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NASA NTRS2019

Verification Benchmarks and Validation of MAT261 for High Energy Dynamic Impact Applications

Advanced computational methods for composite structures can enable smarter testing and potentially certification by analysis. These methods, known as progressive damage and failure analysis (PDFA) methods, can predict lamina level mechanics including failure and subsequent propagation. When introduced into a commercial off the shelf finite element solver such as ABAQUS, LS-DYNA, or ANSYS, it enables end users to effectively exercise PDFA methods; however, it requires an understanding of the assumed mechanics and underlying coded response. In this paper, verification benchmarks developed under the NASA Advanced Composite Consortium for a class of PDFA methods known as continuum damage mechanics approaches are applied to the native LS-DYNA material model MAT261. As a result of the verification, an instability was discovered and subsequently corrected with an engineering solution. The results of the preliminary MAT261 simulations for high energy dynamic impact and the engineering solution are compared and a discussion about the significance is presented.

Molitor, Matthew↗

NASA NTRS2020

Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres

While most of traditional Earth-atmosphere satellite remote sensing relies on radiative transfer in the plane parallel geometry, effects of sphericity are important at high sun and view zenith angles. Broad understanding of these effects is limited and, contrary to the plane-parallel case, finding accurate numerical results to test spherical RT codes is not easy. This paper aims to partially fill in this gap. Using the full-spherical RT code MYSTIC (Monte Carlo), and the plane-parallel RT code VLIDORT (discrete ordinates) corrected for atmospheric sphericity in the single and multiple scattering, we reproduced with better accuracy and extended the benchmark results by Adams & Kattawar [1978].

spherical atmospheres↗

NASA NTRSDate not supplied

Benchmarking and Performance of the NASA Multiscale Analysis Tool

The NASA Multiscale Analysis Tool (NASMAT) is as a “plug and play,” software package which utilizes multiscale recursive micromechanics as a platform for massively multiscale modeling of hierarchical materials and structures subjected to thermomechanical. This paper is intended to give an overview of the design of NASMAT and how the design supports modularity, upgradability and maintainability, interoperability, and utility. First, the software architecture and hierarchy will be explored. Details on each of the 11 NASMAT procedures and the arrangement of NASMAT data will be presented. Application program interfaces (APIs) that were developed to facilitate the communication of NASMAT with other programs will be described. The intended application for NASMAT is massively multiscale modeling on high performance computing systems. As such, results benchmarking the performance of the integration of NASMAT with the Abaqus commercial finite element method software are also presented.

Multiscale Modeling↗

NASA NTRS2021

Efficiency of Mixed-Element USM3D for Benchmark Three-Dimensional Flows

The unstructured, mixed-element, cell-centered, finite-volume flow solver USM3D is enhanced with new capabilities such as line generation for general unstructured grids and optimization of the iterative solver. The efficiency of the new developments is assessed in a massively parallel environment. The assessments are conducted using a baseline method and the recent hierarchical adaptive nonlinear iteration method framework. Three benchmark turbulent flows, namely, a subsonic separated flow around a three-dimensional hemisphere cylinder configuration, a transonic flow around the ONERA M6 wing, and a supersonic flow through a square duct are considered.

Mohagna J Pandya↗

NASA NTRSDate not supplied

Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

Increasingly autonomous Advanced Air Mobility (AAM) vehicles will be required to handle diverse conditions with limited human intervention. Intelligent contingency management (iCM) approaches are under development to address how automated agents can handle unforeseen, unplanned, and unanticipated events. Benchmark scenario is needed to test the maturity of the developed iCM tools and techniques.

Jon Holbrook↗

NASA NTRSDate not supplied

QuAIL Tools for Benchmarking, Analysis and Quantum Algorithm Development

HybridQ and PySA are open-source tools developed by NASA to support benchmarking, analysis and quantum algorithm development in areas such as simulation, optimization and machine learning. These tools leverage classical hardware acceleration via high-performance computing CPU and GPU architectures and support high-performance computing. HybridQ is a highly extensible platform designed to provide a common framework to integrate multiple state-of-the-art techniques to simulate large scale quantum circuits. PySA is an extensible platform to optimize a classical cost function. We provide an outline of each of these open-source tools and highlight projects using each of these tools in contexts of simulation, optimization and machine learning.

