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Homing behavior for autonomous underwater vehicles (AUVs) is vital for autonomous docking and indispensable for recovery of vehicles in logistically difficult or hazardous conditions. Homing to a single acoustic beacon is a low-logistics solution to this engineering challenge. A homing application has been developed in C++ that applies a multilateration-based localization algorithm to estimate transponder location for homing. Mission oriented operating suite interval programming (MOOS-IvP) was implemented as a backseat driver on a Teledyne Gavia AUV to enhance the AUV with adaptive maneuvering capabilities; thus, enabling mission waypoints to be dynamically updated by the homing application ( pHomeToBeacon ) through the MOOS database and a developed iGavia crewmember. To demonstrate MOOS-IvP-GAVIA and homing capabilities using this first-principles approach to localization, field trials were undertaken in Kopavogur, Iceland, in June 2015 and proved consistent homing to a single beacon within 15 m accuracy. These trials were an industry-first of deploying a user-developed application on MOOS-IvP-GAVIA and of having a Gavia enhanced with adaptive maneuvering capabilities for homing. This new capability enables Gavia AUV to be used as a platform for future developer-led autonomy and applications. Ultimately, pHomeToBeacon will enable any AUV enhanced with MOOS-IvP to use acoustics to home to a surface vessel (stationary or underway) in preparation for autonomous subsea docking and recovery.

When a subsea pipeline is laid on an uneven seabed, certain sections may have an initial elevation with respect to the far-field seabed, eo, and thus potentially affecting the on-bottom stability of the pipeline. This paper focuses on quantifying the effects of the upstream dimensionless seabed shear stress, θ∞, and Reynolds number, Re, on: (1) the maximum dimensionless seabed shear stress beneath the pipe, θmax, to be compared to the critical shear stress in order to determine whether scour would occur and progress towards an equilibrium state; and, (2) the dimensionless equilibrium scour depth beneath the pipe, Seq/D. Using a 2-D Reynolds averaged Navier-Stokes (RANS) approach along with the k-ω Shear Stress Transport (SST) turbulence model, a parametric study involving 243 computational fluid dynamics (CFD) simulations was conducted. The simulation results were used to develop a closed-form equation for the prediction of θmax. Subsequently, experimental measurements of Seq/D have been compiled from published literature, to develop a new closed-form equation for the prediction of Seq/D with a high correlation to the experimental data. In summary, we present two closed-form equations for the prediction of θmax and Seq/D for pipelines with an initial eo/D, which are applicable for both clear-water and live-bed conditions. The effects of θ∞ and Re have been included, albeit Re having a small influence as compared to the other parameters.

This paper presents a teach-and-repeat path-following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path, stored as a topological map. The AUV can then renavigate along this path, either to return to the start location or to repeat the route. Utilizing unique assumptions about the sonar image-generation process, this system exhibits robust image-matching capabilities, providing observations to a discrete Bayesian filter that maintains an estimate of progress along the path. Image-matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and performed multiple path completions over both a 1 and 5 km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path-following performance was as desired, with the AUV maintaining close offset to the path.

This article presents the development of a novel artificial potential field technique for a haptic controller of an underwater remotely operated vehicle to assist the pilot to avoid obstacles. The artificial potential field technique is used to replicate potential risks presented by underwater obstacles in the vicinity of the remotely operated vehicle. A risk avoidance vector is calculated based on the artificial potential field then transmitted to a haptic joystick to generate the tactile feedback, which enables the remotely operated vehicle pilot to be alerted to potential dangers due to surrounding obstacles and prompt the pilot through the joystick to avoid the dangers and safely navigate the vehicle. The novel artificial potential field technique can deal with both stationary and moving obstacles as it is combined with an obstacle motion detection algorithm based on fuzzy C-means and Kalman filter algorithms. These algorithms are applied to process raw data from the scanning sensor to identify the relative positions and velocities between the remotely operated vehicle and the obstacles, which are employed within the artificial potential field calculations. To validate the proposed technique, the haptic joystick and the novel artificial potential field formula were applied to control a simulated remotely operated vehicle within a virtual reality environment.

