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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Kansas environmental and resource study: A Great Plains model. Monitoring fresh water resources

The author has identified the following significant results. Processing and analysis of CCT's for numerous ground truth supported passes over Kansas reservoirs has demonstrated that sun angle and atmospheric conditions are strong influences on water reflectance levels as detected by ERTS-1 and can suppress the contributions of true water quality factors. Band ratios, on the other hand, exhibit very little dependence on sun angle and sky conditions and thus are more directly related to water quality. Band ratio levels can be used to reliably determine suspended load. Other water quality indicators appear to have little or no affect on reflectance levels.

Yarger, H. L.↗
NASA NTRS1974

Kansas environmental and resource study: A Great Plains model. Monitoring fresh water resources

The author has identified the following significant results. ERTS MSS ratios derived from CCT's are very effective for quantitative detection of suspended solid up to at least 900 ppm. The relatively high inorganic suspended solids, characteristic of midcontinent reservoirs, dominates the reflected energy present in the four MSS bands. Dissolved solids concentrations up to 500 ppm and algal nutrients up to 20 ppm are not detectable. The MSS5/MSS4 ratio may be weakly correlated with total chlorophyll above approximately 8 micrograms/liter.

Yarger, H. L.↗
DOE OSTI2023

PV Performance Modeling - Data and Resources

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. This dataset includes seven MS-Excel sheets with instructions, notes and all necessary data (weather, irradiance, temperature, power) used for the data analysis of the blind modeling comparison. The hourly data represent six different systems from Albuquerque, NM and Roskilde, Denmark over a period of one year. These data are useful for PV performance model validation studies.

14 SOLAR ENERGY↗
DOE OSTI2020

Validation of RU-WRF, the Custom Atmospheric Mesoscale Model of the Rutgers Center for Ocean Observing Leadership

The Rutgers University Center for Ocean Observing Leadership (RU-COOL) contracted the National Renewable Energy Laboratory (NREL) to evaluate RU-COOL's atmospheric observation and modeling capabilities for characterizing the New Jersey offshore wind resource. The observational network used by RU-COOL consists of mostly public but some private coastal and offshore buoy-based stations. The core wind resource modeling capability of RU-COOL is a custom setup of the Weather Research and Forecasting (WRF) mesoscale model, referred to in this report as RU-WRF. The most unique feature of RU-WRF and not found in other WRF model setups is the use of custom sea surface temperature (SST) product generated by RU-COOL. This custom product was designed to better capture the unique coastal upwelling and strong storm mixing in the Mid-Atlantic Bight, which other typical SST products are not designed to capture. Funding for the development, maintenance, and use of RU-WRF by RU-COOL is provided by the New Jersey Board of Public Utilities, who also funded the validation work presented in this report. In this validation study, NREL was specifically tasked to: 1) Assess the observational network used by RU-COOL to validate RU-WRF and make recommendations for improvement, 2) Assess methods used by RU-COOL to validate RU-WRF and make recommendations for improvement, 3) Examine the inputs to and setup within RU-WRF, compare against available NREL data sets, and make recommendations for improvement.

17 WIND ENERGY↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Numerical Simulations of an Axisymmetric Shock-Wave/Boundary-Layer Interaction

A series of Reynolds-averaged Navier-Stokes (RANS) simulations were performed of two Mach 2.5 axisymmetric shock-wave/boundary-layer interactions (SWBLIs) based off of the NASA Turbulent Computational Fluid Dynamics Validation Experiment (TCFDVE). The goals of the simulations were to (1) determine how well RANS can predict the flow physics of an axisymmetric SWBLI and (2) generate a new validation case for the NASA Turbulence Modeling Resource (TMR). The simulations were run with two different turbulence models and three different computational fluid dynamics (CFD) codes while looking at two different conical shock generator angles, one of which was shown to cause flow separation in the experiment. The results in this paper show that, as expected, the CFD simulations agreed well with each other and the experiment when SWBLI-induced separation was not present. When separation was present, differences in the predicted separation characteristics were noted. These included a stronger interaction and subsequently longer separation extent for the Menter Shear-Stress Transport k-ω (SST) turbulence model simulations compared to both the Spalart-Allmaras (SA) turbulence model simulations and the experiment.

Computational Fluid Dynamics↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
NASA NTRS2012

Space Weathering Investigations Enabled by NASA's Virtual Heliophysical Observatories

