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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,693 records · Page 94

All sources NASA NTRS DOE OSTI

DOE OSTI2017

A comparison of numerical and analytical predictions of the tidal stream power resource of Massachusetts, USA

The coastal waters of Massachusetts, USA encompass tidal phenomena that generate flows of sufficient magnitude for commercially viable power extraction. Here we examine the tidal power resource of the Massachusetts coastal region with two high-resolution hydrodynamic tidal models: a regional model encompassing the coastal waters of southeastern New England and a local domain model of Cape Cod Canal. Both models have been subject to comprehensive skill assessment using available surface elevation and ADCP measurements. Based on the model results, we identify five high-energy sites (Cape Cod Canal, Muskeget Channel, Quicks Hole, Robinson Hole and Woods Hole) for evaluation of the maximum extractable tidal power. The power extraction at these sites is modeled using linear momentum actuator disk theory applied to a cross-channel array of turbines. Of the sites evaluated, Muskeget Channel has the greatest resource, with an estimated maximum extractable power of 24 MW. The estimated total power available from all five sites is 44 MW. These estimates agree within 21% with predictions from analytical approaches at all sites. Potential applications for the models include: providing developers with an initial assessment of the resource, guiding observation programs for further study of the resource, and facilitating optimization of turbine array design.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗

NASA NTRSDate not supplied

Hawaii Water Resources: Monitoring the Impact of Land-Based Sources of Pollution on Water Quality Along the Coast of West Maui, Hawai'i, to Assess Coral Reef Condition

West Maui is at risk of losing ecosystem services provided by coral reefs due to land-based sources of pollution (LBSP). In 2011, the US Coral Reef Task Force (USCRTF) identified the West Maui watershed as a priority watershed (along with its sub-watersheds of Wahikuli, Honokōwai, Kahana, Honokahua, and Honolua) after decades of coral decline, giving rise to the multi-agency West Maui Ridge to Reef (R2R) Initiative. The DEVELOP Hawai’i Water Resources team partnered with the R2R Initiative and the Hawai’i Department of Land and Natural Resources Division of Aquatic Resources (DLNR-DAR) to address the need for better watershed management practices. The team provided the partners with a Google Earth Engine tool that displays land use and land cover changes (LULCC) in the five watersheds and detects near-shore turbidity, chlorophyll-a (chl-a), and sea surface temperature using Landsat 4 Thematic Mapper (TM), Landsat 5 TM, Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and Aqua MODIS. Team members used ancillary data provided by the R2R Initiative and the USGS Pacific Coastal and Marine Science Center (PCMSC) to validate satellite parameter values. The land cover analysis captured a general trend of increasing impervious cover and decreasing vegetated cover from 1989 to 2019; however, the extent of this change varied between each watershed. This analysis, coupled with the tool, can help project partners continually monitor terrestrial and marine patterns associated with coral decline.

Water Resources↗

DOE OSTI2018

Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment

Traditionally, analytical frameworks that underpin building energy policy have focused on the need to reduce annual energy consumption by assessing the cost and efficiency performance of energy-consuming technologies. Investments in distributed energy resources (DERs) such as photovoltaics have generally been evaluated independently, but also on a cost and performance basis. However, buildings are rapidly evolving to incorporate technologies that not just consume energy, but also generate, store, and control energy loads. Concurrently, the electric grid is becoming more dynamic and variable due to the increased proportion electricity production from variable renewable sources. To that end, building energy policy analytical frameworks should be updated to include the interactions between energy efficiency and DERs as well as potential value streams for the grid and building owner that technologies or packages of technologies might offer. As buildings with DERs and controllable loads are able to provide grid services or optimize operations based on electricity rates and grid conditions, the temporal and spatial nature of these technologies should also be incorporated into design decisions. To explore these questions further, the National Renewable Energy Laboratory will use a series of building and electric grid models to simulate the design and operation of a neighborhood of buildings under various electricity rates, grid conditions, and potential compensation scenarios. Scenarios of time-sensitive values for future grid services will also be constructed for use in the analysis. New metrics that can be used in building energy policies will also be explored to capture the responsiveness or flexibility of high efficiency buildings with DERs under various electric grid conditions and future scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.

