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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impact of installation faults in air conditioners and heat pumps in single-family homes on U.S. energy usage

To ensure that new residential air conditioners and heat pumps operate optimally, care must be taken during the initial system design and installation to avoid missteps that immediately degrade a system’s performance. Laboratory and simulation studies have quantified the impact that faults can have on capacity and efficiency. Field studies have demonstrated that installation-related faults are commonplace. However, the national impact of installation-related faults cannot be accurately estimated by only simulating a limited number of homes at several fault levels because of the variety of home characteristics and climates involved. In our analysis, we use an improved residential building stock simulation tool to predict the annual energy increase and additional utility costs resulting from two common installation faults: indoor airflow rate and refrigerant charge level. Our method considers the wide range of building characteristics and climate zones of the U.S. housing stock. We use existing field data to develop fault intensity probability distributions to inform our analysis. The study shows that these two faults result in approximately 20.7 TWh/y of additional energy use for central air conditioners and air-source heat pumps in U.S. single-family detached homes, which is a 9% increase over baseline (no-fault) usage, costing homeowners approximately $2.5 billion annually on utility bills. Air-source heat pumps are responsible for a disproportionate fraction of this energy use increase because of the larger number of operating hours compared to central air conditioners and the sensitivity of heating mode performance to the faults analyzed compared to cooling mode.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A Data Processing Pipeline To Extract A Knowledge Graph From Heterogeneous Data For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest, and a set of SEC form types as well as other data sources (e.g. CrunchBase) from which to extract entities and relations. There are four main components to this pipeline as currently implemented: Entity Extraction, Network Construction, Analysis, and Visualization. First, Entity Extraction, is implemented as the `topear-extract_organizations` Apache Airflow workflow. Given an initial query that specifies a geographic region of interest and a time interval, the software will extract CI facilities of interest and organizations that have a direct influence relationship to those facilities (e.g. ownership). During the course of the LDRD, we focused on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Within the context of the DOE CESER project, we have focused on Battery Energy Storage Systems (BESS). Second, the Network Extraction component will iteratively construct a social network graph given the set of organizations and people extracted in the previous step. Organizations (and eventually People if desired) are then fed as a query to the `topgear-construct_social_network` Apache Airflow workflow which given a set of initial companies and data sets (e.g. SEC EDGAR form types, OpenCorporates, Crunchbase). This Airflow workflow will iteratively query such data sources to discover relationships with new organizations and people. For example, this module can iteratively query SEC EDGAR for metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources from SEC EDGAR for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Again, we note that in additional to SEC data sources, this step can also pull in information on organizations via API services such as CrunchBase and OpenCorporates or bulk data sources. At the end of this step, the resultant social network, the Critical Infrastructure network, and the edges that encode relationships between organizations and CI facilities, form the Adversarial Socio-Technical Network (ASTN) that informs the analysis. Third, the Analysis component processes these generated ASTN. Previously, that has included the ability to compare prevalence of different vendors for a given infrastructure component type across different regions as well as identify common public and private investors across those vendors. This was demonstrated for EV Charging Stations across several different metropolitan areas within an IEEE PES GridEdge publication. More recently, we have looked at ways to identify infrastructure owners and operators of BESS with the most nameplate capacity across different states as well as other indictors of risk resulting from changes in ownership over time. Finally, the Visualization component consists of an HTML/CSS/JS framework by which users can interact geospatial, operational, and organizational relationships across a given portfolio of Critical Infrastructure facilities. The objective is to provide a library of UI/UX modules that can be repurposed for stakeholder-specific dashboards. All of the modules are related via a common event model that enables UI actions in one view to percolate across the other views.

Weaver, Gabriel [Idaho National Laboratory (INL), ↗
DOE OSTI2022

Publishing statistical models: Getting the most out of particle physics experiments

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Development of a Versatile Analysis Method for the Isotopic Characterization of Alpha Spectra

Over the past several years significant work has been performed at Idaho National Laboratory to build an alpha-particle spectrometry capability and expertise for a wide range of applications that include technical nuclear forensics, nuclear safeguards, and environmental monitoring. This development has led to a diverse collection of sample types and preparations measured with varied solid-state detector materials and configurations. Several characteristics of a measured alpha pulse height spectrum make performing localized fits of individual peak shapes unfeasible. Alternatively, the entirety of the spectrum must be fit concurrently to extract isotopic information. An analysis tool has been developed to perform isotopic characterization of alpha spectra. This process included a study of both the mathematical model used to represent the detector response of an alpha-particle as well as the algorithm used to fit the spectrum.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