Autonomous underwater vehicles (AUVs) use secondary velocity over ground measurements to aid the Inertial Navigation System (INS) to avoid unbounded drift in the point-to-point navigation solution. When operating in deep open ocean (i.e., in blue water—beyond the frequency-specific instrument range), the velocity measurements are either based on water column velocities or completely unavailable. In such scenarios, the velocity-relative-to-water measurements from an acoustic Doppler current profiler (ADCP) are often used for INS aiding. ADCPs have a blanking distance (typically ranging between 0.5 and 5 m) in proximity to the device in which the flow velocity data are undetectable. Hence, water velocities used to aid the INS solution can be significantly different from that near the vehicle and are subjected to significant noise. Previously, the authors introduced a nonacoustic method to calculate the water velocity components of a turbulent water column within the ADCP dead zone using the AUV motion response (referred to as the WVAM method). The current study analyzes the feasibility of incorporating the WVAM method within the INS by investigating the accuracy of it at different turbulence levels of the water column. Findings of this work demonstrate that the threshold limits of the method can be improved in the nonlinear ranges (i.e., at low and high levels of energy); however, by estimating a more accurate representation of vehicle hydrodynamic coefficients, this method has proven robust in a range of tidally induced flow conditions. The WVAM method, in its current state, offers significant potential to make a key contribution to blue water navigation when integrated within the vehicle's INS.

This paper presents the development of a heading angle observer for Underwater Remotely Operated Vehicles (ROVs) during dynamic conditions in the presence of roll/pitch oscillation and acceleration disturbances. Unlike previous algorithms, which focused on deep water working environments where the external accelerations and oscillation were rather small, this paper proposes a heading observer that deals with the effects of near surface working conditions on ROVs, such as waves or unexpected water currents. These effects cause significant roll and pitch disturbances as well as high-acceleration drift motions, which affect the measurements from the incorporated sensor system. To overcome this situation, a novel heading observer is proposed, consisting of two Kalman filter (KF) steps: one for acceleration elimination and one for roll and pitch oscillation compensation. The data from the inertial measurement unit and the magnetometer are combined to estimate and compensate for external accelerations and roll/pitch disturbances by adjusting the covariance values. Free running tests, based on a physical ROV model, were conducted under various working environments to verify the performance of the proposed observer. The comparison with previous algorithms was also made to verify the effectiveness of the proposed algorithm.

The hydrodynamic interaction between an Autonomous Underwater Vehicle (AUV) manoeuvring in close proximity to a larger underwater vehicle can cause rapid changes in the motion of the AUV. This interaction can lead to mission failure and possible vehicle collision. Being self-piloted and comparatively small, an AUV is more susceptible to these interaction effects than the larger body. In an aim to predict the manoeuvring performance of an AUV under the effects of the interaction, the Australian Maritime College (AMC) has conducted a series of computer simulations and captive model experiments. A numerical model was developed to simulate pure sway motion of an AUV at different lateral and longitudinal positions relative to a larger underwater vehicle using Computational Fluid Dynamics (CFDs). The variables investigated include the surge force, sway force and the yaw moment coefficients acting on the AUV due to interaction effects, which were in turn validated against experimental results. A simplified method is presented to obtain the hydrodynamic coefficients of an AUV when operating close to a larger underwater body by transforming the single body hydrodynamic coefficients of the AUV using the steady-state interaction forces. This method is considerably less time consuming than traditional methods. Furthermore, the inverse of this method (i.e. to obtain the steady state interaction force) is also presented to obtain the steady-state interaction force at multiple lateral separations efficiently. Both the CFD model and the simplified methods have been validated against the experimental data and are capable of providing adequate interaction predictions. Such methods are critical for accurate prediction of vehicle performance under varying conditions present in real life.

Below the temperature of maximum density (TMD) in freshwater lakes, heating at the lateral margins produces gravity currents along the bottom slope, akin to katabatic winds in the atmosphere and currents on continental shelves. We describe axisymmetric basin-scale circulation driven by heat flux at the shorelines in polar Lake Kilpisjarvi. A dense underflow originating near the shore converges toward the lake center, where it produces warm upwelling and return flow across the bulk of lake water column. The return flow, being subject to Coriolis force, creates a lake-wide anticyclonic gyre with velocities of 2–4 cm s-1. While warm underflows are common on ice-covered lakes, the key finding is the basin-scale anticyclonic gyre with warm upwelling in the core. This circulation mechanism provides a key to understanding transport processes in (semi) enclosed basins subject to negative buoyancy flux due to heating (or cooling at temperatures above TMD) at their lateral boundaries.

