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At least 631 records · Page 35

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NASA NTRSDate not supplied

Plume-Surface Interaction: Preliminary Observations from a Physics Focused Ground Test

Near surface operations conducted by spacecraft using rocket propulsion, such as during landing or the initial portion of ascent, may induce surface interactions that pose a risk to the spacecraft itself or nearby assets. NASA’s Space Technology Mission Directorate is conducting a multi-year project to mature the capability to predict plume-surface interactions (PSI) and reduce uncertainty through modeling, simulation, and ground testing. The Physics Focused Ground Test (PFGT), conducted in summer 2021, aimed to collect PSI data for plume, erosion, and ejecta physics to characterize PSI behaviors across a range of parameters relevant to the validation of computational modeling and with consideration to flight-relevant, though not flight-scale, environments. PFGT is a sub-scale, intrusive half-plane, inert-gas test conducted in a 15 foot-diameter vacuum chamber using a supersonic, heated, gaseous nitrogen plume. Tests were conducted with six regolith simulants, varying in complexity from spherical glass beads to BP-1 lunar soil simulant, and varied vacuum chamber ambient pressures to simulate Martian and lunar conditions. Nozzle height and mass flow rate were also varied to observe PSI behaviors and transitions of interest. Three high speed cameras captured crater formation and ejecta behavior during each test. An overview of this experiment is presented along with preliminary observations and analysis.

Wesley A Chambers↗

NASA NTRSDate not supplied

A Reynolds-Averaged Navier-Stokes Perspective for the High Lift Common Research Model Using the LAVA Framework

An in-depth assessment of the High Lift-Common Research Model (HL-CRM) aerodynamic performance is made using a Reynolds-Averaged Navier-Stokes (RANS) methodology. Results presented here were produced in support of the 4th AIAA High Lift Prediction Workshop(HLPW-4), with additional simulation results and analysis used to support findings from the workshop. Mesh resolution, RANS closure models, and tunnel effects were among the sources of simulation sensitivity addressed, all in the pursuit of evaluating best-practice simulation methods for complex high-lift configurations. In general, free-air simulations using RANS yield accurate predictions of integrated loads in the pre-stall regime for the HL-CRM, while strong sensitivity to simulation method is observed near CLmax. Additionally, a study assessing changes in aerodynamic performance due to flap deflection angle indicated strong sensitivity to turbulence model closure and mesh resolution, particularly at the highest deflection setting. Several available corrections for the Spalart-Allmaras (SA) turbulence model were tested and generally introduced more error relative to the experiment in comparison to the baseline SA closure model. The Standard Menter Baseline Two-Equation (k-ωBSL) turbulence model was also explored, which arguably yielded results highly consistent with experiment, but at a substantially higher computational cost. Therefore, as a compromise between computational cost and accuracy, the baseline SA closure model was selected for additional HL-CRM studies that assess alternative solution methods. These strategies include “warm start” approaches, which initialize the simulation from a previously converged solution at a nearby angle of attack, unsteady calculations, and simulations that model the experimental wind tunnel. Results from these studies would reinforce the shortcomings of RANS in predicting aircraft performance at high-lift conditions, namely at high-αand highly loaded flap conditions, while also answering questions about appropriate modeling techniques to minimize the errors associated with RANS where possible

TTT↗

NASA NTRS2004

High-Fidelity Full System Simulations

High-fidelity full system simulations have the potential for revolutionizing the way complex systems, such as propulsion systems for aerospace vehicles, are designed, developed, manufactured, and operated. Significant time and cost savings will result from simulations that will resolve deleterious component interactions early in the design process. In addition, innovative new system configurations will result from the use of new tools that enable designers to challenge traditional rules and practices. The major challenges to developing and implementing high-fidelity systems simulations are in reducing the time and effort required to build, execute, and analyze data for the high complex simulations. In addition, large scale testing with unique instrumentation is required to validate the simulations. The solution to these problems reside in the application of advanced information technologies to assist the user to effectively manage, process, and synthesize the vast amount of data. The following presentation describes in more detail the benefits of high-fidelity full system simulations, the challenges to developing and implementing large scale simulations, and one approach that is being followed by the NASA Glenn Research Center to overcome these challenges. In addition, topics for discussion by the panel and audience are suggested.

Lytle, John K.↗

DOE OSTI2023

Graph-based quantum response theory and shadow Born–Oppenheimer molecular dynamics

Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations [A. M. N. Niklasson et al., J. Chem. Phys. 144, 234101 (2016)] is adapted to the most recent shadow potential formulations of extended Lagrangian Born–Oppenheimer molecular dynamics, including fractional molecular-orbital occupation numbers [A. M. N. Niklasson, J. Chem. Phys. 152, 104103 (2020) and A. M. N. Niklasson, Eur. Phys. J. B 94, 164 (2021)], which enables stable simulations of sensitive complex chemical systems with unsteady charge solutions. The proposed formulation includes a preconditioned Krylov subspace approximation for the integration of the extended electronic degrees of freedom, which requires quantum response calculations for electronic states with fractional occupation numbers. For the response calculations, we introduce a graph-based canonical quantum perturbation theory that can be performed with the same natural parallelism and linear scaling complexity as the graph-based electronic structure calculations for the unperturbed ground state. Further, the proposed techniques are particularly well-suited for semi-empirical electronic structure theory, and the methods are demonstrated using self-consistent charge density-functional tight-binding theory both for the acceleration of self-consistent field calculations and for quantum-mechanical molecular dynamics simulations. Graph-based techniques combined with the semi-empirical theory enable stable simulations of large, complex chemical systems, including tens-of-thousands of atoms.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2014

