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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71

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DOE OSTI2023

MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS Runtime

Vendor libraries are tuned for a specific architecture and are not portable to others. Moreover, they lack support for heterogeneity and multi-device orchestration, which is required for efficient use of contemporary HPC and cloud resources. To address these challenges, we introduce MatRIS—a multilevel math library abstraction for scalable and performance-portable sparse/dense BLAS/LAPACK operations using IRIS runtime. The MatRIS-IRIS co-design introduces three levels of abstraction to make the implementation completely architecture agnostic and provide highly productive programming. We demonstrate that MatRIS is portable without any change in source code and can fully utilize multi-device heterogeneous systems by achieving high performance and scalability on Summit, Frontier, and a CADES cloud node equipped with four NVIDIA A100 GPUs and four AMD MI100 GPUs. A detailed performance study is presented in which MatRIS demonstrates multi-device scalability. When compared, MatRIS provides competitive and even better performance than libraries from vendors and other third parties.

Monil, M. A. H.↗

DOE OSTI2017

Sparx PCA Module

Sparx, a new environment for Cryo-EM image processing; Cryo-EM, Single particle reconstruction, principal component analysis; Hardware Req.: PC, MAC, Supercomputer, Mainframe, Multiplatform, Workstation. Software Req.: operating system is Unix; Compiler C++; type of files: source code, object library, executable modules, compilation instructions; sample problem input data. Location/transmission: http://sparx-em.org; User manual & paper: http://sparx-em.org;

Yang, Chao↗

DOE OSTI2021

DVRFS Microbiome 2021 Manuscript Code

These scripts document the code used to analyze the Death Valley Regional Flow System (DVRFS) microbial community for a manuscript titled "Subsurface Planktonic Microbial Communities Reflect Regional-Scale Groundwater Hydraulic Connectivity".

Merino, NancyS.↗

DOE OSTI2024

Global Pathway Selection with Zero-RK

Global Pathway Selection (GPS) is an algorithm to effectively generates reduced (skeletal) chemistry mechanisms, which speeds up simulations and can be used as a systematic analytics tool to extract insights from complex reacting system. This release is an extension of the original code to run in parallel and to use LLNL's Zero-RK solver for fast solution of chemical problems.

Whitesides, RussellA↗

DOE OSTI2025

Global Pathway Selection with Zero-RK v0.5

Whitesides, RussellA [Lawrence Livermore National ↗

DOE OSTI2026

fp-tools

The output of a molecular dynamics simulation is a data file containing properties of the motion of the simulated particles as a function of time (e.g., positions, velocities). From this output, scientists can extract various properties which give insight into the physics of the system; for example, the radial distribution function can be computed from the particle positions, which gives insight into how close the system is to melting or freezing. Many publicly available codes to perform molecular dynamics simulations exist and have been well adopted by the scientific community (e.g., LAMMPS, VASP). However, it remains standard practice for scientists to write their own post-processing scripts to extract various properties of interest from the molecular dynamics simulation data. Since in many cases scientists are interested in the same set of “textbook” properties, there is a large duplication of effort in writing these post-processing scripts. Our proposed code, FP-Tools, is a C++ toolkit designed to help scientists extract and analyze quantities of interest from the output of a molecular dynamics simulation, eliminating the need for them to write these codes themselves and thus reducing this duplication of effort. The quantities which are computed by our code are well documented in the literature (either in publications or textbooks), and the algorithms we implement to compute these properties are also well known in the field. We are not introducing new science or methods here; rather, our primary goal is to provide a useful tool to the community in the form of a well-documented, easy to use package.