Quantum Computing↗

NASA NTRS2022

SatNet: A Benchmark for Satellite Scheduling Optimization

Satellites provide essential services such as networking and weather tracking, and the number of near-earth and deep space satellites are expected to grow rapidly in the coming years. Communications with terrestrial ground stations is one of the critical functionalities of any space mission. Satellite scheduling is a problem that has been scientifically investigated since the 1970s. A central aspect of this problem is the need to consider resource contention and satellite visibility constraints as they require line of sight. Due to the combinatorial nature of the problem, prior solutions such as linear programs and evolutionary algorithms require extensive compute capabilities to output a feasible schedule for each scenario. Machine learning based scheduling can provide an alternative solution by training a model with historical data and generating a schedule quickly with model inference. We present SatNet, a benchmark for satellite scheduling optimization based on historical data from the NASA Deep Space Network. We propose formulation of the satellite scheduling problem as a Markov Decision Process and use reinforcement learning (RL) policies to generate schedules. The nature of constraints imposed by SatNet differ from other combinatorial optimization problems such as vehicle routing studied in prior literature. Our initial results indicate that RL is an alternative optimization approach that can generate candidate solutions of comparable quality to existing state-of-the-practice results. However, we also find that RL policies overfit to the training dataset and do not generalize well to new data, thereby necessitating continued research on reusable and generalizable agents.

Wilson, Brian↗

NASA NTRS2022

Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions

As some space missions become more challenging due to new environments, greater distances, or more limited size, weight, and power (SWaP) constraints, spacecraft avionics must adapt to allow the spacecraft to be more autonomous and agile---eliminating the Spacecraft-Earth-Spacecraft feedback loop whenever possible. Prime examples of such missions include Aerobots (such as Ingenuity with extremely low SWaP constraints and demanding signal/image processing during flight) and landers in possibly hostile environments (such as a Europa lander mission, with limited communication capacity, high latency, and constrained power budget). To address these challenges, JPL worked with Qualcomm to demonstrate the use of their Snapdragon 801 system-on-chip (SoC) onboard the Ingenuity Helicopter on Mars. The Qualcomm Snapdragon SoC contains various subsystems, including an ARM cluster, a Graphics processing unit, a Digital Signal Processing subsystem, a Neural Processing Engine, Image Signal Processing subsystem, among others. Since the success of Ingenuity, JPL is continuing to work with Qualcomm to address other applications of the Snapdragon SoC technology. This includes the deployment of two 855 Snapdragon development boards onboard the International Space Station (ISS) for successful in-situ benchmarking of applications in space (beyond those tested on Ingenuity). In this paper, we will examine the performance of various applications that have been identified to benefit from greater onboard computational capability. These applications include (among others): machine vision algorithms that are expected to be critical in autonomous entry-descent-and-landing scenarios and real-time Aerobot flight navigation; Hyperspectral compression algorithms; Synthetic Aperture Radar Processing along with various instrument processing algorithms. We discuss how the infusion of Qualcomm's Snapdragon SoC is capable of enabling missions that may not have been able to achieve their goals with traditional flight computing. In addition, we also show that for some algorithms, the software implementation on the Snapdragon SoC outperforms traditional FPGA implementations.

Cretu, Vlad↗

NASA NTRSDate not supplied

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months.

