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

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

James Webb Space Telescope Integrated Science Instrument Module Thermal Vacuum Thermal Balance Test Campaign at NASA's Goddard Space Flight Center

The James Webb Space Telescope is a large infrared telescope with a 6.5-meter primary mirror, designed as a successor to the Hubble Space Telescope when launched in 2018. Three of the four science instruments contained within the Integrated Science Instrument Module (ISIM) are passively cooled to their operational temperature range of 36K to 40K with radiators, and the fourth instrument is actively cooled to its operational temperature of approximately 6K. Thermal-vacuum testing of the flight science instruments at the ISIM element level has taken place in three separate highly challenging and extremely complex thermal tests within a gaseous helium-cooled shroud inside Goddard Space Flight Centers Space Environment Simulator. Special data acquisition software was developed for these tests to monitor over 1700 flight and test sensor measurements, track over 50 gradients, component rates, and temperature limits in real time against defined constraints and limitations, and guide the complex transition from ambient to final cryogenic temperatures and back. This extremely flexible system has proven highly successful in safeguarding the nearly $2B science payload during the 3.5-month-long thermal tests. Heat flow measurement instrumentation, or Q-meters, were also specially developed for these tests. These devices provide thermal boundaries o the flight hardware while measuring instrument heat loads up to 600 mW with an estimated uncertainty of 2 mW in test, enabling accurate thermal model correlation, hardware design validation, and workmanship verification. The high accuracy heat load measurements provided first evidence of a potentially serious hardware design issue that was subsequently corrected. This paper provides an overview of the ISIM-level thermal-vacuum tests and thermal objectives; explains the thermal test configuration and thermal balances; describes special measurement instrumentation and monitoring and control software; presents key test thermal results; lists problems encountered during testing and lessons learned.

JWST ISIM Thermal↗
NASA NTRS2012

Thermographic Imaging of the Space Shuttle During Re-Entry Using a Near Infrared Sensor

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter s hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA s next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness. Keywords: HYTHIRM, Space Shuttle thermography, hypersonic imaging, near infrared imaging, histogram analysis, singular value decomposition, eigenvalue image sharpness

Zalameda, Joseph N.↗
DOE OSTI2021

A machine learning degradation model for electrochemical capacitors operated at high temperature

Electrochemical capacitors (ECs) have only recently been considered as an alternative power source for telemetry sensors of drilling equipment for geothermal or oil and gas exploration. The lifecycle analysis and modelling of ECs is underrepresented in literature in comparison to other storage devices e.g. Li-ion batteries. This paper investigates the degradation of ECs when cycled outside the manufacturer-specified operating temperature envelope and proposes a machine learning-based approach for modelling the degradation. Experimental results show that end of life, defined as a 30% decrease in capacitance, occurs at 1,000 cycles when the environmental temperature exceeds the maximum operating temperature by 30%. The life-cycle test data is then used as an input to a Gaussian process regression (GPR) algorithm to predict the capacitance fade trend. The GPR is validated on a total of nine commercial cells from two different manufacturers, achieving an average root mean squared percent error of less than 2% and a mean calibration score of 93% when referenced to a 95% confidence interval. The model can be utilized to determine the EC degradation rate at a range of operating temperature values.

42 ENGINEERING↗
DOE OSTI2017

Comparison and validation of acoustic response models for wind noise reduction pipe arrays

The detection capability of the infrasound component of the International Monitoring System (IMS) is tightly linked to the performance of its wind noise reduction systems. The wind noise reduction solution implemented at all IMS infrasound measurement systems consists of a spatial distribution of air inlets connected to the infrasound sensor through a network of pipes. This system, usually referred to as “pipe array,” has proven its efficiency in operational conditions. The objective of this paper is to present the results of the comparison and validation of three distinct acoustic response models for pipe arrays. The characteristics of the models and the results obtained for a defined set of pipe array configurations are described. A field experiment using a newly developed infrasound generator, dedicated to the validation of these models, is then presented. The comparison between the modeled and empirical acoustic responses shows that two of the three models can be confidently used to estimate pipe array acoustic responses. Lastly, this study paves the way to the deconvolution of IMS infrasound data from pipe array responses and to the optimization of pipe array design to IMS applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Evaluation of WSR-88D Level III and MRMS Rainfall Estimates Against Rain Gauge Observations at the Savannah River Site

