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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PandAna: A Python Analysis Framework for Scalable High Performance Computing in High Energy Physics

Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance computing environments. We describe our work to develop a high energy physics analysis framework suitable for high performance computing. This new framework utilizes modern tools for reading files and implicit data parallelism. Framework users analyze tabular data using standard, easy-to-use data analysis techniques in Python while the framework handles the file manipulations and parallelism without the user needing advanced experience in parallel programming. In future versions, we hope to provide a framework that can be utilized on a personal computer or a high performance computing cluster with little change to the user code.

Groh, Micah↗
DOE OSTI2019

Time-resolved ionization measurements with intense ultrashort XUV and X-ray free-electron laser pulses

Abstract Modern free-electron lasers (FEL) operating in XUV (extreme ultraviolet) or X-ray range allow an access to novel research areas. One instance is the ultrafast ionization of a solid by an intense femtosecond FEL pulse in XUV which consequently leads to a change of the complex index of refraction on an ultrashort timescale. The photoionization and subsequent impact ionization resulting in electronic and atomic dynamics are modeled with our hybrid code XTANT(X-ray thermal and non-thermal transitions) and a Monte Carlo code XCASCADE(X-ray-induced electron cascades). The simulations predict the temporal kinetics of FEL-induced electron cascades and thus yield temporally and spatially resolved information on the induced changes of the optical properties. In a series of experiments at FERMI and LCLS, single shot measurements with spatio-temporal encoding of the ionization process have been performed by a correlation of the FEL pump pulse with an optical femtosecond probe pulse. An excellent agreement between the experiment and the simulation has been found. Furthermore, we demonstrate that such kind of experiments forms the basis for pulse duration and arrival time jitter monitoring as currently under development for XUV-FELs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Study of Globus-M Tokamak Poloidal System and Plasma Position Control

In order to provide efficient performance of tokamaks with vertically elongated plasma position, control systems for limited and diverted plasma configuration are required. The accuracy, stability, speed of response, and reliability of plasma position control as well as plasma shape and current control depend on the performance of the control system. Therefore, the problem of the development of such systems is an important and actual task in modern tokamaks. In this study, the measured signals from the magnetic loops and Rogowski coils are used to reconstruct the plasma equilibrium, for which linear models in small deviations are constructed. We apply methods of the H∞-optimization theory to the synthesize control system for vertical and horizontal position of plasma capable to working with structural uncertainty of the models of the plant. These systems are applied to the plasma-physical DINA code which is configured for the tokamak Globus-M plasma. The testing of the developed systems applied to the DINA code with Heaviside step functions have revealed the complex dynamics of plasma magnetic configurations. Being close to the bifurcation point in the parameter space of unstable plasma has made it possible to detect an abrupt change in the X-point position from the top to the bottom and vice versa. Development of the methods for reconstruction of plasma magnetic configurations and experience in designing plasma control systems with feedback for tokamaks provided an opportunity to synthesize new digital controllers for plasma vertical and horizontal position stabilization. It also allowed us to test the synthesized digital controllers in the closed loop of the control system with the DINA code as a nonlinear model of plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment About Older Adults and COVID-19 Using Machine Learning

Objectives This study examined public discourse and sentiment regarding older adults and COVID-19 on social media and assessed the extent of ageism in public discourse. Methods Twitter data (N = 82,893) related to both older adults and COVID-19 and dated from January 23 to May 20, 2020, were analyzed. We used a combination of data science methods (including supervised machine learning, topic modeling, and sentiment analysis), qualitative thematic analysis, and conventional statistics. Results The most common category in the coded tweets was “personal opinions” (66.2%), followed by “informative” (24.7%), “jokes/ridicule” (4.8%), and “personal experiences” (4.3%). The daily average of ageist content was 18%, with the highest of 52.8% on March 11, 2020. Specifically, more than 1 in 10 (11.5%) tweets implied that the life of older adults is less valuable or downplayed the pandemic because it mostly harms older adults. A small proportion (4.6%) explicitly supported the idea of just isolating older adults. Almost three-quarters (72.9%) within “jokes/ridicule” targeted older adults, half of which were “death jokes.” Also, 14 themes were extracted, such as perceptions of lockdown and risk. A bivariate Granger causality test suggested that informative tweets regarding at-risk populations increased the prevalence of tweets that downplayed the pandemic. Discussion Ageist content in the context of COVID-19 was prevalent on Twitter. Information about COVID-19 on Twitter influenced public perceptions of risk and acceptable ways of controlling the pandemic. Finaly, public education on the risk of severe illness is needed to correct misperceptions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

