Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “site data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

NANT Site - Microwave Radiometer Thermodynamic Retrievals TROPoe / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on Nantucket Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗
DOE OSTI2025

WFIP3 - BARG site - NREL Profiling Lidar (Windcube v2.1) / Derived Data

This dataset contains derived data from the profiling lidar (Windcube v2.1) deployed at WFIP3's BARG. The derived data files herein are based on the lidar's STA files (i.e., the 10-min average data files). Note: this version of the data has been corrected to account for the motion of the barge.

17 WIND ENERGY↗
DOE OSTI2025

WFIP3 - BARG site - NREL Profiling Lidar (Windcube v2.1) / Reviewed Data

This dataset contains reviewed data from the profiling lidar (Windcube v2.1) deployed on WFIP3's barge. The reviewed files herein are based on the lidar's RTD files (i.e., the real-time raw data files at near 1 Hz resolution). The data have been corrected for the motion of the ship.

17 WIND ENERGY↗
DOE OSTI2026

BLOC Site - ASSIST Thermodynamic Retrievals TROPoe v0.18 / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). This is a post-processed dataset and recommended for use. The profiles are retrieved every 10 minutes from instantaneous radiances observed with an Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST, Michaud-Belleau et al. 2025) operated by NOAA Physical Sciences Laboratory (PSL) on Block Island for WFIP3. The spectral bands used in the retrieval are in the wavenumber range from 612 - 905.4 cm-1 and are specified in Turner and Löhnert (2021). Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a collocated surface tower operated by NOAA PSL. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY. The TROPoe docker container (version 0.18) is available from Docker Hub at https://hub.docker.com/r/davidturner53/tropoe/tags, and the source code code is available in the GitHub repository https://github.com/OAR-atmospheric-observations/TROPoe.

17 WIND ENERGY↗
DOE OSTI2026

RHOD Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily NetCDF files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Rhode Island (RHOD). WINDoe retrievals datasets are also available at Nantucket Island (NANT, nant.windoe.z01.c1) and Block Island (BLOC, bloc.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main) and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗
DOE OSTI2026

BLOC Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily netcdf files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Block Island (BLOC). WINDoe retrievals datasets are also available at Nantucket Island (NANT, nant.windoe.z01.c1) and Rhode Island (RHOD, rhod.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main), and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗
DOE OSTI2026

NANT Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily NetCDF files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Nantucket Island (NANT). WINDoe retrievals datasets are also available at Block Island (BLOC, bloc.windoe.z01.c1) and Rhode Island (RHOD, rhod.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main), and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗
DOE OSTI2026

NANT Site - ASSIST Thermodynamic Retrievals TROPoe v0.18 / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). This is a post-processed dataset and recommended for use. The profiles are retrieved every 10 minutes from instantaneous radiances observed with an Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST, Michaud-Belleau et al. 2025) operated by NOAA Physical Sciences Laboratory (PSL) on Nantucket Island for WFIP3. The spectral bands used in the retrieval are in the wavenumber range from 612 - 905.4 cm-1 and are specified in Turner and Löhnert (2021). Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a collocated surface tower operated by NOAA PSL. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY. The TROPoe docker container (version 0.18) is available from Docker Hub at https://hub.docker.com/r/davidturner53/tropoe/tags, and the source code code is available in the GitHub repository https://github.com/OAR-atmospheric-observations/TROPoe.

17 WIND ENERGY↗
DOE OSTI2021

Fostering Remote Visualization: Experiences in Two Different HPC Sites

Visualization of scientific data is crucial for scientific discovery to gain insight into the results of simulations and experiments. Remote visualization is of crucial importance to access infrastructure, data and computational resources and, to avoid data movement from where data is produced and to where data will be analyzed. Remote visualization enables geographically diverse collaboration and enhances user experience through graphical user interfaces. This paper presents two approaches deployed by two different HPC centers: The SC3 - Supercomputación y Cálculo Científico Center in Colombia and the Oak Ridge Leadership Computing Facility in USA. We overview our remote visualization experiences, adopted technologies, use cases, and challenges encountered. Our contribution is to signal the commonality between approaches in terms of the end goal, showing their fitness for their contexts, while not focusing only on attempting to provide a general picture of remote visualization, given the differences between centers in terms of purposes, needs, resources, and national impact.