MIDAS: Modeling Individual Differences using Advanced Statistics

This research explores novel methods for extracting relevant information from EEG data to characterize individual differences in cognitive processing. Our approach combines expertise in machine learning, statistics, and cognitive science, advancing the state-of-the art in all three domains. Specifically, by using cognitive science expertise to interpret results and inform algorithm development, we have developed a generalizable and interpretable machine learning method that can accurately predict individual differences in cognition. The output of the machine learning method revealed surprising features of the EEG data that, when interpreted by the cognitive science experts, provided novel insights to the underlying cognitive task. Additionally, the outputs of the statistical methods show promise as a principled approach to quickly find regions within the EEG data where individual differences lie, thereby supporting cognitive science analysis and informing machine learning models. This work lays methodological ground work for applying the large body of cognitive science literature on individual differences to high consequence mission applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

EVI-RoadTrip™: Electric Vehicle Infrastructure for Road Trips [SWR-22-17]

The EVI-RoadTrip™ tool offers high-resolution refueling network design and analysis to inform electric vehicle (EV) charging infrastructure development for road trips or long-distance travels. EVI-RoadTrip helps infrastructure planners, analysts, and decision makers evaluate EV energy consumption and corresponding charging demands along the routes-between origin and destination. It considers the projected location and characteristics of charging stations, potential electric grid impacts, and required infrastructure improvements. Strategically located charging stations for long-distance travel are critical to enabling the widespread adoption of EVs by allowing them to travel further beyond city or town boundaries. Sophisticated analysis and planning can identify the points (e.g., corridors) that may require increased availability of EV charging stations to support electrified road trips.

Wood, Eric↗
DOE OSTI2022

MEITNER Resource Team Modeling and Simulation Support to Holos-Quad Reactor Development (Final CRADA Report)

The main objective of this CRADA is to provide Argonne National Laboratory (ANL)’s modeling and simulation capabilities via ARPA-E's MEITNER (Modeling-Enhanced Innovations Trailblazing Nuclear Energy Reinvigoration) Resource Team (RT) arrangement to support the demonstration of the viability of HolosGen’s Holos-Quad reactor design. The Holos-Quad reactor design is an advanced reactor concept that incorporates many new design features, such as the neutron-coupled Subcritical Power Modules (SPMs) in its core design, elimination of balance of plant (BOP) by direct integration of a helium Brayton cycle power conversion system with each SPM, among many other innovative features. The demonstration of the viability of such an innovative reactor design warrants iterations of modeling and simulation and testing. The purpose of this project is to utilize ANL’s modeling and simulation capabilities in nuclear reactor analysis and power conversion system analysis to inform HolosGen and the Design Team (DT) in the design and optimization of the Holos-Quad concept. The major work scopes of this project include: to investigate conceptual designs and materials for radiation shielding to protect personnel and internal components such as turbomachinery; Assess the the helium Brayton cycle power conversion system performance in both nominal and load following conditions; Investigate power conversion components and overall system performance; Identify control strategies to enable load following; Perform simulations of HolosGen’s subscale simulator and using available test data for code validation/benchmark purpose; Perform core thermal-hydraulics, safety analysis, and structural analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Fire Risk Investigation in 3D (FRI3D) Software and Process for Integrated Fire Modeling

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomena and multiple operational procedures, it is difficult to computationally provide assurance that mitigation methods are adequate for critical areas using current analysis methods in a cost-effective manner. The nuclear industry needs efficient methods to provide more accurate modeling and optimize mitigation methods to improve nuclear power plant understanding for fire scenarios. This report describes the work done over the last two year on the Fire Risk Investigation in 3D (FRI3D) software. This software simplifies the modeling process by importing existing plant models and data, incorporating a 3D modeling environment and coupling with the fire simulation software CFAST. This eliminates the manual labor and errors associated with much of the fire modeling process. The report lays out the status and path of FRID software for the Risk Informed Safety Analysis pathway of the Light Water Reactor Sustainability project at Idaho National Laboratory and industry collaborators to best help reduce costs and improve realism in fire probabilistic risk analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evaluation of the Radioactive Material Released in the Harborview Research and Training Building and Some Implications for Emergency Response

On 2 May 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a mobile hot cell on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%, was released from the mobile hot cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy’s Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. Furthermore, the implications for emergency response are relevant to data quality and management. A Data Quality Objective guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and archiving of samples.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Evaluation of the Radioactive Material Release in the Harborview Research and Training Building and Implications for Emergency Response

