Product Spotlight – ADCP Buoy Frames

Product Spotlight – ADCP Buoy Frames

DeepWater Buoyancy is the world’s largest produced of subsea buoyancy products for the oceanographic community. At the heart of the product line are the deployment solutions for ADCP applications, including spherical and elliptical buoys, the low-drag StableMoor® buoy, trawl-resistant bottom mounts (TRBMs) and diver serviceable bottom mounts.

This article will spotlight DeepWater Buoyancy’s frame designs for ADCP buoys.

For more information, click HERE.

In the early days of acoustic doppler current profilers (ADCPs) most units on the market were designed with four transducer beams. To most effectively accommodate these four-beam ADCPs, buoys were produced with four tie-rods that pass through the buoy and end frames with four legs that attach to the tie-rods. This design allowed for the beams of the ADCP to pass between the frame legs, unobscured.

Advances in ADCP technology have since led to ADCPs with as few as three beams and as many as nine transducer beams. In some cases, a center (vertical) beam is included in the configuration. These technological advances in ADCP design have led to changes in the design of the framework for ADCP buoys.

ADCPs with various transducer configurations.

In the case of a three-beam ADCP, buoys are now offered with three tie-rods and end frames with three legs that pass between the beams.  For customers who have previously purchased a buoy outfitted for a four-beam ADCP, but now look to use a three-beam ADCP, a frame is available that mounts on the four tie-rods and transitions to three legs to pass between the beams. Additionally, a buoy can be outfitted with a four-beam frame on one end and a three-beam frame on the other for compatibility with both systems.

ADCP Buoy Top Frame made for a 3 beam ADCP to be mounted in a buoy with four tie-rods.

When a buoy is at the top of a mooring and a vertical beam is used, or when an ADCP with several beams is used, typical frames would block the beam or beams. And since the buoy is at the top of the mooring string, the need for a top arbor is eliminated. In this case a ring frame is used.  This frame serves to protect the ADCP head during deployment, recovery, and handling on the deck of a vessel, but will not obstruct the beam pattern.

Ring Frame for ADCP with center vertical beam.


All frames are manufactured with 316L stainless steel. The frames are then electropolished and fitted with replaceable zinc anodes for superior corrosion resistance.  Frames with arbors on them are fitted with isolation bushings and allow connection to the mooring line with standard shackles.

Our extensive in-house design, machining, metalworking, and welding capabilities allow us to make an endless variety of these frames to support and protect not only ADCPs, but also a wide range of other instrumentation. DeepWater Buoyancy’s engineering staff will work with you to design the exact frame that best meets the needs of your equipment, pass through loads, and time at depth.


About DeepWater Buoyancy, Inc.

DeepWater Buoyancy creates subsea buoyancy products for leading companies in the oceanographic, seismic, survey, military and offshore oil & gas markets.   Customers have relied on our products for over thirty-five years, from the ocean surface to depths exceeding six thousand meters.

Learn more at

Technical Paper: DoE Approach to Mooring Design

Technical Paper: DoE Approach to Mooring Design

DeepWater Buoyancy collaborated with Maine Marine Composites (MMC) on a paper for the Oceans18 Conference. 

The paper, entitled “A Design of Experiments based approach to engineering a robust mooring system for a submerged ADCP”, was presented by Tobias Dewhurst, PhD of MMC.

A copy of the paper can be downloaded HERE.

A copy of the PowerPoint presentation can be downloaded HERE

A Design of Experiments Based Approach to Engineering a Robust Mooring System for a Submerged ADCP



Michael T. MacNicoll, Tobias Dewhurst, PhD, Richard Akers, P.E. – Maine Marine Composites LLC, Portland, ME, USA

David A. Capotosto, DeepWater Buoyancy, Inc., Biddeford, ME, USA


A model-based engineering approach was used to design an optimal single-point mooring for a subsea Acoustic Doppler Current Profiler (ADCP). Numerous inputs and criteria were considered. Target deployment depth, environmental conditions, and seafloor characteristics were identified for the selected site in the Gulf of Maine. Design variables included buoy shape, buoy volume, gravity anchor mass, chain size, acoustic release buoyancy, and wire rope diameter. Design criteria included wire rope safety factor, chain load safety factor, ADCP pitch, ADCP knockover (set down), anchor sliding, and the recoverability of the Acoustic Release.  A design methodology based on Design of Experiments (DoE) theory was used to develop a mooring system that satisfied all the competing design objectives while minimizing cost. This methodology limited expensive simulation time while resulting in a satisfactory mooring design.

