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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Computing in high-energy physics

I present a very personalized journey through more than three decades of computing for experimental high-energy physics, pointing out the enduring lessons that I learned. This is followed by a vision of how the computing environment will evolve in the coming ten years and the technical challenges that this will bring. I then address the scale and cost of high-energy physics software and examine the many current and future challenges, particularly those of management, funding and software-lifecycle management. Lastly, I describe recent developments aimed at improving the overall coherence of high-energy physics software.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Origin of age softening in the refractory high-entropy alloys

Refractory high-entropy alloys (RHEAs) are emerging materials with potential for use under extreme conditions. As a newly developed material system, a comprehensive understanding of their long-term stability under potential service temperatures remains to be established. This study examined a titanium-vanadium-niobium-tantalum alloy, a promising RHEA known for its superior high-temperature strength and room-temperature ductility. Using a combination of advanced analytical microscopies, Calculation of Phase Diagrams (CALPHAD) software, and nanoindentation, we investigated the evolution of its microstructure and mechanical properties upon aging at 700°C. Trace interstitials such as oxygen and nitrogen, initially contributing to solid solution strengthening, promote phase segregation during thermal aging. As a result of the depletion of solute interstitials within the metal matrix, a progressive softening is observed in the alloy as a function of aging time. This study, therefore, underscores the need for a better control of impurities in future development and application of RHEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Surrogate Models for Estimating Failure in Brittle and Quasi-Brittle Materials

In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI). High-fidelity models for brittle failure that accurately predict these QoI exist but are highly computationally intensive, making them infeasible to incorporate in upscaling and uncertainty quantification frameworks. The goal of this paper is to provide a fast heuristic to reasonably estimate quantities such as failure path and damage in the process of brittle failure. Towards this goal, we first present a method to predict failure paths under tensile loading conditions and low-strain rates. The method uses a k-nearest neighbors algorithm built on fracture process zone theory, and identifies the set of all possible pre-existing cracks that are likely to join early to form a large crack. The method then identifies zone of failure and failure paths using weighted graphs algorithms. We compare these failure paths to those computed with a high-fidelity fracture mechanics model called the Hybrid Optimization Software Simulation Suite (HOSS). A probabilistic evolution model for average damage in a system is also developed that is trained using 150 HOSS simulations and tested on 40 simulations. A non-parametric approach based on confidence intervals is used to determine the damage evolution over time along the dominant failure path. For upscaling, damage is the key QoI needed as an input by the continuum models. This needs to be informed accurately by the surrogate models for calculating effective moduli at continuum-scale. We show that for the proposed average damage evolution model, the prediction accuracy on the test data is more than 90%. In terms of the computational time, the proposed models are ≈ O ( 10 6 ) times faster compared to high-fidelity fracture simulations by HOSS. These aspects make the proposed surrogate model attractive for upscaling damage from micro-scale models to continuum models. We would like to emphasize that the surrogate models are not a replacement of physical understanding of fracture propagation. The proposed method in this paper is limited to tensile loading conditions at low-strain rates. This loading condition corresponds to a dominant fracture perpendicular to tensile direction. The proposed method is not applicable for in-plane shear, out-of-plane shear, and higher strain rate loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The International Virus Bioinformatics Meeting 2020

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8–9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Genomic Island Identification Software v 1.0

Genomic islands are key mobile DNA elements in bacterial evolution, that can distinguish pathogenic strains from each other, or distinguish pathogenic strains from non-pathogenic strains. Their detection in genomes is a challenging problem. We present 3 main software components that attack the island detection problem on two different bases: 1) the preference of islands to insert in chromosomal tRNA or tmRNA genes (islander.pl), and 2) islands' sporadic occurrence among closely related strains. The latter principle is employed in both an algorithm (learnedPhyloblocks.pl) and a visualization method (panGenome.pl). Component islander.pl finds islands based on their preference for a particular target gene type. We annotate each tRNA and tmRNA gene, find fragments of each such gene as candidates for the distal ends of islands, and filter candidates to remove false positives. Component learnedPhyloblocks.pl uses islands found by islander.pl and other methods as a training set to find new islands. Reference genomes are aligned using mugsy, then the "phylotypes" or patterns of occurrence in the reference set are determined for each position in the target genome, and those phylotypes most enriched in the training set of islands are followed to detect yet more islands. Component panGenome.pl produces a big-data visualization of the chromosomally-ordered "pan-genome", that includes every gene of every reference genome (x-axis, pan-genome order; y-axis, reference genomes; color-coding, gene presence/absence etc.), islands appearing as dark patches.

