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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗
NASA NTRS1999

Tilt Modulation Distortions in Wave Topography Measured by a Scanning Radar Altimeter

Work continues on estimating tilt modulation distortions in the wave topography measured by a scanning radar altimeter. To quantify this effect, a two-dimensional simulation has been performed in the cross-track plane only which assumed that sinusoidal waves of constant wavelength propagate in the cross-track direction (and are infinitely long-crested in the along-track direction). The initial results reported earlier for a Gaussian surface scattering model indicated that when the highest reasonable value of mss is used in the simulation (the Plant limit of 0.08), the nadir values of the ratio of the apparent to actual wave height are the same as for the omnidirectional scattering case. But as the off-nadir angle increased, the apparent wave height increased and became larger than the actual wave height by about 10 degrees off-nadir. And the shorter the wavelength, the larger the apparent wave height increase. This represented a systematic over-estimate of the wave amplitude for waves propagating in the cross-track direction. For lower values of mss the situation worsened. The simulation has been improved by incorporating actual variations of backscattered power with incidence angle measured by the SRA instead of the Gaussian model. The resulting distortion was about half that originally reported. The 3-dimensional simulation to model waves propagating at various azimuthal angles relative to the cross-track plane is still in progress. The results of this model will be verified by comparing them with Scanning Radar Altimeter (SRA) data and optimum correction procedures will be developed. An assessment of the improved 2-dimensional model indicates that the distortion will generally be small in the data taken during the Southern Ocean Waves Experiment (SOWEX) presently be analyzed. But tilt modulation effects are of great concern for SRA data collected during the 1998 hurricane season since the minimum aircraft altitude was 1.5 km and it frequently flew higher. For a given wave length and steepness, the effect increases with increasing aircraft altitude, and is larger for waves propagating in the cross-track direction, which was generally the situation during the hurricane flights.

Walsh, Edward J.↗
DOE OSTI2020

A global ensemble of ocean wave climate projections from CMIP5-driven models

This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (H S ), mean wave period (T m ), and mean wave direction (θ m ) computed over time-slices 1979–2004 and 2081–2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.

Science & Technology - Other Topics↗
NASA NTRS1976

Seasat-A - An ocean observation satellite

Mission details, onboard equipment, and measurements to be taken are described for the Seasat-A global ocean monitoring satellite. The satellite is designed for mapping the global ocean geoid, charting ice fields and leads, precision measurement of sea surface topography, global monitoring of wave height and wave directional spectra, surface winds and wind direction, current patterns, and ocean temperature. Data handling subsystems, a compressed pulse radar altimeter, coherent synthetic aperture imaging radar, microwave wind scatterometer, scanning visible/IR radiometer, scanning multispectral (5 freq) microwave radiometer mounted on the satellite are described briefly.

Williams, F. L.↗
NASA NTRS1981

The Seasat commercial demonstration program

The background and development of the Seasat commercial demonstration program are reviewed and the Seasat spacecraft and its sensors (altimeter, wind field scatterometer, synthetic aperture radar, and scanning multichannel microwave radiometer) are described. The satellite data distribution system allows for selected sets of data, reformatted or tailored to specific needs and geographical regions, to be available to commercial users. Products include sea level and upper atmospheric pressure, sea surface temperature, marine winds, significant wave heights, primary wave direction and period, and spectral wave data. The results of a set of retrospective case studies performed for the commercial demonstration program are described. These are in areas of application such as marine weather and ocean condition forecasting, offshore resource exploration and development, commercial fishing, and marine transportation.