Keywords—Acoustic Doppler Current Profiler; ADCP; Mooring Design; Design of Experiments

I.    Introduction

A.   Motivation

Numerous competing criteria must be considered when designing mooring systems for oceanographic instruments. These criteria include the deployment depth range, acceptable pitch angles, and cost. Furthermore, environmental conditions and seafloor characteristics must be accounted for properly. An under-designed system could allow excessive instrument motion or movement of the anchor. An overdesigned system increases component costs and requirements for deployment assets. For example, oversizing the mooring line adds weight to the system, which in turn increases the buoyancy requirement. Increasing the buoyancy creates greater stress on the mooring line and increases the anchor weight requirement. These changes drive up the costs. A successful design approach must balance multiple competing criteria without requiring excessive simulation time, while resulting in a mooring system that meets the design criteria under all expected environmental conditions without overdesigning the system.

B.   Methodology

A simulation-based engineering approach was used to design an optimal single-point mooring for a subsea Acoustic Doppler Current Profiler (ADCP). This approach satisfied the objectives above by applying computer simulations in a Design of Experiments (DoE) framework. Using the DoE methodology, an experiment was designed to identify the factors that drive mooring system performance and cost. The results of the experiment were then used to optimize the system based on linear regression of the DoE results. This regression model accounted for both the first-order interactions between factors, and the competing design objectives discussed above.

Simple experiments often attempt to isolate variables and study their effects on a system one at a time. There are two limitations with this approach. First, the number of variables is artificially limited, to limit the time and effort to carry out an experiment. Second, this approach fails to study how design factors might interact with each other. The Design of Experiments (DoE) approach overcomes these shortcomings [1].

DoE is a systematic approach to quantify how sensitive a system is to factors that are believed to influence that system. A DoE setup will require first identifying the factors to be examined. Next, two levels are selected for each factor, and experiments are carried out on the system. This can be done using each possible combination of levels and factors, or a subset of each combination. When the number of factors is large, then the number of all possible combinations of levels and factors can become excessive, so a fractional factorial experiment may be designed that still ensures there is no aliasing between factors and first order interactions between factors.

In the present study, MMC applied a DoE approach to design a mooring system for a submerged ADCP. The DoE approach allowed for efficient examination of a very large design space, identification of the design factors that have the greatest impact on the design objectives, and development of an optimal design.

Fig. 1 lays out this design approach. An initial design is proposed, and design constraints are quantified. Design factors are identified. Upper and lower levels are determined for each factor. These levels represent the highest and lowest likely values for each design factor. Next, a DoE experiment is set up and computer simulations are run. The results of the DoE simulations are used to develop a regression model based on the design constraints. If the optimal design does not satisfy the design constraints, a revised DoE is developed. The revised DoE will require adjusting the levels of the factors, or adding new factors, to improve the results. The process is repeated until the optimal design converges on one which satisfies the constrained design objectives.

Figure 1. Flowchart of Design Approach

II.    Procedure

A.   Mooring System Initial Design

The ADCP mooring equipment was based on a typical mooring system design (see [2] for example) The arrangement consists of an anchor, connected with chain to an acoustic release (used to retrieve the ADCP) with some added buoyancy, and a wire rope from the acoustic release to a buoy that keeps the ADCP in position. The ADCP is attached to the top of the buoy and is positioned 100 meters below the surface to avoid the most extreme wave motions. The buoy has the dual objectives of (1) providing reserve buoyancy to keep the ADCP upright and in position to minimize pitching and knockover (set down) motions, and (2) to bring the mooring string to the surface when the release is activated. The arrangement is shown in Fig. 2.

Figure 2 Components of moored ADCP. Chain and wire rope lengths are not to scale.

