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The Acoustic Doppler Current Profiler (ADCP) combined with accurate navigation provides absolute current velocities which include information from all the frequencies which have a dynamical presence in the ocean.
A systematic Data Quality Checking Protocol for vessel Mounted Acoustic Doppler Current Profiler observations is proposed. Previous-to-acquisition conditions are considered along with simultaneous ones.
Depth-averaged current shears computed from shipboard acoustic Doppler current profiler (ADCP) and moored Savonius rotor and vane vector-averaging current meter (VACM) measurements are compared at 35, 62.5, 100 and 140 m depths within 7 km of each other near 0 deg, 140 deg W during a 12-day interval in November 1984. The agreement between the VACM and ADCP shears was excellent. The average root-mean-square difference of hourly shear values was small, approximately 0.0021/s, and the average correlation coefficient was 0.90. Spectral estimates were equivalent to within a 95 percent significance level and the VACM and ADCP shears were 95 percent statistically coherent with zero phase difference for frequencies below 0.2 cycles per hour.
The degree to which Acoustic-Doppler Current Profiler (ADCP) and expendable bathythermograph (XBT) data can provide quantitative measurements of the velocity structure and transport of the Gulf Stream is addressed. An algorithm is used to generate salinity from temperature and depth using an historical Temperature/Salinity relation for the NW Atlantic. Results have been simulated using CTD data and comparing real and pseudo salinity files. Errors are typically less than 2 dynamic cm for the upper 800 m out of a total signal of 80 cm (across the Gulf Stream). When combined with ADCP data for a near-surface reference velocity, transport errors in isopycnal layers are less than about 1 Sv (10 to the 6th power cu m/s), as is the difference in total transport for the upper 800 m between real and pseudo data. The method is capable of measuring the real variability of the Gulf Stream, and when combined with altimeter data, can provide estimates of the geoid slope with oceanic errors of a few parts in 10 to the 8th power over horizontal scales of 500 km.
In December 1991, the National Data Buoy Center (NDBC) deployed two meteorological buoys in the Southern California Bight on a transect between San Diego and San Clemente Island. Each buoy consisted of a 10-m discus hull instrumented to measure a suite of meteorological parameters, and, for the first time in the NDBC buoy program, acoustic Doppler current profilers (ADCPs) were included to gather hourly current profiles beneath the two buoys. Moorings instrumented with seven vector-measuring current meters (VMCMs) were deployed adjacent to the NDBC buoys for several months and provided current observations for comparison with the ADCP measurements. When wave-induced buoy motion is not overly large, the observations of horizontal current made by the ADCP and the VMCM are highly correlated. Time series of differences between ADCP and VMCM measurements are characterized by a mean difference (bias error) of about 0.01 m/s and standard deviation of about 0.035 m/s for 1-h observations. Estimates of current spectra from ADCP and VMCM records suggest that the ADCP system can be characterized by a white noise level of 2 x 10(exp -3) sq m/sq s/cph. However, when the in situ environment is such that large surface waves are present (including breaking waves and whitecaps), erroneous current values are usually reported by the ADCP. Mean values of vertical velocities reported by the ADCP appear to be much larger than what could be physically expected and are therefore deemed unreliable.
This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.
Version 2 of MHKDR submission #475, which also contains the metadata for these measurements. Files here are stored in netCDF4 format, which can be read in Python using the "netcdf4" or "xarray" packages or in MATLAB using the "ncread()" function. Changes are as follows: MWM1 (mid-water mooring 1) ADV - Time length of data now ends when bottom track data is lost - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, turbulent kinetic energy (TKE), Reynolds stress, time interval (TI), and dissipation rate estimations MWM1 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM1 Up-Looking ADCP - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified - Velocity unchanged MWM2 ADV - Removes data after instrument was hit by debris - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, TKE, Reynolds stress, TI, and dissipation rate estimations MWM2 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM2 Up-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified THEOM (bottom lander) ADV - Improved Doppler noise subtraction - improved TKE, Reynolds stress, TI, and dissipation rate estimations - Velocity unchanged THEOM ADCP (up-looking) - Improved Doppler noise subtraction - improved TKE, TI, and dissipation rate estimations - Removed vertical TKE component (w'w' bar) - Velocity unchanged
