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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Wind direction estimation using SCADA data with consensus-based optimization

Abstract. Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. To enable cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving a more efficient wind farm is to develop algorithms that ensure reliable, robust, real-time, and efficient operation of wind turbines in a wind farm using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This article presents a framework for developing a cooperative wind farm that incorporates information from nearby turbines in real time to better align turbines in a wind farm. SCADA data from multiple turbines can be used to make better estimates of the local inflow conditions at each individual turbine. By incorporating measurements from multiple nearby turbines, a more reliable estimate of the wind direction can be obtained at an individual turbine. The consensus-based approach presented in this paper uses information from nearby turbines to estimate wind direction in an iterative way rather than aggregating all the data in a wind farm at once. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction. This estimated wind direction signal has implications for potentially decreasing dynamic yaw misalignment, decreasing the amount of time a turbine spends yawing due to a more reliable input to the yaw controller, increasing resiliency to faulty wind-vane measurements, and increasing the potential for wind farm control strategies such as wake steering.

17 WIND ENERGY↗
DOE OSTI2021

Surface Meteorological Station - Forks, WA (FKS) - Reviewed Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗
DOE OSTI2021

Surface Meteorological Station - Astoria, OR (AST) - Raw Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗
DOE OSTI2021

Surface Meteorological Station - Forks, WA (FKS) - Raw Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗
DOE OSTI2016

GoAmazon 2014/15 Particle Sampling Field Campaign Report

As a part of the GoAmazon 2014/15 field deployments, samples of atmospheric particles were collected at the T3 field site (3° 12' 46.70" S, 60° 35' 53.0, Manacapuru, Brazil) established in the Amazonian region. The site was located downwind from Manaus and therefore, experienced clean conditions when winds were from northwest and polluted conditions when winds were from Manaus. During the second intensive operational period of GoAmazon 2014/15 (09/06/2014-10/02/2014), multiple samples of particles were collected using a cascade Multi-Orifice Uniform Deposition Impactor (MOUDI-110). Size-resolved samples by MOUDI (0.056-0.1, 0.1-0.18, 0.18-0.32, 0.32-0.56, 0.56-1.0, 1.0-1.8 μm) were collected for 6-12 hours. A variety of substrates, compatible with different spectro-microscopy methods of analysis, were arranged on the impactor stages. Collected aerosol samples are now stored pending laboratory analysis using multi-modal methods of chemical imaging. Our approach is to analyze only the samples of specific interest. We use the field campaign records and data on meteorology, as well as in situ measurements of gases and aerosols, to select the subset of samples for the in-depth laboratory analysis for selected episodes where changes in chemical composition of particles can be correlated with other data recorded at the site. Hence, we do not expect to perform detailed measurements on all samples—rather, only those samples with the greatest potential to provide scientific insight into aerosol chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Application and Evaluation of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in Poorly Gauged Regions in Western China

The temporal and spatial differentiation of the underlying surface in East Asia is complex. Due to a lack of meteorological observation data, human cognition and understanding of the surface processes (runoff, snowmelt, soil moisture, water production, etc.) in the area have been greatly limited. With the Heihe River Basin, a poorly gauged region in the cold region of Western China, selected as the study area, three meteorological datasets are evaluated for their suitability to drive the Soil and Water Assessment Tool (SWAT): China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), Climate Forecast System Reanalysis (CFSR), and Traditional Weather Station (TWS). Resultingly, (1) the runoff output of CMADS + SWAT mode is generally better than that of the other two modes (CFSR + SWAT and TWS + SWAT) and the monthly and daily Nash–Sutcliffe efficiency ranges of the CMADS + SWAT mode are 0.75–0.95 and 0.58–0.77, respectively; (2) the CMADS + SWAT and TWS + SWAT results were fairly similar to the actual data (especially for precipitation and evaporation), with the results produced by CMADS + SWAT lower than those produced by TWS + SWAT; (3) the CMADS + SWAT mode has a greater ability to reproduce water balance than the other two modes. Overestimation of CFSR precipitation results in greater error impact on the uncertainty output of the model, whereas the performances of CMADS and TWS are more similar. This study addresses the gap in the study of surface processes by CMADS users in Western China and provides an important scientific basis for analyzing poorly gauged regions in East Asia.