B.   Environmental Conditions

The ADCP will be deployed near the National Oceanic and Atmospheric Administration’s (NOAA) National Data Buoy Center (NDBC) Station 44098, Jeffrey’s Ledge in 300 meters of water [3]. A robust metocean study of the deployment location was performed by MMC using historical wave data from NDBC for the years 2008-2015. This study used Principle Component Analysis and the inverse first-order reliability method (I-FORM), as described in [4] and as implemented in the Wave-Energy-Converter Design Response Toolkit [5]. In this approach, linear algebraic methods are used to develop an orthogonal basis whose components are aligned so as to represent the largest degree of variance.  Once these principal components are identified, extreme contours are generated using the I-FORM approach [6]. The extreme contour was limited to the steepness at which waves generally break. The resulting 50-year return period contour is shown in Fig. 3. From this analysis, the largest 50-year return period significant wave height is 10.7 m, with a peak period of 13 s.

Figure 3  50-year sea state contour at Jeffrey’s Ledge, NH (solid blue line). Blue dots are historical observations. Contour lines show probabilities of occurrence.


C.   Design Constraints

As the goal of this study was to use a DoE-based approach to design a robust and cost-effective mooring system, the following seven design objectives were identified:

  • Prevent uplift and sliding of the anchor
  • Minimize knockover of the ADCP
  • Minimize pitch of the ADCP
  • Maintain minimum safety factor of the wire rope of at least 1.67 [7]
  • Maintain minimum safety factor of the anchor chain of at least 1.67 [7]
  • Acoustic release must have enough buoyancy to be recoverable if the wire rope fails and the acoustic release is disconnected from the upper buoy.
  • Minimize the cost of the system

D.   Design Factors

Six design factors were identified. These are the variables of the mooring arrangement that will be tuned by the DoE simulations. Two factors related to the ADCP buoy. Two buoy shapes, a spherical buoy and an elliptical buoy, were simulated. These are based on ADCP buoys made by DeepWater Buoyancy Inc., shown in Fig. 4. In addition, two buoy volumes (and corresponding buoyancy lift forces) were simulated for each shape. The buoy has the primary objectives of mitigating ADCP pitching and knockover. Larger buoys will increase the cost of the system and the loads on the mooring lines, while smaller buoys will be less effective in mitigating ADCP motions.

The third design factor is the mass of the anchor. The anchor must be heavy enough that it does not move, either vertically or laterally. However larger anchors will increase the cost of the system.

The diameter of the chain and wire rope components of the mooring line are the next two factors. The primary trade-off for these components is safety factor vs. cost. Smaller components will have lower safety factors, but larger components will drive up the cost of the system.

The final factor is the buoyancy of the acoustic release. This must provide enough uplift to ensure that the acoustic release can be recovered if the wire rope fails and the acoustic release is separated from the reserve buoyancy.

These design factors, and the corresponding higher and lower levels, are summarized in TABLE I. In a full factorial DoE, every combination of high and low levels for each factor would be simulated, resulting in 27=128 simulations. In this work a fractional factorial matrix was design with resolution four, which ensured that all primary factor and first order interaction effects could be isolated without aliasing, while reducing the number of required simulations [8].

Figure 4  ADCP buoyancy options. Top: spherical buoy; bottom: elliptical buoy (source:


Table 1  Summary of DoE Input Factors


E.   Computer Simulation

A computer simulation of the ADCP and its mooring system was developed using the commercial software OrcaFlex by Orcina [9]. Simulations were run for each row of the fractional factorial matrix during the 50-year return period storm with a steady current.

Three phases of ADCP deployment were investigated in the DoE simulations, including (1) deployment in calm water, (2) survival in 50-year return period storm event, and (3) retrieval using the acoustic release. Deployment involved releasing the ADCP from the surface and allowing the entire system to sink until the anchor reached the seabed. The retrieval was simulated by disconnecting the reserve buoyancy buoy from the wire rope, and the acoustic release from the chain. The acoustic release, provided it was buoyant enough, would rise to the surface with the wire rope.

The results of the DoE simulations are shown in Main Effects plots in Fig. 5. Each subplot shows the sensitivity of a single factor to the corresponding design objective. The steeper the line, the more sensitive the objective is to that factor. Some of the design trade-offs that must be considered are shown clearly in this figure. For example, increasing the buoy volume has the beneficial effects of decreasing the ADCP pitching and set down. However, there are also negative consequences to increasing the buoy volume, such as increasing the mooring loads, increasing the likelihood of anchor sliding, and increasing the cost of the system. To weight the pros and cons of conflicting design objectives, a global objective function was developed. This is discussed in the following section.

