Simulation-based design (SBD) optimization assists the designer in the design process of complex engineering systems. In this context, real-world problems are affected by different sources of uncertainties (operational, environmental, geometrical or numerical) and require reliability-based robust design optimization (RBRDO) formulations to identify the optimal solution. RBRDO is usually computationally very costly (especially if high-fidelity simulations are used) and may be achieved by means of metamodels, with efficient optimization algorithms. Herein, a RBRDO for ship design is solved, for real ocean environment including stochastic sea state and speed.
Multi-objective extensions of the deterministic particle swarm algorithm for RBRDO in ship design: a parametric study
Andrea Serani;Matteo Diez;
2014
Abstract
Simulation-based design (SBD) optimization assists the designer in the design process of complex engineering systems. In this context, real-world problems are affected by different sources of uncertainties (operational, environmental, geometrical or numerical) and require reliability-based robust design optimization (RBRDO) formulations to identify the optimal solution. RBRDO is usually computationally very costly (especially if high-fidelity simulations are used) and may be achieved by means of metamodels, with efficient optimization algorithms. Herein, a RBRDO for ship design is solved, for real ocean environment including stochastic sea state and speed.File | Dimensione | Formato | |
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Descrizione: Multi-objective extensions of the deterministic particle swarm algorithm for RBRDO in ship design: a parametric study
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