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The process of CO 2 capture, transportation, enhanced oil recovery (EOR) and storage is one of the best ways for CO 2 emission reduction, which is also named as Carbon Capture, Utilization and Storage (CCUS). It has been noted that CO 2 transportation cost is an important component of the total investment of CCUS. In this paper, a novel stepwise and piecewise optimization is proposed for CO 2 transportation design, which can compute the minimum transportation pipeline levelized cost under the effect of temperature variation. To develop the proposed approach, several models are referred to lay a foundation for the optimization design. The proposed optimal algorithm is validated by using numerical studies, which show the approach can reduce the levelized cost and improve the optimization performance in comparison with the existing methods.

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Autonomous underwater vehicle (AUV) is one of the most important exploration tools in the ocean underwater environment, whose movement is realized by the underwater thrusters, however, the thruster fault happens frequently in engineering practice. Ocean currents perturbations could produce noise for thruster fault diagnosis, in order to solve the thruster fault diagnostics, a possibilistic fuzzy C-means (PFCM) algorithm is proposed to realize the fault classification in this paper. On the basis of the results of fault diagnostics, a fuzzy control strategy is proposed to solve the fault tolerant control for AUV. Considering the uncertainty of ocean currents, it proposes a min-max robust optimization problem to optimize the fuzzy controller, which is solved by a cooperative particle swarm optimization (CPSO) algorithm. Simulation and underwater experiments are used to verify the accuracy and feasibility of the proposed method of thruster fault diagnostics and fault tolerant control.

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