Figure 5  Summary of Design of Experiments simulation results. Each row shows the Main Effects plots for every factor and a single objective. Each column shows the Main Effects plots for every objective for a single factor.


F.   Optimization Results

The results of the DoE simulations were used to optimize the ADCP mooring system design. For each of the design objectives discussed above, a linear regression model was computed. For objective i, this takes the form:


Here bi are the regression coefficients and X are the levels for each factor, including first-order interactions and a constant intercept.

There are several limitations with using a strictly linear regression model to optimize the mooring design. First, there is no convenient way look at multiple design objectives at the same time. Second, many objectives are not linear. For example, the safety factor of the mooring rope must be at least 1.67, however, once it is over that threshold, it is less critical that it continue to be improved. To account for these limitations, each design objective was normalized with a logistic function,


Here fi(X) is the regression function for objective, i, and ki and x0,i are steepness and midpoint parameters which must be identified. The global objective function is then taken as the minimum of each objective:


This is illustrated in Fig. 6. The wire rope safety factor experiences a steep drop-off when the safety factor approaches the design target. Above the target, the safety factor is not as sensitive to changes in the wire rope diameter. The cost objective function does not experience a steep drop-off, as there is no hard target. The optimal wire rope diameter is the peak of the Combined Objective function, which is located at the intersection of the two sub-objectives.

Figure 6  Illustration of wire rope safety factor and cost objectives as a function of wire rope level. The combined objective function is shown in red.


When all six design factors and all seven design objectives are considered, it is not possible to visualize the objective function in two dimensions. Fig. 7, Fig. 8, and Fig. 9 each show the objective function plotted as a surface plot for two factors.

Fig. 7 shows the objective function as a surface plot with respect to the chain diameter and the wire rope diameter. There is a trade-off between safety factor and cost that suggests that the optimal wire rope and chain diameters are roughly halfway between the upper and lower DoE levels.

Figure 7  Objective surface plot shown with respect to chain diameter (x-axis) and wire rope diameter (y-axis). Yellow regions show the peak objective values.


Fig. 8 shows the objective function with respect to the buoy shape and size. The buoyancy must optimized to balance a reduction in cost with an increase in wire rope safety. As the buoyancy decreases, however, the ADCP pitch increases. An elliptical buoy shape better mitigates ADCP pitch than a spherical buoy.

Figure 8  Objective surface plot shown with respect to reserve buoyancy (buoy) shape (x-axis) and buoy volume (y-axis). Yellow regions show the peak objective values.


Fig. 9 shows the objective function with respect to the anchor mass and acoustic release buoyancy. The optimal design occurs when the anchor mass and acoustic release buoyancy are large, but beyond a certain point the design is less optimal as the cost of the system becomes the limiting factor.

Figure 9  Objective surface plot shown with respect to anchor mass (x-axis) and acoustic release buoyancy (y-axis). Yellow regions show the peak objective values.


III.    Results

Once the objective function was defined, most standard optimization routines can be used to determine the optimal values. TABLE II. summarizes the optimal levels of each factor.

Table 2  Summary of Optimal Design


The optimal ADCP buoy is an elliptical buoy with a diameter of 50.5 inches. The optimal mooring lines are a 7.6 mm diameter wire rope and an 8.1 mm diameter studless chain. To ensure that sliding on the seabed is minimized, the anchor mass must be 1,694 kg, slightly larger than the highest level simulated. The acoustic release needs an additional 0.185 m^3 of buoyancy to ensure that it will be retrieved if it becomes separated from the buoy.

To validate that the DoE procedure successfully converged on a working arrangement, the design summarized in TABLE II. was simulated for a duration of three hours in the maximum 50-year return period sea state at the Jeffrey’s Ledge site. Extreme Value Analysis was used to find the peak expected value and confidence intervals for each objective. For objectives that are Gaussian, or nearly so, the three-hour extremes were computed according to:

Here x is an arbitrary data field, μx is the simulated mean, T is the dominant wave period, and σx is the simulated standard deviation.
For non-Gaussian distributed objectives, such as the mooring tension, the three-hour extremes were fit to a Generalized Pareto Distribution, using a Peaks-Over-Threshold (POT) approach [10], [11]. Then the upper 95th percentile of the expected values are used.
The results are summarized in TABLE III. The wire rope and chain safety factors are acceptable – both well above the target of 1.67 [7]. The pitch angle and knockover are manageable, the anchor stays in place, and the Acoustic Release is successfully recovered.

