithm. The constraints are represented in memory as data structures that include both real and reactive power terms, corresponding to at least one of a power flow model and a transmission line model. The transmission line model is represented using a piecewise linear representation. The power flow model may also include for each node in the power system a real power loss term representing transmission line loss allocated to that node.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING↗
DOE OSTI2021

A comprehensive modeling method for proton exchange membrane electrolyzer development

Hydrogen attracts significant interests as an effective energy carrier that can be derived from renewable sources. Hydrogen production using a proton-exchange membrane (PEM) electrolyzer can efficiently convert renewable power via water splitting in wide scales—from large, centralized generation to on-site production. Mathematical models with multiple scales and fidelities facilitate the continuing improvements of PEM electrolyzer development to improve performance, cost, and reliability. The model scopes and methods are presented in this paper, which also introduces a comprehensive PEM electrolysis modeling tool based on computational fluid dynamics (CFD) software, ANSYS/Fluent. The modeling tool incorporates electrochemical model of a PEM electrolysis cell to simulate the performance of coupled thermal-fluid, species transport, and electrochemical processes in a product-scale cell or stack by leveraging the powerful meshing generation and CFD solver of ANSYS/Fluent. The thermal-fluid modeling includes liquid water/gas two-phase flow and simulates a PEM electrolysis cell by using Fluent user-defined functions as add-on modules accounting for PEM-specific species transport and electrochemical processes. The modeling outcomes expediate PEM electrolyzer scaling up from basic material development and laboratory testing.

08 HYDROGEN↗