Mccandless, S. W.↗
NASA NTRS1992

Wave attenuation in the marginal ice zone during LIMEX

The effect of ice cover on ocean-wave attenuation is investigated for waves under flexure in the marginal ice zone (MIZ) with SAR image spectra and the results of models. Directional wavenumber spectra are taken from the SAR image data, and the wave-attenuation rate is evaluated with SAR image spectra and by means of the model by Liu and Mollo-Christensen (1988). Eddy viscosity is described by means of dimensional analysis as a function of ice roughness and wave-induced velocity, and comparisons are made with the remotely sensed data. The model corrects the open-water model by introducing the effects of a continuous ice sheet, and turbulent eddy viscosity is shown to depend on ice thickness, floe sizes, significant wave height, and wave period. SAR and wave-buoy data support the trends described in the model results, and a characteristic rollover is noted in the model and experimental wave-attenuation rates at high wavenumbers.

Liu, Antony K.↗
NASA NTRS2012

Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

Huntsberger, Terrance L.↗
NASA NTRS2016

Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center

The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.

Moroni, David F.↗
NASA NTRS1991

A laboratory investigation of electromagnetic bias in sea level measurements by microwave altimeters

To contribute to a better understanding of the electromagnetic bias in radar altimetry, a series of experiments was conducted using a focused beam radar set at 13.5-GHz frequency. For pure wind wave fields, the authors found the bias to be a quadratic function of each of the commonly used parameters, namely, the significant wave height, the wind speed, the water elevation skewness, and significant slope. The bias divided by the significant wave height is a linear function of these parameters. The coefficients in bias representation as a function of either the significant wave height or the wind speed are significantly different from values obtained in field experiments. This led to the conclusion that none of the latter parameters can be taken solely to account for all observed bias variations. Instead, dimensionless parameters such as the wave skewness or a dimensionless wave height are shown to be more appropriate.

Branger, H.↗
NASA NTRS1978

Remote sensing of sea state by analysis of backscattered microwave phase fluctuations

The relative phase of a normally incident microwave signal scattered off the sea surface is a random function of space and time. The statistics of these random phase fluctuations contain information about the wave-height statistics. This study demonstrates that the wave-height spectra can be deduced directly in terms of the spectra of the phase fluctuations without recourse to inversion techniques even when surface roughness exceeds many wavelengths of the incident signal. In the particular case of a nadir-directed satellite-mounted microwave source operating in the backscatter mode, the wave-height and phase spatial spectra are proportional with a constant proportionality of (2k0) squared, where k0 is the wavenumber of the scattered signal.

Clifford, S. F.↗
NASA NTRS1977

Limitations on oceanographic use of beam-limited target-referenced radars

A general development is undertaken to determine the limitations on the use of beam-limited target-referenced radars in the measurement of ocean wave height. This class of radars is concerned only with the range extent of the target, not the range to the target. The nonzero range extent of a flat waveless sea and the compounding effect of pointing errors due to radar platform instability cause difficulty in measuring low wave heights and impose a maximum operating altitude on such systems. It is seen that it is impractical to obtain accurate measurements for wave heights of interest at altitudes above those used by commercial aircraft (10,000 m). Additionally, the typical ratio of dominant wavelength to significant wave height (SWH) of 30 for wind-driven gravity waves imposes an upper limit on the SWH measurable for a given altitude and beamwidth.

Walsh, E. J.↗
NASA NTRS1988

Directional measurement of short ocean waves with stereophotography

Stereophotographs of the sea surface, acquired during the Tower Ocean Wave and Radar Dependence experiment are analyzed to yield directional wave height spectra of short surface waves in the 6-80-cm range. The omnidirectional wave height spectra are found to deviate from the k exp -4 distribution, where k is the wave number. The stereo data processing errors are found to be within + or - 5 percent. The omnidirectional spectra yield 514 deg of freedom for 30-cm-long waves. The directional distribution of short waves is processed with a directional resolution of 30 deg, so as to yield 72 deg of freedom for 30-cm-long waves. The directional distributions show peaks that are aligned with the wind and swell directions. It is found that dynamically relevant measurements can be obtained with stereophotography, after removal of the mean surface associated with long waves.

