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At least 577 records · Page 32

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗

An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees

Efficient data compression is becoming increasingly critical for storing scientific data because many scientific applications produce vast amounts of data. This paper presents an end-to-end algorithmic and software pipeline for data compression that guarantees both error bounds on primary data (PD) and derived data, known as Quantities of Interest (QoI).We demonstrate the effectiveness of the pipeline by compressing fusion data generated by a large-scale fusion code, XGC, which produces tens of petabytes of data in a single day. We demonstrate that the compression is conducted by setting aside computational resources known as staging nodes, and does not impact the simulation performance. For efficient parallel I/O, the pipeline uses ADIOS2, which many codes such as XGC already use for their parallel I/O. We show that our approach can compress the data by two orders of magnitude while guaranteeing high accuracy on both the PD and the QoIs. Further, the amount of resources required by compression is a few percent of the resources required by simulation while ensuring that the compression time for each stage is less than the corresponding simulation time.This pipeline consists of three main steps. The first step decomposes the data using domain decomposition into small subdomains. Each subdomain is then compressed independently to achieve a high level of parallelism. The second step uses existing techniques that guarantee error bounds on the primary data for each subdomain. The third step uses a post-processing optimization technique based on Lagrange multipliers to reduce the QoI errors for data corresponding to each subdomain. The Lagrange multipliers generated can be further quantized or truncated to increase the compression level. All of the above characteristics of our approach make it highly practical to apply on-the-fly compression while guaranteeing errors on QoIs that are critical to the scientists.

Banerjee, Tania↗

Biomass yield improvement in switchgrass through genomic prediction of flowering time

The seasonal timing of the transition from vegetative to reproductive growth has a major impact on biomass accumulation in switchgrass. Late-flowering switchgrass cultivars produce greater biomass, a critical trait for sustainable bioenergy production. Genomic prediction (GP) may allow rapid selection of late-flowering individuals with reduced time and expense for field evaluations. To evaluate GP, two flowering time traits (heading date and anthesis date) were collected on 1532 genotypes from four breeding populations: Midwest, Gulf, Atlantic, and Hybrid. These were sequenced using genotype-by-sequencing (530,792 single-nucleotide polymorphisms). Predictive ability of single-trait and multi-trait models were evaluated by cross-validation, by prediction of a progeny trial (n = 122), and through prediction of yield performance in a parallel experiment (n = 52). Predictive ability was not improved by sharing information among breeding groups. Overall, multi-trait models provided an advantage during cross-validation, but a smaller advantage during progeny prediction. Within populations, GP resulted in lower per-cycle progress than previously reported field evaluations (3.1 vs. 5.0 day –1 cycle –1 ). However, GP cycles are potentially much faster than field evaluations. When directly predicting biomass yield, the Hybrid training population had a predictive ability of 0.54–0.63. This reinforces the strong linkage between biomass yields in swards and flowering time. Furthermore, these results highlight the value of GP for rapid yield improvement in switchgrass, particularly in a breeding program designed to share information between biomass yield trials and low-cost flowering time evaluations.

09 BIOMASS FUELS↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

High-throughput native mass spectrometry as experimental validation for in silico drug design

In this project, we developed automated workflows for both experimental validation and computational prediction of protein-ligand interactions. The ultimate goal is to establish an integrated pipeline for high throughput design of inhibitors to enzymes relevant to all areas of biological research. Our experimental approach is based on native mass spectrometry (native MS), which measures accurate masses and quantify the relative abundance of protein-ligand complexes to define binding affinity. We set up an in-house built autosampler with highly flexible configurations to minimize the manual steps for high throughput native MS. In parallel, we also performed manual native MS to characterize the binding of substrates and inhibitors of SARS-Cov-2 nonstructural protein nsp10/16 in order to optimize the experimental parameters for future automation. On the computational side, we streamlined the pipeline to achieve minimal manual intervention for predicting enzyme inhibitors via simulation, using the same nsp10/16 system as an example. Using the native MS method we examined 8 top-ranked designed compounds, 2 of which showed weak binding of ~50 µM. The information from native MS experiment provided critical insights and the foundation for a fully integrated workflow for enzyme inhibitor design.

