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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Porting Ordinary Applications to Blue Gene/Q Supercomputers

Efficiently porting ordinary applications to Blue Gene/Q supercomputers is a significant challenge. Codes are often originally developed without considering advanced architectures and related tool chains. Science needs frequently lead users to want to run large numbers of relatively small jobs (often called many-task computing, an ensemble, or a workflow), which can conflict with supercomputer configurations. In this paper, we discuss techniques developed to execute ordinary applications over leadership class supercomputers. We use the high-performance Swift parallel scripting framework and build two workflow execution techniques-sub-jobs and main-wrap. The sub-jobs technique, built on top of the IBM Blue Gene/Q resource manager Cobalt's sub-block jobs, lets users submit multiple, independent, repeated smaller jobs within a single larger resource block. The main-wrap technique is a scheme that enables C/C++ programs to be defined as functions that are wrapped by a high-performance Swift wrapper and that are invoked as a Swift script. We discuss the needs, benefits, technicalities, and current limitations of these techniques. We further discuss the real-world science enabled by these techniques and the results obtained.

Maheshwari, Ketan C.↗
DOE OSTI2021

Analysis of Tank 38H (HTF-38-21-24, -25) and Tank 43H (HTF-43-21-26, -27) Samples for Support of the Enrichment Control and Corrosion Control Programs

Feed limits have been established for the 2H-Evaporator system to ensure nuclear criticality is not possible and corrosion is minimized. These limits are protected by the Enrichment Control Program (ECP) and the Corrosion Control Program (CCP) that require periodic sampling and analysis to confirm that the waste supernate composition stays within the limits. Savannah River Remediation (SRR) obtained samples from two different heights within each of the two waste tanks supporting the 2H-Evaporator operations on March 26, 2021. The Tank 38H (evaporator drop tank) and Tank 43H (evaporator feed tank) samples were received by the Savannah River National Laboratory (SRNL) Shielded Cells on March 26, 2021. Analysis of these samples provides information necessary for determining compliance with the ECP and CCP. The sample characterization was requested via a Technical Task Request (TTR) and conducted based on a Task Technical and Quality Assurance Plan (TTQAP).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Artificial Intelligence for (AI) Nuclear Security: Expert Perspectives on AI Priorities for the Office of International Nuclear Security

Artificial intelligence (AI) has the potential to transform nuclear security operations, offering opportunities to enhance effectiveness while simultaneously introducing new challenges. As AI technologies rapidly evolve, agencies across the United States Government (USG) are researching, implementing, and evaluating various AI models and systems. Given the broad capabilities and applications of these technologies, it is essential for each agency to identify and articulate those areas where it can make meaningful contributions aligned with its mission and expertise. To address this need for strategic focus, in late Fiscal Year 2025 (FY2025), the Office of International Nuclear Security (INS) established an AI Task Force (AITF) to gather input from subject matter experts (SMEs) regarding the most appropriate role INS could serve in researching, evaluating, or implementing AI for nuclear security. The AITF engaged 15 experts from national laboratories with backgrounds in cyber security, physical security, transport security, insider threat mitigation, nuclear engineering, human-systems engineering, and AI/ML development. This white paper summarizes the insights gathered from these SMEs and presents a potential roadmap for INS engagement with AI technologies. The recommendations outlined here are intended to inform INS leadership as they make strategic decisions about resource allocation and program direction in this rapidly evolving technological domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance

Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-D-207A-05: Investigating Sparse-Sampled MRI for Motion Management in Thoracic Radiotherapy