Williams, KellyPorter↗
DOE OSTI2014

Genomic Island Identification Software v 1.0

Genomic islands are key mobile DNA elements in bacterial evolution, that can distinguish pathogenic strains from each other, or distinguish pathogenic strains from non-pathogenic strains. Their detection in genomes is a challenging problem. We present 3 main software components that attack the island detection problem on two different bases: 1) the preference of islands to insert in chromosomal tRNA or tmRNA genes (islander.pl), and 2) islands' sporadic occurrence among closely related strains. The latter principle is employed in both an algorithm (learnedPhyloblocks.pl) and a visualization method (panGenome.pl). Component islander.pl finds islands based on their preference for a particular target gene type. We annotate each tRNA and tmRNA gene, find fragments of each such gene as candidates for the distal ends of islands, and filter candidates to remove false positives. Component learnedPhyloblocks.pl uses islands found by islander.pl and other methods as a training set to find new islands. Reference genomes are aligned using mugsy, then the "phylotypes" or patterns of occurrence in the reference set are determined for each position in the target genome, and those phylotypes most enriched in the training set of islands are followed to detect yet more islands. Component panGenome.pl produces a big-data visualization of the chromosomally-ordered "pan-genome", that includes every gene of every reference genome (x-axis, pan-genome order; y-axis, reference genomes; color-coding, gene presence/absence etc.), islands appearing as dark patches.

Source record↗
DOE OSTI2017

Sustainable Data Evolution Technology for Power Grid Optimization

The SDET Tool is used to create open-access power grid data sets and facilitate updates of these data sets by the community. Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.

Source record↗
DOE OSTI2017

Sustainable Data Evolution Technology for Power Grid Optimization

The SDET Tool is used to create open-access power grid data sets and facilitate updates of these data sets by the community. Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.

Source record↗
DOE OSTI2020

dCache - Keeping up With the Evolution of Science

The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements of various scientific communities. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, through wide access and easy integration with existing systems, including event driven workflow management. With this presentation, we will show some of the recent developments that optimize data management and access to maximise the gain from stored data.

Mkrtchyan, Tigran↗
DOE OSTI2017

The Beam-Beam Effect and its Consequences for the Jefferson Lab EIC

In this work we address the effect of beam jitter on emittance growth as caused by the beam-beam effect on the Jefferson Lab Electron Ion Collider (JLEIC). This proposed collider would collide up to 100 GeV proton beams with up to 10 GeV electron beams. Due to the asymmetric rigidities of the beams and their non-linear lensing action on each other during a collision, collective effects can limit beam storage times. Using simulations we determined that one of JLEIC’s synchronization concepts would require a new set of software tools to accurately understand phase space evolution.

Nissen, Edward↗
DOE OSTI2021

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Evolution of Oxide–Sulfide Complex Inclusions and Its Correlation with Steel Cleanliness During Electroslag Rapid Remelting (ESRR) of Tool Steel

