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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Biofidelic Digital Head Model Software

Researchers at Los Alamos have extensive capabilities in biofidelic modeling, simulation and software development for predicting traumatic brain injury (TBI). Since injury-causing experiments cannot be performed on live humans, and head dummies are incapable of predicting brain deformations/strain, our approach uses magnetic resonance imaging (MRI) data for the brain combined with advanced computational methods and substructure constitutive properties to identify harmful accelerations that may develop diffused axonal injury in the brain. The goal is to develop this capability to analyze the effectiveness of personal protective equipment (PPE) such as, helmets and the advanced energy-absorbing materials used in PPE to mitigate brain injury. Los Alamos is seeking a collaborative partner (through a cooperative research and development agreement) to develop this capability toward a potential technology that will have commercial viability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Environmental Air Monitoring at LANL: 2023 External Program Assessment [Slides]

Radioactive Air Emissions Management evaluates radiological impacts of LANL operations on members of the public, identifies and quantifies releases, and assesses impacts. It is not directly affiliated with cleanup operations or programmatic work and has independent oversight. The focus areas in Environmental Compliance Programs are stack emissions measurements, ambient air measurements, minor source operations evaluations, data management and quality assurance, collaboration with Meteorology program, and collaboration with Dose Assessment program (EPC-ES).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Cryptographic Obfuscation Sensor System Guarding Restricted Data (CrOSSGRD): Prototype Detailed Design Document

A prototype has been developed at Sandia National Laboratories to collect nominally sensitive data from a mock treaty accountable item, record that information as non-sensitive encrypted outputs, and allow inspectors to subsequently evaluate that information at a time and location of their choice without any risk of the host party’s data being inadvertently (or maliciously) revealed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Extension of SCALE/Sampler’s sensitivity index for the assessment of cross section, fission yield, and decay data uncertainties

Accurate prediction of nuclide compositions and neutron and gamma sources and spectra for fresh and spent nuclear fuel through computational modeling and simulations is the basis for safeguards instruments design, optimization, and calibration, and for validation of the measured responses. The accuracy of these simulations can be significantly impacted by uncertainties in input parameters to the applied computer code. Input parameters are, for example, dimensions, material compositions, and temperatures of the model. Additionally, important but sometimes neglected input parameters for simulations of nuclear systems are the nuclear data that include nuclear reaction cross sections, fission product yields, and decay data. It has been shown that uncertainties of calculated results are dominated by uncertainties of these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Recalculating Dissolver Curves for Critical Parameters for Nuclear Criticality Safety

The dissolver paradox is a phenomenon in criticality safety whereby a high density fissile material is being dissolved in a low fissile density solution and is subcritical before and after dissolution. However, as the metal is being dissolved, there may be an intermediate concentration that leads to a critical state. CCG-184 is a Y-12 report written in 1980 that provided critical parameter data for two separate dissolver paradox scenarios: solid metal spheres and hollow metal spheres with internal moderation effects. The sphere and shell are both surrounded by solution, however the shell contains solution of the same concentration within itself. In 1980, there are limitations to the computational methods to determine critical parameters. These are due to the lower number of energy groups utilized (16-group) at the time, smaller number of established cross-sectional data, as well as a larger uncertainty within the resonance region of neutron energies. With these constraints in mind, these critical parameters are recalculated with newer cross-sectional data, a newer Monte Carlo code: SCALE 6.1.3 using KENO V.a, and a larger number of energy bins.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

CO2 injection with fracturing in geomechanically protected caprock: Task 6 of LLNL's Research Activities to Support DOE's Carbon Storage Program (FWP-FEW0191) (Final Technical Report)

Conventional principles of the design and operation of geologic carbon storage (GCS) require injecting CO 2 below the caprock fracturing pressure to ensure the integrity of the storage complex. In non-ideal storage reservoirs with relatively low permeability, modest injection rates can lead to pressure buildup and hydraulic fracturing of the reservoir and caprock. While the GCS community has generally viewed hydraulic fractures as a key risk to storage integrity, the actual behavior of a caprock hydraulic fracture, particularly from a geomechanical perspective, has not been thoroughly studied. The prevailing method of treating a hydraulic fracture as a high-permeability wing of the storage reservoir might have resulted in erroneous understanding of caprock hydraulic fracture behavior. Comprehensive analyses of monitoring data from the In Salah project suggested that one or more hydraulic fractures may have been created in the reservoir and lower caprock system during injection operations, but did not cause detectable leakage of CO 2 out of the storage complex. This observation coincides with a well-known phenomenon in the oil and gas industry: sedimentary rock formations have many inherent features that naturally protect the formations from unbounded vertical growth of hydraulic fractures.

