Design and Optimization of Multipoint Sampler for Seafloor Sediment Carried by a Deep-Sea Landing Vehicle

The present study proposes a low-energy consumption multipoint sampler carried by deep-sea landing vehicle (DSLV) to meet the requirements of time series sampling in local areas and location wide areas, an optimization method structure based on least-squares support-vector machine (LSSVM) surrogate model multi-objective particle swarm (MOPSO) algorithm. First, overall core components, such as sampler’s structure, were designed. variables cone angle, tube inner diameter, hole length, which determined considering force with penetrates seafloor sediment. Then, process was simulated finite element method-smoothed hydrodynamics (FEM-SPH) method, while accurate LSSVM required for volume established. Finally, MOPSO algorithm used parameters structure. optimal that can provide theoretical support design effectively reduces energy improves efficiency 25.89% lower 34.81% higher than original model.