Table 3  Summary of Optimal Design Results


IV.    Discussion

Maine Marine Composites, in collaboration with DeepWater Buoyancy Inc, applied a Design of Experiments-based simulation approach to developing a robust, cost-effective mooring system for a hypothetical submerged ADCP in the Gulf of Maine. The DoE approach made it possible to quickly examine a broad range of design factors and levels, and the optimal design was shown to meet all the desired objectives.

The objective function used for optimization is based on linear regression of the DoE results. The objective function is constructed in such a way that all objectives are met without needlessly maximizing any objectives beyond their target levels. This approach supports both constraints and objectives, where constraints are a limit the design must achieve (“Ensure that the mooring safety factor is at least 2.2”) and objectives are more open-ended (“Minimize the cost of the mooring system”).


  1. Fisher, R., Design of Experiments, 8th, Oliver and Boyd LTD, Edinburgh, 1960.
  2. Ma, B.B., Lien, R-C., and D.S. Ko, “The variability of internal tides in the Northern South China Sea,” J. Oceanogr. 69, 2013, pp. 619-630.
  3. National Oceanic and Atmospheric Administration’s National Data Buoy Center. “Station 44098 – Jeffrey’s Ledge, NH (160).” S. Dept. of Commerce.
  4. Eckert-Gallup, Sallaberry, Dallman, Neary. “Application of principle component anlysis (PCA) and improved joint probability distribution to the inverse first-order reliability method (I-FORM) for predicting extreme sea states,” Ocean Engineerign, 2016, pp. 307-319.
  5. Coe, R.G. Michelen, C., Eckert-Gallup, A., Yu, Y., and J.v. Rij, “WDRT: A toolbox for design-response analysis of wave energy converters,” Proceedings of the 4th Marine Energy Technology Symposium (METS), Washington D.C., 2016.
  6. Haver, S., and S. Winterstein, “Environmental contour lines: a method for estimating long term extremes by short term anslysis,” Trans. Soc. Nav. Archit. Mar. Eng. 116, 2009, pp. 116-127.
  7. American Bureau of Shipping (ABS), Guide for Position Mooring Systems, Houston, TX, 2018.
  8. Krishnaiah, K., and P. Shahabudeen, Applied Design of Experiments and Taguchi Methods, PHI Learning Private Limited, New Dehli, 2012.
  9. Orcina LTC, OrcaFlex User Manual: OrcaFlex Version 10.2c, Daltongate Ulverston Cumbria, UK, 2018.
  10. Bommier, E., “Peaks-Over-Threshold Modelling of Environmental Data,” U.U.D.M. Project Report, 2014:33.
  11. do Nascimento, F.F., Gamerman, D., and H. Freitas Lopes, “A semiparametric Bayesian approach to extreme value estimation,” Stat. Comput. 22, 2012, pp. 661-675.

About DeepWater Buoyancy, Inc.

DeepWater Buoyancy creates subsea buoyancy products for leading companies in the oceanographic, seismic, survey, military and offshore oil & gas markets.   Customers have relied on our products for over thirty-five years, from the ocean surface to depths exceeding six thousand meters.

Learn more at

About Maine Marine Composites

MMC specializes in motion prediction for ships and platforms, analyses of fluid/structural dynamics, and mooring system design and simulation. Our engineering staff has decades of experience with design and analysis of ships and offshore energy systems, and has successfully completed diverse and challenging projects for many of the most highly regarded offshore and ocean energy companies.

For more information, please contact Richard Akers at

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Mooring Matters: Sustained Measurements of Crucial Ocean Currents

Mooring Matters: Sustained Measurements of Crucial Ocean Currents

For the next installment in our series of technical articles, Dr. Peter Spain of Teledyne RD Instruments discusses the development of ADCP technology and the use of syntactic foam buoyancy in subsea moorings for sustained measurements of ocean currents.

