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.
2014
Istituto di iNgegneria del Mare - INM (ex INSEAN)
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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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/280841
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