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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The EGS Data Collaboration Platform: Enabling Scientific Discovery

Collaboration in the digital age has been stifled in recent years. Reasonable responses to legitimate security concerns have created a virtual landscape of silos and fortified castles incapable of sharing information efficiently. This trend is unfortunately opposed to the geothermal scientific community's migration toward larger, more collaborative projects. To facilitate efficient sharing of information between team members from multiple national labs, universities, and private organizations, the 'EGS Collab' team has developed a universally accessible, secure data collaboration platform and has fully integrated it with the U.S. Department of Energy's (DOE) Geothermal Data Repository (GDR) and the National Geothermal Data System (NGDS). This paper will explore some of the challenges of collaboration in the modern digital age, highlight strategies for active data management, and discuss the integration of the EGS Collab data management platform with the GDR to enable scientific discovery through the timely dissemination of information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Global gridded anthropogenic emissions inventory of carbonyl sulfide

Atmospheric carbonyl sulfide (COS or OCS) is the most abundant sulfur containing gas in the troposphere and is an atmospheric tracer for the carbon cycle. Gridded inventories of global anthropogenic COS are used for interpreting global COS measurements. However, previous gridded anthropogenic data are a climatological estimate based on input data that is over three decades old and are not representative of current conditions. Here we develop a new gridded data set of global anthropogenic COS sources that includes more source sectors than previously available and uses the most current emissions factors and industry activity data as input. Additionally, the inventory is provided as annually varying estimates from years 1980–2012 and employs a source specific spatial scaling procedure. We estimate a global source in year 2012 of 406 Gg S y -1 (range of 223–586 Gg S y -1 ), which is highly concentrated in China and is twice as large as the previous gridded inventory. Our large upward revision in the bottom-up estimate of the source is consistent with a recent top-down estimate based on air-monitoring and Antarctic firn data. Furthermore, our inventory time trends, including a decline in the 1990's and growth after the year 2000, are qualitatively consistent with trends in atmospheric data. Lastly, similarities between the spatial distribution in this inventory and remote sensing data suggest that the anthropogenic source could potentially play a role in explaining a missing source in the global COS budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS)

Here, we present a new data set of annual historical (1750–2014) anthropogenic chemically reactive gases (CO, CH 4 , NH 3 , NO x , SO 2 , NMVOCs), carbonaceous aerosols (black carbon – BC, and organic carbon – OC), and CO 2 developed with the Community Emissions Data System (CEDS). We improve upon existing inventories with a more consistent and reproducible methodology applied to all emission species, updated emission factors, and recent estimates through 2014. The data system relies on existing energy consumption data sets and regional and country-specific inventories to produce trends over recent decades. All emission species are consistently estimated using the same activity data over all time periods. Emissions are provided on an annual basis at the level of country and sector and gridded with monthly seasonality. These estimates are comparable to, but generally slightly higher than, existing global inventories. Emissions over the most recent years are more uncertain, particularly in low- and middle-income regions where country-specific emission inventories are less available. Future work will involve refining and updating these emission estimates, estimating emissions' uncertainty, and publication of the system as open-source software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Production and relevance of cosmogenic radionuclides in NaI(Tl) crystals

The cosmogenic production of long-lived radioactive isotopes in materials is an hazard for experiments demanding ultra-low background conditions. Although NaI(Tl) scintillators have been used in this context for a long time, very few activation data were available. We present results from two 12.5 kg NaI(Tl) detectors, developed within the ANAIS project and installed at the Canfranc Underground Laboratory. The prompt data taking starting made possible a reliable quantification of production of some I, Te and Na isotopes with half-lives larger than ten days. Tnitial activities underground were measured and then production rates at sea level were estimated following the history of detectors; a comparison of these rates with calculations using typical cosmic neutron flux at sea level and a selected description of excitation functions was also carried out. After including the contribution from the identified cosmogenic products in the detector background model, we found that the presence of {sup 3}H in the crystal bulk would help to fit much better our background model and experimental data. We have analyzed the cosmogenic production of {sup 3}H in NaI, and although precise quantification has not been attempted, we can conclude that it could imply a very relevant contribution to the total background below 15 ke in NaI detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Continuous Activity Monitoring During Concurrent Chemoradiotherapy