Sustained Measurements of Crucial Ocean Currents

Teledyne RDI ADCPs and DeepWater Buoyancy Deliver a Go-To Combo

By Peter Spain Ph.D., Teledyne RD Instruments

Current Profiling

ADCPs are sonar systems that measure motion underwater. Using sound waves, they work like hand-held radars used by police to catch speeding motorists. To measure motion, ADCPs emit sound bursts along beams angled upward or downward.

Echoes are returned due to scattering off particles. Because zooplankton and suspended sediments are carried by the moving water, echoes scattered off them carry a change in pitch; this is the Doppler Effect. It tells how fast the current is moving and in what direction.

Sound waves propagate through the water column so echoes are returned and processed from many depths. The vertical range of this collection of measurements—called a profile of ocean current velocities—is greater for lower frequency sound waves.


Next to the eastern seaboard of continents stream the largest currents on the planet. They have been well-known to seafarers for centuries. Found around the globe, these major ocean currents are energetic, narrow and deep. They exist in all ocean basins, north and south of the equator: Gulf Stream, Kuroshio, and Brazil, Agulhas, East Australian Currents respectively.

These strong currents move much warm water poleward from low latitudes; thus, they redistribute heat for the earth’s climate system. On shorter time scales, they affect regional and local weather. These flows transfer organisms, nutrients, chemicals, debris, and pollutants – all affect life in and out of the sea and along coastlines. And strong currents affect routes selected by shipping.

Crucial ocean currents have been studied to measure their structure, transport, and fluxes—and, in recent times, their changes on seasonal and longer times scales. In ball-park numbers, these flows span 100 km, move faster than 100 cm/s, and carry 100 times the outflow of the world’s largest river.

Measuring these currents has been challenging. To capture their extent, measurements need to reach deep. To resolve changes over time, measurements need to be sustained. And to survive, persistent measurement methods need to withstand the energy of these powerful currents. For example, surface drifters, floats, and gliders are quickly swept away in strong upper-ocean currents.

Figure 1. Large ADCP Buoys with Teledyne RDI ADCPs off South Africa. Credit: SAEON Egagasini Node.

Programs making long-term measurements of important currents rely on resilient moorings. And for measuring strong currents in the upper ocean, these moorings carry ADCPs.

In this two-part report, we first review some background to moorings carrying Teledyne RDI ADCPs mounted in DeepWater Buoyancy buoys. Then we look at sustained measurements of crucial ocean currents in some less-familiar places.

Figure 2. William Richardson, pioneer of Buoy Group at WHOI. Credit: Nova Southeastern University. LINK


Almost 60 years ago at WHOI [1], William. S. Richardson launched the modern era of ocean-current metering. For studying deep-sea currents—notably, the Gulf Stream—he identified and invented two essential tools: a recording current meter and an unattended mooring. Richardson’s intent for the mooring was to suspend current meters at several depths. The meters would record long time-series of currents simultaneously. For studying currents across large areas, Richardson deployed several moorings.

Over the next two decades, the Buoy Group at WHOI engineered this reality. Their impressive results were hard won in the harsh and unforgiving environment of the deep sea. You can read more at this link: 50-years-of-the-whoi-buoy-group. For the UK story, see this PDF: UK_moorings.pdf.

Along the way, one key problem was mooring loss. A leading culprit was large drag force caused by strong currents. The adjacent graphic shows a section of the Gulf Stream in the upper 2000 m. Speeds are directed along-stream. Notice the extreme current speeds in the upper ocean and the large spatial gradients.

[1] Woods Hole Oceanographic Institution. See Richardson et al. report (WHOI Ref: 63-1)

Figure 3. Gulf Stream currents and thermal structure. Distance: km, Current speeds: cm/s. Credit: Halkin + Rossby, 1985. LINK

For recording currents accurately, the meters need to hold position in three dimensions. The mooring must therefore be taut. To this end, sizable buoyancy is added to the mooring line. Yet, unavoidably, these elements increase drag forces exerted by strong currents.

Besides sweeping away moorings, strong drag forces caused mooring lines to pull apart (part way up) or to blow-over. The latter mooring motion carried instruments and mooring elements in large vertical excursions: 300-500 m in a tall mooring. See Fig. 4. These excursions confounded interpretation of measurements. Worse, the mooring could sink when in-line buoyancy was crushed by high pressure at unplanned depths.