58 GEOSCIENCES↗
DOE OSTI2023

Reproduction drives changes in space use and habitat selection in a highly adaptable invasive mammal

Abstract For ungulates, it is not well understood how the interaction between habitat and reproduction affects movement behavior, space use, and habitat selection. We used known parturition (farrowing) data to validate First Passage Time (FPT) movement analysis to identify wild pig (Sus scrofa) parturition events from data collected with GPS collars. We examined home range and habitat selection during three physiologically distinct time periods in the reproductive cycle: late-gestation; farrowing; and neonate-care period. Sows exhibited a behavioral change 1-2 days prior to farrowing, suggesting FPT analysis can reliably identify parturition events for wide-ranging species that have a focused birthing area. Home range was smallest during the farrowing period, likely reflective of nest building, parturition, and protection of neonates. Home range size during the neonate-care period was intermediate between the late-gestation and farrowing periods, indicative of offspring care that may restrict maternal movement. Across all periods, sows avoided developed areas that have sparse canopy and ground cover and are associated with human activities. During late-gestation, sows avoided pine forests that have an open understory and less vegetative cover. During late-gestation and neonate-care, sows selected bottomland hardwood forests, habitat associated with ample food, cover, and water. During farrowing and neonate-care periods, sows selected upland hardwood forests, habitat with high quality food and cover for neonates. The physiological requirements of reproduction drive female habitat selection and spatial scale of movement patterns associated with parturition. Our study contributes to delineation of the appropriate scale at which to analyze movement data to provide insight about where individuals chose to place their home range, how much space to use, and how they use resources on the landscape to maximize reproductive success and fitness.

Zoology↗
DOE OSTI2023

A multiscale landscape approach for prioritizing river and stream protection and restoration actions

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tricyclononenes and tricyclononadienes as efficient monomers for controlled ROMP: understanding structure–propagation rate relationships and enabling facile post-polymerization modification

Grubbs 3rd-generation (G3) pre-catalyst-initiated ring-opening metathesis polymerization (ROMP) remains an indispensable tool in the polymer chemist's toolbox. Tricyclononenes (TCN) and tricyclononadienes (TCND) represent under-explored classes of monomers for ROMP that have the potential to both advance fundamental knowledge (e.g., structure-polymerization kinetics relationships) and serve as practical tools for the polymer chemist (e.g., post-polymerization functionalization). In this work, a library of TCN and TCND imides, monoesters, and diesters, along with their exo-norbornene counterparts, were synthesized to compare their behaviors in G3-initiated ROMP. Real-time 1 H NMR was used to study their polymerization kinetics; propagation rates ( k p ) were extracted for each monomer. To understand the relationships between monomer structure and ROMP propagation rates, density functional theory methods were used to calculate a variety of electronic and steric parameters for each monomer. While electronic parameters (e.g., HOMO energy levels) correlated positively with the measured k p values, steric parameters generally gave improved correlations, which indicates that monomer size and shape are better predictors for k p than electronic parameters for this data set. Furthermore, the TCND diester—which contains an electron-deficient cyclobutene that is resistant to ROMP—and its polymer p(TCND) are shown to be highly reactive toward DBU-catalyzed conjugate addition reactions with thiols, providing a protecting- and activating-group free strategy for post-polymerization modification.