Purpose: To perform a prospective trial testing the feasibility and utility of acquiring activity data as a measure of health status during concurrent chemoradiotherapy. Methods and Materials: Ambulatory patients who were planned for treatment with concurrent chemoradiotherapy with curative intent for cancers of the head and neck, lung, or gastrointestinal tract were provided with activity monitors before treatment initiation. Patients were asked to wear the devices continuously throughout the radiation therapy course. Step count data were downloaded weekly during radiation therapy and 2 and 4 weeks after radiation therapy completion. The primary objective was to demonstrate feasibility, defined as collection of step counts for 80% of the days during study subjects' radiation therapy courses. Secondary objectives included establishing step count as a dynamic predictor of unplanned hospitalization risk. Results: Thirty-eight enrolled patients were treated with concurrent chemoradiotherapy. Primary diagnoses included head and neck cancer (n=11), lung cancer (n=13), and a variety of gastrointestinal cancers (n=14). Step data were collected for 1524 of 1613 days (94%) during patients' radiation therapy courses. Fourteen patients were hospitalized during radiation therapy or within 4 weeks of radiation therapy completion. Cox regression modeling demonstrated a significant association between recent step counts (3-day average) and hospitalization risk, with a 38% reduction in the risk of hospitalization for every 1000 steps taken each day (hazard ratio 0.62, 95% confidence interval 0.46-0.83, P=.002). Inferior quality of life scores and impaired performance status were not associated with increased hospitalization risk. Conclusion: Continuous activity monitoring during concurrent chemoradiotherapy is feasible and well-tolerated. Step counts may serve as powerful, objective, and dynamic indicators of hospitalization risk.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

1994 Portland Household Travel Survey

The Portland Household Travel Survey was conducted under the auspices of the Oregon Department of Transportation to provide information suitable for gaining an in-depth understanding of the activity and travel behavior of both households in metropolitan areas and the individuals within those households. The first round of surveys collected household activity data from the four metropolitan planning organization areas around Portland, plus three extra counties (Marion, Polk, and Yamhill). A total of 11,762 households participated in this study. Each household member was asked to record any activity that lasted 30 minutes or longer, or any activity that required travel for the specified 48-hour period.

1Hz data↗
DOE OSTI2025

Recommendations for Best Practices for Data Preservation and Open Science in HEP

These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been done under the umbrella of the Data Lifecycle panel of the International Committee of Future Accelerators (ICFA), drawing on the expertise of a wide range of stakeholders. A key indicator of success in the data preservation efforts is the long-term usability of the data. Experience shows that achieving this requires providing a rich set of information in various forms, which can only be effectively collected and preserved during the period of active data use. The recommendations are intended to be actionable by the indicated actors and specific to the particle physics domain. They cover a wide range of actions, many of which are interdependent. These dependencies are indicated within the recommendations and can be used as a road map to guide implementation efforts. These recommendations are best accessed and viewed through the web application, see https://icfa-data-best-practices.app.cern.ch/

Campana, Simone [CERN]↗
DOE OSTI2024

Efficient Scalable Contact Network Generation from Population Data

Modeling the contacts among a population is critical to understanding the dynamics of a disease outbreak. Contact networks, where nodes are individuals and edges are contacts among them, are used to represent these complex individual-level interactions. In this work, we are given the daily activity schedules of an urban population that represent the activity location and time of individuals in a population during a single twenty four hour period over multiple days. Using collocation to determine contact between individuals, our goal is to extract hourly contact networks from large-scale activity data. We improve upon the existing adjacency matrix-based method by implementing our custom sparse matrix multiplication algorithm. Starting with a Python implementation, we achieve a 1600x speed up in the computation with a fast custom designed sparse matrix multiplier algorithm implemented in the C++ language. This work is central to future parallel designs of the problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Upgrading Limiting Peak-Power Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor

Here, this work demonstrates the acceptability of the 2D deterministic transport code, HELIOS, to replace the legacy diffusion code, PDQ, for computing the peak-power performance parameters of the Advanced Test Reactor (ATR). The 95% Confidence Rule, commonly used in the commercial reactor sector, is explored to develop the so-called “reliability factors” which provide statistical confidence that the peak-power limits within the hottest location along a fuel plate, referred to as the hot-stripe, will not be exceeded. Additionally, an alternative “legacy” methodology was explored that attempts to mimic the exact PDQ analysis process used for defining the peak-power limits. The legacy methodology, involves interpolating power between regions at azimuthal boundaries subtending the regions of interest. In order to apply the 95% Confidence Rule, a statistically significant calculation-to-measurement bias must first be established. Unlike the commercial world where thousands of power observations can be collected every cycle using on-line flux mapping instrumentation, the ATR power distribution must be measured during “depressurized” zero-power measurements using fission wires in polyethylene wands. In 2012, fission wire activation data was collected during a flux run in the Advanced Test Reactor – Critical facility. Also to improve statistical validity, archival data from ATR zero power flux runs from 1977, 1986, and 1994 were digitized from scanned reports and used to create new benchmark models. Borrowing from least-squares adjustment methods commonly used for neutron activation spectroscopy, adjusted fission wire powers were calculated for all four datasets. The mean and standard deviation of the bias between a priori calculated and adjusted wire-powers was then taken as the bias and uncertainty used in the 95% Confidence Rule.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Experimental quantification of the background neutron flux in the Advanced Test Reactor fuel storage canal - 25562