Purpose: Sparse sampling and reconstruction-based MRI techniques represent an attractive strategy to achieve sufficiently high image acquisition speed while maintaining image quality for the task of radiotherapy guidance. In this study, we examine rapid dynamic MRI using a sparse sampling sequence k-t BLAST in capturing motion-induced, cycle-to-cycle variations in tumor position. We investigate the utility of long-term MRI-based motion monitoring as a means of better characterizing respiration-induced tumor motion compared to a single-cycle 4DCT. Methods: An MRI-compatible, programmable, deformable lung motion phantom with eleven 1.5 ml water marker tubes was placed inside a 3.0 T whole-body MR scanner (Philips Ingenia). The phantom was programmed with 10 lung tumor motion traces previously recorded using the Synchrony system. 2D+t image sequences of a coronal slice were acquired using a balanced-SSFP sequence combined with k-t BLAST (accn=3, resolution=0.66×0.66×5 mm3; acquisition time = 110 ms/slice). kV fluoroscopic (ground truth) and 4DCT imaging was performed with the same phantom setup and motion trajectories. Marker positions in all three modalities were segmented and tracked using an opensource deformable image registration package, NiftyReg. Results: Marker trajectories obtained from rapid MRI exhibited <1 mm error compared to kv Fluoro trajectories in the presence of complex motion including baseline shifts and changes in respiratory amplitude, indicating the ability of MRI to monitor motion with adequate geometric fidelity for the purpose of radiotherapy guidance. In contrast, the trajectory derived from 4DCT exhibited significant errors up to 6 mm due to cycle-to-cycle variations and baseline shifts. Consequently, 4DCT was found to underestimate the range of marker motion by as much as 50%. Conclusion: Dynamic MRI is a promising tool for radiotherapy motion management as it permits for longterm, dose-free, soft-tissue-based monitoring of motion, yielding richer and more accurate information about tumor position and motion range compared to the current state-of-the-art, 4DCT. This work was partially supported through research funding from National Institutes of Health (R01CA169102).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Status of the Full Circumference Examination of the Inner Container Closure Weld Region for Selected 3013 DE Container

One of the main focus areas of the 3013 Surveillance Program is a thorough evaluation of the inner container closure weld region (ICCWR) opened for destructive examination (DE). As part of the protocol to investigate the corrosion in the ICCWR a laser confocal microscope (LCM) is used to perform close visual examination of the surface and measurements of corrosion features on the surface. In FY17, DE containers from FY13 through FY16 were evaluated to select candidates for a full circumference analysis of the ICCWR. In FY18, the selected DE containers for full circumference evaluation (FCE) were processed according to the ICCWR protocol. However, due to the time intensive task for collecting high magnification images for a full circumference, only FY15 DE07 was selected for completion of LCM data collection in FY18 with the remaining DE containers scheduled to be completed in FY19.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Alternatives to the 15% Rule

The third solicitation of the California Solar Initiative (CSI) Research, Development, Demonstration and Deployment (RD&D) Program established by the California Public Utility Commission (CPUC) is supporting the Electric Power Research Institute (EPRI), National Renewable Energy Laboratory (NREL), and Sandia National Laboratories (SNL) with collaboration from Pacific Gas and Electric (PG&E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&E), in research to improve the Utility Application Review and Approval process for interconnecting distributed energy resources to the distribution system. Currently this process is the most time - consuming of any step on the path to generating power on the distribution system. This CSI RD&D solicitation three project has completed the tasks of collecting data from the three utilities, clustering feeder characteristic data to attain representative feeders, detailed modeling of 16 representative feeders, analysis of PV impacts to those feeders, refinement of current screening processes, and validation of those suggested refinements. In this report each task is summarized to produce a final summary of all components of the overall project.

Broderick, Robert Joseph↗
DOE OSTI2017

FY17 ISCR Scholar End-of-Assignment Report - Robbie Sadre

Throughout this internship assignment, I did various tasks that contributed towards the starting of the SASEDS (Safe Active Scanning for Energy Delivery Systems) and CES-21 (California Energy Systems for the 21st Century) projects in the SKYFALL laboratory. The goal of the SKYFALL laboratory is to perform modeling and simulation verification of transmission power system devices, while integrating with high-performance computing. The first thing I needed to do was acquire official Online LabVIEW training from National Instruments. Through these online tutorial modules, I learned the basics of LabVIEW, gaining experience in connecting to NI devices through the DAQmx API as well as LabVIEW basic programming techniques (structures, loops, state machines, front panel GUI design etc).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Reported Energy and Cost Savings from the DOE ESPC IDIQ Program: FY2021

