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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2022 Meeting Notes and Information Request Status

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2023 (FY2023) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during these meetings benefit operating, new, and advanced reactors. Significant safety insights have been and are continuing to be obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional benefits to the operating fleet and new LWR and non-LWR designs. U.S. evaluations of obtained examination information and input regarding future Daiichi examinations are of interest to several organizations within Japan. Since its inception, the U.S. has provided consensus input for high priority time-sequenced examination tasks and supporting research activities. In their Mid-to-Long-term Examination Plan for 1F investigations, TEPCO included all remaining U.S. consensus information requests and additional information requests they identified. TEPCO periodically provides reports on the status of these requests (reflecting D&D priorities, new insights from investigations, and new technologies that become available). Hence, U.S. experts agreed that it was appropriate for TEPCO to track and prioritize these information requests as D&D progresses. U.S. experts will continue to review and comment on the information obtained from examinations and, as needed, provide additional details and relevant background material to support future examinations. As documented in this report, several other items, such as additional details on information requests pertaining to ex-vessel examinations, relevant references from prior research, additional documents to provide insights regarding recent investigation findings, and reviews of recently released documents, were agreed to during the FY2023 meeting.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies and Future Work

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

task force, dynamic state estimation, Parameter Es↗
DOE OSTI2020

Energy Intensity Baselining & Tracking Summary Guide: Better Buildings, Better Plants

The Department of Energy (DOE) Better Plants (BP) program is a voluntary energy efficiency leadership initiative for U.S. manufacturers that encourages companies to reduce their energy intensity, typically by 25% within a ten-year period. BP partners are required to report their progress to the DOE annually by establishing an energy intensity baseline and tracking their energy consumption. BP partners receive access to a Technical Account Manager (TAM), DOE resources including software tools and trainings, and recognition when they achieve their goal. This summary guide provides the basics of baselining and tracking your energy intensity. For a more information and special considerations, please see the Energy Intensity Baselining and Tracking Guidance 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

End-to-End Jet Classification of Boosted Top Quarks with CMS Open Data

We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use lowlevel detector information from the simulated CMS Open Data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves a ROC-AUC score of 0.975±0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier ROC-AUC score increases to 0.9824±0.0013, serving as the first performance benchmark for these CMS Open Data samples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

ATLAS BigPanDA monitoring

BigPanDA monitoring is a web application that provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analysing hundreds of millions of computation entities, such as an event or a job, BigPanDA monitoring builds different scales and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe the broad picture such as tracking the computation nucleus and satellites performance or the progress of a whole production campaign. PanDA system was originally developed for the ATLAS experiment. Currently, it manages execution of more than 2 million jobs distributed over 170 computing centers worldwide on daily basis. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about the state of their computations and the source of decision support information for shifters, operators and managers. In this work, we describe the evolution of the architecture, current status and plans for the development of the BigPanDA monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

End-to-end jet classification of boosted top quarks with the CMS open data

Here we describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique uses low-level detector representation of high-energy collision event as inputs to deep learning algorithms. In this study, we use low-level detector information from the simulated Compact Muon Solenoid (CMS) open data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves an area under the receiver operator curve (AUC) score of 0.975 ± 0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier AUC score increases to 0.9824 ± 0.0013, serving as the first performance benchmark for these CMS open data samples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

DIVA/DeviceEditor v6.1.2

DIVA is an end-to-end DNA design and construction management platform that streamlines how researchers design, build, and receive sequence-verified DNA constructs. Through a web-based BioCAD interface (DeviceEditor), researchers independently design DNA constructs and submit them to a centralized queue with a single action. Designs progress transparently through standardized states which allow researchers to track status and access finished constructs via a central DNA repository. Submitted designs are reviewed by dedicated staff for feasibility and optimization, reducing costly failures and improving downstream execution. Automated DNA assembly software optimizes construction strategies by reusing existing parts where possible and sourcing synthetic DNA only when needed. Standardized, sequence-agnostic assembly methods enable many independent constructs to be built in parallel using lab automation, dramatically increasing throughput. High-throughput next-generation sequencing is used to verify construct accuracy, with flexible platforms selected based on task requirements. Throughout the process, detailed success and failure data are captured and analyzed, enabling continuous improvement of assembly protocols. Compared to traditional, manual DNA construction workflows, DIVA offers higher scalability, transparency, reproducibility, and data-driven optimization.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2021