Beneficiation of Stillwater Complex Rock for the Production of Lunar Simulants

The availability of pure, high calcium plagioclase would be a significant asset in any attempt to manufacture high-quality lunar simulants. A suitable plagioclase product can be obtained from materials obtained from the Stillwater Complex of Montana. The access, geology, petrology, and mineralogy of the relevant rocks and the mill tailings are described here. This study demonstrates successful plagioclase recovery from mill tailings produced by the Stillwater Mine Company. Hydrogen peroxide was used to remove carboxymethyl cellulose from the tailing. The characteristics of the plagioclase products are shown and locked grains are identified as a limit to achievable purity. Based on the experimental results, flowsheets were developed showing how these resources could be processed and made into 'separates' of (1) high calcium plagioclase and (2) orthopyroxene/clinopyroxene with the thought that they would be combined later to make simulant.

Rickman, D. L.↗

DOE OSTI2021

Characterizing Impacts of Storage Faults on HPC Applications: A methodology and insights

In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses, which urges high-performance computing (HPC) platforms to equip with more advanced storage infrastructures such as solid-state disks (SSDs). While SSDs offer high-performance I/O, it remains unclear about the reliability challenges faced by the HPC applications under the SSD-related failures, in particular, failures resulting in data corruptions. The goal of this paper is to understand the impact of SSD-related data corruptions on the behaviors of complex HPC applications. To this end, we propose FFIS, a FUSE-based fault injection framework that systematically introduces storage faults into the application layer to model the errors originated from SSDs. FFIS is able to plant different I/O related faults into the data returned from underlying file systems, which also enables the investigation on the error resilience characteristics of the scientific file format for the first time. We demonstrate the use of FFIS with three representative real HPC applications, show how each application reacts to the data corruptions, and provide insights on the error resilience of the widely-adopted HDF5 file format for the HPC applications.

Fang, Bo↗

NASA NTRS2016

DSENDS: multi-mission flight dynamics simulator for NASA missions

Increasingly complex space missions require powerful and ﬂexible simulation environments in order to design, analyze, and operate the missions. NASA’s Jet Propulsion Laboratory has created the DSENDS simulation environment that addresses these needs for a wide range of space missions. In this paper, we describe the DSENDS simulation environment and the key architectural components that make DSENDS a useful simulation and analysis framework. We also overview a variety of NASA missions and ﬂight experiments that are using DSENDS.

Sklyanskiy, Evgeniy↗

NASA NTRSDate not supplied

Development of the Artemis Distributed Simulation FOMs

The National Aeronautics and Space Administration (NASA) is formulating and developing the Artemis Program, a collaboration with domestic commercial and international partners that will establish a long term human presence on the Moon and extend human exploration beyond the Earth-Moon system ahead of exploring Mars. These Artemis partners are developing a portfolio of space and surface systems to support human missions to the lunar surface and beyond. The Artemis systems will provide the mobility, habitation, and logistics infrastructure that will support human exploration and foster robust scientific investigations. Each partner will contribute one or more elements to the Artemis Program with NASA having the overarching responsibility for defining the Artemis architecture and guiding the integration of this complex system of space systems. To successfully accomplish this audacious task, NASA will rely on the development and execution of many complex models and simulations. Many of these simulations will be provided by the Artemis partners. While each of these simulations will provide important insight into the characteristics and performance of an associated system, individually they will not provide insight into the integrated performance of the architecture and the system of systems working in concert to execute a given Artemis mission. To address this need, NASA is developing a distributed simulation capability called the Artemis Distributed Simulation (ADS). ADS’s distributed nature supports the complex aggregation of constituent Artemis element simulations. Artemis partner simulations will be able to join into an ADS-based distributed simulation and interact with other Artemis element simulations while limiting the exposure of proprietary designs and data. ADS is defining a distributed simulation capability built on international simulation interoperability standards, specifically the High Level Architecture (HLA) and the Space Reference Federation Object Model (SpaceFOM). While HLA and SpaceFOM provide the substantive necessary technology basis for ADS, additional common datatypes, message definitions, and execution protocols are required. These extensions constitute the ADS Federation Object Model (FOM). This paper describes the fundamental architectural elements of ADS and the FOM extensions needed to support the complex nature of the Artemis Program. This includes the examination of the ADS FOM modules, ADS base datatypes, ADS SpaceFOM Object Class extensions, new ADS Object Classes, and new ADS Interaction Classes.

