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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Geothermal Heat Pump System Showcase: Short-Term Validation of Borehole Heat Exchanger Performance from Field Data to Numerical Modeling: Preprint

Since 2011, a geothermal heat pump (GHP) system has been operating to provide space heating and cooling for the Solar Radiation and Research Laboratory building at the National Laboratory of the Rockies (NLR) in Golden, Colorado. The system consists of 23 vertical boreholes, each extending to a depth of 300 ft (91 m), connected to 11 water-to-air heat pump units and four circulation pumps. Between fiscal years 2023 and 2025, additional power meters and temperature sensors were retrofitted to support detailed system performance assessment and model development. This study presents preliminary monitoring results and the development of an initial numerical model of the borehole heat exchanger field. The model incorporated site-specific geometry, ground thermal properties derived from thermal response tests, and ambient temperatures, and simulated system behavior over a representative operating day in September. Model predictions of outlet temperatures were compared against corresponding field measurements. Results showed that modeling initialized with a simplified linear subsurface temperature gradient presents systematic discrepancies in outlet temperature, whereas incorporating depth-resolved borehole temperature measurements for initialization yields substantially improved agreement with observations. The findings highlight the sensitivity of short-term predictive modeling to the representation of initial subsurface thermal conditions and underscore the value of high-resolution field measurements for model calibration and validation. These preliminary results inform ongoing efforts to extend the modeling framework to longer time horizons and to refine monitoring and modeling strategies that support the design guidance and operational optimization of GHP systems in research and commercial buildings.

15 GEOTHERMAL ENERGY↗
NASA NTRSDate not supplied

FloodPlanet: High-Resolution Commercial Imagery for Training and Validation of Deep Learning-Based Models of Inundation Extent

Flooding events are becoming increasingly frequent worldwide and are known to cause extensive damage. Public optical and radar satellite imagery can be used to detect large areas of inundation in rural areas, however, long revisit times and coarse spatial resolution limit applications for short-lived events and urban areas. Commercial constellations such as those operated by Planet offer increased spatial and temporal resolution and can supplement mapping efforts to provide more information to disaster response, relief, and mitigation efforts. Deep learning requires high quality labeled data for training across coincident sensors. The FloodPlanet dataset presented here contains labeled surface water for 18 events across the world based on Planetscope imagery with coincident Harmonized Landsat Sentinel-2 ( HLS) or Sentinel-1 and builds upon the previously existing Sen1Floods11, xBD, and NASA Sentinel-1 datasets. Sen1Floods11 includes 4,831 512x512 pixel overlapping tiles of coincident Sentinel-1 and Sentinel-2 data observing 11 flood events across the world from 2017-2019. The dataset contains a combination of automated and hand-labeled surface water for use in training and validation of inundation modeling efforts. The xBD dataset identifies flood-damaged buildings and indicates the scale of damage to each (none, minor, moderate, and major) from four flood events which occurred in the United States, India, Nepal, and Bangladesh from the same time period. The NASA dataset contains hand-labeled water bodies observed in Sentinel-1 imagery during five flood events within the 2017-2019 period. The effort presented here utilizes observations from these previously investigated flood events to generate labels of surface water at the 3-5m spatial resolution provided by Planetscope and facilitate the comparison between public and commercial data. A data pipeline was built which uses clustering algorithms to pick the most suitable overlapping chips between the public data and PlanetScope data for manual labeling. Labels were created manually using NASA’s ImageLabeler tool and include areas of high- and low-confidence water. The high confidence designation is reserved for areas of open, unobstructed water while low confidence is used for areas of suspected water beneath vegetation, clouds, or cloud shadows. Expected to be released in late 2022, the FloodPlanet dataset will include tiled imagery with a unique ID for each 1024x1024 pixel tile, 7 bands of HLS data, and high- and low-confidence flood labels in both shapefile and tiff formats. The authors will follow Spatial Temporal Access Catalog (STAC) guidelines to release FloodPlanet on the Radiant Earth ML hub, which hosts public datasets for machine learning.

