Wave resistance minimisation in practical ship design

A practical and efficient system is described for ship hull form optimisation and its application for minimising wave resistance. Parametric hull form deformations are defined in a CAD system, specific for the case considered and related with flow aspects to be addressed. Surrogate-based global optimisation is applied for multi-objective problems, such as optimisation for a ship’s operational profile

Multi-objective surrogate based hull-form optimization using high-fidelity rans computations

RANS-based optimization procedures for ship design become increasingly complex and require the development of more efficient optimization techniques. The four phases of the design procedure are: shape parameterization, global sensitivity analysis, multi-objective optimization and design review. The dimensions of the design space can be mitigated by a smart choice for the shape parameterization and by screening and ranking the design variables in the global sensitivity phase. Subsequently, Surrogate Based Global Optimization (SBGO) is used to reduce the cost of the multi-objective optimization phase. For a practical application it is shown that the computational time reduces from two weeks to only a day when using SBGO instead of applying a Multi-Objective Genetic Algorithm (MOGA) directly to the solver. The design review phase is then used to verify and further develop the optimal design. Here, we focus on automatic ship design techniques which comprises the first three steps of the design procedure. Accelerating the ship design process is subject of ongoing research at the Maritime Research Institute Netherlands, making it useful for practical applications with turnaround times of only a few weeks

A multi-model incremental adaptive strategy to accelerate partitioned fluid-structure algorithms using space-mapping

High fidelity analysis of fluid-structure interaction systems is often too timeconsuming when a large number of model evaluations are required. The choice for a solution procedure depends often on the efficiency of the method and the possibility of reusing existing field solvers. Aggressive Space-Mapping, a technique originally developed for multi-fidelity optimization, is applied to accelerate the partitioned solution procedure of a high fidelity fluid-structure interaction model. The method supports software modularity. Aggressive Space-Mapping (ASM) is applied to an academic testcase and the results are compared with the corresponding Incremental Quasi-Newton (IQN) method. An efficiency metric is defined to facilitate the comparison. The ASM method is found to be more efficient than the corresponding IQN method for the testcases considered. The efficiency of space-mapping increases with increasing fluid-to-structure mass ratio, indicating that the method is especially useful for strongly coupled problems

Multi-objective hull-form optimization using kriging on noisy computer experiments

Meta-modelling is a key technique for efficient multi-objective optimization in ship design projects using CFD. However, objective functions computed with CFD are not deterministic functions but contain random scatter about a smooth trend. Kriging is a meta-model technique that is well suited for numerical experiments with deterministic errors that can be perceived as random scatter due to varying input parameters. Sim- ple Kriging, universal kriging and polynomial regression are used to obtain approximate Pareto-fronts from the hull-form optimization of a chemical tanker including free-surface effects. Cross-validation is used to assess the quality of the meta-models and the meta- model approximations of the Pareto-fronts are verified. It is found that cross-validation can be used to select the best meta-model but should not be used to estimate the true error of the approximation in case the design of experiment is too coarse. The approach is used in practice in order to accelerate the ship design process and to obtain more efficient ships with less vibration hindrance