Hartman, Leah↗

DOE OSTI2022

Update of the Nuclear Criticality Slide Rule Calculations: Plutonium systems – Delayed Fission Gamma

IRSN (France), LLNL (USA) and ORNL (USA) began a long-term collaboration effort in 2015 to update the nuclear criticality Slide Rule for the emergency response to a nuclear criticality accident. The Slide Rule permits the estimation of neutron and gamma dose rates and integrated doses based upon estimated fission yields, as a function of distance from the fission source, and time after criticality accidents for different critical systems. This paper presents results from the fourth phase of the current update of the Slide Rule project, in which delayed fission-product gamma (DFG) dose rates of unreflected plutonium critical systems were compared by several modern 3D radiation transport codes (MCNP, COG, SCALE), using updated flux-to-dose conversion factors. Dose rates are calculated for fissile material at five moderation ratios (H/Pu), at 1 m above the ground as a function of distance (between 30 cm and 1,200 m) from the external surface of the source to the center of the detector, and for periods between 1 s and 1,000 min after the critical instantaneous event. Further efforts have been devoted to the determination of the delayed gamma source, by comparing the time-dependent energy spectra obtained from several methods. Overall, DFG dose rates calculated by each participant led to consistent results. Extra effort is under way to identify the cause of the remaining differences, by comparing precisely the gamma source, and particularly nuclides inventories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Optimization of a buncher for High Energy H- Beam Transport [Slides]

Accelerators and beam transport systems typically contain numerous beamline devices, diagnostics, system study, and upgrade. Routinely TRACE, MADX and TRANSPORT codes are used for the beam envelope prediction and optimization. Unknown problems of accelerators and beam-transport are addressed based on R&D, such as LFB voltage variation effect study. A nominal diagnostic have used in non-traditional beam transport path to address scientific question (such as use of a BPM in the air). High energy beam operation is a methodical process and routine R&D is required to maintain high standards to deliver beam.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Power System Waveform Classification Using Time-Frequency and CNN

Many modern reclosers and circuit breakers have microprocessor relays that record waveforms of system events. In some cases, utilities may record a half-a-dozen event captures for every event. This is thousands of events per year. The industry needs faster, more automated, more conclusive, and easy-to-use systems that can process massive amounts of event recordings without extensive input/support from power system engineers. To address the need for a commercially viable solution that can classify waveform data, energies were directed to develop a universal neural network (NN) structure (deep learning algorithm) that works for a wide variety of system event types. The structure that showed the most promise was one that included the use of spectrograms. The technique has shown positive results in audio engineering, particularly with respect to speech recognition. A waveform signature could be treated as a spoken word like audio waveforms for specific things such as “YES” or “UP”. No two people produce the exact same waveform when speaking each of these words, but audio processing algorithms based on spectrograms and convolutional neural networks (CNN) can still distinguish the word regardless of the speaker. No two circuits produce the exact same waveform for a given event, but the NN can be trained to classify the event type regardless of the circuit or location on the circuit. A Power System Neural Network (PSNN) has been developed to use a CNN to classify events within waveform data for power systems. The waveform is converted to an array of values by way of spectrograms and interpreted as an image. This image is passed into the CNN. The test results on independent simulated test and validation datasets show greater than 99% accuracy. While the results thus far are based on simulated data, the performance of the PSNN is very promising and should work for a wide variety of power system conditions of interest. Ultimately, much of the custom code and tools used today and much of the manual effort expended today may be automated using this PSNN.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Technical Justifications for Liquid Hydrogen Exposure Distances

The previous separation distances in the National Fire Protection Association (NFPA) Hydrogen Technologies Code (NFPA 2, 2020 Edition) for bulk liquid hydrogen systems lack a well-documented basis and can be onerous. This report describes the technical justifications for revisions of the bulk liquid hydrogen storage setback distances in NFPA 2, 2023 Edition. Distances are calculated based on a leak area that is 5% of the nominal pipe flow area. Models from the open source HyRAM+ toolkit are used to justify the leak size as well as calculate consequence-based separation distances from that leak size. Validation and verification of the numerical models is provided, as well as justification for the harm criteria used for the determination of the setback distances for each exposure type. This report also reviews mitigations that could result in setback distance reduction. The resulting updates to the liquid hydrogen separation distances are well-documented, retrievable, repeatable, revisable, independently verified, and use experimental results to verify the models.