Alexander Melancon↗
DOE OSTI2020

Measurements of Density and Sound Speed in Mixtures Relevant to Supercritical CO2 Cycles

Abstract The objective of this research is to validate properties of mixtures relevant to supercritical carbon dioxide (sCO2) power cycles. Direct-fired sCO2 cycles are a promising technology for the future power generation systems. The working fluid of sCO2 cycles will be near and above critical point of CO2. One of the challenges is that the simulation of mixtures should consider real gas behavior. Expected operating conditions of Allam cycles reach up to 300 bar and 1000 °C. Characterizing the mixtures at the extreme conditions is an important issue in current researches and industrial applications. Thermophysical properties of mixtures may be beyond the valid range of the widely used database such as NIST REFPROP. Experimental data of mixture properties in the literature are limited which is necessary to develop high-fidelity design tools for sCO2 power cycles. We measured the density and sound speed of several multi-component mixtures. A temperature-controlled high-pressure test cell was used for the density measurements. Sound speed was measured by resonant frequency detection using an external speaker and a piezoelectric pressure sensor. Mixtures studied in this work include carbon dioxide, methane, oxygen, and water vapor. Properties of pure CO2 were measured to show the validity of our technique. Compositions were selected to be close to frozen mixtures at the inlet, mid-progress, and exhaust conditions of a model sCO2 combustor in the previous numerical simulation work. Corresponding reaction progress variables (RPV) were RPV = 0, 0.5, and 1. Temperature and pressure conditions of experiments are 310–450 K and 0–150 bar. In our study, density and sound speed from the NIST REFPROP database agree with experimental measurements within the range of our measurement uncertainties.

Energy & Fuels↗
NASA NTRS2014

A Revised Calibration Function and Results for the Phoenix Mission TECP Relative Humidity Sensor

The original calibration function of the R(sub H) sensor on the Phoenix Thermal and Electrical Conductivity Sensor (TECP) has been revised in order to extend the range of the valid calibration, and to improve accuracy. The original function returned non-physical R(sub H) values at the lowest temperatures. To resolve this, and because the original calibration was performed against a pair of hygrometers that measured frost point (T(sub f)), the revised calibration equation is also cast in terms of frost point. Because of the complexity of maintaining very low temperatures and high R(sub H) in the laboratory, no calibration data exists at T is greater than 203K. However, sensor response during the mission was smooth and continuous down to 181 K. Therefore we have opted to include flight data in the calibration data set; selection was limited to data acquired during periods when the atmosphere is known to have been saturated. T(sub f) remained below 210 K throughout the mission(P is greater than 0.75 Pa). R(sub H), conversely, ranged from 1 to well under 0.01 diurnally, due to approximately 50 K temperature variations. To first order, both vapor pressure and its variance are greater during daylight hours. Variance in overnight humidity is almost entirely explained by temperature, while atmospheric turbulence contributes substantial variance to daytime humidity. Likewise, data gathered with the TECP aloft reflect higher H2O abundances than at the surface, as well as greater variance. There is evidence for saturation of the atmosphere overnight throughout much of the mission. In virtually every overnight observation, once the atmosphere cooled to T(sub f), water vapor begins to decrease, and tracks air temperature. There is no evidence for substantial decreases in water vapor prior to saturation, as expected for adsorptive exchange. Likewise, there is no evidence of local control of vapor by phases such as perchlorate hydrates hydrated minerals. The daytime average H2O pressure does not change substantially over the course of the mission, although the H2O column abundance varies by a factor of 2. Column abundances calculated from TECP data are lower than orbital measurements if one assumes that H2O is uniformly mixed through a single scale height. These results argue that the vertical distribution of H2O begins to change well in advance of surface concentrations as northern autumn approaches.

Phoenix Thermal and Electrical Conductivity Sensor↗
DOE OSTI2019

High-resolution wall temperature measurements with distributed fiber optic sensors

Conventional approaches of surface temperature measurement are often unreliable, and other methods may not be practical in closed, high-temperature spaces. In this study, surface temperature measurements of the cooling panel of a natural circulation facility were performed with fiber optic distributed temperature sensors (DTS). High resolution surface temperature profiles of the cooling panel were acquired under two steady experimental conditions, and compared with measurements performed with nearby thermocouples. The total measurement error of the DTS results presented has been estimated to be ±4.4 °C. The findings reflected herein show that these DTS can reasonably measure surface temperature when installed with the methods developed in this study. Through the analysis of the DTS data collected, the interesting behavior of the cooling panel was revealed, providing new insights on the system's behavior that may be beneficial to the design and optimization of such heat transfer devices. These sensors can also provide the measurement density necessary for validation efforts with highly-resolved prediction methods such as finite element analysis (FEA) or computational fluid dynamics (CFD).