14 SOLAR ENERGY↗

DOE OSTI2017

Evaluation of Preventative Radiological/Nuclear Detector Archetypes to Validate Repurpose to the Consequence Management Mission

In the event of a radiological or nuclear emergency involving a large-scale release of radioactive material, local responders would be the primary means to perform radiation measurements to assess impacts and issue protective action recommendations for the responders and the public. Over the first 24-36 hours, Federal responders and resources will deploy to augment the local efforts, and if necessary, provide extensive radiation monitoring and assessment capabilities coordinated by the Department of Energy-led Federal Radiological Monitoring and Assessment Center and Federal Emergency Management Agency-led Multiagency Coordination Group. Unless Federal resources happen to be deployed at the moment an incident occurs, such as a preventative radiological/nuclear detection mission for a scheduled special event, the local response to an incident will commence and persist for many hours with no on-scene Federal support. For a catastrophic incident, such as a nuclear detonation or severe reactor accident, the local jurisdictions may not have a full range of adequate supplies of health physics instruments and personnel dosimetry. Therefore early in a crisis, the local responders will inevitably conduct their operations with the radiation detection and dosimetry capabilities that they have available until additional resources and support are requested and arrive. Most of the radiation detection instruments currently fielded at the local level are carried by law enforcement personnel and are designed for interdiction missions - referred to here as preventative radiological/nuclear detection (PRND) instruments. This study investigated how this PRND equipment can be repurposed in consequence management (CM) missions.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.

Risk Analysis↗

NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model for Predicting In-Flight Medical Risks

Risk Analysis↗

DOE OSTI2024

Transforming Uinta Basin Earth Materials for Advanced Products (TUBE-MAP)

The objectives of this project were to quantify, assess, and plan to enable the transformation of Uinta Basin earth resources, such as coal, oil shale, resin, rare earth elements, and critical minerals into high value metal, mineral, and carbon-based products. The specific major goals were 1) basinal assessments and initial planning (Task 2), 2) basinal assessment for waste stream reuse with associated plan development (Task 3), 3) basinal strategies development for infrastructure, industries, and business (Task 4), 4) technology assessment, development, and field-testing plan (Task 5), 5) technology innovation center plan (Task 6), and 6) stakeholder outreach and education plan (Task 7).

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas

Estimation of daily suspended sediment concentration (SSC) is required for water resources and environment management. In this paper, a copula-based stochastic method was proposed for daily SSC simulation. Here, the multivariate copula function, constructed based on a bivariate copula and two bivariate conditional probability distributions, was used to model the temporal and cross dependence structures in daily SSCs. Then, the daily SSCs were generated by sampling from the multivariate conditional distribution. As a result, synthetic long-term SSCs data beyond the limited observation period can be provided for water resources managers, which plays a critical role in accurately estimating frequency and magnitude of extreme SSCs events. The proposed method was under rigorous examination by applying to a case study at Pingshan station in the Jinsha River Basin, China. Results showed that the generated daily SSC sequences not only had a high degree of accuracy in preserving the statistical characteristics of the daily SSC observations, but also captured both the temporal correlation and the cross-correlation between the daily streamflow and daily SSC. Specifically, the average daily relative error values corresponding to mean, standard deviation, skewness, lag-1 temporal correlation, and cross correlation were 0.87%, 4.24%, 7.52%, 0.51% and 2.02%, respectively. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resources management such as frequency analysis and risk assessment of extreme SSC events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Methods to estimate the transfer of contaminants into recycling products – A case study from Austria

Highlights: • Recycling of waste materials includes the risk of recycling hazardous substances. • Comparison of contaminants in recycling products to primary products and check of compliance with limit values. • Evaluation matrix to quickly scan the environmental and health risks of wastes for recycling. • Optimised sorting and quality control systems prevent transfer of contaminants into product cycles. - Abstract: Recycling of waste materials is desirable to reduce the consumption of limited primary resources, but also includes the risk of recycling unwanted, hazardous substances. In Austria, the legal framework demands secondary products must not present a higher risk than comparable products derived from primary resources. However, the act provides no definition on how to assess this risk potential. This paper describes the development of different quantitative and qualitative methods to estimate the transfer of contaminants in recycling processes. The quantitative methods comprise the comparison of concentrations of harmful substances in recycling products to corresponding primary products and to existing limit values. The developed evaluation matrix, which considers further aspects, allows for the assessment of the qualitative risk potential. The results show that, depending on the assessed waste fraction, particular contaminants can be critical. Their concentrations were higher than in comparable primary materials and did not comply with existing limit values. On the other hand, the results show that a long-term, well-established quality control system can assure compliance with the limit values. The results of the qualitative assessment obtained with the evaluation matrix support the results of the quantitative assessment. Therefore, the evaluation matrix can be suitable to quickly screen waste streams used for recycling to estimate their potential environmental and health risks. To prevent the transfer of contaminants into product cycles, improved data of relevant substances in secondary resources are necessary. In addition, regulations for material recycling are required to assure adequate quality control measures, including limit values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Multi-model Hydroclimate Projections for the Alabama-Coosa-Tallapoosa River Basin in the Southeastern United States