Structural and chemical impact of the heliospheric space environment on exposed planetary surfaces and interplanetary dust grains may be generally defined as space weathering . In the inner solar system, from the asteroid belt inwards towards the Sun, the surface regolith structures of airless bodies are primarily determined by cumulative meteoritic impacts over billions of years, but the molecular composition to meters in depth can be substantially modified by irradiation effects. Plasma ions at eV to keV energies may both erode uppermost surfaces by sputtering, and implant or locally produce exogenic material, e.g. He-3 and H2O, while more energetic ions drive molecular change through electronic ionization. Galactic cosmic ray ions and more energetic solar ions can impact chemistry to meters in depth. High energy cosmic ray interactions produce showers of secondary particles and energetic photons that present hazards for robotic and human exploration missions but also enable detection of potentially useable resources such as water ice, oxygen, and many other elements. Surface sputtering also makes ejected elemental and molecular species accessible for in-situ compositional analysis by spacecraft with ion and neutral mass spectrometers. Modeling of relative impacts for these various space weathering processes requires knowledge of the incident species-resolved ion flux spectra at plasma to cosmic ray energies and as integrated over varying time scales. Although the main drivers for investigations of these processes come from NASA's planetary science and human exploration programs, the NASA heliophysics program provides the requisite data measurement and modeling resources to enable specification of the field & plasma and energetic particle irradiation environments for application to space weather and surface weathering investigations. The Virtual Heliospheric Observatory (VHO), Virtual Energetic Particle Observatory (VEPO), Lunar Solar Origins Exploration (LunaSOX), and Space Physics Data Facility (SPDF) services now provide a wide range of inner heliospheric spacecraft data that can be applied to space weathering of potential exploration destinations including the Moon, asteroids, and the moons of Mars, as well to radiation hazard assessment for the spacecraft and human explorers. For example, the new VEPO service for time-averaging of multi-source ion flux spectra enables the specification of composite flux spectra from a variety of ongoing and legacy missions for applications to surface interaction modeling. Apollo to Artemis data resources of LunaSOX enable specific space weathering investigations for the Moon, while VHO more generally covers the space field and plasma environments of the inner and outer solar system from the sunward-most perihelia of the twin Helios spacecraft to the ongoing heliosheath passages of the twin Voyagers. Composite multi-source spectra from VEPO can also be applied to the continuing compilation of accumulated 1-AU fluence spectra, mostly contributed by solar wind plasma and energetic particle events, for determination of time-averaged particle compositional and kinetic energy output from the Sun and for modeling of long-term irradiation impacts on planetary surfaces.

Cooper, John F.↗
DOE OSTI2024

The Challenges of Modeling Distributed Energy Resources (DERs) as Blackstart Resources and for Volt-VAR Optimality

Modeling, testing and instituting Distributed Energy Resources (DERs) as Blackstart Resoucrces presents several challenges due to the fundamental differences between traditional black start resources (e.g., large generators) versus DERs like solar PV systems with battery storage. This paper addresses some of these key challenges. These include intermittency of coordinating DERs to provide continuous power during a black start event, especially during extended periods of cloud cover or when battery energy storage is depleted. This paper additionally addresses the collapsing voltage and stability control challenges specific to maintaining bulk power system stability during black start synchronization These physical and engineering limitations require careful engineering design, modeling and engineering to ensure that DERs can support critical loads and substations during black start events. A variety of additional challenges also exist. Additionally, there are challenges associated with feeder location and low voltage secondary system impacts on DER functions and settings. We compare typical functions and settings for DERs for power factor control and correction. We also demonstrate how voltag control via Volta-VAR power factor correction can be done

Mukherjee, Srijib↗
DOE OSTI2020

Distributed Wind Representation in Modeling and Simulation Tools: An Assessment of Existing Tools

PNNL evaluated the inclusion of wind in distributed energy resource modeling and simulation tools. Tools were assessed based on a survey of publicly available and readily accessible information. While the authors have made a good faith effort to understand these tools, PNNL does not know the intentions of the developers and acknowledges that some tool capabilities or features may not have been accurately captured in this assessment. This evaluation informs an ongoing effort by PNNL to modernize existing tools both directly by working with developers of some tools and indirectly by providing best practices on how different types of tools could enhance certain modeling features to improve distributed wind’s representation and valuation.

17 WIND ENERGY↗
DOE OSTI2024

Multi-scale Simulation, Calibration, and Optimization of Calcium Carbonate Precipitation in Microbial Communities

Ensuring the efficient engineering of microbially induced calcium carbonate precipitation (MICP) is crucial for a variety of environmental and civil engineering applications, such as soil stabilization and carbon sequestration. Addressing this need, we present a comprehensive multi-scale workflow that begins with the isolation of calcium carbonate-producing microbes from soil samples, followed by metagenomic sequencing and metabolic reconstruction. We then characterize microbial growth phenotypes under diverse nutrient conditions, compare observed growth with metabolic model predictions, and apply the Consistent Reproduction of Phenotype (CROP) algorithm to refine these models. Furthermore, we analyze metabolite consumption and production, and develop a consumer-resource model that is calibrated using time-series measurements of growth rates, pH levels, and calcium carbonate precipitation. The primary benefit of our approach lies in its ability to predict and control MICP outcomes, facilitated by a Bayesian methodology that incorporates priors on initial conditions and parameters. This allows us to compute posteriors by integrating experimental data, and to solve a risk optimization problem under uncertainty to identify nutrient conditions that maximize calcium carbonate production. In contrast to non-Bayesian methods, which fail to quantify uncertainty accurately, our approach provides a more reliable pathway to optimizing nutrient conditions, enhancing the likelihood of achieving desired MICP outcomes. This positions our method as a superior alternative in the quest to improve MICP through engineered microbial consortia.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Dissociation of performance and subjective measures of workload

