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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial in situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Big data↗
DOE OSTI2021

Modeling of particle transport, neutrals and radiation in magnetically-confined plasmas with Aurora

In this work, we present Aurora, an open-source package for particle transport, neutrals and radiation modeling in magnetic confinement fusion plasmas. Aurora's modern multi-language interface enables simulations of 1.5D impurity transport within high-performance computing frameworks, particularly for the inference of particle transport coefficients. A user-friendly Python library allows simple interaction with atomic rates from the Atomic Data and Atomic Structure database as well as other sources. This enables a range of radiation predictions, both for power balance and spectroscopic analysis. We discuss here the superstaging approximation for complex ions, as a way to group charge states and reduce computational cost, demonstrating its wide applicability within the Aurora forward model and beyond. Aurora also facilitates neutral particle analysis, both from experimental spectroscopic data and other simulation codes. Leveraging Aurora's capabilities to interface SOLPS-ITER results, we demonstrate that charge exchange is unlikely to affect the total radiated power from the ITER core during high performance operation. Finally, we describe the ImpRad module in the one modeling framework for integrated task framework, developed to enable experimental analysis and transport inferences on multiple devices using Aurora.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

ECAR-7210 Rev 0 Steady-state Thermo-mechanical Analysis of the MARVEL Fuel Bundle

This document reports the steady-state thermal-hydraulic and static mechanical analyses of the MARVEL micro-reactor core. The objective of this work is to investigate whether fuel-to-fuel contact could occur due to the thermal deformation of the fuel cladding during the normal operation and to assess the resulting impact on the peak cladding temperatures (PCT) if contact occurs. The scope of the work consists of three computational tasks. First, a conjugate heat transfer analysis using computational fluid dynamics (CFD) model was performed to evaluate the PCTs during normal operating conditions. Second, a finite element analysis (FEA) using the cladding temperature field obtained from the CFD analysis was performed to evaluate the thermal deformation of cladding and determine the occurrence of fuel-to-fuel contact. Finally, a CFD analysis of FEA-informed fuel-to-fuel gap (represented by a conservative 0.05 mm uniform gap) was performed to evaluate whether the PCT exceeds the safety criteria.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2015

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist is responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

ASC ATDM Level 2 Milestone #6015: Asynchronous Many-Task Software Stack Demonstration

This report is an outcome of the ASC ATDM Level 2 Milestone 6015: Asynchronous Many-Task Software Stack Demonstration. It comprises a summary and in depth analysis of DARMA and a DARMA-compliant Asynchronous Many-Task (AMT) runtime software stack. Herein performance and productivity of the over- all approach are assessed on benchmarks and proxy applications representative of the Sandia ATDM applications. As part of the effort to assess the perceived strengths and weaknesses of AMT models compared to more traditional methods, experiments were performed on ATS-1 (Advanced Technology Systems) test bed machines and Trinity. In addition to productivity and performance assessments, this report includes findings on the generality of DARMAs backend API as well as findings on interoperability with node- level and network-level system libraries. Together, this information provides a clear understanding of the strengths and limitations of the DARMA approach in the context of Sandias ATDM codes, to guide our future research and development in this area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

IEA Wind TCP Task 26–Wind Technology, Cost, and Performance Trends in Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States: 2008-2016

The International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 26 - The Cost of Wind Energy represents an international collaboration dedicated to exploring the past, present, and future cost of wind energy. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States. This report discusses trends from 2008 through 2016 that affected the cost of land-based wind energy in each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country. This report builds from previous analysis conducted since the inception of Task 26 in 2009. Schwabe et al. (2011) explored differences in the cost of wind energy in 2008 among countries participating in Task 26 at that time. Vitina et al. (2015) presented turbine- and project-level trends in the wind industry from 2008 to 2012, including wind project size, turbine size, specific power and hub height, project performance, investment costs, operation and maintenance (O&M) costs, and project financing. These inputs are used to calculate the levelized cost of energy (LCOE), a widely recognized metric for understanding how technology performance, capital investment, operations, and financing impact the life cycle cost of building and operating a wind project. Both prior reports - as well as this report - used this metric to estimate the cost of wind energy.

17 WIND ENERGY↗
DOE OSTI2020

Tank 49H Solids Disturbance Analysis

Tank 49H will serve as the feed tank for the Salt Waste Processing Facility (SWPF). Transfers into Tank 49H may disturb solids that have settled to the bottom of the tank, resulting in feed that may exceed the insoluble solids content limit of 1200 mg/L from the SWPF Waste Acceptance Criteria (WAC). During a transfer into Tank 49H, material that free falls from the Tank 49H B4 downcomer and passes through the supernate could potentially disturb the solids on the bottom of the tank and scour or suspend solids from a settled solids layer or turbid region. The scope of this task is to perform fluid flow analysis to determine the impact of a “plunging jet” through the B4 downcomer on solids in Tank 49H and to determine a minimum liquid level to be maintained in Tank 49H prior to transfers that will minimize disturbing the solids and exceeding the SWPF WAC limits for insoluble solids carryover to SWPF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