Gelvez Cortes, Sergio Augusto↗
DOE OSTI2020

Big Data and AI at DoE's Legacy Sites - 20546

More than 30 years have passed since DOE started the decommissioning of nuclear weapon complexes and the clean-up of soil and groundwater. All the sites have been collecting and archiving soil and groundwater monitoring datasets; particularly contaminant concentration time-series. These datasets provide unparalleled opportunities to understand the system behavior (including more fundamental hydrological and geochemical processes, the response to various perturbations, the long-term trend and environmental decay rate towards the regulatory limit). This understanding is critical for providing multiple lines of evidences that can support site closure. In this study, we explore the machine learning (ML) and artificial intelligence (AI) applications to the long-term soil and groundwater management at DoE's legacy sites. ML can improve our understanding of the subsurface systems, which is critical for long-term monitoring and management of the sites, while AI can automate or support some of decision-making processes (e.g., anomaly detection, monitoring well placements). The particular focuses are to develop general algorithms to: (1) to identify distinct spatiotemporal patterns and to identify several groups that have similar temporal behaviors, using unsupervised clustering methods, (2) identify the different temporal scales of hydrological responses to climate perturbations by time-series analysis, and (3) reduce the number of monitoring wells by identifying the minimum sufficient number of wells to capture the heterogeneity of the groundwater contaminant plume and concentration distribution, using the Gaussian Process model. We demonstrate our methodology at the Savannah River Site F-Area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Solar Radiometer Instrumentation Evaluation: Cooperative Research and Development (Final Report, CRADA Number CRD-16-00619)

The purpose and intent of this agreement is to evaluate newly manufactured thermopile pyranometers and spectroradiometers. The purpose also extends to provide a framework for Participant to conduct research to improve and develop new radiometric devices and application in the future. The overall objective is to provide more accurate, site-specific, long-term, continuous measurements of the solar resources needed by industry to increase the deployment and improve the operations of photovoltaic and concentrating solar power plants. This CRADA addresses the needs for proven solar irradiance measurement to validate resource assessment models and generate high quality data used for site selection, energy system design, deployment, maintenance, and operation. This work will be conducted at NREL and Participant facilities. This project will place instrumentation at the NREL Solar Radiation Research Laboratory (SRRL) in cooperation with EKO Instruments, USA. Participant instruments will be deployed for the purpose of evaluation under controlled conditions. The scope of the project will be a 3 years-long segmented comparison of the instruments vs. other NREL baseline instruments with a well-characterized history. These evaluations will include planned improvements to instruments as well as extensions of future instrument applications. The final evaluation will be a written report similar to the work done by Wilcox and Myers (see http://www.nrel.gov/docs/fy09osti/44627.pdf).

14 SOLAR ENERGY↗
DOE OSTI2023

A case study of denoising microseismic data in the Farnsworth, TX CO 2 EOR site

As geologic carbon sequestration projects begin to be funded with a higher degree of frequency, microseismic monitoring will become more necessary to establish caprock integrity and induced seismicity risk. The Farnsworth, TX site, which hosts enhanced oil recovery operations, provides an ideal laboratory to test essential components of microseismic monitoring such as surface station placement, denoising, and different autopicker methods. We find that despite careful optimization, the surface station placement at the Farnsworth site was insufficient given the high level of background noise from the industrial operations at the oil field. Thus, we use only borehole geophone data in our processing. Two denoising techniques were examined: the DeepDenoiser and the continuous wavelet transform. The continuous wavelet transform was shown to be a valuable tool in converting between raw waveforms to processed denoised waveforms for microseismic monitoring. In the case of the noisy waveforms, only ten detections are found, compared with 90 in the denoised data for a two-hour window. The DeepDenoiser suffered from the fact that the training data was regional earthquake data. In addition, the PhaseNet machine-learning autopicker was applied to both the noisy and the denoised data, and this algorithm detected thousands of more arrivals in the data denoised with the continuous wavelet transform technique.

58 GEOSCIENCES↗
DOE OSTI2026

Storing Affordability: Battery Storage as an Asset to Reduce Data Center Cost Shifts

This report examines how battery energy storage systems (BESS) can help utilities accommodate large load growth while protecting affordability for existing ratepayers. Rapid growth in electricity demand from artificial intelligence (AI) data centers is straining the U.S. grid. Furthermore, many new data centers are entering rural markets, which could offer economic benefits but may also pose implementation challenges for smaller utilities. At the same time, retail electricity prices are increasing faster than inflation, elevating customer affordability as a key challenge. While data centers have not been the primary driver of increases in residential prices to date, they have pushed wholesale energy and capacity prices higher in several markets. Fundamental utility cost-allocation principles show that data center growth can be rate-positive for existing customers only if new peak demand grows faster than the costs a utility must incur to serve it. Several factors, including a utility’s degree of wholesale market exposure, forecast uncertainty and stranded-asset risk, and tariff design can determine the outcome of load growth on retail rates. Energy storage can make several affordability contributions in the face of this landscape of uncertainty and market volatility, including deferral of higher-cost grid investments through improved utilization of existing assets and flexibility of new large loads, insulation from volatile wholesale prices through peak shaving, and reliability support to address grid risks stemming from the behavior of AI data center loads. Different potential BESS deployment pathways—utility-scale front-of-the-meter systems, aggregated small-scale storage installations, and data center-sited behind-the-meter storage—are compared against each other and against conventional capacity alternatives. This framework is intended as a conceptual resource to utilities, particularly smaller public utilities with rural service territories, who may be considering the role that energy storage can play in insulating existing ratepayers from data center cost shifts.