The Advanced Test Reactor at the Idaho National Laboratory is one of only a few high-power, versatile, research reactors of its type in the world. The ATR fuel storage canal features a gamma irradiation facility that has various uses as well. It is composed of a simple dry tube that extends down into one of the fuel storage rack positions. This tube is surrounded by used fuel elements that can be selected from the inventory to produce the desired gamma radiation level and, to some extent, spectrum within the dry tube. The gamma field within the dry tube is accompanied by a small background neutron flux, produced primarily by photoneutron production in the small fraction of heavy water (D{sub 2}O) that is naturally present in light water. Neutron activation spectrometry was employed to quantify the background neutron flux in the dry tube in a configuration where the gamma exposure rate was approximately 5x10{sup 6} Roentgens per hour. The measurement technique used is very sensitive and provided self-consistent results in terms of raw activation data quality. The background neutron fluxes in the gamma facility were very low, but still detectable. The total neutron flux in the energy region above 0.414 eV and the thermal neutron flux (below 0.414 eV) were estimated from the activation measurements to be 7.5x10{sup 2} and 1.0x10{sup 2} n/cm{sup 2}-s, respectively. High uncertainties (factors of approximately 20-30% in the above-thermal range and 100% in the thermal range) apply to these results. These high uncertainties are primarily due to the limited number of activation interactions that could be used to detect such small fluxes and the resulting propagation of uncertainties associated with the various input parameters involved in the spectral unfolding process. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Experimental Quantification of the Background Neutron Flux in the Advanced Test Reactor Fuel Storage Canal

The Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL) is one of only a few high-power research reactors (HPRR) of its type in the world, with a variety of missions involving accelerated testing of nuclear fuel and other materials in a very high neutron flux (5.0x1014 n/cm2 -s) environment, medical and industrial isotope production, and other applications. It typically runs several cycles per year with lengths varying from 40-60 days depending on specific experimental requirements for each cycle. The highly radioactive used fuel elements that are discharged from the ATR after each cycle are stored in an adjacent canal (Figure 1) and can be used for as many as three cycles before being retired. The ATR canal features a gamma irradiation facility that has various uses. It is composed of a simple dry tube that extends down into one of the fuel storage rack positions. This tube is surrounded by used fuel elements that can be selected from the inventory to produce the desired gamma radiation level and, to some extent, spectrum within the dry tube. Typical gamma fields that can be produced in this manner can be as high as several megarads per hour. The gamma field within the dry tube is accompanied by a small background neutron flux, produced by photoneutron production in the small fraction of heavy water (D2O) that is naturally present in light water at a concentration of approximately 0.015% by weight, and by a very low level of photofission and spontaneous fission in the fuel elements. The measurement technique used is very sensitive and provided self-consistent results in terms of raw activation data quality. The background neutron fluxes in the gamma facility are very low, but still detectable. The total neutron flux in the energy region from 0.414 eV to 1 MeV and the thermal neutron flux (below 0.414 eV) were estimated from the activation measurements to be 1.0x104 and 2.0x102 n/cm2 -s, respectively. ncertainties of approximately an order of magnitude apply to both results. No neutrons above about 1 MeV were detected. The high uncertainties quoted here are primarily due to uncertainties in the a priori neutron fluxes computed by MCNP6 as well as uncertainties in the spectrum-averaged foil activation cross sections used in the few-group least-squares flux adjustment procedure that was applied. Detailed analyses are currently underway with the aim of reducing these sources of uncertainty.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

CSEWG 2016 Minutes

The Cross Section Evaluation Working Group met November 14 - 16, 2016. Brief status reports are given on nuclear data activities at various DOE laboratories and universities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Residential Demand Flexibility: Modeling Occupant Behavior using Sociodemographic Predictors