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature

Abstract. Measuring soil and snow temperature with high vertical and lateral resolution is critical for advancing the predictive understanding of thermal and hydro-biogeochemical processes that govern the behavior of environmental systems. Vertically resolved soil temperature measurements enable the estimation of soil thermal regimes, frozen-/thawed-layer thickness, thermal parameters, and heat and/or water fluxes. Similarly, they can be used to capture the snow depth and the snowpack thermal parameters and fluxes. However, these measurements are challenging to acquire using conventional approaches due to their total cost, their limited vertical resolution, and their large installation footprint. This study presents the development and validation of a novel distributed temperature profiling (DTP) system that addresses these challenges. The system leverages digital temperature sensors to provide unprecedented, finely resolved depth profiles of temperature measurements with flexibility in system geometry and vertical resolution. The integrated miniaturized logger enables automated data acquisition, management, and wireless transfer. A novel calibration approach adapted to the DTP system confirms the factory-assured sensor accuracy of ±0.1 ∘C and enables improving it to ±0.015 ∘C. Numerical experiments indicate that, under normal environmental conditions, an additional error of 0.01 % in amplitude and 70 s time delay in amplitude for a diurnal period can be expected, owing to the DTP housing. We demonstrate the DTP systems capability at two field sites, one focused on understanding how snow dynamics influence mountainous water resources and the other focused on understanding how soil properties influence carbon cycling. Results indicate that the DTP system reliably captures the dynamics in snow depth and soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes. Overall, the DTP system fulfills the needs for data accuracy, minimal power consumption, and low total cost, enabling advances in the multiscale understanding of various cryospheric and hydro-biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Multispectral data acquisition and classification - Computer modeling for smart sensor design

In this paper a model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing and evaluating smart sensors. The model has both stochastic and deterministic elements and accounts for solar radiation, atmospheric radiative transfer, surface reflectance, sensor spectral reponses, and classification algorithms. Preliminary results are presented which indicate the validity and usefulness of this approach. Future capabilities of smart sensors will ultimately be limited by the accuracy with which multispectral remote sensing processes and their error sources can be computationally modeled.

Park, S. K.↗
NASA NTRS1997

JOVE

The focus of our JOVE research has been to develop a field instrument that provides high quality data for atmospheric corrections and in-flight calibration of airborne and satellite remote sensing imaging systems. The instrument package is known as the Portable Ground-based Atmospheric Monitoring System or PGAMS. PGAMS collects a comprehensive set of spectroscopic/radiometric observations that describe the optical properties of the atmosphere and reflectance of a target area on the earth's surface at the time of the aircraft or satellite overpass. To date, the PGAMS instrument system and control software has been completed and used for data collection in several NASA field experiments across the continental US and Puerto Rico. Where do you see your JOVE research going after the initial JOVE Funding Expires? Our JOVE initiated research will continue to be very active in supporting validation and calibration activities in remote sensing involving NASA, DOE, DOD, NSF, and possibly commercial supported programs. Future effort will focus on projects related to NASA's Mission to Planet Earth. This will include field work using PGAMS and data analysis that evaluates sensor calibration and atmospheric effects in images recorded by ASTER, MODIS, and MISR instruments aboard the AM-1 platform.

Schiller, Stephen↗
NASA NTRS1998

Remote Sensing Measurements of Vertical and Horizontal Moisture Variations from Aircraft Instruments