CMADS, SWAT, poorly gauged regions↗
DOE OSTI2026

Tethered Balloon System Ozone Profiles during CoURAGE Summer Intensive Operational Period Field Campaign Report

During the summer IOP, the small ARM field campaign CRGTBSO3 collected measurements to gain an improved understanding of differences between the atmospheric composition in and just above the marine layer at the CoURAGE TBS site near the eastern shore of Chesapeake Bay. CRGTBSO3 included guest instrumentation with ozone (O 3 ) profile measurements on the TBS and surface O3 and meteorological measurements at the TBS site. An En-Sci 2Z electrochemical cell (ECC) ozonesonde (Komhyr 1969, 1986, Witte et al. 2018) was included on the TBS. The ozonesonde was connected to an InterMet iMet-4RSB radiosonde, and the overall data collected included vertical profiles of ozone, relative humidity, temperature, pressure, and altitude. The CRGTBSO3 iMet-4 radiosonde data is identical to that of the iMet in the Tethered Balloon System Merged Data Product (TBSMERGED; Gaustad and Dexheimer 2025). The TBSMERGED data product also includes meteorological data from a different sensor, the iMet XQ2. In some cases, the iMet XQ2 relative humidity (RH) data may be more accurate than the iMet-4, such as for some instances when the iMet-4 RH data stays at 100% for an extended period throughout a profile.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Studying the effect of meteorological factors on the SO2 and PM10 pollution levels with refined versions of the SARIMA model

Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

High Latitude Climate Modeling: ARM Takes Us Beyond Case Studies (Final Report)

The main thrust of this project was to devise a method by which the majority of North Slope of Alaska (NSA) meteorological and radiometric data, collected on a daily basis, could be used to evaluate and improve global climate model (GCM) simulations and their parameterizations, particularly for cloud microphysics. Although the standard ARM Program sensors for a less complete suite of instruments for cloud and aerosol studies than the instruments on an intensive field program such as the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC), the advantage they offer lies in the long time base and large volume of data that covers a wide range of meteorological and climatological conditions. The challenge has been devising a method to interpret the NSA data in a practical way, so that a wide variety of meteorological conditions in all seasons can be examined with climate models. If successful, climate modelers would have a robust alternative to the usual “case study” approach (i.e., from intensive field programs only) for testing and evaluating their parameterizations’ performance. Understanding climate change on regional scales requires a broad scientific consideration of anthropogenic influences that goes beyond greenhouse gas emissions to also include aerosol-induced changes in cloud properties. For instance, it is now clear that on small scales, human-induced aerosol plumes can exert microclimatic radiative and hydrologic forcing that rivals that of greenhouse gas–forced warming. This project has made significant scientific progress by investigating what causes successive versions of climate models continue to exhibit errors in cloud amount, cloud microphysical and radiative properties, precipitation, and radiation balance, as compared with observations and, in particular, in Arctic regions. To find out what is going wrong, we have tested the models' cloud representation over the full range of meteorological conditions found in the Arctic using the ARM North Slope of Alaska (NSA) data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m2 area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

The Impact of Plane-of-Array-Based TMYs on Solar Resource for PV Applications: Preprint

This study attempts to apprise stakeholders about the accurate use of a typical meteorological year (TMY) data set for decision-making that could potentially speed up the acceptance and deployment of projects and reduce risks to financiers and developers. A TMY data set represents hourly concatenation of 12 typical meteorological months constructed using multiyear data sets. Typically, TMY data sets are constructed under horizonal irradiance conditions that are then used in photovoltaic (PV) performance models for available energy calculations in a location after transposing the data to represent a desired plane-of-array (POA) orientation. In this study, we attempt to show that a POA TMY generated with corresponding POA irradiance time-series information produces significantly different results than a POA TMY generated by transposing a TMY data set. In some months, the differences can be more than 3% for irradiance and energy yield. These results point to the need for generating TMY data sets using POA irradiance time series representing the orientation at which PV panels will be deployed.

14 SOLAR ENERGY↗
DOE OSTI2024

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH 4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Evaluating Wind Direction Consensus Methods: A Case Study

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. To enable cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving these cooperative wind farms is to develop algorithms that provide necessary information to ensure reliable and efficient operation of turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This presentation demonstrates a framework for implementing a cooperative wind. Farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more reliable estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbines spends yawing due to a more reliable input to the yaw controller, and increase resiliency to faulty wind-vane measurements. The concept was evaluated on data provided by WindESCo and was evaluated across several other averaging techniques to demonstrate the resiliency of the proposed consensus method.

