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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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NASA NTRSDate not supplied

Implicit Thermochemical Nonequilibrium Flow Simulations on Unstructured Grids using GPUs

Thermochemical nonequilibrium flow simulation capabilities have been previously implemented, verified, and validated for central processing unit (CPU) systems in NASA’s unstructured-grid computational fluid dynamics solver FUN3D. Many exascale-class high-performance computing systems will rely on graphics processing unit (GPU) architectures for high throughput and energy efficiency; thus, CPU-based scientific computing software unable to effectively utilize these systems must be updated. In this work, we present a CUDA C++ implementation of FUN3D’s thermochemical nonequilibrium flow simulation capabilities targeting NVIDIA Tesla GPUs. An overview of the porting and optimization strategy is described and performance comparisons with other recent architectures are presented. Scaling to thousands of GPUs is demonstrated, yielding computational performance equivalent to that of several million CPU cores. The implementation enables efficient, high-fidelity, scale-resolving simulations of thermochemical nonequilibrium flows for many applications including atmospheric entry, hypersonics, and combustion.

GPU↗
NASA NTRS1990

Interactive real time flow simulations

An interactive real time flow simulation technique is developed for an unsteady channel flow. A finite-volume algorithm in conjunction with a Runge-Kutta time stepping scheme was developed for two-dimensional Euler equations. A global time step was used to accelerate convergence of steady-state calculations. A raster image generation routine was developed for high speed image transmission which allows the user to have direct interaction with the solution development. In addition to theory and results, the hardware and software requirements are discussed.

Sadrehaghighi, I.↗
DOE OSTI2017

Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop: August 4-5, 2015, Washington, D.C.

This report details the impact exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the DOE applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The workshop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

Use of advanced computers for aerodynamic flow simulation

The current and projected use of advanced computers for large-scale aerodynamic flow simulation applied to engineering design and research is discussed. The design use of mature codes run on conventional, serial computers is compared with the fluid research use of new codes run on parallel and vector computers. The role of flow simulations in design is illustrated by the application of a three dimensional, inviscid, transonic code to the Sabreliner 60 wing redesign. Research computations that include a more complete description of the fluid physics by use of Reynolds averaged Navier-Stokes and large-eddy simulation formulations are also presented. Results of studies for a numerical aerodynamic simulation facility are used to project the feasibility of design applications employing these more advanced three dimensional viscous flow simulations.

Bailey, F. R.↗
DOE OSTI2020

Deep learning for in situ data compression of large turbulent flow simulations

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Parallel Fokker–Planck-DSMC algorithm for rarefied gas flow simulation in complex domains at all Knudsen numbers

A major challenge for the conventional Direct Simulation Monte Carlo (DSMC) technique lies in the fact that its computational cost becomes prohibitive in the near continuum regime, where the Knudsen number (Kn)—characterizing the degree of rarefaction—becomes small. In contrast, the Fokker–Planck (FP) based particle Monte Carlo scheme allows for computationally efficient simulations of rarefied gas flows in the low and intermediate Kn regime. The Fokker–Planck collision operator—instead of performing binary collisions employed by the DSMC method—integrates continuous stochastic processes for the phase space evolution in time. This allows for time step and grid cell sizes larger than the respective collisional scales required by DSMC. Dynamically switching between the FP and the DSMC collision operators in each computational cell is the basis of the combined FP-DSMC method, which has been proven successful in simulating flows covering the whole Kn range. Until recently, this algorithm had only been applied to two-dimensional test cases. In this contribution, we present the first general purpose implementation of the combined FP-DSMC method. Utilizing both shared- and distributed-memory parallelization, this implementation provides the capability for simulations involving many particles and complex geometries by exploiting state of the art computer cluster technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Gene flow simulations demonstrate resistance of long-lived species to genetic erosion from habitat fragmentation

Habitat fragmentation restricts the movement of individuals across a landscape. In terrestrial and aquatic systems, barriers to movement can modify population and community dynamics at local or regional scales. This research contrasted life history traits related to lifespan with habitat fragmentation to determine impacts on species population genetic structure in the Neuse River Basin, USA. For this, we simulated gene flow among evenly-spaced populations in a river network and tracked individual and population genetics for 200 years. The modeled scenarios represent a full cross between five life history strategies and four riverscapes representing varying degrees of fragmentation. The five life history strategies include species (based on freshwater mussels) with average lifespans ranging from 10 to 50 years and age at maturity from 2 to 6 years. The movement landscapes included a (1) panmictic, (2) stepping-stone landscape allowing movement to only neighboring populations during each dispersal event, (3) partially-fragmented landscape divided by dams currently in the network, and (4) fully-fragmented landscape. Results suggest species with shorter lifespans have higher population genetic structure in fragmented landscapes than species with longer lifespans. Additionally, species with shorter lifespans in highly fragmented landscapes may be harboring genetic degradation or decline as allele fixation and loss. Although anthropogenic fragmentation of many river systems is only 100–200 years old, the simulation indicates that species can respond genetically in that period of time. Moreover, the time frame of the simulation suggests that genetic impacts of habitat fragmentation in some species present in the Neuse River Basin may not yet be manifesting and restoration activities could be successful.