The research in this paper focuses on describing vertical and horizontal of water vapor variability using two remote sensing aircraft instruments. To achieve this goal we will compare precipitable water and upper level humidity estimates derived from the each of the instruments. The Multispectral Atmospheric Mapping Sensor (MAMS) is a visible and infrared radiometer with similar channels to that of the GOES imager. MAMS has flown aboard the NASA ER-2 numerous times. It has been used to validate features observed with the previous series of GOES satellites. MAMS data has been used to study precipitable water and upper level water vapor as well as other geophysical parameters. MAMS provides the opportunity to obtain water vapor Imagery at 6.7 mm. Upper tropospheric humidity can be computed using this channel in a similar fashion to that of Soden and Bretherton. In addition to the water vapor channel, MAMS records data In 3 other Infrared channels and 8 visible and near Infrared bands at high spatial resolution (I 00 Abstract: m). The 1 1 and 12 mm infrared channels allow for the application of a split technique to derive total precipitable water. The Udar Atmospheric Sensing Experiment (LASE) which uses the Differential Absorption Udar (DIAL) technique for obtaining simultaneous water vapor and aerosol profiles through the entire troposphere. LASE operates In the 81 5 nm wavelength region and uses a double pulsed Ti:sapphire laser that is locked onto a water vapor line. LASE has good horizontal (IO km) and excellent vertical (300 m) resolution. MAMS and LASE collected data simultaneously on several ER-2 flights in September 1995. LASE mixing ratio profiles will be Integrated for comparison with MAMS precipitable water estimates and the upper tropospheric humidity will be computed for the layer observed by the MAMS 6.7 mm channel for comparison for this time period. Results show a significant correlation between the measurements of the two Instruments. Regions of high/low upper tropospheric humidity are apparent In measurements from both instruments. Also changes in boundary layer moisture depicted by LASE are reflected in the total precipitable water measured by MAMS.

Atkinson, R. J.↗
NASA NTRS2007

Radiometric Calibration of the AWiFS Sensor and a Cross-calibration Enhanced Vicarious Calibration Technique

Using vicarious calibration validation of moderate resolution sensors such as AWiFS is complicated by requiring more land area to ensure proper registration and sufficient pixel numbers. A trial AWiFS calibration was performed on a grass site that consisted of two dramatically different grass heights. Ground truth data was collected over relatively small areas representing only a few pixels. The radiometric gain results for each of these areas will be reported. To enhance this analysis, since a near coincidence high resolution image was collected, the high resolution data was effectively resized to produce pixels comparable to AWiFS and the atmospheric model was used to produce a top of canopy radiance map. Multiple uniform vegetated areas of several radiances were then identified and subsequently propagated to the top of atmosphere viewpoint of the moderate resolution (AWiFS) satellite. The radiometric gain was then calculated based on the vendor high resolution satellite gains (for the 3 bands with comparable wavelengths). Band-to-band conversion was performed assuming a hyperspectral reflectance based on the standard vegetated site. The initial comparison produces AWiFS radiometric gain values that agree to better than 10% of the values measured using the standard vicarious gain technique.

Aaron, David↗
NASA NTRS2011

Pad A Main Flame Deflector Sensor Data and Evaluation

Space shuttle launch pads use flame deflectors beneath the vehicle to channel hot gases away from the vehicle. Pad 39 A at the Kennedy Space Center uses a steel structure coated with refractory concrete. The solid rocket booster plume is comprised of gas and molten alumina oxide particles that erodes the refractory concrete. During the beginning of the shuttle program the loads for this system were never validated with a high level of confidence. This paper presents a representation of the instrumentation data collected and follow on materials science evaluation of the materials exposed to the SRB plume. Data collected during STS-133 and STS-134 will be presented that support the evaluation of the components exposed to the SRB plume.

Parlier, Christopher R.↗
NASA NTRS2014

Embedded Data Acquisition Tools for Rotorcraft Diagnostic Sensors

Rotorcraft drive trains must withstand enormous pressure while operating continuously in extreme temperature and vibration environments. Captive components, such as planetary and spiral bevel gears, see enormous strain but are not accessible to fixed instrumentation, such as a piezoelectric transducer. Thus, it is difficult to directly monitor components that are most susceptible to damage. This innovation is a self-contained data processing unit within a specialized fixture that installs directly inside the rotating pinion gear in the gearbox. From this location, it detects and transmits high-resolution prognostic data to a fixed transceiver. The sensor is based on microelectromechanical systems (MEMS) technology and uses innovative circuit designs to capture high-bandwidth data and transmit it wirelessly from inside an operational helicopter transmission. With Ridgetop's advanced MEMS-based sensor, researchers have, for the first time, been able to extract high-resolution acoustic signatures wirelessly from sensors within the transmission that would otherwise be muffled by background gear noises. Ridgetop's innovative instrument will help researchers perform dynamic analysis of gear interaction and develop improved designs for gear components. In addition, data from this instrument can be used to validate new algorithms that detect and predict faults based on external acoustic signatures, for prognostic purposes. The result of this work will be an improvement in safety, performance, and cost for future generations of rotating components.