08 HYDROGEN↗

DOE OSTI2024

Verification of the PERSENT Software

Ongoing commercial design activities require a thorough verification of the Argonne Reactor Computation codes to be performed. DIF3D is central to this system and substantial work has been done to verify its accuracy on several identified commercial needs. This manuscript details the verification work done on PERSENT which relies upon the DIF3D for its forward and adjoint flux solution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Dataset from 3D FLASH Computation of National Ignition Facility Shot N210201-001

This data comes from a 3D FLASH [Fryxell et al. ApJS 131, 273 (2000); Tzeferacos et al. HEDP 17, 24-31(2015)] computation of a cylindrical implosion experiment performed at the National Ignition Facility (shot number N210201-001). FLASH is an open-access radiation-hydrodynamics code being used to simulate high-energy-density systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Deoptimization of FMDV P1 Region Results in Robust Serotype-Independent Viral Attenuation

Foot-and-mouth disease (FMD), caused by the FMD virus (FMDV), is a highly contagious disease of cloven-hoofed livestock that can have severe economic impacts. Control and prevention strategies, including the development of improved vaccines, are urgently needed to effectively control FMD outbreaks in endemic settings. Previously, we employed two distinct strategies (codon pair bias deoptimization (CPD) and codon bias deoptimization (CD)) to deoptimize various regions of the FMDV serotype A subtype A12 genome, which resulted in the development of an attenuated virus in vitro and in vivo, inducing varying levels of humoral responses. In the current study, we examined the versatility of the system by using CPD applied to the P1 capsid coding region of FMDV serotype A subtype, A24, and another serotype, Asia1. Viruses carrying recoded P1 (A24-P1Deopt or Asia1-P1Deopt) exhibited different degrees of attenuation (i.e., delayed viral growth kinetics and replication) in cultured cells. Studies in vivo using a mouse model of FMD demonstrated that inoculation with the A24-P1Deopt and Asia1-P1Deopt strains elicited a strong humoral immune response capable of offering protection against challenge with homologous wildtype (WT) viruses. However, different results were obtained in pigs. While clear attenuation was detected for both the A24-P1Deopt and Asia1-P1Deopt strains, only a limited induction of adaptive immunity and protection against challenge was detected, depending on the inoculated dose and serotype deoptimized. Our work demonstrates that while CPD of the P1 coding region attenuates viral strains of multiple FMDV serotypes/subtypes, a thorough assessment of virulence and induction of adaptive immunity in the natural host is required in each case in order to finely adjust the degree of deoptimization required for attenuation without affecting the induction of protective adaptive immune responses.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

StreamGen: Connecting Populations of Streams and Shells to Their Host Galaxies

In this work, we study how the abundance and dynamics of populations of disrupting satellite galaxies change systematically as a function of host galaxy properties. We apply a theoretical model of the phase-mixing process to classify intact satellite galaxies and stellar streamlike and shell-like debris in ∼1500 Milky Way–mass systems generated by a semi-analytic galaxy formation code, SatGen. In particular, we test the effect of host galaxy halo mass, disk mass, ratio of disk scale height to length, and stellar feedback model on disrupting satellite populations. We find that the counts of tidal debris are consistent across all host galaxy models, within a given host mass range, and that all models can have streamlike debris on low-energy orbits, consistent with that observed around the Milky Way. However, we find a preference for streamlike debris on lower-energy orbits in models with a thicker (lower-density) host disk or on higher-energy orbits in models with a more massive host disk. Importantly, we observe significant halo-to-halo variance across all models. These results highlight the importance of simulating and observing large samples of Milky Way–mass galaxies and accounting for variations in host properties when using disrupting satellites in studies of near-field cosmology.

dark matter↗

DOE OSTI2019

Solar Research Spotlight: Systems Integration

This Solar Energy Technologies Office fact sheet provides an overview of the systems integration subprogram, which funds research and development projects in five broad, interrelated focus areas: planning and operation, solar plus X, power electronics, sensing and communication, and codes and standards.