17 WIND ENERGY↗
DOE OSTI2020

Ice Nucleating Particles, Aerosols and Clouds over the Higher Latitude Southern Ocean

Improved understanding of aerosol-cloud-precipitation interactions is a key goal of the DOE-ASR program. Ice Nucleating Particles (INPs) are rare aerosol particles that trigger ice formation in clouds. By doing so they may initiate precipitation in clouds, and this impacts cloud lifetime. Nowhere may the role of INPs be manifested so dramatically as in the Southern Ocean (SO). This vast region was the focus of the DOE-ARM MARCUS (Measurement of Aerosols, Radiation and CloUds over the Southern Oceans) and MICRE (Macquarie Island Cloud and Radiation Experiment) campaigns. In the SO, a deficit of INPs has been a leading hypothesis for why liquid clouds persist, which underlays the bias of global climate models in predicting excess shortwave radiation reaching the ocean surface between 55°S and Antarctica. In this study, we used the 6-month acquisition of INP data on four MARCUS cruises from Hobart, Tasmania, to Antarctica, and the single-location full annual INP cycle observed in MICRE, to gain a holistic, quantitative picture of the INP number concentrations as a function of temperature and their variability over SO latitudes from 43°S to Antarctica. Augmenting initial processing of filter collections of aerosol particles during MARCUS and MICRE, additional freezing studies following thermal treatment (to removes INPs associated with microbes) and peroxide treatment (to remove all organics), as well as ionic chemistry and total organic carbon analysis, were applied to samples to improve time and space resolution, and differentiate marine from terrestrial contributions. We also performed Next Generation Sequencing to determine that bacterial composition can tag periods of enhanced and degraded marine organic INPs and the relative lack of occurrence of land-sourced bio-particles. Through these and other analyses, INP data were categorized into representative source types (e.g., marine versus terrestrially-influenced). The products of our analyses are being used to parameterize ice formation for use in numerical modeling studies to determine if, and when, ocean-derived INPs control the microphysical composition and radiative balance of SO clouds in a manner not presently captured by global models. The specific objectives and approaches proposed were largely accomplished, including: 1) Additional and value-added chemical and biological analyses of archived samples of aerosols were completed to categorize and quantify INP types and concentrations over the SO. 2) Analyses were completed to place INP data in meteorological and aerosol context. 3) Sea spray aerosol INPs were demonstrated to dominate the SO region in all but episodic events. 4) New parameterizations for INP sources relevant to the SO were constructed. 5) Collaborative modeling studies demonstrating the crucial role of INPs in determining cloud radiative and precipitation properties were conducted with MARCUS and MICRE partners. Collaborative publication submissions in this regard ensued within the two year study. This work will advance the science of interactions of aerosols, clouds and precipitation, to improve their representation in regional and global climate models. Results have informed representation of primary ice crystal nucleation, give inference to the role of secondary processes, and improve investigations of aerosol influences on clouds via ice nucleation over SO high latitudes and similar vast ocean regions. Application will improve representation of such interactions for clouds in both regional and global climate models. The data base and analyses methods applied will continue to serve research studies in the future.

58 GEOSCIENCES↗
DOE OSTI2016

The control room radiological habitability assessment of high temperature reactor pebble bed module (HTR-PM) - 18465

The control room radiological habitability is important for staff safety in nuclear power plant accident, which is also a licensing requirement of the High Temperature Reactor Pebble Bed Module (HTR-PM) in China. In this study, a comprehensive evaluation of the control room radiological habitability is performed for three design basis accident scenario of HTR-PM. For each scenario, three exposure pathways are taken into account, which includes the immersion external exposure, the inhalation exposure and the direct exposure from radioactive cloud in the environment. The atmospheric concentration is calculated using the NRC-recommended ARCON96 code, based on the two-year meteorological observation data at HTR-PM s site and the final building layout. The evaluation result demonstrates that the individual dose level of staffs in the control room is far below the requirement of the regulatory, which guarantees the radiological habitability of control room of HTR-PM. The contribution of each radionuclide has been analyzed, which suggests that iodine and metal radionuclides such as Cs-137 and Co-60 are primary contributor of the total dose, which are worthy of particular attention in the control room habitability design. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

U.S. Offshore Pipeline and Reported Incident Datasets

The U.S. Offshore Pipeline and Reported Incident Datasets provide a compilation of data from a variety of credible resources, spatially-temporally integrated into multivariate resources. This spatial resource includes more than 80,000 points along existing and abandoned pipelines in the Gulf with matched incidents based on similar lease blocks and temporal timelines (e.g., the incident date occurs within reported pipeline lifespan), structural characteristics, geologic and seafloor data, and meteorological, oceanographic, and biochemical statistics spatially and temporally matched to each point. This is provided as both a feature class in a file geodatabase, as well as a CSV file for ease of use. The pipeline incidents table is a CSV file containing more than 900 reported incidents from 1986 to 2021, including incident date, area (Outer Continental Shelf (OCS) lease block and area code), reported causes, reported incident information, and results (i.e., cost, repairs, inspections), along with quantitative severity metrics. Field dictionaries are included for both the pipeline locations and incidents datasets, which detail field definitions. The pipeline locations field dictionary includes original resource reference information.

Advanced Infrastructure Integrity Model↗