Abstract This study uses a high-resolution, process-based modeling framework to assess the impacts of changing climate on water resources for the Alabama-Coosa-Tallapoosa River Basin in the southeastern United States. A 33-member ensemble of hydrologic projections was generated using 3 distributed hydrologic models (Precipitation-Runoff Modeling System, Variable Infiltration Capacity, and Distributed Hydrology Soil Vegetation Model) of different complexity. These hydrologic models were driven by dynamically downscaled and bias-corrected future climate simulations from 11 Coupled Model Intercomparison Project Phase 5 global climate models under Representative Concentration Pathway 8.5 emission scenario, with 40 years each in baseline (1966–2005) and future (2011–2050) periods. The hydroclimate response, in general, projects an increase in mean seasonal precipitation, runoff, and streamflow. The high and low flows are projected to increase and decrease, respectively, in general, suggesting increased likelihood of extreme rainfall events and intensification of the hydrologic cycle. The uncertainty associated with the ensemble hydroclimate response, analyzed through an analysis of variance technique, suggests that the choice of climate model is more critical than the choice of hydrologic model for the studied region. This study provides in-depth insights of hydroclimate response and associated uncertainties to support informed decisions by water resource managers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty

Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.

Environmental sciences↗

DOE OSTI2022

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗

DOE OSTI2016

Hotspots of uncertainty in land-use and land-cover change projections: A global-scale model comparison

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Furthermore, current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Charged Species Concentration in Combusting Mixtures Using Equilibrium Chemistry

Ionization in flames is of interest in the design and development of modern combustion devices. The identity and concentration of various charged species in reacting mixtures can play an important role in the diagnostics and control of such devices. Simplified chemistry computations that provide good estimates of ionic species in complex flow-fields can be used to model turbulent reacting flows in various combustion devices, greatly reducing the required computational resources for design and development studies. A critical assessment of the use of the equilibrium chemistry method to compute charged species concentration in combusting mixtures under various temperatures, pressures, and thermal disequilibrium conditions is presented. The use of equilibrium chemistry to compute charged species concentrations in propane-air mixtures performed by Calcote and King has been extended. A more accurate computational methodology that includes the effect of negative ions, chemi-ions (H 3 O + and CHO + ), and thermal nonequilibrium was investigated to evaluate the suitability of equilibrium computations for estimating charged species concentrations in reacting mixtures. The results show that equilibrium computations which include the effects of H 3 O + and elevated electron temperatures can indeed explain the levels of ion concentrations observed in laboratory flame experiments under lean and near-stoichiometric conditions. Furthermore, under engine-like conditions at higher temperatures and pressures, equilibrium computations can be used to obtain useful estimates of charged species concentrations in modern combustion devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Dataset for report: Non-Technical Barriers to Geothermal Development in California and Nevada

In California and Nevada, geothermal projects are subject to non-technical barriers, which may create development delays leading to higher project costs and risks and decreased competitiveness with other electricity generation technologies. These non-technical barriers may include federal and state permits, authorizations, environmental reviews, and other regulatory requirements that are applicable throughout different phases of geothermal project development. The 2022 National Renewable Energy Laboratory (NREL) report, "Non-Technical Barriers to Geothermal Development in California and Nevada" presents findings of a study on non-technical barriers that may influence geothermal project development. The set of data resources relied upon for the report includes: 1) interviews conducted with relevant geothermal stakeholders including regulators and project developers, 2) federal and state environmental review documents developed for specific projects, 3) a techno-economic analysis conducted using the NREL Annual Technology Baseline (ATB) framework, and 4) an analysis of the impacts of site-specific land access and permitting considerations on project development readiness conducted using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) Socioeconomic Assessment Tool (SEAT).

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

Guide to the Distributed Energy Resources Cybersecurity Framework

In May 2018, the U.S. Department of Energy (DOE) released its Cybersecurity Strategy document, a multiyear plan specifically regarding cybersecurity in the energy sector. The framework outlined in this report aligns with strategies identified in the DOE Cybersecurity Strategy document to deliver cybersecurity solutions and continually improve cybersecurity posture. Researchers from federal facilities and industry can now make use of this framework, the Distributed Energy Resources Cybersecurity Framework (DERCF), through a web-based application. This report provides an overview of the DERCF and serves as a guide to applying this framework to DERs. It also provides guidance on a method to conduct a cybersecurity assessment, using the controls presented in Appendix A.

24 POWER TRANSMISSION AND DISTRIBUTION↗