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22. A copula‐based method of risk prediction for autonomous underwater gliders in dynamic environments.

Author

Chen, Xi, Bose, Neil, Brito, Mario, Khan, Faisal, and Zou, Ting

Subjects
UNDERWATER gliders, BAYESIAN analysis, COPULA functions, ENVIRONMENTAL research, DECISION making
Abstract

Autonomous underwater gliders (AUGs) are effective platforms for oceanic research and environmental monitoring. However, complex underwater environments with uncertainties could pose the risk of vehicle loss during their missions. It is therefore essential to conduct risk prediction to assist decision making for safer operations. The main limitation of current studies for AUGs is the lack of a tailored method for risk analysis considering both dynamic environments and potential functional failures of the vehicle. Hence, this study proposed a copula‐based approach for evaluating the risk of AUG loss in dynamic underwater environments. The developed copula Bayesian network (CBN) integrated copula functions into a traditional Bayesian belief network (BBN), aiming to handle nonlinear dependencies among environmental variables and inherent technical failures. Specifically, potential risk factors with causal effects were captured using the BBN. A Gaussian copula was then employed to measure correlated dependencies among identified risk factors. Furthermore, the dependence analysis and CBN inference were performed to assess the risk level of vehicle loss given various environmental observations. The effectiveness of the proposed method was demonstrated in a case study, which considered deploying a Slocum G1 Glider in a real water region. Risk mitigation measures were provided based on key findings. This study potentially contributes a tailored tool of risk prediction for AUGs in dynamic environments, which can enhance the safety performance of AUGs and assist in risk mitigation for decision makers. [ABSTRACT FROM AUTHOR]

Published
2024
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35. ASSESSMENT OF DETECTION CAPABILITY OF OIL SENSORS FOR USE IN ADAPTIVE SAMPLING CONTROL OF AN AUTONOMOUS UNDERWATER VEHICLE.

Author

Jimin Hwang, Bose, Neil, and Robinson, Brian

Subjects
REMOTE submersibles, AUTONOMOUS underwater vehicles, ADAPTIVE control systems, CHEMICAL detectors, DETECTORS
Abstract

This paper presents experiments conducted to test and calibrate two submersible oil detecting sensors: a UviLux and a laser-based hydrocarbon sniffer. The tests were conducted in the seawater tank at the Bedford Institute of Oceanography, in Dartmouth, N.S., Canada. The results of the tests indicate that the sensors have reliable sensing capacity. The calibrating equation for the UviLux sensor was derived by comparing the sensor readings and the chemical analysis results. The hydrocarbons released from natural seeps in Scott Inlet are known to be in a mixed phase, consisting of a combination of liquid oil and gaseous hydrocarbons, and the experimental results indicate the need for a robust decision algorithm to deal with conflicting measurements obtained from the UviLux and CH4 (methane) sniffer. The collected data will be used to develop a sensor-based decision-making algorithm using Bayes filter. Ultimately, the goal is to enable an adaptive mission for an autonomous underwater vehicle (AUV) in Baffin Bay in September 2023, which will rely solely on real-time data sensed during the mission and adapt to changing conditions by continuously collecting and analyzing in-situ data. [ABSTRACT FROM AUTHOR]

Published
2023

46. Human error in autonomous underwater autonomous vehicle deployment: A system dynamics approach

Author

Loh, Tzu Yang, Brito, Mario, Bose, Neil, Xu, Jingjing, and Tenekedjiev, Kiril

Abstract

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.

Published
2020

47. Particle swarm optimization algorithms with selective differential evolution for AUV path planning

Author

Lim, Hui Sheng, Fan, Shuangshuang, Chin, Christopher K.H., Chai, Shuhong, and Bose, Neil

Subjects
Particle swarm optimization, Autonomous underwater vehicle, Monte Carlo methods, Hybridization, Path planning
Abstract

Particle swarm optimization (PSO)-based algorithms are suitable for path planning of the Autonomous Underwater Vehicle (AUV) due to their high computational efficiency. However, such algorithms may produce sub-optimal paths or require higher computational load to produce an optimal path. This paper proposed a new approach that improves the ability of PSO-based algorithms to search for the optimal path while maintaining a low computational requirement. By hybridizing with differential evolution (DE), the proposed algorithms carry out the DE operator selectively to improve the search ability. The algorithms were applied in an offline AUV path planner to generate a near-optimal path that safely guides the AUV through an environment with a priori known obstacles and time-invariant non-uniform currents. The algorithm performances were benchmarked against other algorithms in an offline path planner because if the proposed algorithms can provide better computational efficiency to demonstrate the minimum capability of a path planner, then they will outperform the tested algorithms in a realistic scenario. Through Monte Carlo simulations and Kruskal-Wallis test, SDEAPSO (selective DE-hybridized PSO with adaptive factor) and SDEQPSO (selective DE-hybridized Quantum-behaved PSO) were found to be capable of generating feasible AUV path with higher efficiency than other algorithms tested, as indicated by their lower computational requirement and excellent path quality.

Published
2020

48. Ice loads acting on a model podded propeller blade (OMAE2005-67416)

Author

Wang, Jungyong, Akinturk, Ayhan, Jones, Stephen J., Bose, Neil, Kim, Moon-Chan, and Chun, Ho-Hwan

Subjects
Ice -- Mechanical properties, Strains and stresses -- Analysis, Stress relaxation (Materials) -- Analysis, Stress relieving (Materials) -- Analysis, Science and technology
Abstract

With the increase in popularity of podded propulsors and arctic navigation, understanding the interaction between a podded propulsor and ice has become more important. Propeller-ice interaction itself is a complicated process with a high level of uncertainty resulting from the uncertainties associated with the properties of the ice and with the propeller-ice interaction conditions. Model tests provide relatively well-controlled ice properties and interaction conditions to reduce the uncertainties. In order to improve the understanding of this interaction and to develop numerical models of it, a model podded propulsor was used in 'Puller' mode, and ice loads were measured on its instrumented blade and propeller shaft. The results of the experiments conducted to simulate the interactions (milling) of the instrumented blade with ice in different operating conditions are reported in this paper. Loads measured during the milling consist of ice milling loads, 'inseparable' hydrodynamic loads, and 'separable' hydrodynamic loads. The sample results presented here include ice milling and inseparable hydrodynamic loads for various advance coefficients and depths of cut (amount of blade penetration into ice). Some results are compared with existing ice load models. [DOI: 10.111511.2426993] Keywords: ice class, propeller, propeller-ice interaction, model test, ice tank

Published
2007

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