The objective of this work was to determine the realization rate of energy and cost savings from the U.S. Department of Energy’s (DOE’s) Energy Savings Performance Contract (ESPC) program based on information reported by the energy services companies (ESCOs) that are carrying out ESPC projects at federal sites. Information was extracted from 201 measurement and verification (M&V) reports covering 193 projects to determine reported, estimated, and guaranteed cost savings and the associated reported and estimated energy savings for the previous contract performance year. This report covers projects that had a performance year ending in fiscal year 2021, between October 1, 2020 and September 30, 2021, and had an M&V report issued. Additionally, the annual cost to perform M&V was extracted from the individual project Task Order (TO) Schedules.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Reported Energy and Cost Savings from the DOE ESPC IDIQ Program: FY 2022

The objective of this work was to determine the realization rate of energy and cost savings from the U.S. Department of Energy’s (DOE’s) Energy Savings Performance Contract (ESPC) program based on information reported by the energy services companies (ESCOs) that are carrying out ESPC projects at federal sites. Information was extracted from 190 measurement and verification (M&V) reports covering 182 projects to determine reported, estimated, and guaranteed cost savings and the associated reported and estimated energy savings for the previous contract performance year. This report covers projects that had a performance year ending in fiscal year 2021, between October 1, 2021 and September 30, 2022, and had an M&V report issued. Additionally, the annual cost to perform M&V was extracted from the individual project Task Order (TO) Schedules.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Reported Energy and Cost Savings from the DOE ESPC IDIQ Program: FY 2023

The objective of this work was to determine the realization rate of energy and cost savings from the U.S. Department of Energy’s (DOE’s) Energy Savings Performance Contract (ESPC) program based on information reported by the energy services companies (ESCOs) that are carrying out ESPC projects at federal sites. Information was extracted from 201 measurement and verification (M&V) reports covering 191 projects to determine reported, estimated, and guaranteed cost savings and the associated reported and estimated energy savings for the previous contract performance year. This report covers projects that had a performance year ending in fiscal year 2023, between October 1, 2022 and September 30, 2023, and had an M&V report issued. Additionally, the annual cost to perform M&V was extracted from the individual project Task Order (TO) Schedules.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Conducting Beyond the Standard Model Searches in the MicroBooNE Detector with Machine Learning

MicroBooNE is one of the three neutrino detectors that comprise the Short Baseline Neutrino program at Fermilab. It utilizes Liquid Argon Time Projection Chamber (LArTPC) technology to probe the anomalous excess of electron-like events seen by its predecessor, MiniBooNE. Additionally, it provides a rich avenue of study for Beyond the Standard Model (BSM) theories. In the GeV energy regime relevant to MicroBooNE's beam neutrino program, many such theories lead to signatures which produce electron-positron (e+e-) final-states in the detector. While photons can pair produce into e+e- pairs with negligible opening angles, BSM theories often predict e+e- pairs with a broader range of opening angles. Thus, developing a tool that can reliably measure the opening angles of e+e- events is crucial for conducting rigorous BSM studies. However, these e+e- pairs result in topologically complex showers instead of clean tracks, making non-machine learning (ML) based methods such as line-fitting unsuitable for this task. This poster discusses the effectiveness of ML, namely a graph neural network called PointNet++, in accomplishing this goal. Our studies show promising results, with a resolution for the opening angle of 5 or less.