This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Energy Oceanographic Mooring (THEOM) bottom lander and two Mid-Water Mooring (MWM) Stablemoor buoys from 1 July 2021 to 31 August 2021 (60 days). The west-most mooring (MWM1) was deployed at 60.720225 N, 151.436196 W in ~50 m of water. The middle mooring (THEOM) was deployed at 60.720703 N, 151.429500 W in ~52 m of water. The east-most buoy (MWM2) was deployed at 60.720081 N, 151.420896 W in ~50 m of water. Each Stablemoor carried three instruments: 1. A Nortek Vector acoustic Doppler velocimeter (ADV) mounted at the Stablemoor's nose. Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was motion-corrected using the internal IMU and external ADCP bottom-track data and then bin-averaged into 4 minute bins and converted to the Principal (streamwise, cross-stream, vertical) coordinate system. (Note: 30 seconds were trimmed from the beginning and end of each 5 minute duty cycle to account for the filter end-effects from turning on and turning off the IMU.) 2. A down-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the first Stablemoor instrument well. Data were recorded in 2 Hz with 5-beam burst and bottom-track enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. 3. An up-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the second Stablemoor instrument well. Data were recorded at 4 Hz with 5 beam burst enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. Note: the down-facing ADCP on MWM1 failed on July 10th, 2021, only recording 9 days of data. Because ADV motion-correction required bottom track, the ADV from MWM1 also only has 9 days processed. Additionally, only 25 days of data were processed from the MWM2 ADV because it appeared to have been impacted by debris on 7/25. Two instruments were mounted on the THEOM (see MHKDR link further below for THEOM raw data): 4. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was bin-averaged into 5 minute bins, and converted to the Principal coordinate system. 5. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 10 minutes bins and converted to the Principal coordinate system.
These datasets are from tidal resource characterization measurements collected on the Terrasond High Energy Oceanographic Mooring (THEOM) from 1 July 2021 to 30 August 2021 (60 days) in Cook Inlet, Alaska. The lander was deployed at 60.7207031 N, 151.4294998 W in ~50 m of water. The dataset contains raw and processed data from the following two instruments: 1. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 5 minutes bins and converted to the East-North-Up (ENU) coordinate system. 2. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz in the beam coordinate system. Processed data has been averaged into 5 minutes bins and converted to the Streamwise - Cross-stream - Vertical (Principal) coordinate system. Turbulence statistics were calculated from 5-minute bins, with an FFT length equal to the bin length, and saved in the processed dataset. Data was read and analyzed using the DOLfYN (version 1.0.2) python package and saved in MATLAB (.mat) and netCDF (.nc) file formats. Files containing analyzed data (".b1") were standardized using the TSDAT (version 0.4.2) python package. NetCDF files can be opened using DOLfYN (e.g., `dat = dolfyn.load(''*.nc")`) or the xarray python package (e.g. `dat = xarray.open_dataset("*.nc"). All distances are in meters (e.g., depth, range, etc), and all velocities in m/s. See the DOLfYN documentation linked in the submission, and/or the Nortek documentation for additional details.
This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time frame. The priority for this measurement campaign was to collect data while the turbine was electrically connected to the grid by means of a rectifier and inverter. The Fall_2021_UNH_Measurement_Timeline.png highlights when each instrument was functioning and the Fall_2021_UNH_Test_Log.jpg indicates the four main regions for analysis available from this measurement campaign. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal forcing with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Kaelin Chancey (Assessment Of The Localized Flow And Tidal Energy Conversion System At An Estuarine Bridge - UNH MS Thesis 2019). The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. This project was pursued to quantify device performance for cross flow turbines operating in a marine environment. Accurate physical models, to characterize cross flow turbine performance, require real operational data sets due to the complexity of blade fluid interactions. This data can help support model development which will help predict turbine performance when analyzing perspective project locations in the future. Instrumentation was deployed to measure; water speed/direction, electrical power output, turbine shaft speed, turbine thrust force, and platform motion. Concurrent measurements of these parameters allow for correlations (cause and affect) to be inferred, allowing for characterization of device performance over a range of operating conditions. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) directly upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier and the Shark power meter. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. This submission includes zipped folders for each instrument containing quality controlled (QC'd) data in daily .csv files for the relevant duration specific to each instrument, along with separate .csv file that contains the units for each variable. Some instrument daily files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. Note the degree of QC varied between each instrument due to time constraints. Particular time and attention was given to perform quality control tests on the acoustic based instruments that are particularly suscep...
Pseudosound caused by turbulent pressure fluctuations in fluid flow past a hydrophone, referred to as flow noise, can mask propagating sounds of interest. Flow shields can mitigate flow noise by reducing non-acoustic pressure fluctuations sensed by a hydrophone. We evaluate the performance of three hydrophone flow shields (two nylon fabrics and an oil-filled enclosure) in a tidal channel with peak current speed of 1.3 m s−1. All three flow shields reduced flow noise without attenuating propagating sound below 20 kHz. The oil-filled enclosure performed best, reducing flow noise by over 30 dB at frequencies below 40 Hz.
