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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Time-temperature history and input files for ExaCA v2.0 scaling, performance, and demonstration simulations

The files in this data repository are used in various sections of the manuscript "ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification" by Rolchigo et al. (DOI: 10.1016/j.commatsci.2025.113734). The README file references dataset numbers as given in the manuscript's Table 2, as well as the manuscript's relevant subsections.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Study of reference burnup steps optimization in fuel segment data file generation for NEXUS/ANC9 code system

For any two-step core design code system, the cross-section files are the primary factor to determine the accuracy of the system prediction. For a once-through cross-section system to cover all potential applicable conditions, the system may need to perform tens of thousands state points of lattice calculations. These calculations take a significant amount of CPU times and computing power, especially when a fine or ultra-fine energy group library is used. As computer power increases, so does the calculational complexity. Therefore, it is important to make the lattice calculations effective and efficient. Based on the Westinghouse core design code system NEXUS/ANC9, this work focuses on the reference burnup steps used by the lattice code when performing the calculations. Following the fundamental cross-section methodology and analyzing the contribution of each individual terms, this study provides an applicable solution of the optimized reference burnup steps. The test results show that, with the existing cross-section methodology, it is possible to significantly reduce the lattice calculation cases and cross-section file generation time without sacrificing the accuracy of system prediction. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Enabling AI in synthetic biology through Construction File specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Geothermal Exploration Raster Files for Utah Play Fairway Analysis

This submission contains raster files associated with several datasets that include earthquake density, Na/K geothermometers, fault density, heat flow, and gravity. Integrated together using spatial modeler tools in ArcGIS, these files can be used for play fairway analysis in regard to geothermal exploration.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

TEAMER: Crossflow Turbine Fairing Geometry Optimization - Report and CFD Modeling Files

The dataset includes computational fluid dynamics (CFD) models and simulation files for crossflow turbines as well as a detailed project report. The report documents the project undertaken by the Ocean Renewable Power Company (ORPC) to design and optimize a modular fairing for the Modular RivGen Marine Hydrokinetic (MHK) turbine, which enhances the efficient deployment and operation of turbine arrays. The project focused on optimizing the hydrodynamic performance of the fairing using CFD, with an emphasis on two key geometric parameters: the fairing's cross-sectional shape and the spacing between the rotor and the fairing. The analysis aimed to maximize net power output while also assessing discretized loading to evaluate ultimate and fatigue loads on the turbine components. The numerical modeling was conducted using both the commercial CFD software Star-CCM+ and the open-source code openFOAM, with the latter utilizing the actuator line library, turbinesFOAM. This dual-code approach was intended to increase confidence in the results and demonstrate the viability of using open-source tools for high-fidelity marine energy modeling. This dataset includes all necessary files for actuator line simulations in openFOAM, as well as 2D blade-resolved CFD results, along with Python and Java scripts for setting up and post-processing simulations.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Files and scripts to support manuscript Shuman et al 2023 FATES-SPITFIRE ecosystem assembly across tropics

The dataset includes the parameter and domain files, relevant output files, and scripts to generate simulations and perform analysis with Jupyter notebooks that support the manuscript Shuman, JK et al 2023 “Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0”. We have adapted the fire-behavior and effects module, SPITFIRE, for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture, and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire burned area and its effects, which could fee back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period, but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m-1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m-1. The results support a positive grass-fire feedback across the region, and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files

First-principles computational spectroscopy is a critical tool for interpreting experiment, per- forming structure refinement, and developing new physical understanding. Systematically setting up input files for different simulation codes and a diverse class of materials is a challeng- ing task with a very high barrier-to-entry, given the complexities and nuances of each individual simulation package. This task is non-trivial even for experts in the electronic structure field and nearly formidable for non-expert researchers. Lightshow solves this problem by providing a uniform abstraction for writing computational x-ray spectroscopy input files for multiple popular codes, including FEFF, VASP, OCEAN, exciting and XSpectra. Its extendable framework will also allow the community to easily add new functions and to incorporate new simulation codes.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Using the Sirocco File System for high-bandwidth checkpoints.

The Sirocco File System, a file system for exascale under active development, is designed to allow the storage software to maximize quality of service through increased flexibility and local decision-making. By allowing the storage system to manage a range of storage targets that have varying speeds and capacities, the system can increase the speed and surety of storage to the application. We instrument CTH to use a group of RAM-based Sirocco storage servers allocated within the job as a high-performance storage tier to accept checkpoints, allowing computation to potentially continue asynchronously of checkpoint migration to slower, more permanent storage. The result is a 10-60x speedup in constructing and moving checkpoint data from the compute nodes. This demonstration of early Sirocco functionality shows a significant benefit for a real I/O workload, checkpointing, in a real application, CTH. By running Sirocco storage servers within a job as RAM-only stores, CTH was able to store checkpoints 10-60x faster than storing to PanFS, allowing the job to continue computing sooner. While this prototype did not include automatic data migration, the checkpoint was available to be pushed or pulled to disk-based storage as needed after the compute nodes continued computing. Future developments include the ability to dynamically spawn Sirocco nodes to absorb checkpoints, expanding this mechanism to other fast tiers of storage like flash memory, and sharing of dynamic Sirocco nodes between multiple jobs as needed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