59 BASIC BIOLOGICAL SCIENCES↗

High Order Wall-Modeled Large-Eddy Simulation on Mixed Unstructured Meshes

In the present study, an algebraic equilibrium wall model previously developed for hexahedral elements is extended to handle mixed meshes including prismatic, tetrahedral, and pyramidal elements in the context of a discontinuous high-order method. This extension is needed for complex geometries, for which high-order mixed elements (e.g., tetrahedral and pyramidal elements) are often necessary near solid walls to avoid meshing challenges. Various design decisions are discussed to achieve the best performance on massively parallel CPU/GPU architectures for a production-level high-order large-eddy simulation solver based on the flux reconstruction/correction procedure via reconstruction method, hpMusic. The extension to other elements is first evaluated using a benchmark channel flow problem at various Reynolds numbers. After that, flow over the NASA high-lift Common Research Model (CRM-HL) from the 4th AIAA High-lift Prediction Workshop is computed to further test the new implementation. Computational results at the third- and fourth-order accuracies are compared with experimental data.

Engineering↗

Ice-nucleating particles in precipitation samples from the Texas Panhandle

Ice-nucleating particles (INPs) influence the formation of ice crystals in clouds and many types of precipitation. This study reports unique properties of INPs collected from 42 precipitation samples in the Texas Panhandle region from June 2018 to July 2019. We used a cold stage instrument called the West Texas Cryogenic Refrigerator Applied to Freezing Test system to estimate INP concentrations per unit volume of air (nINP) through immersion freezing in our precipitation samples with our detection capability of >0.006 INP L -1 . A disdrometer was used for two purposes: (1) to characterize the ground-level precipitation type and (2) to measure the precipitation intensity as well as size of precipitating particles at the ground level during each precipitation event. While no clear seasonal variations of n INP values were apparent, the analysis of yearlong ground-level precipitation observation as well as INPs in the precipitation samples showed some INP variations, e.g., the highest and lowest n INP values at -25°C both in the summer for hail-involved severe thunderstorm samples (3.0 to 1130 INP L -1 ), followed by the second lowest at the same temperature from one of our snow samples collected during the winter (3.2 INP L -1 ). Furthermore, we conducted bacteria community analyses using a subset of our precipitation samples to examine the presence of known biological INPs. In parallel, we also performed metagenomics characterization of the bacterial microbiome in suspended ambient dust samples collected at commercial open-lot livestock facilities (cattle feedyards hereafter) in the Texas Panhandle (i.e., the northernmost counties of Texas, also known as “West Texas”) to ascertain whether local cattle feedyards can act as a source of bioaerosol particles and/or INPs found in the precipitation samples. Some key bacterial phyla present in cattle feedyard samples appeared in precipitation samples. However, no known ice nucleation active species were detected in our samples. Overall, our results showed that cumulative n INP in our precipitation samples below -20°C could be high in the samples collected while observing > 10 mm h -1 precipitation with notably large hydrometeor sizes and an implication of cattle feedyard bacteria inclusion.

54 ENVIRONMENTAL SCIENCES↗

Experiments in spatial coherent optical filtering

Coherent optical techniques provide a means of processing entire pictures in parallel. Experiments were performed demonstrating the effectiveness of spatial frequency filtering in a coherent optical data processing system.

Larsen, R. K.↗

Study of a hybrid multispectral processor

A hybrid processor is described offering enough handling capacity and speed to process efficiently the large quantities of multispectral data that can be gathered by scanner systems such as MSDS, SKYLAB, ERTS, and ERIM M-7. Combinations of general-purpose and special-purpose hybrid computers were examined to include both analog and digital types as well as all-digital configurations. The current trend toward lower costs for medium-scale digital circuitry suggests that the all-digital approach may offer the better solution within the time frame of the next few years. The study recommends and defines such a hybrid digital computing system in which both special-purpose and general-purpose digital computers would be employed. The tasks of recognizing surface objects would be performed in a parallel, pipeline digital system while the tasks of control and monitoring would be handled by a medium-scale minicomputer system. A program to design and construct a small, prototype, all-digital system has been started.