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

Classification of (2 + 1) D invertible fermionic topological phases with symmetry

Here we provide a classification of invertible topological phases of interacting fermions with symmetry in two spatial dimensions for general fermionic symmetry groups G f and general values of the chiral central charge c - . Here G f is a central extension of a bosonic symmetry group G b by fermion parity, (-1) F , specified by a second cohomology class [ω 2 ]∈ $\mathscr{H}^2$(Gb,$\mathbb{Z}_2$). Our approach proceeds by gauging fermion parity and classifying the resulting G b symmetry-enriched topological orders while keeping track of certain additional data and constraints. We perform this analysis through two perspectives, using G-crossed braided tensor categories and Spin(2c - ) 1 Chern-Simons theory coupled to a background G gauge field. These results give a way to characterize and classify invertible fermionic topological phases in terms of a concrete set of data and consistency equations, which is more physically transparent and computationally simpler than the more abstract methods using cobordism theory and spectral sequences. Our results also generalize and provide a different approach to the recent classification of fermionic symmetry-protected topological phases by Wang and Gu, which have chiral central charge c - = 0. We show how the tenfold way classification of topological insulators and superconductors fits into our scheme, along with general nonperturbative constraints due to certain choices of c - and G f . Mathematically, our results also suggest an explicit general parametrization of deformation classes of (2 + 1)D invertible topological quantum field theories with G f symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Streamlined Approach for Environmental Restoration (SAFER) Plan for Corrective Action Unit 114: Area 25 EMAD Facility Nevada National Security Site, Nevada, (Rev.0, with ROTC 1)

This Streamlined Approach for Environmental Restoration (SAFER) Plan addresses the actions needed to achieve closure for Corrective Action Unit (CAU) 114, Area 25 EMAD Facility, identified in the Federal Facility Agreement and Consent Order (FFACO). CAU 114 comprises the following corrective action sites (CASs) located in Area 25 of the Nevada National Security Site (formerly, the Nevada Test Site): 25-41-03, EMAD Facility; 25-99-23, Manned Control Car (MCC) and Engine Installation Vehicle (EIV); and 25-33-05, Building 3901, Engine Transport System Maintenance Building. This plan provides the methodology for field activities needed to gather the necessary information for closing CAU 114. There is sufficient information and process knowledge from historical documentation and investigations of similar sites regarding the expected nature and extent of potential contaminants to recommend closure of CAU 114 using the SAFER process. Additional information will be obtained by conducting a field investigation before selecting the appropriate corrective actions for CAU 114. It is anticipated that the results of the field investigation and implementation of corrective actions will support a defensible recommendation that no further corrective action is necessary. The purpose of the corrective action investigation will be to document and verify the adequacy of existing information; to affirm the decision for either clean closure, closure in place, or no further action; and to provide sufficient data to implement the corrective action. The actual corrective action selected will be based on characterization activities implemented under this SAFER Plan. If specific conditions or findings fall outside the bounds of the SAFER Plan, the Nevada Division of Environmental Protection (NDEP) will be consulted to determine the path forward before proceeding. Upon completion of SAFER activities, a closure report will be prepared and submitted to NDEP for review and approval. The schedule for completion of the closure report will be established at the FFACO annual meeting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Universal Refrigerant Charge Fault Detection and Diagnostics Method Based on Pump Down Operation

The performance of the heat pump system varies greatly depending on the refrigerant charge amount. Improving the refrigerant charge fault detection and diagnostics (FDD) method of vapor compression systems have the potential for increasing energy efficiency and reducing service cost. Previous studies to predict refrigerant charge amount are mostly empirical methods which require significant amount of experimental data for high accuracy. The primary goal of this research is to develop a universal charge fault detection method which requires only a few experimental data with high prediction accuracy.Currently, pump down operations are typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repairment. In addition, compressors have a built-in low-pressure cut-off protection function, and the compressor performance maps are commonly available from manufacturers. The proposed method innovatively utilizes the typical pump down operation, the compressor low-pressure cut-off protection, and the compressor performance map. It does not require any geometry information of heat exchangers, refrigerant lines, or charge buffers.The new charge prediction method is firstly formulated through theoretical analysis, then verified and calibrated by a quasi-steady-state simulation of the pump down process for a residential heat pump system. The quasi steady-state simulation uses an HVAC system simulation framework driven by DOE/ORNL Heat Pump Design Model (HPDM). Preliminary experiment validations with heat pump refrigerant leakage tests demonstrate the deviation of the proposed charge prediction method compared with measurement is within 8%. This technology makes refrigerant charge amount available at the technician’s fingertips and leads to shorter maintenance time and fewer site visits.