INSPIRE and SPIRES Log File Analysis

SPIRES, an aging high-energy physics publication data base, is in the process of being replaced by INSPIRE. In order to ease the transition from SPIRES to INSPIRE it is important to understand user behavior and the drivers for adoption. The goal of this project was to address some questions in regards to the presumed two-thirds of the users still using SPIRES. These questions are answered through analysis of the log files from both websites. A series of scripts were developed to collect and interpret the data contained in the log files. The common search patterns and usage comparisons are made between INSPIRE and SPIRES, and a method for detecting user frustration is presented. The analysis reveals a more even split than originally thought as well as the expected trend of user transition to INSPIRE.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

The Fifth Workshop on HPC Best Practices: File Systems and Archives

The workshop on High Performance Computing (HPC) Best Practices on File Systems and Archives was the fifth in a series sponsored jointly by the Department Of Energy (DOE) Office of Science and DOE National Nuclear Security Administration. The workshop gathered technical and management experts for operations of HPC file systems and archives from around the world. Attendees identified and discussed best practices in use at their facilities, and documented findings for the DOE and HPC community in this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Portable File Format (PFF) specifications

Created at Sandia National Laboratories, the Portable File Format (PFF) allows binary data transfer across computer platforms. Although this capability is supported by many other formats, PFF files are still in use at Sandia, particularly in pulsed power research. This report provides detailed PFF specifications for accessing data without relying on legacy code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Sandia Data Archive (SDA) file specifications

The Sandia Data Archive (SDA) format is a specific implementation of the HDF5 (Hierarchal Data Format version 5) standard. The format was developed for storing data in a universally accessible manner. SDA files may contain one or more data records, each associated with a distinct text label. Primitive records provide basic data storage, while compound records support more elaborate grouping. External records allow text/binary files to be carried inside an archive and later recovered. This report documents version 1.0 of the SDA standard. The information provided here is sufficient for reading from and writing to an archive. Although the format was original designed for use in MATLAB, broader use is encouraged.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Composition and Realization of Source-to-Sink High-Performance Flows: File Systems, Storage, Hosts, LAN and WAN

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. To support such capabilities, significant progress has been made in various components including the deployment of 100 Gbps networks with future 1 Tbps bandwidth, increases in end-host capabilities with multiple cores and buses, capacity improvements in large disk arrays, and deployment of parallel file systems such as Lustre and GPFS. High-performance source-to-sink data flows must be composed of these component systems, which requires significant optimizations of the storage-to-host data and execution paths to match the edge and long-haul network connections. In particular, end systems are currently supported by 10-40 Gbps Network Interface Cards (NIC) and 8-32 Gbps storage Host Channel Adapters (HCAs), which carry the individual flows that collectively must reach network speeds of 100 Gbps and higher. Indeed, such data flows must be synthesized using multicore, multibus hosts connected to high-performance storage systems on one side and to the network on the other side. Current experimental results show that the constituent flows must be optimally composed and preserved from storage systems, across the hosts and the networks with minimal interference. Furthermore, such a capability must be made available transparently to the science users without placing undue demands on them to account for the details of underlying systems and networks. And, this task is expected to become even more complex in the future due to the increasing sophistication of hosts, storage systems, and networks that constitute the high-performance flows. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align and transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections. These solutions will be tested using (1) 100 Gbps connection(s) between Oak Ridge National Laboratory (ORNL) and Argonne National Laboratory (ANL) with storage systems supported by Lustre and GPFS file systems with an asymmetric connection to University of Memphis (UM); (2) ORNL testbed with multicore and multibus hosts, switches with OpenFlow capabilities, and network emulators; and (3) 100 Gbps connections from ESnet and their Openflow testbed, and other experimental connections. This proposal brings together the expertise and facilities of the two national laboratories, ORNL and ANL, and UM. It also represents a collaboration between DOE and the Department of Defense (DOD) projects at ORNL by sharing technical expertise and personnel costs, and leveraging the existing DOD Extreme Scale Systems Center (ESSC) facilities at ORNL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Covariance Data File Formats for Whisper-1.0 & Whisper-1.1

Whisper is a statistical analysis package developed in 2014 to support nuclear criticality safety (NCS) validation. It uses the sensitivity profile data for an application as computed by MCNP6 along with covariance files for the nuclear data to determine a baseline upper-subcritical-limit (USL) for the application. Whisper version 1.0 was first developed and used at LANL in 2014. During 2015-2016, Whisper was updated to version 1.1 and is to be included with the upcoming release of MCNP6.2. This report describes the file formats used for the covariance data in both Whisper-1.0 and Whisper-1.1.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Unification of Monitoring in the Fermi File Transfer Service

Written in Python, the Fermi File Transfer Service (FTS) is a sitewide program used by Fermilab to safely transfer files to storage. With the scale of FTS, monitoring its status has become increasingly important. By using Kafka-Python, FNAL Landscape, and Elasticsearch, the project's goal is to provide enhanced remote monitoring to compliment FTS's pre-existing monitoring. This will enable new ways to visually graph and interpret logs in a non-local environment. The associated poster briefly describes the changes made, details about Elasticsearch, and illustrates the monitoring data received thus far.

97 MATHEMATICS AND COMPUTING↗