Wagoner, Robert↗
NASA NTRS2015

Evolvable Cryogenics (ECRYO) Pressure Transducer Calibration Test

This paper provides a summary of the findings of recent activities conducted by Marshall Space Flight Center's (MSFC) In-Space Propulsion Branch and MSFC's Metrology and Calibration Lab to assess the performance of current "state of the art" pressure transducers for use in long duration storage and transfer of cryogenic propellants. A brief historical narrative in this paper describes the Evolvable Cryogenics program and the relevance of these activities to the program. This paper also provides a review of three separate test activities performed throughout this effort, including: (1) the calibration of several pressure transducer designs in a liquid nitrogen cryogenic environmental chamber, (2) the calibration of a pressure transducer in a liquid helium Dewar, and (3) the calibration of several pressure transducers at temperatures ranging from 20 to 70 degrees Kelvin (K) using a "cryostat" environmental chamber. These three separate test activities allowed for study of the sensors along a temperature range from 4 to 300 K. The combined data shows that both the slope and intercept of the sensor's calibration curve vary as a function of temperature. This homogeneous function is contrary to the linearly decreasing relationship assumed at the start of this investigation. Consequently, the data demonstrates the need for lookup tables to change the slope and intercept used by any data acquisition system. This ultimately would allow for more accurate pressure measurements at the desired temperature range. This paper concludes with a review of a request for information (RFI) survey conducted amongst different suppliers to determine the availability of current "state of the art" flight-qualified pressure transducers. The survey identifies requirements that are most difficult for the suppliers to meet, most notably the capability to validate the sensor's performance at temperatures below 70 K.

Diaz, Carlos E., Jr.↗
DOE OSTI2014

NEET Micro-Pocket Fission Detector. Final Project report

A collaboration between the Idaho National Laboratory (INL), the Kansas State University (KSU), and the French Alternative Energies and Atomic Energy Commission, Commissariat à l'Énergie Atomique et aux Energies Alternatives, (CEA), is funded by the Nuclear Energy Enabling Technologies (NEET) program to develop and test Micro-Pocket Fission Detectors (MPFDs), which are compact fission chambers capable of simultaneously measuring thermal neutron flux, fast neutron flux and temperature within a single package. When deployed, these sensors will significantly advance flux detection capabilities for irradiation tests in US Material Test Reactors (MTRs). Ultimately, evaluations may lead to a more compact, more accurate, and longer lifetime flux sensor for critical mock-ups, and high performance reactors, allowing several Department of Energy Office of Nuclear Energy (DOE-NE) programs to obtain higher accuracy/higher resolution data from irradiation tests of candidate new fuels and materials. Specifically, deployment of MPFDs will address several challenges faced in irradiations performed at MTRs: Current fission chamber technologies do not offer the ability to measure fast flux, thermal flux and temperature within a single compact probe; MPFDs offer this option. MPFD construction is very different than current fission chamber construction; the use of high temperature materials allow MPFDs to be specifically tailored to survive harsh conditions encountered in-core of high performance MTRs. The higher accuracy, high fidelity data available from the compact MPFD will significantly enhance efforts to validate new high-fidelity reactor physics codes and new multi-scale, multi-physics codes. MPFDs can be built with variable sensitivities to survive the lifetime of an experiment or fuel assembly in some MTRs, allowing for more efficient and cost effective power monitoring. The small size of the MPFDs allows multiple sensors to be deployed, offering the potential to accurately measure the flux and temperature profiles in the reactor. This report summarizes the status at the end of year two of this three year project. As documented in this report, all planned accomplishments for developing this unique new, compact, multipurpose sensor have been completed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2006

Validation and Verification of Composite Pressure Vessel Design

Ten composite pressure vessels were instrumented with fiber Bragg grating sensors and pressure tested Through burst. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and also compare the fiber Bragg grating sensor data with data obtained against that obtained from foil strain gages.

Kreger, Stephen T.↗
NASA NTRS2010

Methods for In-Flight Wing Shape Predictions of Highly Flexible Unmanned Aerial Vehicles: Formulation of Ko Displacement Theory

The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.