Bhelande, Vedang Adutya [Los Alamos]↗
DOE OSTI2017

An accurate and efficient algorithm for detection of radio bursts with an unknown dispersion measure, for single-dish telescopes and interferometers

Astronomical radio signals are subjected to phase dispersion while traveling through the interstellar medium. To optimally detect a short-duration signal within a frequency band, we have to precisely compensate for the unknown pulse dispersion, which is a computationally demanding task. We present the “fast dispersion measure transform” algorithm for optimal detection of such signals. Our algorithm has a low theoretical complexity of 2N{sub f}N{sub t}+N{sub t}N{sub Δ}log{sub 2}(N{sub f}), where N{sub f}, N{sub t}, and N{sub Δ} are the numbers of frequency bins, time bins, and dispersion measure bins, respectively. Unlike previously suggested fast algorithms, our algorithm conserves the sensitivity of brute-force dedispersion. Our tests indicate that this algorithm, running on a standard desktop computer and implemented in a high-level programming language, is already faster than the state-of-the-art dedispersion codes running on graphical processing units (GPUs). We also present a variant of the algorithm that can be efficiently implemented on GPUs. The latter algorithm’s computation and data-transport requirements are similar to those of a two-dimensional fast Fourier transform, indicating that incoherent dedispersion can now be considered a nonissue while planning future surveys. We further present a fast algorithm for sensitive detection of pulses shorter than the dispersive smearing limits of incoherent dedispersion. In typical cases, this algorithm is orders of magnitude faster than enumerating dispersion measures and coherently dedispersing by convolution. We analyze the computational complexity of pulsed signal searches by radio interferometers. We conclude that, using our suggested algorithms, maximally sensitive blind searches for dispersed pulses are feasible using existing facilities. We provide an implementation of these algorithms in Python and MATLAB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

IMPLEMENTING CYBERSECURITY INTO AN EXISTING NATIONAL NUCLEAR NON-PROLIFERATION PROGRAMME – A CASE STUDY

Cyber threat profiling and risk mitigation is critical to any nuclear state organization and should be considered as part of any comprehensive nuclear security programme. Defining and evaluating the impact of the cyber threat to mission can be challenging. An existing national nuclear non-proliferation organization undertook an effort to incorporate computer security activities into its programme to address cyber risk. One of the primary goals of this endeavour was to develop a set of prioritised recommendations for organizational follow-through. The organization dedicated subject matter expert resources in the form of a cyber task force to support this goal. Opportunities were identified where computer security could be built into each programme including office-level strategies and tools. Of course, no new identified threat vector is easily considered and incorporated into existing programmes without impact. There are many obstacles to be overcome. Technically literate subject matter experts are difficult to find, management has comparatively less experience applying computer security into its programmes, and trying to change the culture to consider computer security risk at policy and programmatic levels takes time and management attention. As an outcome of this process, a roadmap for program integration was developed, including the establishment of a cyber support team. This paper will discuss the challenges and successes associated with establishing such a team.

Cyber Security, Nuclear, Non-proliferation↗
DOE OSTI2016

MO-DE-BRA-05: EUTEMPE-RX: Combining E-Learning and Face-To-Face Training to Build Expert Knowledge, Skills and Competences for Medical Physicists in Diagnostic and Interventional Radiology

Purpose: In 2013, the EURATOM authorities of the European Commission decided to support the Horizon2020 project submission ‘EUTEMPE-RX’ that aimed for a new set of course modules to train medical physicists in diagnostic and interventional radiology to expert level with small group deep learning. Each module would consist of 2 phases: an e-learning and a face-to-face phase, each phase requiring typically 40h of participant time. Methods: The European Federation (EFOMP) and 13 European partners, all of them selected for their excellent scientific and/or educational skills, led the 12 course modules. A quality manual ensured the quality of course content and organization. Educational workshops familiarized the teachers with e-learning techniques and methods for assessment. Content was set in accordance with the EC document RP174 that lists learning outcomes in terms of knowledge, skills and competences (KSCs) for different specialties and levels of medical physics. Surveys for stake holder satisfaction were prepared. Results: Today the course modules are being realized. The modules cover most of the KSCs in RP174 document. Teachers have challenged the participants with unique tasks: case studies in medical physics leadership, Monte Carlo simulation of a complete x-ray imaging chain, development of a task specific QA protocol, compilation of optimization plans, simulation tasks with anthropomorphic breast models, etc. Participants undertook practical sessions in modern hospitals and visited a synchrotron facility, a calibration lab, screening organizations, etc. Feedback form quality surveys was very positive and constructive. A sustainability plan has been worked out. Conclusion: The modules have enabled the participants to develop their KSCs and cope with challenges in medical physics. The sustainability plan will be implemented to continue the unique combined e-learning and face to face training at high level training in diagnostic and interventional radiology also beyond Europe. The EUTEMPE-RX project is funded by the Horizon2020 - EURATOM program of the European Commission.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Long term predictions of coal fired power plant data using evolved recurrent neural networks