SPATIOTEMPORAL TRACKING OF WIDE AREA POWER OUTAGE FROM NIGHT-TIME LIGHT IMAGERY

Monitoring progress of power restoration following extreme events is essential for situational awareness about spatio-temporal distribution of populations without power and to help with response efforts. Because of the proprietary nature of restoration data, and the difficulty in obtaining power outage data from utility companies in near real-time (e.g., during hurricane Maria (2017)), this project used satellite derived nighttime lights data from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to (i) monitor wide area power outage and (ii) estimate impacted customers over time to assist with restoration. A discussion of the methodology and its implementation during hurricanes Maria (2017) and Eta (2020) is presented in this paper. Future work will focus on calibrating estimated customers based on light intensity and density distribution, and generation of restoration profiles for emergency response.

Kar, Bandana↗
DOE OSTI2016

SU-F-T-100: Development and Implementation of a Treatment Planning Tracking System Into the Radiation Oncology Clinic

Purpose: With increasing numbers of cancer patients being diagnosed and the complexity of radiotherapy treatments rising it’s paramount that patient plan development continues to stay fluid within the clinic. In order to maintain a high standard of care and clinical efficiency the establishment of a tracking system for patient plan development allows healthcare providers to view real time plan progression and drive clinical workflow. In addition, it provides statistical datasets which can further identify inefficiencies within the clinic. Methods: An application was developed utilizing Microsoft’s ODBC SQL database engine to track patient plan status throughout the treatment planning process while also managing key factors pertaining to the patient’s treatment. Pertinent information is accessible to staff in many locations, including tracking monitors within dosimetry, the clinic network for both computers and handheld devices, and through email notifications. Plans are initiated with a CT and continually tracked through planning stages until final approval by staff. Patient’s status is dynamically updated by the physicians, dosimetrists, and medical physicists based on the stage of the patient’s plan. Results: Our application has been running over a six month period with all patients being processed through the system. Modifications have been made to allow for new features to be implemented along with additional tracking parameters. Based on in-house feedback, the application has been supportive in streamlining patient plans through the treatment planning process and data has been accumulating to further improve procedures within the clinic. Conclusion: Over time the clinic will continue to track data with this application. As data accumulates the clinic will be able to highlight inefficiencies within the workflow and adapt accordingly. We will add in new features to help support the treatment planning process in the future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Large Scale Tracking Algorithms

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase significantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classification steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Are You Resilient? Site Energy and Water Resilience Indicators

There is growing interest among operators of individual or co-located facilities to plan for utility disruptions caused by natural hazards and threats. Energy and water resilience at the site level can be characterized as the ability to withstand, adapt, and recover from an energy and/or water supply disruption. But how can a site’s energy and water resilience posture be measured? An evaluation framework with clear performance measures or indicators can help organizations establish what it means to be energy and water resilient and assess progress towards meeting resilience goals across sites and over time. Tracking a consistent set of indicators can help organizations identify problem areas that should be addressed and ascertain if energy and water resilience has improved as a result of investments or operational or policy changes. Resilience indicators also provide a means for organizations with geographically distributed sites to identify common problem areas that may require higher-level attention. This paper outlines an approach that organizations can use to measure site energy and water resilience. This approach was developed by Pacific Northwest National Laboratory for the U.S. Department of Energy’s Federal Energy Management Program as part of an effort to help federal agencies plan for energy and water resilience in a more systematic and rigorous way. The paper defines a general structure for defining energy and water resilience indicators, and provides example indicators and potential rating methods.

resilience, metrics for resilience, site resilienc↗
DOE OSTI2018

Organization Change: Leadership Speaks the Future, Management Makes It Happen - 18462