Marshall, R. E.↗

Water system virus detection

A monitoring system developed to test the capability of a water recovery system to reject the passage of viruses into the recovered water is described. A nonpathogenic marker virus, bacteriophage F2, is fed into the process stream before the recovery unit and the reclaimed water is assayed for its presence. Detection of the marker virus consists of two major components, concentration and isolation of the marker virus, and detection of the marker virus. The concentration system involves adsorption of virus to cellulose acetate filters in the presence of trivalent cations and low pH with subsequent desorption of the virus using volumes of high pH buffer. The detection of the virus is performed by a passive immune agglutination test utilizing specially prepared polystyrene particles. An engineering preliminary design was performed as a parallel effort to the laboratory development of the marker virus test system. Engineering schematics and drawings of a fully functional laboratory prototype capable of zero-G operation are presented. The instrument consists of reagent pump/metering system, reagent storage containers, a filter concentrator, an incubation/detector system, and an electronic readout and control system.

Fraser, A. S.↗

Development of a preliminary design of a method to measure the effectiveness of virus exclusion during water process reclamation at zero-G

Organon Diagnostics has developed, under NASA sponsorship, a monitoring system to test the capability of a water recovery system to reject the passage of viruses into the recovered water. In this system, a non-pathogenic marker virus, bacteriophage F2, is fed into the process stream before the recovery unit and the reclaimed water is assayed for its presence. An engineering preliminary design has been performed as a parallel effort to the laboratory development of the marker virus test system. Engineering schematics and drawings present a preliminary instrument design of a fully functional laboratory prototype capable of zero-G operation.

Fraser, A. S.↗

A review of Curtiss-Wright rotary engine developments with respect to general aviation potential

Aviation related rotary (Wankel-type) engine tests, possible growth directions and relevant developments at Curtiss-Wright have been reviewed. Automotive rotary engines including stratified charge are described and flight test results of rotary aircraft engines are presented. The current 300 HP engine prototype shows basic durability and competitive performance potential. Recent parallel developments have separately confirmed the geometric advantages of the rotary engine for direct injected unthrottled stratified charge. Specific fuel consumption equal to or better than pre- or swirl-chamber diesels, low emission and multi-fuel capability have been shown by rig tests of similar rotary engine.

Jones, C.↗

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.↗

Two-Dimensional Systolic Array For Kalman-Filter Computing

Two-dimensional, systolic-array, parallel data processor performs Kalman filtering in real time. Algorithm rearranged to be Faddeev algorithm for generalized signal processing. Algorithm mapped onto very-large-scale integrated-circuit (VLSI) chip in two-dimensional, regular, simple, expandable array of concurrent processing cells. Processor does matrix/vector-based algebraic computations. Applications include adaptive control of robots, remote manipulators and flexible structures and processing radar signals to track targets.

Chang, Jaw John↗

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↗

CSM activities at the NASA Langley Research Center

The objective and goals of the Computational Structural Mechanics (CSM) Program as applied to airframe structures are given. It is recognized that the rapid evolution of computer hardware has opened up new opportunities for solving more complex and larger structural analysis problems than was hitherto imagined. To utilize these computers, new methods of computational structural mechanics are required. Methods are now being developed, assessed, and validated to meet the goals, and each of these goals is addressed. Plans and approaches are shown and highlights of results achieved in meeting these goals are given. Three research thrusts are shown in the five-year plan: advanced robust CSM methods, large-scale solutions, and validation/demonstration studies. The areas of research activity reflect the CSM goals. The mapping of developed methods onto high-performance and massively parallel computers is an integral part of the CSM five-year plan.

Housner, Jerrold M.↗