On May 2, 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a Mobile Hot Cell (MHC) on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%) was released from the Mobile Hot Cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy's Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. The implications for emergency response are relevant to data quality and management. A Data Quality Objective (DQO) guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and sample archival.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. This report summarizes the research outcomes in FY-2021, which the project progressed from the planning and methodology development phase to the early demonstration phase. The highlights of these activities are: (1) the development of a multi-objective optimization process using Genetic Algorithms (GAs); (2) the development and test of an approach for optimization process acceleration using artificial intelligence (AI) that significantly reduces the computational burden; (3) the demonstration of the fuel reload optimization framework for a generic pressurized water reactor (PWR); and (4) the demonstration of limiting design basis accident (DBA) scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel reload optimization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Small Signaling Peptides in Sorghum bicolor : Integrating Phylogeny and Gene Expression to Characterize Roles in Stem Development

Small signaling peptides (SSPs) are important regulators of plant growth, development, and responses to biotic and abiotic stress, yet their role in the C4 grass Sorghum bicolor is largely uncharacterized. To help fill this knowledge gap, 219 sorghum genes that encode SSPs were identified based on SSP sequences previously identified in Arabidopsis thaliana, Zea mays, Oryza sativa, Triticum aestivum , and Brachypodium distachyon . The 219 sorghum SSP-encoding genes were assigned to 19 gene families, analyzed for the presence of motifs, and aligned with genes that encode SSPs in other plants using phylogenetic analysis. Sorghum genes in 12 of the 19 SSP gene families had not been previously characterized. Expression of the 219 SSP-encoding genes in sorghum organs, during stem development, and in stem tissues and cell types revealed distinct spatial, temporal, and developmental patterns of expression. Genes associated with the SbCEP and SbRGF families were preferentially expressed in roots, whereas SbEPF genes were expressed in stem epidermal and pith parenchyma cells and panicles. The expression of genes during bioenergy sorghum stem growth and development was investigated because stems account for ~80% of harvested biomass and serve as conduits for water and nutrient transport between leaves and roots. During stem development, 28 SSP genes in several families ( CLE, EPF, CEP, GASS, PSY, ES, PSK, CAPE, POE ) were expressed at higher levels in zones of cell proliferation. For example, the TDIF homologs SbCLE41 and SbCLE42 were expressed at high levels in nascent stem nodes where they may regulate vascular bundle cambial activity and cell differentiation. A different set of 15 genes in the CIF, POE, CAPE, PSY, CEP, RALF , and CLE families were expressed at higher levels in zones of stem tissue differentiation highlighted by elevated expression of five SbRALFR s in the stem nodal plexus. Cell type–specific expression of many sorghum genes that encode SSPs was observed in fully elongated internodes indicating gene expression is regulated with high spatial resolution. Overall, the results provide a foundation of information for analysis of SSP function in sorghum that can be integrated with knowledge of sorghum gene regulatory networks to modulate traits important for production of sorghum crops.

bioenergy sorghum↗
DOE OSTI2022

Safety Analysis for Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The ERP research and development efforts in FY22 focused on the safety analysis of ATF with increased enrichment and extended burnup to provide scientific knowledge of the ATF fuel performance, failure mechanism and source term analysis during severe accident of the NPP. FeCrAl clad ATF was selected as basis of the reactor fuel. An optimized equilibrium cycle was developed for 24-months extended burnup operation. A 4-loop PWR model under loss-of-coolant accident (LOCA) was assessed and the behavior of the major source term from failed ATF has been analyzed. The result showed that grace to enhanced mechanical characteristics of ATF, the fuel failure starts up to 200~500 seconds later than conventional Zr clad fuel. This time gives sufficient buffer until low pressure safety injection (LPSI) of the emergency core cooling system (ECCS) restarted by the operator which reduces fuel fragmentation, relocation and dispersal (FFRD). As a consequence, the total amount of major radioactive materials released from FeCrAl clad fuel into the reactor containment was found up to three times less compare to Zr clad fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Reassessing Double-Ended Guillotine Break Requirements: Evidence-Based Analysis of Regulatory Assumptions After Five Decades of Nuclear Operation

