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DOE OSTI2024

High Fidelity Simulations of Air-Cooled Reactor Cavity Cooling System

High Temperature Gas Reactor (HTGR) designs incorporate passive safety systems (e.g., the Reactor Cavity Cooling System [RCCS]) that utilize natural principles to manage heat dissipation from the reactor pressure vessel (RPV) during accidents or routine shutdowns. The industry community is experiencing a pressing need for advanced simulation tools that can accurately assess the performance of these types of systems. In the literature, a knowledge gap exists concerning high-fidelity data for the RCCS, and this gap is one of the areas of focus of the present study. This research focuses on a specific RCCS designed for General Atomics' Modular High-Temperature Gas Reactor (GA-MHTGR). Experimental studies on a scaled version (can be seen in Figure 1) of the air-cooled RCCS used in GA-MHTGR were conducted by the University of Wisconsin-Madison (UW-Madison). This work contributes to a broader initiative aimed at establishing a numerical benchmark based on the UW-Madison experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Evaluation of LLVM Flang for Production HPC Applications and Modern Fortran Features

In 2025, LLVM released its first Flang Fortran compiler version considered ready for widespread evaluation. We know of no published assessment of Flang compiling a workload- derived portfolio of high-performance computing (HPC) applications. We address this gap using workload data from the National Energy Research Scientific Computing Center (NERSC), which supports more than 10,000 scientists on approximately 1,000 projects. The NERSC workload analyses identify many Fortran components in heavily used applications. We selected 10 such packages with available source code. We compiled them with Flang 22.1.3 on NERSC’s Perlmutter system. Six compiled without code modifications, though some required build-system changes. Three compiled after minor source edits, mostly to address Fortran standard violations. One built only without OpenMP enabled. We evaluated seven additional packages selected for their use of, or enablement of, standard Fortran parallel features: multi-image execution and do concurrent. Six such codes compiled with most or all unit tests passing.

Rasmussen, Katherine↗

DOE OSTI2020

GeoRePORT (Geothermal Resource Portfolio Optimization & Reporting Technique)

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) Protocol provides a system for reporting resource grade and project readiness level. It is particularly useful for describing early-stage exploration projects. GeoRePORT can assist in evaluating project risk and return, identifying gaps in reported data, evaluating research and design impacts, and gathering insights on successes and failures. It helps users objectively and quantitatively compare project potential in geological, technical, and socioeconomic areas.

Young, Katherine↗

NASA NTRSDate not supplied

The Satellite Needs Working Group (SNWG) Biennial Survey: Analyzing Satellite Earth Observation Needs Across U.S. Federal Civilian Agencies

The Satellite Needs Working Group (SNWG) is part of the U.S. Group on Earth Observations (USGEO) and was established to identify high-priority Earth observation satellite needs across U.S. federal civilian agencies. Federal agencies often rely on Earth observation data to fulfill multidisciplinary agency responsibilities such as assessing agricultural crop conditions, detecting wildfires, and monitoring water quality; however, the data sets and tools required to meet these needs are not always readily available or accessible to agency personnel. SNWG conducts a biennial survey of federal satellite needs in order to bridge the gap between Earth observation data providers and their government stakeholders and users. The SNWG Management Office completes an analysis of these survey submissions to gain insight into the types of satellite needs that exist across the government. Within the survey, agencies provide details on how satellite data are used to meet their objectives, measurement requirements needed for their use cases, and gaps that exist in currently available satellite data products and services. For the SNWG 2024 cycle, there were 125 surveys submitted from 25 different agencies. This presentation will discuss findings from the statistical analysis of the SNWG 2024 survey responses and highlight the diverse nature of the needs, common themes in agency requests, and differences in the responses compared to previous cycles. The presentation will also discuss the newly approved SNWG Aggregate Statistics Report that will make these analysis results available to the public and help inform what’s next for science.