Allison Collow↗

NASA NTRS2023

Benchmark Performance Metrics of a Vane Propellant Management Device for a 0.15 m3 Liquid Hydrogen Tank

The use of cryogenic propellants has and will continue to play an integral role in manned-space exploration due the high specific impulses offered and its ubiquity through in-situ resource utilization. But guaranteeing vapor-free transfer of such low-surface tension liquids is difficult for traditional capillary-action propellant management devices (PMDs). Screen-channel liquid acquisition devices and compliant origami bladders are potential solutions, but to quantify the benefits these technologies offer, this paper present a cast study analyzing the performance metrics of an orthodox vane PMD as a benchmark for comparison. A 0.15 m3 liquid hydrogen tank at 20.3 K and 103 kPa was selected for study. Then assuming no body forces and no heat transfer (for simplicity), a steady-state 1-D differential equation was numerically solved in tandem with four possible wetted area configurations to yield an expulsion efficiency for a theoretically maximum inputted expulsion flow rate. Maximization of the flow rate was constrained by the onset of choked flow. Additional inputs, including vane height and vane number, were parametrically varied between 0.1 – 10 cm and 4 – 28 vanes, respectively.

Liquid Acquisition Device↗

NASA NTRSDate not supplied

Benchmark Problem for Autonomous Urban Air Mobility

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

NASA NTRSDate not supplied

Community Benchmark Problem for Intelligent Contingency Management

autonomy↗

NASA NTRSDate not supplied

Transonic Limit Cycle Oscillations of the Benchmark Supercritical Wing

This paper considers transonic flutter mechanisms of the Benchmark Supercritical Wing, a model under study in the Aeroelastic Prediction Workshop series. Flutter boundaries are mapped out across an angle of attack sweep at Mach 0.8, utilizing both time-domain and linearized frequency-domain solvers, manual meshes and adapted meshes, and various governing equations. With increased angle of attack, linearized and finite amplitude flutter predictions exhibit differences above 3◦ as the flow begins to separate; the latter predictions are found to be driven by subcritical limit cycle oscillations whose strength increases with angle of attack. Moderate perturbation values provide a stability boundary at 5◦ which matches the experimental data, but it is not clear how the experimental perturbation, from one test condition to the next, can be reasonably characterized.

Bret Stanford↗

NASA NTRSDate not supplied

Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗

DOE OSTI2014

Comparison of Homogeneous and Heterogeneous CFD Fuel Models for Phase I of the IAEA CRP on HTR Uncertainties Benchmark

Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Python/Lua Benchmarks

This is an adaptation of the pre-existing Scimark benchmark code to a variety of Python and Lua implementations. It also measures performance of the Fparser expression parser and C and C++ code on a variety of simple scientific expressions.

Busby, L.↗

DOE OSTI2015

Processor Emulator with Benchmark Applications

A processor emulator and a suite of benchmark applications have been developed to assist in characterizing the performance of data-centric workloads on current and future computer architectures. Some of the applications have been collected from other open source projects. For more details on the emulator and an example of its usage, see reference [1].

Lloyd, G. Scott↗

DOE OSTI2016

VERA Benchmarking Results for Watts Bar Nuclear Plant Unit 1 Cycles 1-12

The Consortium for Advanced Simulation of Light Water Reactors, the first US DOE Energy Innovation Hub, is developing and deploying a suite of directly coupled, high-fidelity physics methods known as VERA for performing engineering analyses of operating commercial nuclear power reactors. The centerpiece of VERA is the reactor core simulator, which employs the direct coupling of a 3D neutron transport code, a two-phase sub-channel thermal-hydraulic code, and a well-known isotopic depletion and decay code. Together these tools represent the most rigorous reactor simulator available today. Recently added capabilities include the depletion, shuffling, and discharge of fuel assemblies, enabling VERA to simulate multiple fuel cycles of operation. To demonstrate this capability, VERA has been used to simulate over 18 years of operation of TVA’s Watts Bar Nuclear Unit 1, and the results of these calculations have been used to quantify its performance in an industry-grade benchmarking activity. Comparisons are made with measured critical boron concentrations, control bank reactivity worths, isothermal temperature coefficients, and in-core neutron flux distributions. These results demonstrate that the advanced tools in VERA are capable for application to practical and common industrial problems.

Godfrey, Andrew T↗