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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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At least 1,765 records · Page 98

Composite Nanomechanics: A Mechanistic Properties Prediction

A unique mechanistic theory is described to predict the properties of nanocomposites. The theory is based on composite micromechanics with progressive substructuring down to a nanoscale slice of a nanofiber where all the governing equations are formulated. These equations have been programmed in a computer code. That computer code is used to predict 25 properties of a mononanofiber laminate. The results are presented graphically and discussed with respect to their practical significance. Most of the results show smooth distributions. Results for matrix-dependent properties show bimodal through-the-thickness distribution with discontinuous changes from mode to mode.

Chamis, Christos C.↗

Mercury Toolset for Spatiotemporal Metadata

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Wilson, Bruce E.↗

Heatshield Entry Modeling Using a Design, Analysis, and Optimization Toolbox

The Mars Science Laboratory (MSL) was protected during its Mars atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA). PICA is a lightweight carbon fiber/polymeric resin material that offers excellent performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of atmospheric entry and material response. MEDLI recorded, among others, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase the capability of the Design, Analysis, and Optimization of Thermal Protection Materials (DAOTPM) software. DAO-TPM is a Python based framework that works as a link between mission design, aerothermal and radiative environment computation, Thermal Protection Systems (TPS) microstructure analysis, material response and optimization tools. The toolbox has a Graphical User Interface (GUI) that allows the user to build as well as run the various software and utilities used to design, analyze and optimize a heatshield during atmospheric entry.

Meurisse, Jeremie B. E.↗

HL-LHC Analysis With ROOT: ROOT Project Input to the HL-LHC Computing Review (Stage 2)

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Electronic Engineering Notebook: A software environment for research execution, documentation and dissemination

The electronic engineering notebook (EEN) consists of a free form research notebook, implemented in a commercial package for distributed hypermedia, which includes utilities for graphics capture, formatting and display of LaTex constructs, and interfaces to the host operating system. The latter capability consists of an information computer-aided software engineering (CASE) tool and a means to associate executable scripts with source objects. The EEN runs on Sun and HP workstations. The EEN, in day-to-day use can be used in much the same manner as the sort of research notes most researchers keep during development of projects. Graphics can be pasted in, equations can be entered via LaTex, etc. In addition, the fact that the EEN is hypermedia permits easy management of 'context', e.g., derivations and data can contain easily formed links to other supporting derivations and data. The CASE tool also permits development and maintenance of source code directly in the notebook, with access to its derivations and data.

Moerder, Dan↗

Flow studies in close-coupled ventral nozzles for STOVL aircraft

Flow in a generic ventral nozzle system was studied experimentally and analytically with the PARC3D computational fluid dynamics program (a full Navier-Stokes equations solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. A generic model of a tailpipe with a rectangular ventral nozzle, about one-third of full size, was tested with unheated air at steady-state pressure ratios up to 4.0. Measurements showed about 5.5 percent flow-turning loss and reasonable nozzle performance coefficients. The flow turned more than the designed 90 deg, causing an aftward axial component in the total thrust. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. PARC3D graphic images are shown for comparison with the experiment photographs. The program successfully predicted internal flow patterns; it also computed thrust and discharge coefficients within 1 percent of measured values.

Mcardle, Jack G.↗

Integrated analysis capability for large space systems

The development of an integrated analysis computer program capable of performing the conceptual/preliminary structural system design analysis of large space systems is addressed. The integrated analysis capability (IAC) specifications include thermal/structural/controls integration, an emphasis on existing software and interactive graphics and I/O, a project size capability of 1 to 50 users (1 to 5 users concurrent), and the use of the FORTRAN '77 language. The advantages of the DISCOS and NASTRAN computer programs to the IAC are outlined and recommendations for other programs are made. Barriers to the development of the system arising from the interdisciplinary data flow are defined.

Vos, R. G.↗

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

59 BASIC BIOLOGICAL SCIENCES↗

Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolution of the Data Quality Monitoring and Prompt Processing System in the proto DUNE-SP experiment

The DUNE Collaboration currently operates an experimental program based at CERN which includes a beam test and an extended cosmic ray run of two large-scale prototypes of the massive Liquid Argon Time Projection Chamber (LArTPC) for the DUNE Far Detector. The volume of data collected by the single-phase prototype (protoDUNE-SP) amounts to 3PB and the sustained rate of data sent to mass storage is O(100) MB/s. Data Quality Monitoring was implemented by directing a fraction of the data stream to the protoDUNE prompt processing system (p3s) which is optimized for continuous low-latency calculation of the vital detector metrics and various graphics including event displays. It served a crucial role throughout the life cycle of the experiment. We present our experience in leveraging the CERN computing environment and operating the system over an extended period of time, while adapting to evolving requirements and computing platform.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. In this report, we evaluate the performance of the kernel using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board. Compared to the M506 module, the board provides more hardware resources for a larger design exploration space. The kernel performance is measured with the compute kernel throughput, an upper bound to the FPGA throughput. The report presents the experimental results in details. The Appendix lists the kernel source code.

