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NASA NTRS2017

First benchmark of the Unstructured Grid Adaptation Working Group

Unstructured grid adaptation is a technology that holds the potential to improve the automation and accuracy of computational fluid dynamics and other computational disciplines. Difficulty producing the highly anisotropic elements necessary for simulation on complex curved geometries that satisfies a resolution request has limited this technology's widespread adoption. The Unstructured Grid Adaptation Working Group is an open gathering of researchers working on adapting simplicial meshes to conform to a metric field. Current members span a wide range of institutions including academia, industry, and national laboratories. The purpose of this group is to create a common basis for understanding and improving mesh adaptation. We present our first major contribution: a common set of benchmark cases, including input meshes and analytic metric specifications, that are publicly available to be used for evaluating any mesh adaptation code. We also present the results of several existing codes on these benchmark cases, to illustrate their utility in identifying key challenges common to all codes and important differences between available codes. Future directions are defined to expand this benchmark to mature the technology necessary to impact practical simulation workflows.

Ibanez, Daniel↗

NASA NTRS2021

Comparing Commercial and Research Computational Fluid Dynamic Codes Using High-Order Workshop Benchmark Problems

The commercial computational fluid dynamic (CFD) code ANSYS Fluent and multiple research CFD codes (ez4d with uses the conservation element and solution element (CESE) method and codes that use the flux reconstruction (FR) method) were tested using three different benchmark problems from the International Workshop for High-Order CFD Methods. The benchmark problems included the transonic Ringleb flow, vortex transport by uniform flow, and laminar boundary layer on a flat plate. Simulation results from all three benchmark problems showed that the Fluent solutions had less error than the ez4d solutions for a given degree of freedom. As expected, both the Fluent and ez4d solutions had larger errors for a given degree of freedom than the simulations that used the FR method because both Fluent and ez4d utilized a second-order scheme whereas the FR codes utilized a fourth-order scheme.

CFD↗

NASA NTRSDate not supplied

Benchmark Models for Classification of Radiation Type Induced in Immune Cells

NASA Biological and Physical Sciences and the Science Mission Directorate have published a benchmark dataset of mouse immune cells subjected to radiation-induced DNA damage. The dataset comprises ML-ready microscopic imagery of said cells, including labels indicating radiation type and dose. The machine learning team at NASA Interagency Implementation and Advanced Concept Team (IMPACT) created multiple benchmark models. Initially, we conducted a preliminary analysis using thresholding. The algorithm used thresholds on average brightness of the available images to classify them into their respective radiation type. We also tested machine learning approaches. Convolutional Neural Networks (CNN) emerged as the best-performing model. This poster presents the benchmark scores obtained by the models.

Vishal Perekadan↗

NASA NTRS2021

Benchmarking Planning Applications on the Qualcomm Snapdragon

We benchmark several space planning/scheduling applications on the Qualcomm Snapdragon 855 Handheld Development Kit (HDK), a high performance embedded processor used in many mobile phones.We are flying 2 Snapdragon HDKs onboard the International Space Station (ISS) where they are hosted by the the Spaceborne Computer-2 by Hewlett Packard Enterprise linked by USB and 12V power delivery. We run computational benchmarks using three planner/ schedulers that are used for several space missions: Multi- Mission Executive (MEXEC), Compressed Large-scale Activity Scheduling and Planning (CLASP), and M2020 Ground Scheduler (Surrogate). We compare the Snapdragon performance to a performance baseline on Linux workstations. In addition, we are currently working on benchmarking the same applications on other space flight processors, such as the LEON4 Processor on the Sabertooth card, the LEON3 Processor on the Sphinx card, and the RAD750 processor.

Chien, Steve↗

NASA NTRSDate not supplied

Investigations of an Aeroelastic Optimization Benchmark Problem with MPhys and FUN3D

High-fidelity aeroelastic optimization capabilities are becoming more common in recent years. In this field, researchers typically present results on the design problems of greatest interest to them. The lack of consistency with respect to baseline configurations, design variables, objectives and constraints, etc., makes it difficult to compare approaches and creates an obstacle for the community to work together to advance the state of the art. The High-Fidelity Aeroelastic Optimization Benchmark Working Group has been established to create and study a series of benchmark aeroelastic optimization problems that the community can utilize to compare methods on the same optimization problem. This paper presents optimization results from NASA Langley Research Center for the first benchmark case of this series with analysis based on MPhys, a multiphysics library for OpenMDAO, and FUN3D, an unstructured computational fluid dynamics suite of tools. For the optimization case presented, it is demonstrated that a progression of increasing aerodynamic model fidelity reduces the wall time required to complete the optimization.

Aeroelasticity↗

NASA NTRSDate not supplied

Investigations of an Aeroelastic Optimization Benchmark Problem with MPhys and FUN3D

CFD↗

NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗

NASA NTRS2016

Final Report of the NASA Office of Safety and Mission Assurance Agile Benchmarking Team

To ensure that the NASA Safety and Mission Assurance (SMA) community remains in a position to perform reliable Software Assurance (SA) on NASAs critical software (SW) systems with the software industry rapidly transitioning from waterfall to Agile processes, Terry Wilcutt, Chief, Safety and Mission Assurance, Office of Safety and Mission Assurance (OSMA) established the Agile Benchmarking Team (ABT). The Team's tasks were: 1. Research background literature on current Agile processes, 2. Perform benchmark activities with other organizations that are involved in software Agile processes to determine best practices, 3. Collect information on Agile-developed systems to enable improvements to the current NASA standards and processes to enhance their ability to perform reliable software assurance on NASA Agile-developed systems, 4. Suggest additional guidance and recommendations for updates to those standards and processes, as needed. The ABT's findings and recommendations for software management, engineering and software assurance are addressed herein.