Essence Raphael↗

NASA NTRS2015

Robotic Missions to Small Bodies and Their Potential Contributions to Human Exploration and Planetary Defense

Introduction: Robotic missions to small bodies will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration and planetary defense. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission involves sending astronauts to study and sample a near-Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. The science and technical data obtained from robotic precursor missions that investigate the surface and interior physical characteristics of an object will help identify the pertinent physical properties that will maximize operational efficiency and reduce mission risk for both robotic assets and crew operating in close proximity to, or at the surface of, a small body. These data will help fill crucial strategic knowledge gaps (SKGs) concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations. These data can also be applied for gaining an understanding of pertinent small body physical characteristics that would also be beneficial for formulating future impact mitigation procedures. Small Body Strategic Knowledge Gaps: For the past several years NASA has been interested in identifying the key SKGs related to future human destinations. These SKGs highlight the various unknowns and/or data gaps of targets that the science and engineering communities would like to have filled in prior to committing crews to explore the Solar System. An action team from the Small Bodies Assessment Group (SBAG) was formed specifically to identify the small body SKGs under the direction of the Human Exploration and Operations Missions Directorate (HEOMD), given NASA's recent interest in NEAs and the Martian moons as potential human destinations. The action team organized the SKGs into four broad themes: 1) Identify human mission targets; 2) Understand how to work on and interact with the small body surface; 3) Understand the small body environment and its potential risk/benefit to crew, systems, and operational assets; and 4) Understand the small body resource potential. Of these four SKG themes, the first three have significant overlap with planetary defense considerations. The data obtained from investigations of small body physical characteristics under these three themes can be directly applicable to planetary defense initiatives. Conclusions: Missions to investigate small bodies can address small body strategic knowledge gaps and contribute to the overall success for human exploration missions to asteroids and the Martian moons. In addition, such reconnaissance of small bodies can also provide a wealth of information relevant to the science and planetary defense of NEAs.

Abell, Paul A.↗

DOE OSTI2021

Creating the First Interactive Mobility Data Landscape

As the world continues to be driven increasingly driven by data, the ways this data is sorted and collected is critical for researchers and specification creators. In the world of mobility data, there are few if any de jure standards connecting data, and there is little knowledge on the gaps that exist in the data. In this project we have created an interactive landscape where mobility data and data specifications can be categorized and organized in an easy-to-use living document.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Developing an Interactive Landscape for Mobility Resources: Preprint

As the world continues to be increasingly driven by data, the ways researchers and professionals sort and collect this data is critical. In the world of mobility data, new levels of data from public transportation systems, location services, and other means are being lost due to how little organization exists. Much of the data is proprietary, and there are few if any de jure or even de facto standards connecting data. There is also little knowledge about the gaps that exist in the data. In this project, we created an interactive landscape where mobility resources are categorized and organized in an easy to use, living document. We made this landscape with open-source code from the CNCF Cloud Native Landscape and repurposed it to the mobility data's needs. Additionally, unlike previous sources that organize mobility data, this document can be updated through GitHub by those in the field to keep its sources relevant. Following the creation of a beta version of the landscape, we conducted several interviews with industry researchers and professionals to ensure the landscape would be useful. The result is an online hub where mobility researchers and resource creators can easily access research and collaborate.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Proton Shell Gaps in N = 28 Nuclei from the First Complete Spectroscopy Study with FRIB Decay Station Initiator

The first complete measurement of the $β$-decay strength distribution of $_{17}^{45}$Cl 28 was performed at the Facility for Rare Isotope Beams (FRIB) with the FRIB Decay Station Initiator during the second FRIB experiment. The measurement involved the detection of neutrons and $γ$ rays in two focal planes of the FRIB Decay Station Initiator in a single experiment for the first time. This enabled an analytical consistency in extracting the $β$-decay strength distribution over the large range of excitation energies, including neutron unbound states. Here, we observe a rapid increase in the $β$-decay strength distribution above the neutron separation energy in $_{18}^{45}$Ar 27 . This was interpreted to be caused by the transitioning of neutrons into protons excited across the Z = 20 shell gap. The SDPF-MU interaction with reduced shell gap best reproduced the data. The measurement demonstrates a new approach that is sensitive to the proton shell gap in neutron rich nuclei according to SDPF-MU calculations.