AthenaK: A Performance-portable Version of the Athena++ Adaptive Mesh Refinement Framework

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic, and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers, we describe (1) a new solver for the Einstein equations based on the Z4c formalism, and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging Advanced RISC Machine processors. AthenaK shows excellent performance and weak scaling, achieving over 1 billion cell updates per second for hydrodynamics in three dimensions on a single NVIDIA Grace Hopper processor. It does this with a typical parallel efficiency of 80% on 65,536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2024

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

HPC Annual Report 2017

Sandia National Laboratories has a long history of significant contributions to the high performance community and industry. Our innovative computer architectures allowed the United States to become the first to break the teraFLOP barrier—propelling us to the international spotlight. Our advanced simulation and modeling capabilities have been integral in high consequence US operations such as Operation Burnt Frost. Strong partnerships with industry leaders, such as Cray, Inc. and Goodyear, have enabled them to leverage our high performance computing (HPC) capabilities to gain a tremendous competitive edge in the marketplace. As part of our continuing commitment to providing modern computing infrastructure and systems in support of Sandia missions, we made a major investment in expanding Building 725 to serve as the new home of HPC systems at Sandia. Work is expected to be completed in 2018 and will result in a modern facility of approximately 15,000 square feet of computer center space. The facility will be ready to house the newest National Nuclear Security Administration/Advanced Simulation and Computing (NNSA/ASC) Prototype platform being acquired by Sandia, with delivery in late 2019 or early 2020. This new system will enable continuing advances by Sandia science and engineering staff in the areas of operating system R&D, operation cost effectiveness (power and innovative cooling technologies), user environment and application code performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Modification and validation of an analytical source model for external beam radiotherapy Monte Carlo dose calculations

Purpose: A dose calculation tool, which combines the accuracy of the dose planning method (DPM) Monte Carlo code and the versatility of a practical analytical multisource model, which was previously reported has been improved and validated for the Varian 6 and 10 MV linear accelerators (linacs). The calculation tool can be used to calculate doses in advanced clinical application studies. One shortcoming of current clinical trials that report dose from patient plans is the lack of a standardized dose calculation methodology. Because commercial treatment planning systems (TPSs) have their own dose calculation algorithms and the clinical trial participant who uses these systems is responsible for commissioning the beam model, variation exists in the reported calculated dose distributions. Today’s modern linac is manufactured to tight specifications so that variability within a linac model is quite low. The expectation is that a single dose calculation tool for a specific linac model can be used to accurately recalculate dose from patient plans that have been submitted to the clinical trial community from any institution. The calculation tool would provide for a more meaningful outcome analysis. Methods: The analytical source model was described by a primary point source, a secondary extra-focal source, and a contaminant electron source. Off-axis energy softening and fluence effects were also included. The additions of hyperbolic functions have been incorporated into the model to correct for the changes in output and in electron contamination with field size. A multileaf collimator (MLC) model is included to facilitate phantom and patient dose calculations. An offset to the MLC leaf positions was used to correct for the rudimentary assumed primary point source. Results: Dose calculations of the depth dose and profiles for field sizes 4 × 4 to 40 × 40 cm agree with measurement within 2% of the maximum dose or 2 mm distance to agreement (DTA) for 95% of the data points tested. The model was capable of predicting the depth of the maximum dose within 1 mm. Anthropomorphic phantom benchmark testing of modulated and patterned MLCs treatment plans showed agreement to measurement within 3% in target regions using thermoluminescent dosimeters (TLD). Using radiochromic film normalized to TLD, a gamma criteria of 3% of maximum dose and 2 mm DTA was applied with a pass rate of least 85% in the high dose, high gradient, and low dose regions. Finally, recalculations of patient plans using DPM showed good agreement relative to a commercial TPS when comparing dose volume histograms and 2D dose distributions. Conclusions: A unique analytical source model coupled to the dose planning method Monte Carlo dose calculation code has been modified and validated using basic beam data and anthropomorphic phantom measurement. While this tool can be applied in general use for a particular linac model, specifically it was developed to provide a singular methodology to independently assess treatment plan dose distributions from those clinical institutions participating in National Cancer Institute trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Compiler-Driven FPGA Virtualization with SYNERGY