13 HYDRO ENERGY↗
DOE OSTI2022

Iterative Workflow for Quantification and Minimization of Reduced Chemistry-Induced Uncertainties in Reacting Flow Simulation

Reduced chemistry models mitigate computational cost but introduce two sources of uncertainties in reacting flow simulation, including chemical information loss due to model reduction, and approximation errors due to non-optimal projection. We present an iterative workflow for quantification and minimization of reduced chemistry-induced uncertainties in reacting flow simulations.

chemistry↗
NASA NTRS2002

Progress in Unsteady Turbopump Flow Simulations

This viewgraph presentation discusses unsteady flow simulations for a turbopump intended for a reusable launch vehicle (RLV). The simulation process makes use of computational grids and parallel processing. The architecture of the parallel computers used is discussed, as is the scripting of turbopump simulations.

Kiris, Cetin C.↗
NASA NTRS2002

Progress in Unsteady Turbopump Flow Simulations Using Overset Grid Systems

This viewgraph presentation provides information on unsteady flow simulations for the Second Generation RLV (Reusable Launch Vehicle) baseline turbopump. Three impeller rotations were simulated by using a 34.3 million grid points model. MPI/OpenMP hybrid parallelism and MLP shared memory parallelism has been implemented and benchmarked in INS3D, an incompressible Navier-Stokes solver. For RLV turbopump simulations a speed up of more than 30 times has been obtained. Moving boundary capability is obtained by using the DCF module. Scripting capability from CAD geometry to solution is developed. Unsteady flow simulations for advanced consortium impeller/diffuser by using a 39 million grid points model are currently underway. 1.2 impeller rotations are completed. The fluid/structure coupling is initiated.

Kiris, Cetin C.↗
NASA NTRS2001

Coupled-Flow Simulation of HP-LP Turbines Has Resulted in Significant Fuel Savings

Our objective was to create a high-fidelity Navier-Stokes computer simulation of the flow through the turbines of a modern high-bypass-ratio turbofan engine. The simulation would have to capture the aerodynamic interactions between closely coupled high- and low-pressure turbines. A computer simulation of the flow in the GE90 turbofan engine's high-pressure (HP) and low-pressure (LP) turbines was created at GE Aircraft Engines under contract with the NASA Glenn Research Center. The three-dimensional steady-state computer simulation was performed using Glenn's average-passage approach named APNASA. The areas upstream and downstream of each blade row mutually interact with each other during engine operation. The embedded blade row operating conditions are modeled since the average passage equations in APNASA actively include the effects of the adjacent blade rows. The turbine airfoils, platforms, and casing are actively cooled by compressor bleed air. Hot gas leaks around the tips of rotors through labyrinth seals. The flow exiting the high work HP turbines is partially transonic and, therefore, has a strong shock system in the transition region. The simulation was done using 121 processors of a Silicon Graphics Origin 2000 (NAS 02K) cluster at the NASA Ames Research Center, with a parallel efficiency of 87 percent in 15 hr. The typical average-passage analysis mesh size per blade row was 280 by 45 by 55, or approx.700,000 grid points. The total number of blade rows was 18 for a combined HP and LP turbine system including the struts in the transition duct and exit guide vane, which contain 12.6 million grid points. Design cycle turnaround time requirements ran typically from 24 to 48 hr of wall clock time. The number of iterations for convergence was 10,000 at 8.03x10(exp -5) sec/iteration/grid point (NAS O2K). Parallel processing by up to 40 processors is required to meet the design cycle time constraints. This is the first-ever flow simulation of an HP and LP turbine. In addition, it includes the struts in the transition duct and exit guide vanes.