DECOVALEX-2023 Task E Specification (Rev. 0)

This report is the Task E specification (Revision 0) for DECOVALEX-2023. Task E is focused on understanding thermal, hydrological, mechanical and chemical (THMC) processes, especially related to predicting brine migration in heated salt. The main test case being used is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. This report provides short motivational background, a summary of relevant experiments and data, and a step-by-step plan for the analysis by the teams participating in Task E (Rev. 0 includes detailed description of steps 0 and 1). This document will be revised, and more detail will be added to later steps during DECOVALEX-2023.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy

Over the past several decades, electron and scanning probe microscopes have become critical components of condensed matter physics, materials science and chemistry research. At the same time, the infrastructure for establishing a connection between microscopy observations and materials behaviour over a broader parameter space is lacking. In this work, we introduce AtomAI, an open-source software package bridging instrument-specific Python libraries, deep learning and simulation tools into a single ecosystem. AtomAI allows direct applications of deep neural networks for atomic and mesoscopic image segmentation converting image and spectroscopy data into class-based local descriptors for downstream tasks such as statistical and graph analysis. For atomically resolved imaging data, the output is types and positions of atomic species, with an option for subsequent refinement. AtomAI further allows the implementation of a broad range of image and spectrum analysis functions, including invariant variational autoencoders for disentangling structural factors of variation and im2spec type of encoder–decoder models for mapping structure–property relationships. Finally, our framework allows seamless connection to the first principles modelling with a Python interface on the inferred atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer

Molecular dynamics (MD) simulations must take very small (femtosecond) integration steps in simulation-time to avoid numerical errors. Efficient use of parallel programming models and accelerators in state-of-the art MD programs now is pushing Moore’s limit for time-per-MD step. As a result, directly simulating timescales beyond milliseconds will not be attainable directly, even at exascale. However, concepts from statistical physics can be used to combine many parallel simulations to provide information about longer timescales and to adequately sample the simulation space, while preserving details about the dynamics of the system. Implementing such an approach requires a workflow program that allows adaptable steering of task assignments based on extensive statistical analysis of intermediate results. Here we report the implementation of such an adaptable workflow program to drive simulations on the Summit IBM Power System AC922, a pre-exascale supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). We compare to experiences on Titan, Summit’s predecessor, report the performance of the workflow and its components, and describe the porting process. We find that using a workflow program managed by a Mongo database can provide the fault tolerance, scalable performance, task dispatch rate, and reconfigurability required for robust and portable implementation of ensemble simulations such as are used in enhanced-sampling molecular dynamics. This type of workflow generator can also be used to provide adaptive steering of ensemble simulations for other applications in addition to MD.

Ossyra, John R.↗
DOE OSTI2018

Analysis of the Frequency and Diversity of 1,3-Dialkylimidazolium Ionic Liquids Appearing in the Literature

The hypothetical assertion that there are potentially millions of ionic liquids (ILs) can be validated using basic knowledge of IL precursors and simple calculations. While it is an interesting thought exercise to ponder the possibilities of ILs, it is important to investigate how many discrete ILs (i.e., unique cation and anion pairings) have actually been synthesized and reported in the literature. A complete analysis of all ILs is a daunting task, especially if the definition of what constitutes an IL is broad. Nonetheless, insight can be gained into the use of ILs over the past ~20 years from a focused analysis of systematically varied 1,3-dialkylimidazolium-based ILs (i.e., [R 1 R 2 im][X], where R 1 and R 2 are n-alkyl chains and X is either a halide or molecular anion). This family of ILs includes many of the most widely used and most thoroughly studied IL substances, including 1-butyl-3-methylimidazolium hexafluorophosphate ([C 4 mim][PF 6 ]) and 1-ethyl-3-methylimidazolium bistriflimide ([C 2 mim][Tf 2 N]). Using data retrieved from SciFinder searches, we analyzed the variety and frequency of 1,3-dialkylimidazolium-based ILs appearing in the literature. Our analysis reveals that there is a relatively large number of simple 1,3-dialkylimidazolium cations which have not yet been synthesized. Our findings indicate that despite the broad possibilities of IL structures available, there are but a handful of ILs that are commonly used and studied. Within the 1248 [R 1 R 2 im][X] ILs studied, there were only 12 cations extensively used, which included [R 1 R 2 im] + (R 1 = C 1 and R 2 = C 1 –C 12 ). Of the 16 anions studied, only 5, including [BF 4 ] – , [Cl] – , [PF 6 ] – , [Tf 2 N] – , and [Br] – , were used significantly. Thus, it appears that although ILs can be used as designer solvents with task-specific properties, there is a small default subset of ILs, which are “go-to” or “one-size-fits-all.” Here, we rationalize the current state of the IL landscape in terms of the historical perceptions (and misconceptions) around ILs, familiarity, availability and cost of starting materials, commercial availability of ILs, and the motivations from which researchers choose to synthesize and characterize new ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

FY18 ASC CSSE L2 Milestone 6362: Local Failure Local Recovery (LFLR) Resiliency for Asynchronous Many Task (AMT) Programming and Execution Models