25 ENERGY STORAGE↗
DOE OSTI2025

AmeriFlux US-GL2 Granite Island

This is the AmeriFlux version of the carbon flux data for the site US-GL2 Granite Island. Site Description - Granite Island is a small island on Lake Superior approximately 10 miles due north of Marquette, Michigan. It is roughly 6.5 miles from shore and is occupied by a lighthouse, bell tower, Coast Guard light tower, and other small structures. A flux tower to measure H, LE, and meteorological data was installed atop the bell tower in July of 2009 and has been in continuous operation since then (aside from occasional power outages or other sources of data loss). CO2 measurements were added to the flux tower in October of 2010.

Lenters, John [University of Michigan Biological S↗
DOE OSTI2026

Energy response characterization of current-mode MeV Cherenkov aerogel detectors

Current-mode Cherenkov aerogel detectors have been used to measure time resolved spectra of MeV radiographic x-ray sources and have been considered to replace gas Cherenkov systems. The simulations of the Cherenkov response of aerogel detectors have uncertainties in how to model the complex structure of aerogels. Data from three sites—the Idaho electron beam, the Los Alamos Site electron beam and microtron sources at Los Alamos—have been used to calibrate the relative energy response of 15 aerogels, varying in density from 10 to 430 mg/cm 3 , from incident electrons with energies from 1 to 12 MeV. Detector simulations need to introduce density variation in the aerogels to match the collected data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Play Fairway Analysis: Structurally Controlled Geothermal Systems in the Eastern Great Basin Extensional Regime, Utah

A research team with membership from the University of Utah/Energy & Geoscience Institute, the University of Utah/Dept. of Geology & Geophysics, and the Utah Geological Survey, undertook a play fairway analysis (PFA) for geothermal resources in the Eastern Great Basin (EGB) extensional tectonic regime of western Utah. This is a high-priority region for geothermal exploration because active Basin and Range (B&R) extension with volcanism having a N-S strike is superimposed upon pre-existing E-W belts of plutonic rocks and large-scale structural lineaments. Cumulative heat flow along the N-S strike of the state totals approximately 5 GWt above background stable interior. Three electricity producing power plants currently exist with substantial potential for increase. Succinctly, our PFA approach aims to resolve potential sources of heat and permeability in the region, which are the two principal criteria for establishing a geothermal resource. An initial Phase 1 was carried out using only existing geoscientific data in the area. Criteria selected for focusing heat potential include direct heat flow measurements in boreholes, magnetotelluric (MT) low resistivity anomalies, fluid/gas geochemistry, and proximity to recent volcanic eruptions. Permeability is established through geological structures (fault density, critically stressed areas, seismicity, gravity), and MT low resistivity anomalies. In Phase II of this PFA project, additional geological, geophysical and geochemical data were acquired and analysis carried out primarily over promising composite common risk (CCR) areas initially identified in Phase I in order to focus prospectivity and prepare for drilling recommendations. These prospects are near the Twin Peaks rhyolite field, high heat flow areas north of the producing Cove Fort system, and geophysical structure beneath the Crater Knoll area off the northeast flank of the Mineral Mountains. Additional data included MT site fill-in, structural mapping and analysis using high-resolution imagery, gravity and on-ground mapping, Nodal 3C passive seismic collection, and passive 3He surveying. Heat source and permeability potential are again expressed in terms of their individual common risk segment (CRS) maps, with a color scheme using green for most favorable (low risk) and red for least favorable (high risk). Diverse data types are united through the technique of probability kriging, which establishes prospectivity thresholds for each data type and then computes probability of exceeding that threshold over the PFA area. Modified CRS and CCRS maps are compared to those of Phase I to highlight tighter prospectivity focus. In doing so, the prospectivity threshold for heat was increased significantly to narrow the targeting. In the final Phase III of this project where a recommended deep thermal gradient hole was sited, additional geophysical, geochemical and geological field collection and analysis was carried out to refine drill hole targeting. This includes prospect-scale MT, gravity, structure, passive seismic deployment (Cove Fort area), and detailed 3He isotope profiling. It was the recommendation of the DOE Technical Monitoring Team (TMT) that one or more holes be sited in the north-ern Cove Fort area where legacy TG gradient holes showed high cumulative heat flow. These were to be of moderate depth, 2000-3000 feet, to reach the geothermal fluid table expected to start in excess of 1000 feet depth. The drilling organization stipulated by the DOE/GTO was that of the USGS Research Drilling Program (RDP) centered in Las Vegas, NV. A detailed well plan, appended to this report, was developed principally by Dr. Ben Barker consulting to University of Utah, Dr. Steve Pye on the DOE TMT, Mr. Steven Crawford of the USGS-RDP, and the project PI Phil Wannamaker. However, temperature and possible H 2 S at the systems lead to cancellation of the drilling last-minute as this appeared outside the experience base of the USGS-RDP. We hope to have the opportunity to revisit the test drilling and expand the Play Fairway Analysis of this region at some point in the future.

15 GEOTHERMAL ENERGY↗