A theory is presented to identify sources that produce dissociations between performance and subjective measures of workload. The theory states that performance is determined by (1) amount of resources invested, (2) resource efficiency, and (3) degree of competition for common resources in a multidimensional space described in the multiple-resources model. Subjective perception of workload, multidimensional in nature, increases with greater amounts of resource investment and with greater demands on working memory. Performance and subjective workload measures dissociate when greater resources are invested to improve performance of a resource-limited task; when demands on working memory are increased by time-sharing between concurrent tasks or between display elements; and when performance is sensitive to resource competition and subjective measures are more sensitive to total investment. These dissociation findings and their implications are discussed and directions for future research are suggested.

Yeh, Yei-Yu↗
DOE OSTI2026

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗
DOE OSTI2020

Impact of climate change on adaptive management decisions in the face of water scarcity

Reoccurring drought through the early 2000s has caused a serious water scarcity issue in the Colorado River Basin. Previous modeling studies have focused on the impact of climate change without considering the adaptive behaviors of farmers and under-utilized Indian water rights. Here, we use a coupled agent-based water resource model (ABM) to investigate how the adaptive decisions of farmers can affect water resource management under both climate change impacts and fully utilized Indian water right conditions. We used five General Circulation Model projections with RCP8.5 scenarios for the study. The results of farm-level decision-making showed different responses in irrigated areas that were changing due to climate change impact. While winter precipitation changes might partially explain the behavior changes, no specific pattern could be concluded based on their location. Also, farmers’ responses about annual water diversion showed more significant inter-year variation compared to irrigated areas. Basin-level metrics showed that climate change impacts will generally worsen water scarcity issues as measured in Navajo Reservoir storage, flow to Lake Powell, and instream flow requirement. But these basin-level water scarcity metrics cannot reflect individual farm-level impacts under climate change, which is why modeling the bottom-up management actions is necessary. When the under-utilized Indian water rights are fully used, it is more likely to trigger the shortage sharing agreement due to the higher tribal water depletion. Evaluation of model uncertainty and a more realistic setup for adaptive actions under drought contingency plans are suggested for future research.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Performance modeling of earth resources remote sensors

A technique is presented for constructing a mathematical model of an earth resources remote sensor. The technique combines established models of electronic and optical components with formulated models of scan and vibration effects, and it includes a model of the radiation effects of the earth's atmosphere. The resulting composite model is useful for predicting in-flight sensor performance, and a descriptive set of performance parameters is derived in terms of the model. A method is outlined for validating the model for each sensor of interest. The validation for one airborne infrared scanning system is accomplished in part by a satisfactory comparison of predicted response with laboratory data for that sensor.

Kidd, R. H.↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
NASA NTRS2011

Integrated Modeling, Mapping, and Simulation (IMMS) Framework for Exercise and Response Planning

EmergenCy management personnel at federal, stale, and local levels can benefit from the increased situational awareness and operational efficiency afforded by simulation and modeling for emergency preparedness, including planning, training and exercises. To support this goal, the Department of Homeland Security's Science & Technology Directorate is funding the Integrated Modeling, Mapping, and Simulation (IMMS) program to create an integrating framework that brings together diverse models for use by the emergency response community. SUMMIT, one piece of the IMMS program, is the initial software framework that connects users such as emergency planners and exercise developers with modeling resources, bridging the gap in expertise and technical skills between these two communities. SUMMIT was recently deployed to support exercise planning for National Level Exercise 2010. Threat, casualty. infrastructure, and medical surge models were combined within SUMMIT to estimate health care resource requirements for the exercise ground truth.

Mapar, Jalal↗
NASA NTRSDate not supplied

Recent Progress on Rans-Based Transition Model Verification

The current efforts to assess and improve the Reynolds-averaged Navier-Stokes (RANS)-coupled transition models in the NASA FUN3D and OVERFLOW codes are summarized in this study. The first AIAA Transition Modeling Workshop and the NATO AVT-313 Transition Workshop both emphasized the need for code verification for transport equations based transition models as a top priority. We discuss the methods used for the model verification, the resulting grid families, the flow solutions, and other supporting information collected with at least two established NASA flow solvers, namely, FUN3D and OVERFLOW. These results, which will be uploaded onto the NASA Turbulence Modeling Resource, should assist other members of the computational fluid dynamics (CFD) community in verifying their own implementations of various transition models, such as the Langtry-Menter (LM2009) model, the one-equation γ model, and Coder’s amplification factor transport (AFT) model. Grid convergence is assessed using both global and local flow metrics of interest such as lift and drag as well as local skin-friction coefficients. We also explore the anisotropic unstructured metric-based adaptive mesh refinement library known as refine with the NASA FUN3D solver to determine if this capability can achieve the same accuracy as handcrafted structured grids with a significantly smaller node count and to learn the characteristics of the resulting grid distribution, especially in the vicinity of the transition zone.

Transition↗