97 MATHEMATICS AND COMPUTING↗

Evaluation of CHO Benchmarks on the Arria 10 FPGA using Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. Benchmarking of OpenCL-based framework is an effective way for analyzing the performance of system by studying the execution of the benchmark applications. CHO is a suite of benchmark applications that provides support for OpenCL [1]. The authors presented CHO as an OpenCL port of the CHStone benchmark. Using Altera OpenCL (AOCL) compiler to synthesize the benchmark applications, they listed the resource usage and performance of each kernel that can be successfully synthesized by the compiler. In this report, we evaluate the resource usage and performance of the CHO benchmark applications using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board that features an Arria 10 FPGA device. The focus of the report is to have a better understanding of the resource usage and performance of the kernel implementations using Arria-10 FPGA devices compared to Stratix-5 FPGA devices. In addition, we also gain knowledge about the limitations of the current compiler when it fails to synthesize a benchmark application.

97 MATHEMATICS AND COMPUTING↗

Modular Aero-Propulsion System Simulation

The Modular Aero-Propulsion System Simulation (MAPSS) is a graphical simulation environment designed for the development of advanced control algorithms and rapid testing of these algorithms on a generic computational model of a turbofan engine and its control system. MAPSS is a nonlinear, non-real-time simulation comprising a Component Level Model (CLM) module and a Controller-and-Actuator Dynamics (CAD) module. The CLM module simulates the dynamics of engine components at a sampling rate of 2,500 Hz. The controller submodule of the CAD module simulates a digital controller, which has a typical update rate of 50 Hz. The sampling rate for the actuators in the CAD module is the same as that of the CLM. MAPSS provides a graphical user interface that affords easy access to engine-operation, engine-health, and control parameters; is used to enter such input model parameters as power lever angle (PLA), Mach number, and altitude; and can be used to change controller and engine parameters. Output variables are selectable by the user. Output data as well as any changes to constants and other parameters can be saved and reloaded into the GUI later.

Parker, Khary I.↗

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gravity effects on Hawking radiation from charged black strings in Rastall theory

Highlights: • Introductory review of charged black strings in Rastall theory. • Detailed description of Hawking temperature. • Graphically Analysis of Hawking temperature. • Discuss the stability of charged black strings. The Rastall theory of gravity is the generalized form of the Einstein theory which describes the conservation law of energy and momentum tensor. In our work, we compute the charged black strings solution in the background of Rastall theory by applying the Newman–Janis approach. After computing the charged black strings solution in the background of Rastall theory, we study the thermodynamical property (i.e., Hawking temperature) for the charged black strings. Furthermore, we investigate the graphical representation of Hawking temperature via event horizon to check the stability conditions of charged black strings under the influence of Rastall theory. Moreover, we examine the modified Hawking temperature for charged black strings in Rastall theory by taking into account the quantum gravity effects. We also discuss the physical state of charged black strings under the effects of quantum gravity and spin parameter (appears due to Rastall theory in charged black strings solution).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Institute for Sustained Performance, Energy, and Resilience (SUPER): University of Utah Final Report

Over the course of this project, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) were exploiting a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry and material science. The computational systems underpinning this work increased in performance potential from tens to hundreds of Pflop/s, and evolved significantly from those in use at the beginning of the project in terms of available concurrency; wider use of accelerators such as graphics processing units(GPUs); and changes to the memory hierarchy including the incorporation of a new generation of persistent devices (e.g., phase change memory). To ensure that DOE's computational scientists can successfully exploit this emerging generation of high performance computing (HPC) systems, the University of Southern California (USC) assembled a broad team of computer scientists with the expertise to address the most pressing challenges of DOE's computing systems: (a) end-to-end performance optimization, including single-node performance, interprocessor communication, load balancing and I/O; (b) performance portability for heterogeneous systems, including accelerators; (c) minimizing energy consumption; (d) resilient computation; and, (e) exploiting new memory technology.

97 MATHEMATICS AND COMPUTING↗

On the application of betweenness centrality in chemical network analysis: Computational diagnostics and model reduction

Here, the concept of shortest path and betweenness centrality (BC) is introduced in combustion systems, with its application demonstrated in chemical network analysis and skeletal mechanism generation. After establishing the graphical representation of a chemical network for given pressure, temperature, and species concentrations, a metric BC is defined to rank the shortest paths passed by other nodes between the pair of source and target node, and as such captures the dominant indirect kinetic pathways between any pair of nodes in the network for computational diagnostics. As a result, the controlling pathways are retained by collecting the species with larger BC values. Such a notion then indicates that the index of importance of species could then be assigned based on their BC values to further guide skeletal mechanism generation. Unlike existing methods, the betweenness centrality approach takes into account of both the fluxes between species and their relative positioning within the chemical network. To demonstrate its potential utility to combustion studies, the approach was applied to the GRI-3.0, LLNL and USC-Mech II mechanisms to identify the important pathways in the chemical network at each local reaction state, and develop skeletal mechanisms from all reaction state samples in auto-ignition and perfectly stirred reactor (PSR) simulations. The performance of the BC ranking is compared to the methods of directed relation graph (DRG), DRG with error propagations (DRGEP) and sensitivity analysis (SA), and is shown to possess sufficient utility in producing skeletal mechanisms with good accuracy and flexibility for the cases studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