Li, Zhenning↗
DOE OSTI2022

Coastal Acoustic Buoy for Offshore Wind: Project Synthesis

The population of North Atlantic right whales is critically endangered and their habitat overlaps with offshore windfarm leases. It is therefore imperative that effective mitigation strategies be used to avoid impacts on right whales during the construction of offshore windfarms. The Department of Energy issued FOA Number DE-FOA-0001924 to encourage the development of technology that could monitor large exclusion zones for right whales in order to mitigate potential impact of construction noise on right whales. This report summarizes the past two years of the development and evaluation of the Coastal Acoustic Buoy for Offshore Wind (CABOW) project which aimed to develop technology to monitor large exclusion zones for North Atlantic right whales. Over the course of the project SMRU Consulting have implemented a rigorous design process including comparison of different approaches (e.g., single sensor vs multiple sensors), as well as consideration of placement and timing of acoustic monitoring. We have evaluated critical components of the CABOW system including, reliability, detection range, and bearing accuracy in areas adjacent to offshore windfarm leases in Maryland by conducting 3,536 playbacks of simulated right whale upcalls. The maximum call detection range was 7.5 km when noise was 99 dB re 1µPa rms (50-225 Hz), but this reduced to < 1 km when ambient noise levels were high. Our detection probability in the field was measured as a function of range as well as the source-to-noise level ratio allowing us to build a model to predict the probability of detection under various scenarios (sample size: 3,536 calls x 5 buoys = 17,680). The median bearing error was -0.25° but this is likely an underestimate of error due to experimental design. Using the published recall and precision of the two detectors we implemented in the CABOW system, we estimate that at a recall of 80%, our precision was > 80%, within the range of what we were aiming for in this project. To estimate our exclusion zone false negative and false positive rates, we built a simulation model using the empirical data from our field trial. We modelled three to nine CABOW units placed on the 10 km exclusion zone and estimated our false negative rate to be 1% or less (which was our project goal) and our false positive rate to be between seven and nine percent, slightly above our goal of 5%. However, we also modelled an equivalent PAM system that does not have bearing capabilities and found the false positive rates for that system to be six to eight times higher than the CABOW rate. This higher false positive rate of PAM systems with low spatial information could have significant cost repercussions for offshore wind developers by adding work shutdowns or delays without providing additional protection for right whales. The model we built allows us to explore the placement of PAM systems under various scenarios and will thus help facilitate planning of PAM mitigation systems to meet NOAA Incidental Harassment Authorizations for specific windfarms. We achieved an average system uptime of 98.3%, just below our goal of 99%. The issues that caused these short losses of data have been identified and fixed. Right whale detections and audio clips were typically transferred via radio from the buoys to the base station in two to four seconds. We therefore believe we have developed a highly robust real-time PAM system. Based on the above, we feel we have achieved the stated funding goal of developing a cost-effective and robust real-time PAM system that enables the monitoring of large exclusion zones for right whales during the constructions of offshore windfarms. This should lead to decreased costs and risks for the offshore wind sector while providing robust mitigation for right whales. It is important to state that PAM mitigation will need to be implemented with other mitigation strategies (e.g., visual observers) to provide a complete mitigation strategy to ensure that any effects on right whales from offshore windfarm construction is minimized.

17 WIND ENERGY↗
DOE OSTI2020

Los Alamos National Laboratory Meteorology Monitoring Program: 2019 Data Completeness (Quality Report)

This report summarizes data completeness by tower and by instrument for 2019 and compares that data with the Los Alamos National Laboratory (LANL) and the ANSI/ANS-3.11-2015 standard. This report is designed to make data users aware of data completeness and any data quality issues. LANL meteorology monitoring goals include 95% completeness for all measurements. The ANS 2015 standard requires 90% completeness for all measurements. This report documents instrument/tower issues as they impact data completeness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep Learning Systems for Increased Safeguards Surveillance Review Productivity