Figure 4. Large vertical excursions of a mooring line in the Gulf Stream. Time series of two pressure sensors mounted in-line and separated by 200 m.  Credit: Hogg, 1986.  LINK

Mooring Changes

By the mid 1980’s, the design of both moorings and current meters had evolved substantially. Fig. 5 shows typical designs. Highlighted are important changes in mooring components. Notice the change in where buoyancy is added.

One strategy to decrease mooring losses was reducing drag. Major currents have strong near-surface speeds. To avoid these, moorings that terminated subsurface were developed. Many were topped with large spherical buoys. They provide the same buoyancy for less drag than smaller options. To solve the crushing problem during severe blow-over, these large spheres were made of syntactic foam.

Figure 5. Deep-sea moorings—pre ADCPs: Changes from early-1960’s to mid-1980’s. Credit: Richardson et al., 1963 WHOI Ref 63-1;  Molinari, 1986 LINK

Beginning with Hogg (1986), scientists introduced methods for correcting measurements confounded by blow-over of a mooring. As well, methods for evaluating the design and dynamics of moorings were more available. See Mooring Design and Dynamics

Figure 6. Spherical syntactic foam buoys housing Teledyne RDI ADCPs. Credit: NOAA. LINK


From the mid 1980’s, ADCPs provided a new solution for measuring strong surface currents. A mechanical current meter must be immersed in the flow it measures. In contrast, ADCPs are sonar systems; they can measure current velocity remotely. They emit an acoustic signal and then process the informational content of returning echoes.

Scientists realized that ADCPs looking upward could be used to measure strong surface currents while deployed in slower waters below. This helped reduce drag on the mooring. To this end, ADCPs were mounted in the flotation buoy atop subsurface moorings. Pioneering this approach was Friedrich A. Schott at University of Miami.

DeepWater Buoyancy’s antecedent, Flotation Technologies, developed these buoys as standard kit for ADCPs. Using syntactic foam for flotation elements permitted custom designs. Notably, a cylindrical instrument well was inserted along the vertical axis of the large spheres. Housing ADCPs in this sheltered location reduced current drag on the mooring. Since the late 1980’s, ADCPs have been commonly mounted atop a subsurface mooring within a collar of syntactic foam.

To further decrease drag on the mooring, new designs evolved for syntactic flotation buoys. An elliptical-shaped float that is more hydrodynamic became a common component on many deep sea moorings.

Figure 7. DeepWater Buoyancy Elliptical ADCP Buoy.  LINK

For measuring very strong currents, such as tidal streams, a torpedo-shaped buoy is now state-of-the-art. This approach reduces drag and increases stability in pursuit of moored nirvana—low tilt and minimal vertical excursions.

Figure 8. DeepWater Buoyancy StableMoor® Buoy holding Teledyne RDI ADCP. Credit: Bedford Institute of Oceanography. LINK

Moored ADCP Arrays

A mix of methods is needed to clarify the long-term effects of global warming. Moored arrays in major ocean currents provide an essential ingredient. Insights have come from researchers using computer models and satellite-based observations. And drifters, gliders, and floats can provide snapshots. Yet there is no substitute for hanging around in these deep and energetic flows.

For scientists to see long-term trends and large-scale connections, moored arrays must collect sustained time series. And for collecting this information Teledyne RDI ADCPs mounted in DeepWater Buoyancy flotation provide a go-to combination.

.   .   .   .   .   .   .  


In Part 2 of this report, we review some compelling examples of moored ADCP arrays measuring crucial ocean currents around the globe.

About DeepWater Buoyancy, Inc.

DeepWater Buoyancy creates subsea buoyancy products for leading companies in the oceanographic, seismic, survey, military and offshore oil & gas markets.   Customers have relied on our products for over thirty-five years, from the ocean surface to depths exceeding six thousand meters.

Learn more at

About Teledyne RD Instruments

With well over 30,000 Doppler products delivered worldwide, Teledyne RD Instruments is the industry’s leading manufacturer of Acoustic Doppler Current Profilers (ADCPs) for current profiling and wave measurement applications; and Doppler Velocity Logs (DVLs) for precision underwater navigation applications. Teledyne RDI also supplies Citadel CTD sensors for a variety of oceanographic applications.

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