Abstract This work presents an investigation into the ability of recurrent neural networks (RNNs) to provide long term predictions of time series data generated by coal fired power plants. While there are numerous studies which have used artificial neural networks (ANNs) to predict coal plant parameters, to the authors’ knowledge these have almost entirely been restricted to predicting values at the next time step, and not farther into the future. Using a novel neuro-evolution strategy called Evolutionary eXploration of Augmenting Memory Models (EXAMM), we evolved RNNs with advanced memory cells to predict per-minute plant parameters and per-hour boiler parameters up to 8 hours into the future. These data sets were challenging prediction tasks as they involve spiking behavior in the parameters being predicted. While the evolved RNNs were able to successfully predict the spikes in the hourly data they did not perform very well in accurately predicting their severity. The per-minute data proved even more challenging as medium range predictions miscalculated the beginning and ending of spikes, and longer range predictions reverted to long term trends and ignored the spikes entirely. We hope this initial study will motivate further study into this highly challenging prediction problem. The use of fuel properties data generated by a new Coal Tracker Optimization (CTO) program was also investigated and this work shows that their use improved predictive ability of the evolved RNNs.

Automation & Control Systems↗
DOE OSTI2020

DECOVALEX-2019 (Task G Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task G which was proposed by the Swedish Radiation Safety Authority (SSM) and coordinated by geomecon GmbH, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task G in DECOVALEX-2019 is primarily concerned with the evolution of transmissivity throughout the lifetime of a repository for radioactive waste, and in particular of spent nuclear fuel, in sparsely fractured and competent crystalline rock masses, and the representation of these processes via numerical simulation. The numerical simulations were to be evaluated for their suitability, and to be validated. Over the course of the work presented here, not only were transmissivity changes and the best approaches to simulate those change examined, but also strategies were to be developed on how to monitor transmissivity change. Guidelines on what a control program and a monitoring system for a repository should include and be able to measure, and how this can be done in practice, was a key objective of the research project.

58 GEOSCIENCES↗
DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS): Task 6.0 Deliverable – CarbonSAFE Phase III Readiness

The OASIS CarbonSAFE Phase II Project OASIS (Optimizing Alabama’s CO 2 Storage in Shelby County) is a geologic and reservoir characterization study designed to evaluate deep saline formations for potential long-term carbon dioxide (CO 2 ) storage in central Alabama near the National Carbon Capture Center (NCCC) and Alabama Power’s Plant Gaston. The project centers on understanding the potential of the Cambro-Ordovician Knox Group and underlying strata such as the Conasauga and Rome Formations for geologic storage of CO 2 . These formations were investigated as part of SECARB-USA (DE-FE0031830) and Project OASIS through the drilling of two stratigraphic test wells to obtain electronic well logs, core, and sidewall core plugs. These data provide direct measurements of porosity, permeability, and lithologic variability critical for reservoir characterization. Complementing the well program, a limited 2D seismic survey was conducted to help select the site for Westover #2 as part of SECARB-USA (DE-FE0031830), and a more regional Seismic Exchange (SEI) seismic survey was licensed and interpreted to define structural and stratigraphic frameworks in a new Static Earth Model (SEM), map reservoir continuity, and to identify potential sealing intervals. Integrated with geologic and reservoir modeling, these datasets form the basis for evaluating storage capacity, injectivity, and containment. While this document endeavors to provide readers with a high-level overview of Project OASIS activities and its suitability for subsequent CarbonSAFE Phases, such as a Phase III effort. Other project deliverables and milestones will provide more details on individual subjects.

20 FOSSIL-FUELED POWER PLANTS↗