Implementing an organization change is challenging, because many changes touch unexpected organizational units and processes, requiring unplanned inter-group communications and collaboration. Organization change communications can be designed to engage people, and to coordinate their actions for a successful change completion. Leadership communication focuses on presenting the idea for an organization change as a purposeful and worthwhile process that will deliver benefits to the organization and its customers and stakeholders. A series of discussions with personnel to clarify the change objectives, success metrics, and timelines serve to engage them in productive participation in the change process. Management communication ensures that the actions taken will be effective to accomplish the intended results and benefits of the change. The depth, detail, and orientation of the information delivered in these three types of communication is different, but the intention, in all cases, is to have people work together to successfully complete the goal(s) of the change. An example of these communications is included in this paper, focusing on the communications of a change leader. Change leadership communications are usually delivered by high-level people but can be delivered by individuals at any level. They speak a vision for a possibility, i.e., a new future, in a way that engages people in its value and desirability. The shift from change leadership communications to change management communications is best made as a collection of dialogues with groups of people who will be leading, managing, supporting and/or participating in various aspects of the change. These dialogues take several forms, including Q and A sessions, dialogues to clarify what 'success' will look like, and discussions that develop management tools and practices for the change. These 'engagement' discussions create a bridge from leadership vision to management implementation. Change managers often head up departments, teams, or smaller groups. Their communications are designed to have group members participate in refining the change goals into team goals, measures, and assignments; collaboration with key players; and tracking and updating elements of the change process as it progresses toward completion. This work is often more daunting than the leadership phase, due to forces of increasing detail, complexity, and disorganization over time, such as unexpected interruptions, changes in resources, and new requirements for coordination. (authors)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

Large scale tracking algorithms

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2022 State-of-Technology Cases

The Department of Energy's (DOE) Bioenergy Technologies Office (BETO) aims to develop and deploy technologies to transform renewable biomass resources into commercially viable, high-performance biofuels, bioproducts, and biopower through public and private partnerships. BETO and its national laboratory teams conduct in-depth techno-economic assessments (TEA) of biomass feedstock supply and logistics and conversion technologies to produce biofuels. There are two general types of TEAs: A design case outlines a target case (future projection) for a particular biofuel pathway. It informs R&D priorities by identifying areas in need of improvement, tracks sustainability impact of R&D, and provides goals and benchmarks against which technology progress is assessed. A state of technology (SOT) analysis assesses progress within and across relevant technology areas based on actual results at current experimental scales relative to technical targets and cost goals from design cases, and includes technical, economic, and environmental criteria as available. In addition to developing a TEA for a pathway of interest, BETO also performs a supply chain sustainability analysis (SCSA). The SCSA takes the life-cycle analysis approach that BETO has been supporting for over 20 years. It enables BETO to identify energy consumption, environmental, and sustainability issues that may be associated with biofuel production. Approaches to mitigating these issues can then be developed. Additionally, the SCSA allows for comparison of energy and environmental impacts across biofuel pathways in BETO's research and development portfolio. This technical report describes the SCSAs for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies in the 2022 SOTs: (1) renewable hydrocarbon fuels via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (2) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (3) renewable hydrocarbon fuels via HTL of an algae/woody biomass blend; and (4) renewable hydrocarbon fuels via combined algae processing (CAP).