Nuclear safeguards inspectors expend significant time and maintain intense focus in reviewing video surveillance for safeguards relevant events. To increase efficiency and reduce the time burden of safeguards inspectors performing surveillance data review, this paper presents a novel deep learning (DL) systems concept to integrate generalized DL models into the safeguards surveillance review workflow. The Agency is investigating several DL algorithms for object recognition, localization, tracking, and flagging relevant activities. The project team is working closely with nuclear safeguards inspectors to identify review use cases (based on specific safeguards objectives) and collect their associated requirements. We focused on CANDU and LWR Nuclear Power Plants (NPPs) and their associated dry storage areas as these present a particularly heavy burden on the inspector surveillance review process due to the number of these facilities under safeguards worldwide. Initial DL algorithm results on safeguards data are promising. Using a convolutional neural network, the team attained a mean average precision (mAP) of 92.9% identifying and localizing spent fuel (SF) casks from a 475 surveillance image dataset. Further, the team had initial success in training a recurrent neural network to identify reactor area activities in video clips, successfully indicating when SF casks enter or exit a pool. We discuss how such DL algorithms would be integrated into the Next Generation Surveillance Review (NGSR) software application. Another issue impacting review productivity is the long time inspectors may have to wait when running these algorithms in NGSR. We present a concept to pre-process remotely collected surveillance data with DL models as the data arrives to IAEA headquarters so that results are already available when starting a new review in NGSR. The proposed DL system concept shows a pathway and workflow for increasing an inspector’s surveillance review productivity by quickly and accurately identifying declared and undeclared safeguards relevant objects and activities in large quantities of surveillance imagery data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Neural MUSE Analysis

Researchers at Oak Ridge National Laboratory (ORNL) created data as part of the MUSE (Multi-Agency Urban Search Experiment Detector and Algorithm Test Bed) project simulating illicit nuclear materials located in various buildings along a road. In the simulation, a truck containing a radiation detector drives down the road gathering listmode data (counting the and energy of incident gamma radiation). Building materials, source shielding, driving speed, truck direction, truck location on the road, source type, and source placement are all varied between runs of the data set. This data was created using deterministic neutron transport and Monte Carlo methods through a combination of SCALE, MAVRIC, MCNP, and GADRAS. As part of a follow-on NA-22 project, two Kaggle competitions were created to determine the best algorithms for finding and identifying gamma sources in this simulated urban environment. The winning algorithm was neural network-based and had a test accuracy of 76.4% accuracy for source identification. This work seeks to build upon this work and improve the results through the application of novel machine learning techniques. As a first step, the data was classified by a simple Convolutional Neural Network (CNN) To accomplish this, the data was first preprocessed into “waterfall plots.” These plots are composed of energy vs count plots that are stacked vertically to show progression in time. The horizontal axis indicating the particle energy incorporated user defined bin spacing with options for in linear-, logarithmic-, square root-, and user-spaced bins. The z or color dimension showed the number of counts corresponding the energy-time combination. This data was then used to generate more data, by generating a local estimate of the mean of the distribution for a bin and then randomly re-sampling that bin from a Poisson distribution. Once all of this data was generated, it was fed into a well-known CNN architecture, ResNet50. The output layer of this model was removed and replaced with layers corresponding to the shape desired isotope outputs. The provided training data was used to train the classifier and the remaining testing data was used to evaluate the model. Results are soon to be forthcoming.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Using Structured Intelligence Graph (STIG) to protect our critical infrastructure against cyber attacks [Poster]

STIG is a revolutionary cybersecurity tool developed by researchers at the U. S. Department of Energy's Idaho National Laboratory and it is a software that allows utility owners and operators to easily visualize, create, and edit cyberthreat intelligence information. STIG uses Structured Threat Information eXpression (STIX) and converts complex data on cybersecurity vulnerabilities into a visualization that is easy to understand and act on. With STIG, utility owners and operators have a common system for sharing threat intelligence information, thus increasing the chances of detecting and mitigating cyber exploits before they lead to a cyberattack.

24 POWER TRANSMISSION AND DISTRIBUTION↗