The evolution of CaO-Al{sub 2}O{sub 3}-MgO-(SiO{sub 2}) inclusions associated with CaS during electroslag rapid remelting (ESRR) of the tool steel with ultra low oxygen (8 ppm) under protective atmosphere was investigated. Thermodynamic calculation was performed to evaluate the oxygen level of liquid steel and the inclusion evolution during ESRR with the help of FactSage software (CON2 database). The results demonstrated that the reoxidation of liquid steel took place during industrial ESRR, resulting in the oxygen pickup of approximately double content. The oxygen level in the steel was determined by [Al]-[O] equilibrium during ESRR, whereas FeO in the slag transferred oxygen into the liquid steel, as indicated by the significant oxygen pickup. The inclusions in the steel electrode are oxide–sulfide type of CaO-Al{sub 2}O{sub 3}-MgO partially wrapped with CaS. The original oxide inclusions that had not been removed in ESRR process were transformed to liquid CaO-Al{sub 2}O{sub 3}-SiO{sub 2}-MgO inclusions through reacting with the dissolved oxygen supplied from the reoxidation of liquid steel and concerned elements in liquid steel during ESRR. These CaO-Al{sub 2}O{sub 3}-SiO{sub 2}-MgO inclusions were invariably associated with patch-type or shell-type CaS, which hold different formation mechanisms. The inclusions ranging from 2 to 4 µm take up a dominant proportion (a little more than 50 pct of the total inclusions) in the remelted ingots, and those larger than 8 µm account for about 3 pct. Melting rates of ESRR not only exerted a negligible effect on the steel cleanliness and the removal efficiency of oxide inclusions, but also on the inclusion size distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Application of Portable Parallelization Strategies for GPUs on track reconstruction kernels

Utilizing the computational power of GPUs is one of the key ingredients to meet the computing challenges presented to the next generation of High-Energy Physics (HEP) experiments. Unlike CPUs, developing software for GPUs often involves using architecturespecific programming languages promoted by the GPU vendors and hence limits the platform that the code can run on. Various portability solutions have been developed to achieve portable, performant software across different GPU vendors. Given the rapid evolution of these portability solutions, an early adoption of them in simple HEP testbed applications will help us understand the strengths and weaknesses of respective approaches.We apply several portability solutions, including Alpaka, Kokkos, SYCL and std::execution::par, on kernels for track propagation extracted from the mkFit project. We report on the development experience of the same application with different portability solutions, as well as their performance on GPUs, measured as the throughput of the kernels, from different manufacturers such as NVIDIA, AMD and Intel.

Kwok, Martin [Fermilab] (ORCID:0000000286936146)↗
DOE OSTI2025

FORECASTOR – II. Simulating galaxy surveys with the Cosmological Advanced Survey Telescope for Optical and UV Research

The Cosmological Advanced Survey Telescope for Optical and UV Research (CASTOR) is a planned flagship space telescope, covering the blue-optical and UV part of the spectrum. Here, we introduce the CASTOR image simulator, a python GalSim package-based script capable of generating mock CASTOR images from an input catalogue. We generate example images from the CASTOR Wide, Deep, and Ultra-Deep surveys using simulated lightcones from the Santa Cruz semi-analytic model. We make predictions for the performance of these surveys by comparing galaxies that are extracted from each image using Source Extractor to the input catalogue. We find that the Wide, Deep, and Ultra-Deep surveys will be 75 per cent complete for point sources down to $\sim 27$, 29, and 30 mag, respectively, in the UV, u, and g filters, with the UV-split and u-split filters reaching a shallower depth. With a large area of $\sim 2200$ deg$^2$, the Wide survey will detect hundreds of millions of galaxies out to $z\sim 4$, mostly with $M_\ast \gtrsim 10^{9}\,{\rm M}_{\odot }$. The Ultra-Deep survey will probe to $z\sim 5$, detecting galaxies with $M_\ast \gtrsim 10^{7}{\rm M}_{\odot }$. These galaxy samples will enable precision measurements of the distribution of star formation in the cosmic web, connecting the growth of stellar mass to the assembly of dark matter haloes over two thirds of the history of the Universe, and other core goals of CASTOR’s legacy surveys. These image simulations and the tools developed to generate them will be a vital planning tool to estimate CASTOR’s performance and iterate the telescope and survey designs prior to launch.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Sci—Fri PM: Dosimetry—06: Commissioning of a 3D patient specific QA system for hypofractionated prostate treatments