09 BIOMASS FUELS↗
DOE OSTI2015

Tracking radioactivity content in the spent fuel pool in PWRS - 15150

Over the last decade, significant progress has been made in managing radioisotopes generated in the PWR primary systems. These include limiting the use of cobalt containing materials, along with improved fuel performance and zinc injection to passivate the corrosion layers to limit the accumulation of Co-58 and Co-60 on primary coolant surfaces. Attention here is directed to the spent fuel pool where accumulation of spent fuel and activated material represents a growing source of mobile radioactivity supplemented with periodic exchanges of water from the reactor cooling system. Characterization of this source is increasingly important to effective management of disposal options. This paper examines the radioactive resin source term as determined from routine sampling of the coolant and fuel pool liquids. Targeted resin stream sampling and radiochemical analyses conducted at Diablo Canyon serve to inform and provide context for this examination. This examination is supplemented with computer modelling using the DW James Consulting computer program, 3R-SCAN. At most operating plants daily reactor coolant samples are counted using gamma spectroscopy and recorded. These samples serve to track fuel performance and maintain water chemistry. A secondary use for this data is to maintain a day to day tracking of releases of radioisotopes important to waste disposal. Given the coolant concentrations, plant operating history, and corroborative mathematical models and sampling, accumulation of these radioisotopes in coolant cleanup system ion-exchangers can be predicted. Fuel pool sampling is less frequent, but at the same time, things change more slowly there. The fuel pool contains about ten times the volume of the reactor coolant but its cleanup system process rate is comparable to reactor coolant letdown, i.e. 5.047 - 8.833 liters per second [lps] (80-140 gallons per minute [gpm]). A spent fuel pool clean-up demineralizer flow rate is typically about 5.047 lps (80 gpm). Concentrations of longer lived radioisotopes in the spent fuel pool can be comparable to those in reactor coolant. Releases of corrosion products and fission products from the stored fuel occur at a low rate but given the overall inventory can be significant. Recognized scaling factor ratios, particularly those to Co-60, are skewed by the aging of the material in the pool. An additional consideration stems from refueling operations themselves. Prior to refueling, it is common practice to conduct a forced oxidation of the corrosion films within the reactor. This spikes the activity within the reactor coolant. Most of this activity is removed by the reactor coolant purification system prior to removing the reactor head. This paper examines the accumulation of activity in the fuel pool purification ion exchange resins and how it impacts the overall classification of those ion exchange resins. The following discussion focuses on the transport of nickel and cobalt isotopes particularly as it relates to determination of Ni-63 which has become increasingly prominent in disposal classification. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Irradiation-Induced Structural Disorder and Its Influence on the Mechanical Response of Polycrystalline MoS2

Molybdenum disulfide (MoS2) thin films are widely used as dry-film lubricants and protective coatings in aerospace and other radiation-exposed environments. Conventional synthesis routes produce polycrystalline films whose grain boundaries and other native defects cause their mechanical and tribological behavior to differ substantially from that of ideal single crystals. Under irradiation, these films progressively evolve from polycrystalline structures, composed of layered MoS2 grains, into highly disordered and eventually amorphous structures, altering both their tribological performance and mechanical integrity. Here, we employ reactive atomistic simulations to investigate irradiation-driven structural evolution in bulk polycrystalline MoS2. Using controlled primary knock-on atom (PKA) events, we characterize the progressive transition from a polycrystalline microstructure to an amorphous network by tracking defect accumulation and structural disorder. We then establish how this transition modifies the dominant deformation mechanisms and the temperature-dependent tensile response. Specifically, irradiation suppresses interlayer sliding and delamination, mechanisms which facilitate the deformation of the pristine polycrystal, resulting in defect-induced hardening. Broadly, our results establish direct process–structure–property relationships linking irradiation-induced defect accumulation, microstructural evolution, deformation mechanisms, and mechanical behavior, providing an atomistic framework for understanding the structural integrity and long-term reliability of irradiated MoS2 coatings.

Moore, Daniel [Sandia National Laboratories (SNL)]↗
DOE OSTI2020

Status Update: Deposition Modeling For SNF Canister CISCC

This report fulfills the M3 milestones M3SF-21PN010207025 & M3SF-20PN0102070412. During fiscal year (FY) 2020, Pacific Northwest National Laboratory (PNNL) worked to further develop the FY 2019 deposition and particle tracking models. This status report outlines these efforts and presents the progress made so far. Model development work is ongoing and is planned to continue in FY 2021. The FY 2020 model development included work on: Wind Effects. Model development and sensitivity studies, investigated how wind direction and speed affect deposition; Brownian Motion. Implementing Brownian Motion into existing models; Particle Size Variability. Depending on the particle composition, the diameter of the particle may vary with changes in relative humidity. Models were developed to analyze this; Multiphase and Fluid Film Modeling. Investigating canister surface wetting and drying, and how this effects overall deposition. Models were developed to analyze this; Difusophoresis. Performing initial work to implement diffusiophoresis into the existing models; Turbophoresis. Performing initial work to implement turbophoresis into the existing models. Much of this work will continue into FY21. The authors present initial results and discus current and future work.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