After five decades of nuclear power operation encompassing more than 20,000 reactor-years across 35 countries and 647 reactors, zero double-ended guillotine breaks (DEGBs) have been documented in commercial reactor coolant systems—despite DEGB being the fundamental design-basis assumption driving Emergency Core Cooling System (ECCS) sizing, structural protection requirements, and containment design specifications. This report examines the basis for DEGB requirements in nuclear power plant design. The DEGB postulate assumes the instantaneous, complete circumferential severance of the largest diameter pipes in reactor coolant systems, driving major design requirements under 10 Code of Federal Regulations 50.46, General Design Criterion 4 and containment design specifications. The United States (4,880 reactor-years) and France (2,505 reactor-years) contribute the largest operational datasets. Probabilistic assessments estimate direct DEGB occurrence probabilities with extremely low event frequencies, far below the 10-5/reactor-year thresholds typically used to define non-credible events in nuclear-safety analyses; i.e., events with probability this low fall into beyond-design-basis events. Current material-science knowledge demonstrates that the ductile steel materials used in nuclear piping systems exhibit stable crack-growth behavior fundamentally incompatible with instantaneous severance. International regulatory experience, particularly Germany’s comprehensive break-preclusion implementation, and successful leak-before-break (LBB) applications in almost all of U.S. pressurized water reactor units validate that alternatives can maintain safety performance while reducing economic burden. Current DEGB protection systems impose estimated lifetime costs of hundreds of millions of dollars per unit, over the life of a plant across the nuclear industry (including ongoing costs), representing substantial resource allocation toward scenarios with extremely low probability. Although this report acknowledges uncertainties regarding long-term aging effects, potential synergistic degradation mechanisms, and site-specific seismic considerations that warrant continued evaluation as regulatory policy evolves, there remains no documented evidence that a DEGB has occurred as a consequence of the conditions or mechanisms described in this report. This report acknowledges the Nuclear Regulatory Commission’s (NRC’s) recent efforts—outlined in the draft Interim Staff Guidance (ISG) NRC-DSS-ISG-2025-XX (“Treatment of Certain Loss-of-Coolant Accident Locations as Beyond-Design-Basis Accidents Draft Interim Staff Guidance”)—to reduce overly conservative requirements for large-break loss of coolant accidents through technical justifications and exemptions. However, extensive operating experience and validated methodologies—such as LBB and in-service inspection programs—demonstrate that the probability of a DEGB in reactor coolant-loop piping is extremely low, even under seismic conditions. The authors and reviewers of this report recommend that DEGB be removed as a design-basis event through formal rulemaking, rather than case-by-case exemptions, to better reflect credible failure modes, align with current data, and align with modern, risk-informed safety analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

On the relation between the subadditivity cone and the quantum entropy cone

Given a multipartite quantum system, what are the possible ways to impose mutual independence among some subsystems, and the presence of correlations among others, such that there exists a quantum state which satisfies these demands? This question and the related notion of a pattern of marginal independence (PMI) were introduced in [1], and then argued in [2] to be central in the derivation of the holographic entropy cone. Here we continue the general information theoretic analysis of the PMIs allowed by strong subadditivity (SSA) initiated in [1]. We show how the computation of these PMIs simplifies when SSA is replaced by a weaker constraint, dubbed Klein’s condition (KC), which follows from the necessary condition for the saturation of subadditivity (SA). Formulating KC in the language of partially ordered sets, we show that the set of PMIs compatible with KC forms a lattice, and we investigate several of its structural properties. One of our main results is the identification of a specific lower dimensional face of the SA cone that contains on its boundary all the extreme rays (beyond Bell pairs) that can possibly be realized by quantum states. We verify that for four or more parties, KC is strictly weaker than SSA, but nonetheless the PMIs compatible with SSA can easily be derived from the KC-compatible ones. For the special case of 1-dimensional PMIs, we conjecture that KC and SSA are in fact equivalent. To make the presentation self-contained, we review the key ingredients from lattice theory as needed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of energy resolution with the NEXT-White silicon photomultipliers

The NEXT-White detector, a high-pressure gaseous xenon time projection chamber, demonstrated the excellence of this technology for future neutrinoless double beta decay searches using photomultiplier tubes (PMTs) to measure energy and silicon photomultipliers (SiPMs) to extract topology information. This analysis uses $^{83m}$Kr data from the NEXT-White detector to measure and understand the energy resolution that can be obtained with the SiPMs, rather than with PMTs. The energy resolution obtained of (10.9 ± 0.6)%, full-width half-maximum, is slightly larger than predicted based on the photon statistics resulting from very low light detection coverage of the SiPM plane in the NEXT-White detector. The difference in the predicted and measured resolution is attributed to poor corrections, which are expected to be improved with larger statistics. Furthermore, the noise of the SiPMs is shown to not be a dominant factor in the energy resolution and may be negligible when noise subtraction is applied appropriately, for high-energy events or larger SiPM coverage detectors. These results, which are extrapolated to estimate the response of large coverage SiPM planes, are promising for the development of future, SiPM-only, readout planes that can offer imaging and achieve similar energy resolution to that previously demonstrated with PMTs.[graphic not available: see fulltext]

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability

This paper describes a milling stability identification approach that simultaneously considers: physics-based models for the tool tip frequency response functions and stability predictions; the binary result from a milling test (automatically labeled as stable or unstable based on frequency content); chatter frequency when an unstable result is obtained; and user risk tolerance. The algorithm applies probabilistic Bayesian machine learning with adaptive, parallelized Markov Chain Monte Carlo sampling to update the probability of stability with each milling test. Furthermore, the result is a robust solution for rapid convergence to optimized milling parameters for maximum metal removal rate using all available information.

42 ENGINEERING↗