Solar Energy Technologies Office fact sheet, syste↗

DOE OSTI2019

A Knowledge Graph Approach for the Secondary Use of Cancer Registry Data

Population-based central cancer registries collect valuable structured and unstructured data primarily for cancer surveillance and research, enhancing insights into clinical features associated with cancer occurrence, cancer treatment, and cancer outcomes to guide interventions which reduce the cancer burden. Cancer registries primarily collect data on (1) cancer type (case or tumor); (2) patient demographics such as age, gender, and residential address at time of diagnosis; (3) planned first course of treatment; and (4) date of last contact, vital status, and cause of death. Cancer registry data is dynamic, structured data, which is extracted from many unstructured sources such as electronic healthcare records, and consolidated for reporting and other purposes. While available advanced analytic tools such as SEER*Stat have the ability to build SAS queries, we, however, explore an innovative knowledge graph approach to organizing cancer registry data for advanced analytics and visualization, which has unique advantages over approaches of existing tools. This innovative knowledge graph approach semantically enriches the data and easily enables linkage with third-party data, which can better explain variation in outcomes. We have developed a prototype knowledge graph based on data from the Louisiana Tumor Registry and other publicly available datasets including Behavioral Risk Factor Surveillance System, Clinical Trials, DBpedia, GeoNames, Rural-Urban Continuum Codes, and Semantic MEDLINE. The resource description framework (RDF) data model was selected to represent our knowledge graph, which contains more than 25 billion triples and is ~4TB in storage size. To exhibit the benefits of the knowledge graph approach, we used scenario specific queries, which find the relationships between cancer treatment sequences and outcomes. To illustrate its ease of use in iterative analysis, the knowledge graph was linked to external datasets for performing complex queries across multiple datasets. In addition, we used knowledge graphs to identify data discrepancies and to handle schema changes. Finally, we visualized the knowledge graph to discover data patterns. Our results demonstrate this graph-based solution enables cancer researchers to execute complex queries and more easily perform iterative analyses to improve understanding of cancer registry data. In the future, we would like to use high-performance computing (HPC) resources for faster-generating hypotheses with clinical potential from our knowledge graph.

Hasan, S M Shamimul↗

DOE OSTI2023

Statistical Approaches for Pebble Bed Reactor Operations and Safeguards

The design of pebble bed reactors (PBRs) and their method of operation align more closely with statistical approaches used in manufacturing and process control than traditional safeguards statistical approaches. The reason is PBRs will employ a nondestructive assay (NDA) measurement (burnup measurement system [BUMS]) that is part of the fuel handling system supporting discharge decisions in addition to the reactor code which monitor performance. The integration of these two approaches provides the opportunity to monitor reactor performance statistically for both operations and safeguards in ways not achievable using other reactor designs. For light water reactors (LWRs), knowledge about reactor code performance in predicting irradiated special nuclear material (SNM) content historically was only achieved from special measurement campaigns or from fuel reprocessing. Conversely, through statistical comparison of the BUMS with the reactor code-predicted values, PBRs can achieve this in real time. The resulting SNM distribution is an indicator of reactor performance because factors such as transit time and path of the pebble fuel through the reactor determine the plutonium production and uranium depletion. By analyzing the predicted and measured values, opportunities exist to adjust operating parameters, fuel design, and other characteristics to optimize performance and fuel utilization. From a safeguards perspective, this approach also provides the information necessary to validate declared values and evaluate whether the reactor is being operated as expected. This paper outlines statistical approaches for PBRs that can be used to support both operations and safeguards.

Ball, Cory↗