The objective of this work is to commission the 6MV-SRS beam model in COMPASS (v2.1, IBA-Dosimetry) and validate its use for patient specific QA of hypofractionated prostate treatments. The COMPASS system consists of a 2D ion chamber array (MatriXX{sup Evolution}), an independent gantry angle sensor and associated software. The system can either directly calculate or reconstruct (using measured detector responses) a 3D dose distribution on the patient CT dataset for plan verification. Beam models are developed and commissioned in the same manner as a beam model is commissioned in a standard treatment planning system. Model validation was initially performed by comparing both COMPASS calculations and reconstructions to measured open field beam data. Next, 10 hypofractionated prostate RapidArc plans were delivered to both the COMPASS system and a phantom with ion chamber and film inserted. COMPASS dose distributions calculated and reconstructed on the phantom CT dataset were compared to the chamber and film measurements. The mean (± standard deviation) difference between COMPASS reconstructed dose and ion chamber measurement was 1.4 ± 1.0%. The maximum discrepancy was 2.6%. Corresponding values for COMPASS calculation were 0.9 ± 0.9% and 2.6%, respectively. The average gamma agreement index (3%/3mm) for COMPAS reconstruction and film was 96.7% and 95.3% when using 70% and 20% dose thresholds, respectively. The corresponding values for COMPASS calculation were 97.1% and 97.1%, respectively. Based on our results, COMPASS can be used for the patient specific QA of hypofractionated prostate treatments delivered with the 6MV-SRS beam.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Software Quality Metrics for Geant4: An Initial Assessment - Paper 122

In the context of critical applications, such as shielding and radiation protection, ensuring the quality of simulation software they depend on is of utmost importance. The assessment of simulation software quality is crucial both to determine its adoption in experimental applications and to guarantee reproducibility of outcome over time. Geant4 is a simulation system used in a wide range of experimental applications, some of which, such as radiation protection and biomedical studies, may involve critical use cases and would especially profit from an objective assessment of the software quality. In this study, we present the first results from an ongoing analysis of Geant4 code based on established software metrics from the perspective of software engineering. The analysis evaluates the current status of the code to quantify its characteristics with respect to documented quality standards; further appraisals concern evolutions over a series of release distributions. The quantitative assessment of the software is initially focused on a subset of Geant4 packages, which play a key role in scientific applications and are representative of different software development processes. We describe the chosen software metrics that map the entities of a software system to numeric values through mathematical definitions, quantifying software attributes ranging from functionality to maintainability. To measure such metrics, we exploited a set of software metrics tools, i.e. programs that implement a set of software metrics definitions. They allow software engineers to assess a software system by extracting the required attributes from the software and providing the corresponding metric values. To correlate software metrics values in a well-defined way, we used software quality standard models, such as the ISO/IEC 9126 standard, which aggregate numerical values to aid quality analysis and assessment. With this work we aim to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. Furthermore, we intend to highlight what metrics are most effective at evaluating radiation transport software quality. We are confident that the result will provide constructive guidance both to improve key software tools, such as Geant4, and to estimate their contribution in risk analysis concerning sensitive applications. The remainder of this paper is structured as follows. We first discuss the approach adopted to fulfil our assessment. Then, we present the setup of our experiments and the way we collected data. We provide an initial interpretation of a subset of data resulting from measurements made on the selected Geant4 packages. As the analysis is still ongoing at the time of submitting this abstract, some results will be documented in the final paper and in the conference presentation. With this work we aim to create a proper Geant4 data set for evaluating its software characteristics and identifying both strengths and weaknesses. In this initial study, we considered the geometry and processes packages, which play a major role in most simulation applications. The data analysis is in progress at the time of writing; its complexity is related to the differences among software metrics tools, to the large amount of data to be evaluated and to the pioneering character of this project. We are confident that the results will provide valuable indications for the Geant4 user community and constructive guidance to improve key Geant4 packages. Other Monte Carlo codes could profit from the methodology developed in this pilot project for similar assessments of their software quality. At the end of this study, we intend to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Toward Process-Based Quality through a Fundamental Understanding of Weld Microstructural Evolution

Here, in this overview paper, the possibility of qualifying welded components by integrating software and hardware tools that are capable of describing physical processes that occur during welding is explored. The existing and emerging tools to define geometrical boundary conditions, process parameters, heat and mass transfer, solidification, solid-state transformation, plastic deformation, distortion, residual stress, and performance of welded components are reviewed. Existing challenges relevant to the fundamental understanding of complex alloying, processing environment, and transients in energy deposition are discussed with reference to microstructure evolution. Finally, approaches to address these challenges were articulated with published case studies relevant to welding and additive manufacturing.

36 MATERIALS SCIENCE↗