Observations of a cyclonic gyre in an ice-covered, midsize (, 5 km2), temperate lake are presented. Horizontal and vertical measurements of temperature and electrical conductivity measurements were collected using a conductivity–temperature–depth logger mounted on an autonomous underwater vehicle and additional instrumentation. These measurements revealed a cylindrical density anomaly with a radius of , 110 m extending from the surface to , 14 m depth. The observed radius is smaller than the internal Rossby radius of deformation (, 200 m), which suggests a cyclogeostrophic balance between centripetal, Coriolis, and pressure forces. The maximum azimuthal velocity, calculated assuming this balance, was , 2.1 cm s21 at 6–8 m depth. The Rossby number associated with this velocity was 1.7; this is consistent with the cyclogeostrophic assumption (i.e., Rossby number . 1) and nearly twice that of similar under-ice eddies in the Arctic Ocean. The estimated Ekman spindown timescale is 1.5–15 d, but despite this, the gyre appeared to be relatively unchanged over 6 d of field observations. This persistence implies the gyre was forced over the course of the field study; however, the source of the forcing is unknown. Horizontal temperature transects at and below the bottom of the gyre revealed coherent temperature fluctuations suggestive of vertical transport associated with the gyre.

Since the beginning of space exploration, methods and protocols of exploration have been developed using space analogs on Earth to reduce research costs, develop safe deployment/retrieval protocols, and ready astronauts for hostile environments in less threatening settings. Space analogs are required as much as ever today as astronauts and scientists develop new tools and techniques for exploration, while working to address evolving mission objectives from low-earth orbit to deep-space exploration. This study examines coordinated human and robotic exploration at the Aquarius Underwater Habitat off of the coast of Key Largo, Florida, in support of the NEEMO 15 (NASA Extreme Environment Mission Operations) program. The exploration scheme presented in this work fuses (1) robotic precursor missions as a means of remote sensing data collection; (2) crowdsourcing to process immense amounts of data to identify key targets of interest that might be missed in the tight cycle of mission operations; and (3) human exploration to examine locations directly up close and collect physical samples that require involved sampling techniques. Autonomous underwater vehicles (AUVs) and single-person submersibles, called DeepWorkers™, were used as underwater analogs of robotic systems currently being used and human-operated vehicles (HOVs) proposed for use on a Near Earth Asteroid (NEA), the Moon, or Mars. In addition to operational lessons learned for space exploration that are directly applicable to ocean exploration, ocean floor mapping provides new levels of detail of benthic habitat critical for coral reef monitoring and management. Opportunistic (onsite adaptive) data sampling also took place by placing self-recording instrumentation onto each of the DeepWorkers, increasing the collection of scientific information during the submersible missions and contributing to mission planning for optimal and efficient use of expensive assets.

The establishment, spread, and impact of the invasive bivalve Corbicula fluminea (C. fluminea), in Lake Tahoe threatens native species distribution in the lake and, potentially, has long-term implications for water clarity. In 2009, UBC-Gavia, an Autonomous Underwater Vehicle (AUV), was used as a platform to collect georeferenced imagery of the benthic regions of Lake Tahoe to determine the lake-wide distribution of C. fluminea. Images were collected in water depths less than 10 m at an approximately constant height above the bottom of 2 m. Images were processed using a semi-automated procedure to determine the ratio of the lakebed covered by exposed C. fluminea shells. A visual review was conducted on a subset of the images to determine presence of filamentous algae that has been observed in association with C. fluminea. Nearly 100km of shoreline was covered over a 7-d period, and C. fluminea presence was reconfirmed in 4 regions and additional 10 regions identified. In regions where the presence of C. fluminea was confirmed, C. fluminea depth distribution was validated by comparing image detection counts and results from a benthic sediment grab sample survey. Three regions around the lake were identified to have filamentous green algae or charophyte species. It was impossible to identify species of the known filamentous algal taxa (Cladophora glomerata, Spirogyra spp., and Zygnema spp.). The collected imagery provides a synoptic view on species distribution within the lake that can be used for efficient monitoring of invasive species in freshwater and saltwater bodies. © 2012, by the American Society of Limnology and Oceanography, Inc.

Detailed sea ice draft mapping was recently accomplished in the Beaufort Sea, north of Alaska, in 2007 and in the Lincoln Sea, north of Canada's Ellesmere Island, in 2008 using a small (3 m long, 20 cm diameter), man-handleable Gavia AUV incorporating an inertial navigation system and a 500 kHz phase-measuring swath sonar. The topography of specific ice features was mapped across 80 m-wide swaths by performing repeated runs in the vicinity of access holes drilled in the sea ice. The paper discusses the technical and operational developments undertaken to successfully accomplish the missions, including test deployments in a frozen Canadian lake prior to each Arctic deployment. Example data are shown and accuracy issues discussed. (C) 2008 Elsevier B.V. All rights reserved.