HLA↗

NASA NTRSDate not supplied

Development of the Artemis Distributed Simulation FOMs

HLA↗

DOE OSTI2023

Molecular Symmetry in VQE: A Dual Approach for Trapped-Ion Simulations of Benzene

Understanding complex chemical systems—such as biomolecules, catalysts, and novel materials—is a central goal of quantum simulations. Near-term strategies hinge on the use of variational quantum eigensolver (VQE) algorithms combined with a suitable ansatz. However, straightforward application of many chemically-inspired ansatze yields prohibitively deep circuits. In this work, we employ several circuit optimization methods tailored for trapped-ion quantum devices to enhance the feasibility of intricate chemical simulations. The techniques aim to lessen the depth of the unitary coupled cluster with singles and doubles (uCCSD) ansatz's circuit compilation, a considerable challenge on current noisy quantum devices. Furthermore, we use symmetry-inspired classical post-selection methods to further refine the outcomes and minimize errors in energy measurements, without adding quantum overhead. Our strategies encompass optimal mapping from orbital to qubit, term reordering to minimize entangling gates, and the exploitation of molecular spin and point group symmetry to eliminate redundant parameters. The inclusion of error mitigation via post-selection based on known molecular symmetries improves the results to near milli-Hartree accuracy. These methods, when applied to a benzene molecule simulation, enabled the construction of an 8-qubit circuit with 69 two-qubit entangling operations, pushing the limits for variational quantum eigensolver (VQE) circuits executed on quantum hardware to date. 1 1 This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-000R22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan(https://energy.gov/doe-public-access-plan).

Goings, Joshua↗

DOE OSTI2025

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1970

Program automated documentation methods

The mission analysis and trajectory simulation program is summarized; it provides an understanding of the size and complexity of one simulation for which documentation is mandatory. Programs for automating documentation of subroutines, flow charts, and internal cross reference information are also included.

Lanzano, B. C.↗

NASA NTRS2001

Locating Anomalies in Complex Data Sets Using Visualization and Simulation

The research goals are to create a simulation framework that can accept any combination of models written at the gate or behavioral level. The framework provides the ability to fault simulate and create scenarios of experiments using concurrent simulation. In order to meet these goals we have had to fulfill the following requirements. The ability to accept models written in VHDL, Verilog or the C languages. The ability to propagate faults through any model type. The ability to create experiment scenarios efficiently without generating every possible combination of variables. The ability to accept adversity of fault models beyond the single stuck-at model. Major development has been done to develop a parser that can accept models written in various languages. This work has generated considerable attention from other universities and industry for its flexibility and usefulness. The parser uses LEXX and YACC to parse Verilog and C. We have also utilized our industrial partnership with Alternative System's Inc. to import vhdl into our simulator. For multilevel simulation, we needed to modify the simulator architecture to accept models that contained multiple outputs. This enabled us to accept behavioral components. The next major accomplishment was the addition of "functional fault models". Functional fault models change the behavior of a gate or model. For example, a bridging fault can make an OR gate behave like an AND gate. This has applications beyond fault simulation. This modeling flexibility will make the simulator more useful for doing verification and model comparison. For instance, two or more versions of an ALU can be comparatively simulated in a single execution. The results will show where and how the models differed so that the performance and correctness of the models may be evaluated. A considerable amount of time has been dedicated to validating the simulator performance on larger models provided by industry and other universities.

Panetta, Karen↗

NASA NTRS2012

Does Dynamical Downscaling Introduce Novel Information in Climate Model Simulations of Recipitation Change over a Complex Topography Region?

Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

Tselioudis, George↗

DOE OSTI2024

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Pore-scale simulation of gas flow in microscopic permeable media with complex geometries

Lattice Boltzmann method (LBM) is an efficient tool to perform direct numerical simulation of gas flow in micro-size pores. Despite great advances in LBM and its use in describing gas flow in micro-size channels in slip and transitional flow regimes, exploring formulations that are able to capture flow behavior in domains with complex boundary geometries remains a challenging task. As a result, the impact of complexities in pore structures on gas flow may not be fully explored using LBM. In this study, we propose to use the combined bounce-back and Maxwellian diffusive reflection scheme to capture the slip velocity with a new set of slip coefficients. Optimal values of slip coefficients are determined using a gradient based method, where the results from the linearized Boltzmann equation is used as the reference solution. The proposed formulation is further validated against predictions from molecular dynamics simulation in the presence of complex geometries by introducing obstacles of different shapes in straight channels. LBM with the proposed boundary treatment is then used to investigate gas flow in a synthetic microscopic permeable medium. Here, results indicate that gas exhibits different flow configurations as Knudsen number varies, and apparent gas permeability appears to have up to a second-order dependency on the reciprocal mean pressure in slip and transitional flow regimes.

03 NATURAL GAS↗

DOE OSTI2021

Simulation of Low-Rm physics in complex geometries on GPUs with LGR

Efficient modeling of low magnetic Reynolds number (low-Rm) magnetohydrodynamics is often challenging and requires the implementation of innovative techniques to avoid key barriers experienced with prior approaches. We detail a new paradigm for first-principles simulation of the solution to the low-Rm governing equations in complex geometries. As a result of a number of innovative numerical advances, the next-generation GPU (graphics processing unit) accelerated physics code LGR has been successfully applied to the modeling of exploding wire problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