Veres, Joseph P.↗
DOE OSTI2021

Parallel exponential time differencing methods for geophysical flow simulations

Two ocean models are considered for geophysical flow simulations: the multilayer shallow water equations and the multilayer primitive equations. For the former, we investigate the parallel performance of exponential time differencing (ETD) methods, including exponential Rosenbrock–Euler, ETD2wave, and B-ETD2wave. For the latter, we take advantage of the splitting of barotropic and baroclinic modes and propose a new two-level method in which an ETD method is applied to solve the fast barotropic mode. Furthermore, these methods could improve the computational efficiency of numerical simulations because ETD methods allow for much larger time step sizes than traditional explicit time-stepping techniques that are commonly used in existing computational ocean models. Several standard benchmark tests for ocean modeling are performed and comparison of the numerical results demonstrates a great potential of applying the parallel ETD methods for simulating real-world geophysical flows.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools

First- and second-order accurate numerical methods, implemented for CPUs, underpin the majority of industrial CFD solvers. Whilst this technology has proven very successful at solving steady-state problems via a Reynolds Averaged Navier–Stokes approach, its utility for undertaking scale-resolving simulations of unsteady flows is less clear. High-order methods for unstructured grids and GPU accelerators have been proposed as an enabling technology for unsteady scale-resolving simulations of flow over complex geometries. In this study we systematically compare accuracy and cost of the high-order Flux Reconstruction solver PyFR running on GPUs and the industry-standard solver STAR-CCM+ running on CPUs when applied to a range of unsteady flow problems. Specifically, we perform comparisons of accuracy and cost for isentropic vortex advection (EV), decay of the Taylor–Green vortex (TGV), turbulent flow over a circular cylinder, and turbulent flow over an SD7003 aerofoil. We consider two configurations of STAR-CCM+: a second-order configuration, and a third-order configuration, where the latter was recommended by CD-adapco for more effective computation of unsteady flow problems. Results from both PyFR and STAR-CCM+ demonstrate that third-order schemes can be more accurate than second-order schemes for a given cost e.g. going from second- to third-order, the PyFR simulations of the EV and TGV achieve 75× and 3× error reduction respectively for the same or reduced cost, and STAR-CCM+ simulations of the cylinder recovered wake statistics significantly more accurately for only twice the cost. Moreover, advancing to higher-order schemes on GPUs with PyFR was found to offer even further accuracy vs. cost benefits relative to industry-standard tools.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Time-Accurate Unsteady Flow Simulations Supporting the SRM T+68-Second Pressure Spike Anomaly Investigation (STS-54B)

Time-accurate unsteady flow simulations are being performed supporting the SRM T+68sec pressure 'spike' anomaly investigation. The anomaly occurred in the RH SRM during the STS-54 flight (STS-54B) but not in the LH SRM (STS-54A) causing a momentary thrust mismatch approaching the allowable limit at that time into the flight. Full-motor internal flow simulations using the USA-2D axisymmetric code are in progress for the nominal propellant burn-back geometry and flow conditions at T+68-sec--Pc = 630 psi, gamma = 1.1381, T(sub c) = 6200 R, perfect gas without aluminum particulate. In a cooperative effort with other investigation team members, CFD-derived pressure loading on the NBR and castable inhibitors was used iteratively to obtain nominal deformed geometry of each inhibitor, and the deformed (bent back) inhibitor geometry was entered into this model. Deformed geometry was computed using structural finite-element models. A solution for the unsteady flow has been obtained for the nominal flow conditions (existing prior to the occurrence of the anomaly) showing sustained standing pressure oscillations at nominally 14.5 Hz in the motor IL acoustic mode that flight and static test data confirm to be normally present at this time. Average mass flow discharged from the nozzle was confirmed to be the nominal expected (9550 lbm/sec). The local inlet boundary condition is being perturbed at the location of the presumed reconstructed anomaly as identified by interior ballistics performance specialist team members. A time variation in local mass flow is used to simulate sudden increase in burning area due to localized propellant grain cracks. The solution will proceed to develop a pressure rise (proportional to total mass flow rate change squared). The volume-filling time constant (equivalent to 0.5 Hz) comes into play in shaping the rise rate of the developing pressure 'spike' as it propagates at the speed of sound in both directions to the motor head end and nozzle. The objectives of the present analysis are to: (1) capture the dynamic responses of the motor combustion gas flow to correlate with available low-frequency (less than 12.5 sample/sec) data and (2) observe the high-frequency (up to 50 Hz) characteristics of the response to determine any potentials for dynamic coupling.