Struvite, a crystalline structure comprised of ions of magnesium (Mg2+), ammonium (NH4-N) and phosphate (PO4-P), is commonly encountered in wastewater treatmentplants (WWTPs) through struvite encrustation. The gradual growth of this crystal can lead to h igh maintenance costs, due to downtime and replacement parts. Several struvite recovery unit processes have been developed in an effort to reduce this problem, through the preferential removal of the constituent ions (Mg2+, NH4-N, and PO4-P) upstream of problem areas (e.g. anaerobic digester supernatants). One of the key elements of process control for these systems is accurately determining the constituent concentrations. Although a wide variety of measurement techniques exist for both NH4-N and PO4-P, the presence of PO4-P interferes with the measurement of Mg2+. Ion selective electrodes (ISEs) were tested on wastewater samples to determine Mg2+ concentrations. It was found that the two ISE tested produced unreliable results, as they both proved non-specific t o Mg2+. A modification, using polyaluminum chloride (PAC), was developed to remove the interference of phosphates from the colorimetric technique. It was found to produce reliable results within 10% of those results predicted by atomic absorption. The resulting technique averaged about 10 minutes per sample and could be conducted inexpensively at a laboratory facility at WWTPs.

Struvite, a crystalline structure comprised of ions of magnesium Mg +2 , ammonium NH4 -N , and phosphate PO4 -P ,i s commonly encountered in wastewater treatment plants WWTPs through struvite encrustation. The gradual accumulation of this crystal in pipes and fittings leads to high costs due to downtime and replacement of parts. Technologies that are used to reduce this problem are ideally located in biological nutrient removal plants downstream of anaerobic digesters, as high levels of NH4 - N and PO4 - P typically characterize anaerobic digester supernatants. In 2003-2004, two technical-scale, struvite recovery studies were conducted on-site at the City of Penticton, B.C., Canada and the City of Richmond, B.C., Canada using a novel technology developed by the environmental engineering group at the University of British Columbia. The results of these studies showed an average reduction of 80% in phosphate and a dense, spherical product, 5-10 times larger than any commercially available struvite to date. Overall, the recovery of struvite has enormous commercial potential, which results in WWTP becoming more sustainable, concurrently reducing problems typically associated with their operation.

In advanced wastewater treatment plants (AWWTP), the recovery of phosphorus (P) has become a recent focus of the wastewater engineering industry. The potential economic savings behind improved sludge management and the control of struvite encrustation in AWWTP are two of the primary driving forces behind this. Process control of phosphorus (struvite) recovery systems has only been partially successful because: (1) key control variables have yet to be identified and (2) there is no adequate performance evaluation model that is applicable to struvite recovery technologies. In process control, two different types of modeling are most commonly seen: mechanistic and “black-box” style models. In recent years, varying models have been developed to try to predict the formation of struvite in both sludge digestion process lines and P-recovery technologies designed for struvite removal. All of these are strictly mechanistic models, based on either the chemical equilibrium of the system or the associated kinetic parameters, with varying degrees of complexity. Artificial neural networks (ANN), as a type of black-box modeling, have seen limited application in wastewater treatment with regards to phosphate recovery. The analysis of several historical daily operational databases evaluated the predictive ability of two mechanistic and one ANN models. It was determined that the newly developed ANN model was not site specific and had the highest predictive ability of the three. This would be beneficial for the development of an automated control system for struvite removal package treatment processes.

Layers of sediment that are deposited on the floor of Lake Ohau, New Zealand, offer a means to reconstruct past climate conditions in the Southern Hemisphere at subdecadal and annual resolution. A robust understanding of the modern physical processes that control the influx and dispersal of sediment in the lake is required to reconstruct climate from these sedimentary archives. In this study, water temperature and velocity measurements collected during 2012–13 were analysed to determine the primary physical processes that influence sediment transport in the lake. Sediment input from river inflow occurs throughout the year but exhibits strong seasonal variation. Large inflow events (Q>500m3s–1) that follow strong summer rainstorms trigger high-concentration turbidity currents, which are the main agents for sediment delivery and deposition. During winter, smaller turbidity currents also occur after rain events and contribute to annual sediment accumulation. In addition, large internal waves were observed during the summer and may influence sedimentation. In conclusion, several processes including river inflow, internal waves and convectively driven flows control sediment deposition and accumulation in the Lake Ohau system. We utilise these observations to establish a conceptual model to explain the observed infill stratigraphy in Lake Ohau and guide interpretation of the longer sedimentary record.