Ko, William L.↗
DOE OSTI2017

Field evaluation of remote wind sensing technologies: Shore-based and buoy mounted LIDAR systems

In developing a national energy strategy, the United States has a number of objectives, including increasing economic growth, improving environmental quality, and enhancing national energy security. Wind power contributes to these objectives through the deployment of clean, affordable and reliable domestic energy. To achieve U.S. wind generation objectives, the Wind and Water Power Program within the Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE) instituted the U.S. Offshore Wind: Removing Market Barriers Program in FY 2011. Accurate and comprehensive information on offshore wind resource characteristics across a range of spatial and temporal scales is one market barrier that needs to be addressed through advanced research in remote sensing technologies. There is a pressing need for reliable offshore wind-speed measurements to assess the availability of the potential wind energy resource in terms of power production and to identify any frequently occurring spatial variability in the offshore wind resource that may impact the operational reliability and lifetime of wind turbines and their components and to provide a verification program to validate the “bankability” of the output of these alternative technologies for use by finance institutions for the financing of offshore wind farm construction. The application of emerging remote sensing technologies is viewed as a means to cost-effectively meet the data needs of the offshore wind industry. In particular, scanning and buoy mounted LIDAR have been proposed as a means to obtain accurate offshore wind data at multiple locations without the high cost and regulatory hurdles associated with the construction of offshore meteorological towers. However; before these remote sensing technologies can be accepted the validity of the measured data must be evaluated to ensure their accuracy. The proposed research will establish a unique coastal ocean test-bed in the Mid-Atlantic for the evaluation of LIDAR-based wind measurement systems to validate the accuracy of remotely measured wind data in marine applications. Specifically, the test-bed will be utilized to systematically evaluate the capability of emerging scanning LIDAR and buoy mounted vertically profiling LIDAR by: (1) Evaluating a fixed scanning LIDAR against land-based 50 and 60 meter high meteorological masts fitted with research quality cup-vane and/or sonic anemometers; (2) Evaluating a buoy mounted vertically profiling LIDAR fixed on land and floating in a sheltered bay against a co-located 60 meter high meteorological mast fitted with a research quality cup-vane and/or sonic anemometers and the fixed scanning LIDAR; and (3) Offshore field evaluation of both LIDAR platforms through a comparison of the fixed scanning LIDAR data and data obtained by the buoy mounted LIDAR located 10 miles offshore. The proposed research will systematically validate Light Detection and Ranging (LIDAR) based wind measurement systems and assess the temporal and spatial variability of the offshore wind resource in the Mid-Atlantic east of New Jersey. The goal of the proposed project is to address the technical and commercial challenges of the offshore wind energy industry by validating and assessing cost-effective, over ocean wind resource characterization technologies. The objective is to systematically evaluate the capability of both scanning and vertically profiling LIDARs to accurately measure 3D wind fields through comparison with fixed met masts and intercomparison among LIDAR platforms. Once validated, data collected by both buoy mounted vertically profiling LIDARs and shore-based, pulsed horizontally scanning LIDARs can be used to accurately assess offshore wind resources and to quantify the spatial and temporal variability in the offshore wind fields. One of the fundamental research questions to be addressed in phase 1 is the assessment of various measurement and data processing schemes to retrieve accurate wind vectors in the marine environment over large sampling ranges (10 to 12 km) and varying atmospheric aerosol levels. Atmospheric conditions and aerosol content within the coastal ocean region of the Mid-Atlantic seaboard of the US can vary significantly over short time periods in response to frontal passages and extratropical and tropical low pressure system passage offshore of the coast. Since aerosols provide the scattering medium for the determination of LIDAR Doppler shifts in the atmosphere the accuracy and range of LIDAR derived velocity measurements as a function of variation in aerosol content in the marine environment is a key research question to be addressed. In phase 1, it is desired to capture as much variation in atmospheric conditions and aerosol content as possible. To this end, collocated measurements of LIDAR and standard anemometer wind fields will be captured by the project PIs over all four seasons and during specific events (e.g., coastal low pressure system passage) in year 1. Additionally, since the meteorological masts are permanent structures, additional events can be captured over the three year duration of the field research project. All research instruments are owned by Fishermen’s Energy