The overall goal of this work was to perform an in-depth analysis of resilience schemes adapted to the Asynchronous Many-Task (AMT) programming and execution model with the goal of informing the Sandia Advanced Simulation and Computing (ASC) program's application development strategy for next generation platforms (NGPs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-11: A Cloud Based CT and LINAC QA Data Management System

Purpose: The current status quo of QA data management consists of a mixture of paper-based forms and spreadsheets for recording the results of daily, monthly, and yearly QA tests for both CT scanners and LINACs. Unfortunately, such systems suffer from a host of problems as, (1) records can be easily lost or destroyed, (2) data is difficult to access — one must physically hunt down records, (3) poor or no means of historical data analysis, and (4) no remote monitoring of machine performance off-site. To address these issues, a cloud based QA data management system was developed and implemented. Methods: A responsive tablet interface that optimizes clinic workflow with an easy-to-navigate interface accessible from any web browser was implemented in HTML/javascript/CSS to allow user mobility when entering QA data. Automated image QA was performed using a phantom QA kit developed in Python that is applicable to any phantom and is currently being used with the Gammex ACR, Las Vegas, Leeds, and Catphan phantoms for performing automated CT, MV, kV, and CBCT QAs, respectively. A Python based resource management system was used to distribute and manage intensive CPU tasks such as QA phantom image analysis or LaTeX-to-PDF QA report generation to independent process threads or different servers such that website performance is not affected. Results: To date the cloud QA system has performed approximately 185 QA procedures. Approximately 200 QA parameters are being actively tracked by the system on a monthly basis. Electronic access to historical QA parameter information was successful in proactively identifying a Linac CBCT scanner’s performance degradation. Conclusion: A fully comprehensive cloud based QA data management system was successfully implemented for the first time. Potential machine performance issues were proactively identified that would have been otherwise missed by a paper or spreadsheet based QA system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

El Agente: An autonomous agent for quantum chemistry

Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

agentic systems↗
DOE OSTI2015

ParaView Catalyst: Enabling In Situ Data Analysis and Visualization

Computer simulations are growing in sophistication and producing results of ever greater fidelity. This trend has been enabled by advances in numerical methods and increasing computing power. However these advances come with several costs including massive increases in data size, difficulties examining output data, challenges in configuring simulation runs, and difficulty debugging running codes. Interactive visualization tools, like ParaView, have been used for post-processing of simulation results. However, the increasing data sizes, and limited storage and bandwidth make high fidelity post-processing impractical. In situ analysis is recognized as one of the ways to address these challenges. In situ analysis moves some of the post-processing tasks in line with the simulation code thus short circuiting the need to communicate the data between the simulation and analysis via storage. ParaView Catalyst is a data processing and visualization library that enables in situ analysis and visualization. Built on and designed to interoperate with the standard visualization toolkit VTK and the ParaView application, Catalyst enables simulations to intelligently perform analysis, generate relevant output data, and visualize results concurrent with a running simulation. Here, we provide an overview of the Catalyst framework and some of the success stories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Comprehensive Evaluation of the Geothermal Resource Potential within the Pyramid Lake Paiute Reservation Phase III Report

This project integrated state-of-the-art exploration technologies with a geologic framework and reservoir modeling to ultimately determine the efficacy of future geothermal production within the PLPT reservation. The information gained during this study should help the PLPT to make informed decisions regarding construction of a geothermal power plant. Additional benefits included the transfer of new technologies and geothermal data to the geothermal industry and it created and/or preserved nearly three dozen jobs accordance with the American Recovery and Reinvestment Act of 2009. A variety of tasks were conducted to achieve the above stated objectives. The following are the tasks completed within the project: 1. Permitting 2. Shallow temperature survey 3. Seismic data collection and analysis 4. Fracture stress analysis 5. Phase I reporting Permitting 7. Shallow temperature survey 8. Seismic data collection and analysis 9. Fracture stress analysis 10. Phase I reporting 11. Drilling two new wells 12. Borehole geophysics 13. Phase II reporting 14. Well testing and geochemical analysis 15. Three-dimensional geologic model 16. Three-dimensional reservoir analysis 17. Reservation wide geothermal potential analysis 18. Phase III reporting Phase I consisted of tasks 1 – 5, Phase II tasks 6 – 8, and Phase III tasks 9 – 13. This report details the results of Phase III tasks. Reports are available for Phase I, and II as separate documents.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Demonstration of a prototype hydrogen sensor and electronics package

This is a progress report for the demonstration of a prototype hydrogen sensor and electronics package. There are five tasks associated with this, and four have been completed as of August 2016: Station Demonstration and Site Recommendation, Order Sensor Equipment, Build Sensors, and Install Sensors. The final task to be completed is Sensor Demonstration and Data Analysis, and expected completion date is January 26, 2017. This progress report details each of the tasks and goes into detail about what is currently being worked on, along with the budget and planned work for July 27, 2016 to January 26, 2017.

36 MATERIALS SCIENCE↗