39 ≤ A ≤ 58↗

DOE OSTI2022

Synthetic Data Generation Using Machine Learning

Robust machine learning techniques for image analysis require a substantial amount of data to yield confident results. In the nuclear domain, data scarcity is a substantial challenge because there are so few facilities worldwide. This research focuses on being able alleviate the data scarcity problem by generating synthetic data to bridge the gap between large and small datasets. This work achieves that goal using a Generative Adversarial Network (GAN) architectural approach, by training a model on real-world data and expands that small dataset through synthetic data amendments. Model performance is impacted by the size of the real-world dataset and the number of training epochs utilized. This means that 1) It is important to develop your GAN to be optimized with the specific data type, and 2) approaches taken when training the GAN should be specialized to encompass important aspects of the dataset that it is generating. By taking a step to improve dataset sizes in this way, the gap between models trained by parties with significant amount of data and those without access to large data, closes, allowing for robust analyses of satellite imagery for nuclear domain applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2010

Optimal Codes for the Burst Erasure Channel

Deep space communications over noisy channels lead to certain packets that are not decodable. These packets leave gaps, or bursts of erasures, in the data stream. Burst erasure correcting codes overcome this problem. These are forward erasure correcting codes that allow one to recover the missing gaps of data. Much of the recent work on this topic concentrated on Low-Density Parity-Check (LDPC) codes. These are more complicated to encode and decode than Single Parity Check (SPC) codes or Reed-Solomon (RS) codes, and so far have not been able to achieve the theoretical limit for burst erasure protection. A block interleaved maximum distance separable (MDS) code (e.g., an SPC or RS code) offers near-optimal burst erasure protection, in the sense that no other scheme of equal total transmission length and code rate could improve the guaranteed correctible burst erasure length by more than one symbol. The optimality does not depend on the length of the code, i.e., a short MDS code block interleaved to a given length would perform as well as a longer MDS code interleaved to the same overall length. As a result, this approach offers lower decoding complexity with better burst erasure protection compared to other recent designs for the burst erasure channel (e.g., LDPC codes). A limitation of the design is its lack of robustness to channels that have impairments other than burst erasures (e.g., additive white Gaussian noise), making its application best suited for correcting data erasures in layers above the physical layer. The efficiency of a burst erasure code is the length of its burst erasure correction capability divided by the theoretical upper limit on this length. The inefficiency is one minus the efficiency. The illustration compares the inefficiency of interleaved RS codes to Quasi-Cyclic (QC) LDPC codes, Euclidean Geometry (EG) LDPC codes, extended Irregular Repeat Accumulate (eIRA) codes, array codes, and random LDPC codes previously proposed for burst erasure protection. As can be seen, the simple interleaved RS codes have substantially lower inefficiency over a wide range of transmission lengths.

Hamkins, Jon↗

DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Data refactoring↗

DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Chen, Jieyang↗

NASA NTRS1989

Optical evidence for the metallization of Xenon at 132(5) GPa

Xe has been compressed in a diamond-anvil cell to approximately 200 GPa. The metallization of Xe by band-gap closure was investigated by obtaining optical data in both the metallic and insulating states. In the metallic state, the pressure dependence of the plasma frequency was determined from absorption data fitted with a free-electron model. In the insulating state, the pressure dependence of the band gap was determined from absorption data fitted with an indirect-band-gap model. The optical data indicate that the insulator-to-metal transition in Xe occurs at 132(5) GPa.