Shemdin, Omar H.↗
NASA NTRS1994

Differential sea-state bias: A case study using TOPEX/POSEIDON data

We used selected data from the NASA altimeter TOPEX/POSEIDON to calculate differences in range measured by the C and Ku-band altimeters when the satellite overflew 5 to 15 m waves late at night. The range difference is due to free electrons in the ionosphere and to errors in sea-state bias. For the selected data the ionospheric influence on Ku range is less than 2 cm. Any difference in range over short horizontal distances is due only to a small along-track variability of the ionosphere and to errors in calculating the differential sea-state bias. We find that there is a barely detectable error in the bias in the geophysical data records. The wave-induced error in the ionospheric correction is less than 0.2% of significant wave height. The equivalent error in differential range is less than 1% of wave height. Errors in the differential sea-state bias calculations appear to be small even for extreme wave heights that greatly exceed the conditions on which the bias is based. The results also improved our confidence in the sea-state bias correction used for calculating the geophysical data records. Any error in the correction must influence Ku and C-band ranges almost equally.

Stewart, Robert H.↗
NASA NTRS1991

Relationship between wind, waves and radar backscatter

The aim of the research was to investigate the relationship between wind, waves, and radar backscatter from water surface. To this end, three field experiments with periods of 2 to 4 weeks were carried out during summer months in 1988, 1989 and 1990. For these periods, the University of Washington group provided (1) environmental parameters such as wind speed, wind stress, and atmospheric stratification through measurements of surface fluxes (of momentum, sensible heat and latent heat) and of air and water temperatures; and (2) wave height spectra including both the dominant waves and the short gravity-capillary waves. Surface flux measurements were performed by using our well tested instruments: a K-Gill twin propeller-vane anemometer and a fast response thermocouple psychrometer. Wave heights were measured by a resistance wire wave gauge. The University of Kansas group was responsible for the operation of the microwave radars.

Katsaros, Kristina B.↗
DOE OSTI2021

Modeling Sea Ice Effects for Wave Energy Resource Assessments

Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Hawaii Wave Surge Energy Converter (HAWSEC) OSU O.H. Hinsdale Basin

The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...

16 TIDAL AND WAVE POWER↗
NASA NTRS2012

Calibration of Ocean Wave Measurements by the TOPEX, Jason-1, and Jason-2 Satellites

The calibration and validation of ocean wave height measurements by the TOPEX, Jason-1, and Jason-2 satellite altimeters is addressed by comparing the measurements internally among them- selves and against independent wave measurements at moored buoys. The two six-month verification campaigns, when two of the satellites made near-simultaneous measurements along the same ground track, are invaluable for such work and reveal subtle aspects that otherwise might go undetected. The two Jason satellites are remarkably consistent; Topex reports waves generally 1-2% larger. External calibration is complicated by some systematic errors in the buoy data. We confirm a recent report by Durrant et al. that Canadian buoys underestimate significant wave heights by about 10% relative to U.S. buoys. Wave heights from all three altimetric satellites require scaling upwards by 5 6% to be consistent with U.S. buoys.

Ray, Richard D.↗
NASA NTRS1991

On the sea-state bias of the Geosat altimeter

The sea-state bias in a satellite altimeter's range measurement is caused by the influence of ocean waves on the radar return pulse; it results in an estimate of sea level that is too low according to some function of the wave height. This bias is here estimated for Geosat by correlating collinear differences of altimetric sea-surface heights with collinear differences of significant wave heights (H1/3). Corrections for satellite orbit error are estimated simultaneously with the sea-state bias. Based on twenty 17-day repeat cycles of the Geosat Exact Repeat Mission, the solution for the sea-state bias is 2.6 + or - 0.2 percent of H1/3. The least-squares residuals, however, show a correlation with wind speed U, so the traditional model of the bias has been supplemented with a second term: H1/3 + alpha-2H1/3U. This second term produces a small, but statistically significant, reduction in variance of the residuals. Both systematic and random errors in H1/3 and U tend to bias the estimates of alpha-1 and alpha-2, which complicates comparisons of the results with ground-based measurements of the sea-state bias.

Ray, Richard D.↗