Rainfall data for the Savannah River Site (SRS) has been historically measured by rain gauges. These instruments serve as ground truth for most climatological and weather applications; however, gauge measurements are prone to errors or biases under certain weather conditions. Rainfall estimates from radar reflectivity values have been developed and improved over the years and serve as an alternative or supplement for gauge measurements. This study compares measurements from tipping bucket rain gauges with rainfall estimates from the NOAA NWS WSR-88D Level III hourly rainfall product and the Multi-Radar Multi-Sensor (MRMS) gauge-corrected precipitation estimate. Results show good agreement between radar derived amounts and ground measurements, with MRMS values showing correlation coefficients of 0.60-0.95 and RMSE values of less than 1.0 cm (0.4 in). The WSR-88D Level III estimates result in correlation coefficients of 0.46-0.86 and RMSE values of less than 1.3 cm (0.5 in). Few outliers are observed for each data pair and are evaluated against precipitation classification products (WSR-88D Hybrid Hydrometeor Classification product and MRMS Precipitation Flag product). The rain gauges used in this study are not part of the Hydrometeorological Automated Data System (HADS) network used to correct the MRMS estimates and therefore, results of this work provide an independent validation of the MRMS gauge correction scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Challenging Issues for On-orbit Calibration in the VIS and NIR

On-orbit calibration of Earth-observing sensors in the VIS and NIR spectral regions is usually performed using the sensors on-board devices such as internal lamp(s) or solar diffuser plate(s) to provide calibration parameters. For sensors with no (or with less reliable) on-board calibrators, lunar calibration or ground validation approaches are often used. Each of these has its own set of problems that need to be fully addressed in order to support high quality on-orbit calibration and characterization. Some science products, such as Ocean color, may impose more stringent requirements that demand greater calibration precision. This paper uses MODIS as an example to illustrate challenging issues involved in VIS and NIR on-orbit calibration. It focuses on the solar diffuser (SD) calibration approach, including the effects due to SD BRF, SD attenuation screen(s), and earthshine. The impact of optics (solar diffuser and scan mirror) on-orbit degradation, including changes in the sensor s response versus scan angle (RVS), on the calibration and subsequent data quality is also discussed.

Xiong, X.↗
NASA NTRS2011

LADEE Satellite Modeling and Simulation Development

As human activity on and around the Moon increases, so does the likelihood that our actions will have an impact on its atmosphere. The Lunar Atmosphere and Dust Environment Explorer (LADEE), a NASA satellite scheduled to launch in 2013, will orbit the Moon collecting composition, density, and time variability data to characterize the current state of the lunar atmosphere. LADEE will also test the concept of the "Modular Common Bus" spacecraft architecture, an effort to reduce both development time and cost by designing reusable, modular components for use in multiple missions with similar requirements. An important aspect of this design strategy is to both simulate the spacecraft and develop the flight code in Simulink, a block diagram-style programming language that allows easy algorithm visualization and performance testing. Before flight code can be tested, however, a realistic simulation of the satellite and its dynamics must be generated and validated. This includes all of the satellite control system components such as actuators used for force and torque generation and sensors used for inertial orientation reference. My primary responsibilities have included designing, integrating, and testing models for the LADEE thrusters, reaction wheels, star trackers, and rate gyroscopes.

Adams, Michael↗
DOE OSTI2021

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the ngstr m exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products.

Hsu, N. Christina↗
NASA NTRS2011

Passive Microwave Remote Sensing of Falling Snow and Associated GPM Field Campaigns

Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds and have been used to estimate falling snow from space. While satellite-based remote sensing provides global coverage of falling snow events and the science is relatively new, retrievals are still undergoing development with challenges remaining. There are several current satellite sensors, though not specifically designed for estimating falling snow, are capable of measuring snow from space. These include NOAA's AMSU-B, the MHS sensors, and CloudSat radar. They use high frequency (greater than 85 GHz) passive and active microwave and millimeter-wave channels that are sensitive to the scattering from ice and snow particles in the atmosphere. Sensors with water vapor channels near 183 GHz center line provide opaqueness to the Earth's surface features that can contaminate the falling snow signatures, especially over snow covered surface. In addition, the Global Precipitation Measurement (GPM) mission scheduled for launch in 2013 is specifically designed to measure both liquid rain and frozen snow precipitation. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, and surface types. For example, can a lake effect snow system with low cloud tops having an ice water content (IWC) at the surface of 1.0 gram per cubic meter be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. In this work, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases [9] since simulations provide all the information to determine the measurements from space and the ground truth. This analysis relies on data from the Canadian CloudSat/CALIPSO Validation Program (C3VP) field campaign held from October 31, 2006 through March 1, 2007. In January 2012 GPM will return to the C3VP area for the GPM Cold Precipitation Experiment (GCPEx). This presentation will describe the thresholds-of-detection procedure and results, as well as the field campaign details.