Dougherty, N. S.↗
DOE OSTI2022

In situ feature analysis for large-scale multiphase flow simulations

The study of multiphase flow is essential for designing chemical reactors such as fluidized bed reactors (FBR), as a detailed understanding of hydrodynamics is critical for optimizing reactor performance and stability. An FBR allows scientists to conduct different types of chemical reactions involving multiphase materials, especially interaction between gas and solids. During such complex chemical processes, the formation of void regions in the reactor, generally termed as bubbles, is an important phenomenon. The study of these bubbles has a deep implication in predicting the reactor’s overall efficiency. But physical experiments needed to understand bubble dynamics are costly and non-trivial due to the technical difficulties involved and harsh working conditions of the reactors. Therefore, to study such chemical processes and bubble dynamics, a state-of-the-art computational simulation MFIX-Exa is being developed. Despite the proven accuracy of MFIX-Exa in modeling bubbling phenomena, the large-scale output data prohibits the use of traditional post hoc analysis capabilities in both storage and I/O time. Herein, to address these issues and allow the application scientists to explore the bubble dynamics in an efficient and timely manner, we have developed an end-to-end analytics pipeline that enables in situ detection of bubbles, followed by a flexible post hoc visual exploration methodology of bubble dynamics. The proposed method enables interactive analysis of bubbles, along with quantification of several bubble characteristics, enabling experts to understand the bubble interactions in detail. Positive feedback from the experts has indicated the efficacy of the proposed approach for exploring bubble dynamics in very-large-scale multiphase flow simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Upscaling ab-initio chemistry models to non-equilibrium flow simulations

Thermochemical nonequilibrium is generated by hypersonic cruise vehicles, high speed combustion and detonations. Nonequilibrium interactions affect reaction rates and energy transfer that are critical for many engineering applications. Ab-initio potential energy surfaces can be used in quasi-classical trajectory (QCT) calculations to calculate state-specific dissociation rates and cross sections, as well as state-to-state energy exchange rates and cross sections. These rates and cross sections are needed for simulating such nonequilibrium flows. However, there are two main challenges in extending QCT calculations to modeling all chemical processes found in typical engineering flowfields. First, ab-initio surfaces for many collision partners are not available and when available their fidelity is not quantified. Second, state-to-state cross section datasets are typically on the order of 1000 4, , and are too large to be efficiently implemented in engineering simulations. This work focuses on O 2 +O interactions because of prevalence of oxygen in many engineering application; however, all of the models developed here may be applied to other diatom-atom interactions and can be extended to other diatom-diatom combinations. It is shown in this work that at temperatures between 2,500 and 20,000K, state-specific cross sections are not highly sensitive to potentials and a Morse additive pairwise (MAP) potential is proposed for modeling collisions for which ab-initio potentials are not available. Next, this work suggests an approach to model state-to-state cross sections based on maximum entropy considerations. The calculated cross sections are fit to a new model with just 8 parameters, which can be easily scaled up to flow simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Classroom aerosol dispersion modeling: experimental assessment of a low-cost flow simulation tool

The purpose of this study was to assess the utility of a low-cost flow simulation tool for an indoor air modeling application by comparing its outputs with the results of a physical experiment, as well as those from a more advanced computational fluid dynamics (CFD) software package. In this study, five aerosol dispersion tests were performed in two different classrooms by releasing a CO 2 tracer gas from six student locations. Resultant steady-state concentrations were monitored at 13 locations around the periphery of the room. Subsequently, the experiments were modeled using both a low-cost tool (SolidWorks Flow Simulation) and a more sophisticated tool (STAR-CCM+). Models were evaluated based on their ability to predict the experimentally measured concentrations at the 13 monitoring locations by calculating four performance parameters commonly used in the evaluation of dispersion models: fractional mean bias (FB), normalized mean-square error (NMSE), fraction of predicted value within a factor of two (FAC2), and normalized absolute difference (NAD). The more sophisticated model performed better in 15 of the 20 possible cases (five tests at four parameters each), with parameters meeting acceptance criteria in 19 of 20 cases. However, the lower-cost tool was only slightly worse, with parameters meeting acceptance criteria in 18 of 20 cases, and it performed better than the other tool in 3 of 20 cases. Because it provides useful results at a fraction of the monetary and training cost and is already widely accessible to many institutions, such a tool may be worthwhile for many indoor aerosol dispersion applications, especially for students or researchers just beginning CFD modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A physical-based gas–surface interaction model for rarefied gas flow simulation

Empirical gas–surface interaction models, such as the Maxwell model and the Cercignani–Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas–surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas–surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations. - Highlights: • The new physical-based gas–surface interaction model satisfies the basic relations of boundary condition so that it can be used in rarefied gas flow simulations. • The new physical model possesses several advantages comparing to the empirical gas–surface interaction models, hence it's a more accurate boundary condition for rarefied gas flow study. • The new physical model is a statistical model which can be efficiently implemented by Monte Carlo method. It's much more efficient comparing to the MD simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