FPGAs are increasingly common in modern applications, and cloud providers now support on-demand FPGA acceleration in datacenters. Applications in datacenters run on virtual infrastructure, where consolidation, multi-tenancy, and workload migration enable economies of scale that are fundamental to the provider's business. However, a general strategy for virtualizing FPGAs has yet to emerge. While manufacturers struggle with hardware-based approaches, we propose a compiler/runtime-based solution called Synergy. We show a compiler transformation for Verilog programs that produces code able to yield control to software atsub-clock-tickgranularity according to the semantics of the original program. Synergy uses this property to efficiently support core virtualization primitives: suspend and resume, program migration, and spatial/temporal multiplexing, on hardware which is availabletoday.We use Synergy to virtualize FPGA workloads across a cluster of Intel SoCs and Xilinx FPGAs on Amazon F1. The workloads require no modification, run within 3--4x of unvirtualized performance, and incur a modest increase in FPGA fabric usage.

Computer Science↗
DOE OSTI2026

Trilinos: Enabling Scientific Computing across Diverse Hardware Architectures at Scale

Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has undergone substantial changes to support new applications and new hardware architectures, this document is an update to “An Overview of the Trilinos project” by Heroux et al. (ACM Transactions on Mathematical Software, 31(3):397–423, 2005). It describes the design of Trilinos, introduces its new organization in product areas, and highlights established and new features available in Trilinos. Particular focus is put on the modernized software stack based on the Kokkos ecosystem to deliver performance portability across heterogeneous hardware architectures. This article also outlines the organization of the Trilinos community and the contribution model to help onboard interested users and contributors.

Heterogeneous Hardware Architectures↗
DOE OSTI2017

Developing the User Experience for a Next Generation Nuclear Fuel Cycle Simulator (NGFCS)

This project made substantial progress on its original aim for providing a modern user experience for nuclear fuel cycle analysis while also creating a robust and functional next- generation fuel cycle simulator. The Cyclus kernel experienced a dramatic clari cation of its interfaces and data model, becoming a full- edged agent-based framework, with strong support for third party developers of novel archetypes. The most important contribution of this project to the the development of Cyclus was the introduction of tools to facilitate archetype development. These include automated code generation of routine archetype components, metadata annotations to provide re ection and rich description of each data member's purpose, and mechanisms for input validation and output of complex data. A comprehensive social science investigation of decision makers' interests in nuclear fuel cycles, and speci cally their interests in nuclear fuel cycle simulators (NFCSs) as tools for understanding nuclear fuel cycle options, was conducted. This included document review and analysis, stakeholder interviews, and a survey of decision makers. This information was used to study the role of visualization formats and features in communicating information about nuclear fuel cycles. A exible and user-friendly tool was developed for building Cyclus analysis models, featuring a drag-and-drop interface and automatic input form generation for novel archetypes. Cycic allows users to design fuel cycles from arbitrary collections of facilities for the rst time, with mechanisms that contribute to consistency within that fuel cycle. Interacting with some of the metadata capabilities introduced in the above-mentioned tools to support archetype development, Cycic also automates the generation of user input forms for novel archetypes with little to no special knowledge required by the archetype developers. Translation of the fundamental metrics of Cyclus into more interesting quantities is accomplished in the Cymetric python package. This package is speci cally designed to support the introduction of new metrics by building upon existing metrics. This concept allows for multiple dependencies and encourages building complex metrics out of incremental transformations to those prior metrics. New archetype developers can contribute their own archetype-speci c metric using the same capability. A simple demonstration of this capability focused on generating time-dependent cash ows for reactor deployment that could then be analyzed in di erent ways. Cyclist, a dedicated application for exploration of Cyclus results, was developed. It's primary capabilities at this stage are best-suited to experienced fuel cycle analysts, but it provides a basic platform for simpler visualizations for other audiences. An important part of its interface is the ability to uidly examine di erent slices of what is fundamentally a ve-dimensional sparse data set. A drag-and-drop interface simpli es the process of selecting which data is displayed in the plot as well as which dimensions are being used for