Skofronick-Jackson, Gail↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗
NASA NTRS1996

Guidance and Control Design for High-Speed Rollout and Turnoff (ROTO)

A ROTO architecture, braking and steering control law and display designs for a research high speed Rollout and Turnoff (ROTO) system applicable to transport class aircraft are described herein. Minimum surface friction and FMS database requirements are also documented. The control law designs were developed with the aid of a non-real time simulation program incorporating airframe and gear dynamics as well as steering and braking guidance algorithms. An attainable objective of this ROTO system, as seen from the results of this study, is to assure that the studied aircraft can land with runway occupancy times less then 53 seconds. Runway occupancy time is measured from the time the aircraft crosses the runway threshold until its wing tip clears the near side of the runway. Turnoff ground speeds of 70 knots onto 30 degree exits are allowed with dry and wet surface conditions. Simulation time history and statistical data are documented herein. Parameters which were treated as variables in the simulation study include aircraft touchdown weight/speed/location, aircraft CG, runway friction, sensor noise and winds. After further design and development of the ROTO control system beyond the system developed earlier, aft CG MD-11 aircraft no longer require auto-asymmetric braking (steering) and fly-by-wire nose gear steering. However, the auto ROTO nose gear hysteresis must be less than 2 degrees. The 2 sigma dispersion certified for MD-11 CATIIIB is acceptable. Using this longitudinal dispersion, three ROTO exits are recommended at 3300, 4950 and 6750 feet past the runway threshold. The 3300 foot exit is required for MD-81 class aircraft. Designs documented in this report are valid for the assumptions/models used in this simulation. It is believed that the results will apply to the general class of transport aircraft; however further effort is required to validate this assumption for the general case.

Goldthorpe, S. H.↗
NASA NTRSDate not supplied

Pace OCI Crosstalk Characterization Based on Pre-Launch Testing

Scheduled to launch in 2024, the Ocean Color Instrument (OCI) onboard the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will collect hyperspectral data from 315 nm – 895 nm via two grating spectrometers (in both the blue and red spectral regions) and 9 multi-spectral bands in the short-wave infrared (940 nm – 2260 nm). The increased spectral resolution and radiometric accuracy is expected to improve upon data collected by heritage sensors such as SeaWiFs, MODIS, and VIIRS, allowing new applications in ocean color, aerosol, and cloud science. During ground testing, higher than expected spatial-spectral crosstalk was measured for the hyperspectral bands in the blue spectrograph. Using a monochromatic-collimated light source, light from a single science pixel (1km x 1km) was found to produce crosstalk signals over 31 pixels in the cross-track direction. This spatial augmentation is caused by the spectral crosstalk’s asynchronous spatial movement during Time Delay Integration (TDI). To fully characterized the magnitude and spectral dependency from this, a crosstalk model was developed by synthesizing data collected from monochromatic-collimated light and monochromatic light that filled the OCI optical aperture. The model was validated by showing good agreement between predicted values and other relevant test data collected using both monochromatic and white light sources.

PACE↗
NASA NTRS1984

The validation of Nimbus 7 LIMS measurements of ozone

Approximately seven and one half months of stratospheric ozone profiles have been processed from the LIMS (Limb Infrared Monitor of the Stratosphere) experiment on the Nimbus 7 satellite. Data profiles cover the stratosphere and mesosphere from 100 to 0.1 mbar and from 84 degrees N to 64 degrees S latitude. Topics covered include the ozone channel characteristics, precision, systematic uncertainties, and comparisons with data from balloon and rocket underflights, Umkehr soundings, and Dobson measurements. Comparisons with Dobson total ozone are made by integrating combined LIMS plus balloon profiles. The estimated on-orbit precision is 0.02-0.16 ppmv. Simulations of the experiment indicate potential systematic uncertainties ranging from 15 percent in the 1-mbar region to an upper limit of 40 percent at 100 mbar and 0.1 mbar. Results are well within the uncertainties for the correlative sensors themselves. LIMS detects significant vertical structure in the ozone profile even below the ozone mixing ratio peak. Several other comparisons showing good agreement are noted.

Remsberg, E. E.↗
DOE OSTI2018

Under canopy light detection and ranging–based autonomous navigation

This study describes a light detection and ranging (LiDAR)–based autonomous navigation system for an ultralightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2D Hokuyo UTM–30LX LiDAR sensor as the single source for perception. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row–based and high–leaf–cover semistructured crop plantations, such as corn ( Zea mays ) and sorghum ( Sorghum bicolor ). The key contribution of our work is a LiDAR–based navigation algorithm capable of rejecting outlying measurements in the point cloud due to plants in adjacent rows, low–hanging leaf cover or weeds. The algorithm addresses this challenge using a set of heuristics that are designed to filter out outlying measurements in a computationally efficient manner, and linear least squares are applied to estimate within–row distance using the filtered data. Moreover, a crucial step is the estimate validation, which is achieved through a heuristic that grades and validates the fitted row–lines based on current and previous information. The proposed LiDAR–based perception subsystem has been extensively tested in production/breeding corn and sorghum fields. In such variety of highly cluttered real field environments, the robot logged more than 6 km of autonomous run in straight rows. These results demonstrate highly promising advances to LiDAR–based navigation in realistic field environments for small under–canopy robots.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling

This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture. The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.

16 TIDAL AND WAVE POWER↗