This submission contains raw Acoustic Doppler Current Profiler (ADCP) data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.
The underway current profiling system which consists of a microprocessor controlled data logger that collects and formats data from a four beam Ametek-Straza 300 kHz acoustic Doppler current profiler, heading from the ship's gyrocompass, and navigation information from a Loran-C receiver and a satellite navigation unit is discussed. Data are recorded on magnetic tape and real time is calculated. Time averaging is required to remove effects of ship motion. An intercomparison is made with a moored vector measuring current meter (VMCM). The mean difference in hourly averaged APOC and VMCM currents over the four hour intercomparison is a few mm s minus including: two Gulf Stream crossings, a warm core ring survey, and shallow water in a frontal zone to the east of Nantucket Shoals.
Observations and theoretical models of small-scale phenomena in the oceans are reviewed, with a focus on progress during the period 1983-1986. Topics examined include surface layers, equatorial turbulence, off-equator mixed layers, the scaling of mixing, turbulence concepts, laboratory results, internal waves and mixing, rings, the nature of the bottom layer, double diffusion and intrusions, salt fingers, and biological interactions. Also discussed are developments in instrumentation (fast sampling profilers with upward-profiling capability, deep profilers, ship-motion correction, horizontal samplers, small submersibles, submarines, towed packages, conductivity sensors, dissolved-oxygen sensors, and acoustic Doppler current profilers) and goals for future research.
This paper presents an integrated path planning and tracking control framework for a marine current turbine (MCT), where the MCT is treated as an energy-harvesting autonomous underwater vehicle (AUV). Considering the ocean (space of action) is continuous, the proposed framework employs two modules to address path planning and path tracking enabled by the proximal policy optimization (PPO) algorithm, which is a policy gradient deep reinforcement learning (RL) method. Further, to enable fully autonomous operation in a stochastic oceanic environment, the proposed path planning seeks a primary objective of maximizing the harvested energy; then, the path tracking module is designed to minimize the tracking error and avoid collisions with static and dynamic obstacles. Using field-collected acoustic Doppler current profiler (ADCP) data, the performance of the proposed framework is evaluated. Comparative studies with baseline algorithms in three different scenarios of path planning, path tracking without an obstacle, and path tracking with collision avoidance verify the effectiveness of our proposed approach.
Tidal stream energy holds great potential as a renewable energy source in regions of the world where tidal currents are strong and predictable. The tidal stream energy resource of a region is strongly controlled by its tidal wave characteristics, the local bathymetry, and coastal geometric features. The Salish Sea, a large estuary on the Pacific Northwest coast, represents a great tidal stream resource because of its strong tidal currents in many tidal channels. However, the tidal resource in the Salish Sea has not been systematically characterized, primarily because of its large area and complex bathymetry and coastlines. This paper presents a modeling study conducted to characterize the tidal energy resource of the Salish Sea based on a high-resolution three-dimensional tidal hydrodynamic model of the Salish Sea, which was extensively validated using data derived from 10 tidal gauge stations and 132 Acoustic Doppler Current Profiler stations. Model validation results indicated the Salish Sea hydrodynamic model is skillful in simulating tidal wave propagation and velocity distributions in the Salish Sea. Based on model results, a total of 16 tidal channels with strong tidal currents, 9 in the San Juan Islands and Rosario Strait regions and 7 in the Puget Sound, were identified as hotspots for potential tidal energy development. Velocity probability distributions and exceedance curves of cross-channel average velocity magnitudes were calculated at all 16 channels based on the recommendations of the International Electrotechnical Commission Technical Specifications for tidal energy resource characterization. The tidal energy resource at the 16 hotspots was also characterized using power density distributions and kinetic energy fluxes. The ranking of the kinetic energy fluxes suggested that Admiralty Inlet, Rosario Strait, and Middle Channel are the top three hotspot sites in the Salish Sea for tidal stream energy development. The study demonstrated the need for a high-resolution 3-D modeling framework for accurate simulation of tidal currents in large complex estuarine systems, in the context of tidal energy resource characterization.
Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.
Re-analyzed acoustic Doppler current profiler (ADCP) data originally collected by NOAA CO-OPS (Center for Operational Oceanographic Products and Services) and equivalent point data from Pacific Northwest National Laboratory's FVCOM (Finite Volume Community Ocean Model) model of the region. Data are processed to products describing characteristics of tidal currents relevant to tidal turbines, as well as power output estimates for a notional turbine deployed from a surface platform or from the seabed at each location. These data underpin the results presented in their associated paper - see below.