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

WHONDRS-GUI: a web application for global survey of surface water metabolites

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811 , which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server ( https://xmlin.shinyapps.io/whondrs/ ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Photosynthetic reaction center variants made via genetic code expansion show Tyr at M210 tunes the initial electron transfer mechanism

Significance Reaction centers (RCs) are critical to photosynthetic energy conversion. RCs in all characterized photosynthetic organisms contain two symmetrically arranged branches of chromophores and enable light-induced electron transfer with high yield. We fine-tune the properties of a key bacterial RC symmetry-breaking tyrosine via its replacement with noncanonical tyrosine analogs and determine kinetic outcomes. Results are interpreted through energetic characterization made possible by resonance Stark spectroscopy. Analysis indicates this tyrosine modulates the mechanism of the initial light-induced electron transfer, affording an alternative functional pathway that maintains the RC’s robust electron transfer. Modern molecular biology, ultrafast spectroscopy, crystallography, and energetic characterization enable the mechanistic model we describe. Our results deepen understanding of RC function and may have implications for other photocatalysts and enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A Plug-and-Play Duct System Evaluation

This report describes an air distribution system composed of a series of uniformly-sized ducts that terminate in rooms throughout the home and return to a central manifold, similar in fashion to a “home-run” cross-linked polyethylene plumbing system. With a well-designed manifold, each duct receives an equal static pressure potential for airflow from the air handling unit, and the number of needed ducts for each room are simply attached to fittings located on the manifold; in this sense, the system is plug-and-play (PnP). As indicated, all ducts in the PnP system are identical in size and small enough to fit in the ceiling and wall cavities of a house (i.e., less than 3.5-in. outer diameter). These ducts are also more appropriately sized for the lower airflow requirements of modern, energy-efficient homes; therefore, the velocity of the air moving through the duct is between that of conventional duct systems (approximately 700 ft/min) and high-velocity systems (more than 1,500 ft/min) on the market today. The PnP duct system uses semi-rigid plastic pipes, which have a smooth inner wall and are straightforward to install correctly, resulting in a system that has minimal air leakage. However, plastic ducts are currently not accepted by code for use in residential buildings; therefore, the project team considered other duct materials for the system that are currently accepted by code, such as small-diameter, wirehelix, flexible ductwork.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A Plug-and-Play Duct System Evaluation

This report describes an air distribution system composed of a series of uniformly-sized ducts that terminate in rooms throughout the home and return to a central manifold, similar in fashion to a “home-run” cross-linked polyethylene plumbing system. With a well-designed manifold, each duct receives an equal static pressure potential for airflow from the air handling unit, and the number of needed ducts for each room are simply attached to fittings located on the manifold; in this sense, the system is plug-and-play (PnP). As indicated, all ducts in the PnP system are identical in size and small enough to fit in the ceiling and wall cavities of a house (i.e., less than 3.5-in. outer diameter). These ducts are also more appropriately sized for the lower airflow requirements of modern, energy-efficient homes; therefore, the velocity of the air moving through the duct is between that of conventional duct systems (approximately 700 ft/min) and high-velocity systems (more than 1,500 ft/min) on the market today. The PnP duct system uses semi-rigid plastic pipes, which have a smooth inner wall and are straightforward to install correctly, resulting in a system that has minimal air leakage. However, plastic ducts are currently not accepted by code for use in residential buildings; therefore, the project team considered other duct materials for the system that are currently accepted by code, such as small-diameter, wirehelix, flexible ductwork.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