Goettel, Kenneth A.↗

DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗

NASA NTRS1980

Data base for the prediction of inlet external drag

Results are presented from a study to define and evaluate the data base for predicting an airframe/propulsion system interference effect shown to be of considerable importance, inlet external drag. The study is focused on supersonic tactical aircraft with highly integrated jet propulsion systems, although some information is included for supersonic strategic aircraft and for transport aircraft designed for high subsonic or low supersonic cruise. The data base for inlet external drag is considered to consist of the theoretical and empirical prediction methods as well as the experimental data identified in an extensive literature search. The state of the art in the subsonic and transonic speed regimes is evaluated. The experimental data base is organized and presented in a series of tables in which the test article, the quantities measured and the ranges of test conditions covered are described for each set of data; in this way, the breadth of coverage and gaps in the existing experimental data are evident. Prediction methods are categorized by method of solution, type of inlet and speed range to which they apply, major features are given, and their accuracy is assessed by means of comparison to experimental data.

Mcmillan, O. J.↗

NASA NTRS1992

CFD validation experiments for hypersonic flows

A roadmap for CFD code validation is introduced. The elements of the roadmap are consistent with air-breathing vehicle design requirements and related to the important flow path components: forebody, inlet, combustor, and nozzle. Building block and benchmark validation experiments are identified along with their test conditions and measurements. Based on an evaluation criteria, recommendations for an initial CFD validation data base are given and gaps identified where future experiments could provide new validation data.

Marvin, Joseph G.↗

NASA NTRS2020

Recovery, Restoration and Archiving of Previously Lost Data and Metadata from the Apollo Lunar Surface Experiments Package (ALSEP)

The Apollo Lunar Surface Experiments Package (ALSEP) is the name used to collectively represent the geophysical instruments deployed on the lunar surface by the astronauts on Apollo 12, 14, 15, 16, and 17. These instruments were active from the times of their deployment (November 1969 – December 1972) to September 1977. During that time, fourteen types of experiments were conducted, and their data were transmitted to Earth. The experiment PIs processed them. At the conclusion of the experiments, some of these data were submitted to the NASA Space Science Data Coordinated Archive (NSSDCA) for archiving, while others were not. The raw instrument data received from the Moon prior to March 1976 were not archived, either. The unarchived data, resided on open-reel magnetic tapes, became lost in the decades since, along with much of the metadata (the information necessary/useful in properly processing/analyzing the data). This article retraces the history of the ALSEP data archiving efforts in the 1970s, the subsequent loss of the data tapes, and the search, recovery, and restoration of the lost data by contemporary researchers in the 21st century. In 2006, NSSDCA began reformatting some of the ALSEP data archived in the 1970s to conform with the current Planetary Data System (PDS). In 2010, 440 of the previously lost magnetic tapes containing the raw ALSEP data were recovered. From these tapes, the data were extracted, re-packaged for individual experiments, and, for those with sufficient metadata, processed into higher order data readily usable by researchers. All of these data products have been recently archived with either PDS or NSSDCA. These newly restored data fill a number of gaps in the previously existing archive of the ALSEP data. In addition, tens of thousands of pages of Apollo era documents have been optically scanned and compiled into an online searchable catalog. This article also describes the content, organization, and usage of the restored raw ALSEP data and metadata.

S Nagihara↗

DOE OSTI2025

Streaming Data in HPC Workflows Using ADIOS

The “IO Wall” problem, in which the gap between computation rate and data access rate grows continuously, poses significant problems to scientific workflows which have traditionally relied upon using the filesystem for intermediate storage between workflow stages. One way to avoid this problem in scientific workflows is to stream data directly from producers to consumers and avoiding storage entirely. However, the manner in which this is accomplished is key to both performance and usability. This paper presents the Sustainable Staging Transport, an approach which allows direct streaming between traditional file writers and readers with few application changes. SST is an ADIOS “engine”, accessible via standard ADIOS APIs, and because ADIOS allows engines to be chosen at run-time, many existing file-oriented ADIOS workflows can utilize SST for direct application-to-application communication without any source code changes. This paper describes the design of SST and presents performance results from various applications that use SST, for feeding model training with simulation data with substantially higher bandwidth than the theoretical limits of Frontier’s file system, for strong coupling of separately developed applications for multiphysics multiscale simulation, or for in situ analysis and visualization of data to complete all data processing shortly after the simulation finishes.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