Demand flexibility (DF) has the potential to increase the saturation of renewables in the grid and reduce operating costs for both utilities and customers. However, less than 8% of U.S. residential electric customers are enrolled in DF programs. A major research gap on this topic is an uneven understanding of behavioral drivers of electricity use and DF program participation at the household level. In this study, we employ machine learning models to predict residential occupant behavior in activities relevant to DF. We model occupants' extensive decisions (i.e., choice of action) and intensive behaviors (i.e., amount of time spent) during peak and off-peak time periods using the publicly available American Time Use Survey, which includes activities data for approximately 200,000 respondents. In our machine learning models, predictions for both extensive and intensive behavior fell within a +/-20% error margin at the aggregate level. We identify 13 key sociodemographic predictors of DF-related intensive behavior using LASSO inference and beta coefficient ranking. However, these top predictors differ by activity, suggesting potential scope for differential user targeting for DF events and technologies during program design. This work also contributes to understanding when and who might adopt these DF technologies based on their daily routine activities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Developing and Evaluating a Smart Curtailment Strategy Integrated with a Wind Turbine Manufacturer Platform

The Renewable Energy Wildlife Institute lead a team of scientists, wind developers, and turbine manufacturers in a study to develop and test a “smart curtailment” system intended to help reduce bat collisions with wind turbines. The Vestas Bat Protection System (VBPS) is a newly developed software module within the Supervisory Control and Data Acquisition (SCADA) system of Vestas turbines. The VBPS combines data from commercially available environmental sensors and the turbine’s built-in sensors with the Vestas SCADA system. VBPS is designed to receive environmental data from sensors on the turbine such as temperature, wind speed, wind direction, time of day, and time of year, relays that information to the SCADA system to determine whether to execute turbine curtailments at any given time. The goals of this study were to 1) develop a bat fatality risk model based on bat activity data and environmental data collected in year 1, and to 2) evaluate the VBPS, using the bat fatality risk model to implement curtailment, in comparison to “blanket curtailment” (turbines curtailed when wind speed is below 5.0 meters per second (m/s)) and “control” (normally operating, feathered below 3.0 m/s) turbines in year 2. The field study took place at a wind energy facility in Iowa during the fall bat migration seasons (July – October) in 2021 and 2022. For VBPS to succeed as a viable strategy for the minimization of bat fatalities, it should meet or exceed the performance of blanket curtailment. Specifically, the VBPS should meet the following performance targets to demonstrate whether it an effective, practical risk reduction measure: (1) Turbines operating VBPS should have equal or fewer bat fatalities compared to turbines operating with blanket curtailment, and significantly fewer bat fatalities compared to control turbines; and (2) Turbines operating VBPS should have greater power production compared to turbines operating with blanket curtailment. The study was completed in accordance with the Statement of Project Objectives and within the terms of the Budget Justification. This Final Report describes the progress, challenges, and outcomes of the study.

17 WIND ENERGY↗
DOE OSTI2018

Enhancement of STAYSL_PNNL with IRDFF/V1.05 to 60 MeV

The STAYSL PNNL program performs a least-squares adjustment of the neutron spectrum based on the IRDFF cross section library and user-defined activation data and a starting neutron spectrum. All known covariances are included. Required corrections are included for the irradiation history, gamma absorption, neutron burn-up, and neutron self-shielding using separate utility programs prior to the execution of STAYSL PNNL. Several new neutron cross section libraries based on IRDFF V1.05 to 60 MeV are provided with the program including energy group structures of 69 (WIMS), 129 (14 MeV), 140 (prior 100 groups extended to 60 MeV), 175 (Vitamin J), 640 (old SANDII to 20 MeV), and 725 (old Sand II extended to 60 MeV) energy groups. Twelve new reactions were included in IRDFF V1.05. At higher neutron energies, calculations demonstrate the need for activation cross sections from natural targets such as Ti(n,x)46Sc rather than only isotopic targets such as 46Ti(n,p)46Sc and 47Ti(n,x)46Sc. The effects of such reactions increase dramatically with increasing neutron energies and cannot be neglected. Some critical reactions such as 56Fe(n,x)54Mn are not currently included in IRDFF and prevent the use of the 54Fe(n,p)54Mn reaction at higher neutron energies. It is recommended that natural element cross sections be included in future releases of IRDFF for a list of reactions that suffer from reactions on multiple isotopes that lead to the same activation product. Spectral adjustments are illustrated in Be(d,n) thick target neutron fields at deuteron energies of 30 and 40 MeV.

reactor dosimetry, neutron spectral adjustment↗