Software Assurance↗

NASA NTRS2021

IFAR Liner Benchmark Challenge #1 - DLR Impedance Eduction of Uniform and Axially Segmented Liners and Comparison with NASA Results

This paper presents the contribution from the German Aerospace Center (DLR) to the first liner benchmark challenge under the framework of the International Forum for Aviation Research (IFAR).Therefore, two sets of acoustically damping wall treatment, called ’liner samples’, have been produced by additive manufacturing based on the design data provided by NASA coordinating this benchmark. These liner samples have been integrated and acoustically characterized in the liner flow test facility DUCT-R at DLR Berlin as well as in the liner flow test facility GFIT at NASA Langley. Besides the dissipation coefficients and the axial pressure profiles, the liner wall impedance was educed by first determining the axial wave numbers and then applying a straightforward method based on the one-dimensional Convected Helmholtz Equation. Finally, the comparison of the liner impedance values to the NASA results show a fairly good agreement.

liner characterization↗

NASA NTRS1985

The NAS kernel benchmark program

A collection of benchmark test kernels that measure supercomputer performance has been developed for the use of the NAS (Numerical Aerodynamic Simulation) program at the NASA Ames Research Center. This benchmark program is described in detail and the specific ground rules are given for running the program as a performance test.

Bailey, D. H.↗

NASA NTRS1986

Benchmarks of programming languages for special purposes in the space station

Although Ada is likely to be chosen as the principal programming language for the Space Station, certain needs, such as expert systems and robotics, may be better developed in special languages. The languages, LISP and Prolog, are studied and some benchmarks derived. The mathematical foundations for these languages are reviewed. Likely areas of the space station are sought out where automation and robotics might be applicable. Benchmarks are designed which are functional, mathematical, relational, and expert in nature. The coding will depend on the particular versions of the languages which become available for testing.

Knoebel, Arthur↗

NASA NTRS1986

Benchmarking hypercube hardware and software

It was long a truism in computer systems design that balanced systems achieve the best performance. Message passing parallel processors are no different. To quantify the balance of a hypercube design, an experimental methodology was developed and the associated suite of benchmarks was applied to several existing hypercubes. The benchmark suite includes tests of both processor speed in the absence of internode communication and message transmission speed as a function of communication patterns.

Grunwald, Dirk C.↗

NASA NTRS1986

Toward real-time performance benchmarks for Ada

Benchmarks are developed to measure the Ada notion of time, the Ada features believed important to real-time performance, and other time-related features that are not part of the language, but are part of the run-time system; these benchmarks are then applied to the language and run-time system, and the results evaluated.

Clapp, Russell M.↗

NASA NTRS1987

A benchmark for galactic cosmic ray transport codes

A nontrivial analytic benchmark solution for galactic cosmic ray transport is presented for use in transport code validation. Computational accuracy for a previously-developed cosmic ray transport code is established to within one percent by comparison with this exact benchmark. Hence, solution accuracy for the transport problem is mainly limited by inaccuracies in the input spectra, input interaction databases, and the use of a straight ahead/velocity-conserving approximation.

Wilson, John W.↗

NASA NTRS1988

A benchmark for galactic cosmic-ray transport codes

Wilson, John W.↗

NASA NTRS1988

Benchmark solutions for the galactic ion transport equations with spatial and energy coupling

In order to anticipate future space shielding requirements, NASA has initiated an effort to formulate computational methods to simulate radiation effects in space. As part of the program, numerical transport algorithms have been developed for the deterministic Boltzman equation describing galactic cosmic ray (GCR) interactions with matter. It thus becomes necessary to assess the accuracy of proposed deterministic algorithms. For this reason, analytical benchmark solutions to mathematically tractable galactic cosmic ray equations have recently been obtained. Even though these problems involve simplifying assumptions of the associated physics, they still contain the essential features of the basic transport processes. The solutions obtained are features of the basic transport processes. The solutions obtained are compared to results from numerical algorithms in order to ensure proper coding and to provide a measure of the accuracy of the numerical methods used in the algorithm. For the first time, mathematical methods have been applied to the galactic ion transport (GIT) equations in the straight ahead approximation with constant nuclear properties. The approach utilizes a Laplace transforms inversion yielding a closed form benchmark solution which is also computationally efficient.

Ganapol, Barry D.↗

NASA NTRS1989

Benchmark solutions for the galactic ion transport equations: Energy and spatially dependent problems

Nontrivial benchmark solutions are developed for the galactic ion transport (GIT) equations in the straight-ahead approximation. These equations are used to predict potential radiation hazards in the upper atmosphere and in space. Two levels of difficulty are considered: (1) energy independent, and (2) spatially independent. The analysis emphasizes analytical methods never before applied to the GIT equations. Most of the representations derived have been numerically implemented and compared to more approximate calculations. Accurate ion fluxes are obtained (3 to 5 digits) for nontrivial sources. For monoenergetic beams, both accurate doses and fluxes are found. The benchmarks presented are useful in assessing the accuracy of transport algorithms designed to accommodate more complex radiation protection problems. In addition, these solutions can provide fast and accurate assessments of relatively simple shield configurations.

Ganapol, Barry D.↗

NASA NTRS1989

Benchmarking Ada tasking on tightly coupled multiprocessor architectures

The development of benchmarks and performance measures for parallel Ada tasking is reported with emphasis on the macroscopic behavior of the benchmark across a set of load parameters. The application chosen for the study was the NASREM model for telerobot control, relevant to many NASA missions. The results of the study demonstrate the potential of parallel Ada in accomplishing the task of developing a control system for a system such as the Flight Telerobotic Servicer using the NASREM framework.

Collard, Philippe↗