and made available to the PIs though a lease agreement as part of the DOE grant. Energy Fishermen’s Energy will be responsible for the operation and maintenance of the scanning LIDAR and met mast anemometers. On a daily basis, environmental data and systems performance indicators will be transmitted from each measurement station to the Fishermen’s project team consisting of both in-house personnel and equipment manufacturer engineers. Data sets include compiled LIDAR files as well as data sets from ancillary sensors. Diagnostic parameters to be monitored include standard deviations of measured values, battery levels and charging systems output, and the operational status. Once data have been confirmed as complete and reliable, files will be transferred to the Garrad Hassan (a subcontractor to Fishermen’s Energy) for incorporation in to the validation database, which is accessible to other scientific team members. Data collection times and durations will be determined by the PI and Co-PIs in consultation with instrument engineers to ensure the capture of data representative of the expected range of mid-Atlantic atmospheric conditions (e.g., temperature, moisture, coastal low pressure systems, tropical systems, rain, snow, fog). The collection and processing of the data is a function of site specific measurement requirements (Kelley et.al. 2007; Hannon et.al. 2008). To determine the optimal profiles of wind speed and direction from the LIDAR radial velocities as a function of azimuth angle, rigorous estimates of the bias and random error of each radial velocity estimate are required. Lockheed Martin Coherent Technologies, Inc., under contract with Fishermen’s Energy, will provide analyses of raw and processed data using various scan patterns to determine optimal performance settings for the pulsed scanning LIDAR. Once optimized, appropriate processing and analyses techniques will be evaluated by Garrad Hassan for use in validating the accuracy of the LIDAR wind field measurements against the standard anemometer measurements from the meteorological masts. The most attractive capability of the scanning LIDAR is the ability to provide high spatial resolution observations in a three-dimensional volume which provides superior statistical accuracy due to the large number of samples obtained. Each radial scan provides measurements in 100 range gates over a distance of 10 to 12 km at an update rate of 5 to 10 Hz and rotation of 2.5° per second. Each rotation at a fixed azimuth requires 2.4 minutes. Depending on the number of azimuths desired a complete scan can take up to 10 minutes or longer to complete. Once collected the radial velocities are processed to produce vector wind velocity estimates based on a set of data distributed in angle and range around points of interest, typically a standard grid within the radial wind map. To calculate wind vectors over a limited spatial area of interest for the comparison of data with other measurement platforms a localized least-squares approach has been applied by Hannon et.al. (2008) and a Variation Assimilation (VAR) processing technique has been applied by Chan and al Assimilation (VAR) processing technique has been applied by Chan and Shao (2006). Additionally, Kelley et.al. (2007) applied a “stare” technique that fixed a scanning LIDAR in both azimuth and elevation angles to measure over collocated sampling volumes of the LIDAR and a 3D sonic anemometer mounted to a fixed mast. Although the stare technique is limited to wind directions aligned with the sampling radial of the LIDAR, it does provide a direct comparison of sampling volumes. Each of the processing techniques described above (and possibly others) will be evaluated to determine the validity of the LIDAR derived wind fields in the marine environment. Numerical methods such as linear regression and comparison of probability density functions of wind fields measured by each instrument platform will be used to assess the processing techniques. Linear regression has the advantage of directly evaluating corresponding pairs of wind data measured by each instrument and can lend insight into deviations and bias between instruments as a function of wind speed. Assessment of the coherency between the probability density function of the wind measured by each instrument provides insight into processes that may not be accurately resolved by each instrument at specific frequencies. Once processed and assessed the most appropriate technique will be utilized to provide valid wind measurements from the pulsed scanning LIDAR. A detailed analysis of the measurement data from the LIDAR and the three meteorological towers and comparison of the coastal wind characteristics from the different systems will be performed by the CO_PI at NREL. This analysis will evaluate how the WT LIDAR performance and measurement of the wind characteristics vary with distance from the LIDAR and by atmospheric conditions; using the tower measurements at different distances (4.8, 9.6, and 19 km) from the LIDAR as a reference. The comparative analysis will include, to the extent possible, evaluation of parameters such as wind speed and direction distributions, wind shear, turbulence intensity and their variations by atmospheric conditions, month or season, and time of day.

17 WIND ENERGY↗