Are random coefficients needed in particle swarm optimization for simulation-based ship design?

Simulation-based design optimization (SBDO) methods integrate computer simu- lations, design modification tools, and optimization algorithms. In hydrodynamic applications, often objective functions are computationally expensive and likely noisy, their derivatives are not directly provided, and the existence of local minima cannot be excluded a priori, which motivates the use of derivative-free global optimization algorithms. This type of algorithms (such as Particle Swarm Optimization, PSO) usually follow a stochastic formulation, requiring computationally expensive numerical experiments in order to provide statistically significant re- sults. The objective of the present work is to investigate the effects of using (versus suppressing) random coefficients in PSO for ship hydrodynamics SBDO. A comparison is shown of 1,000 random PSO to deterministic PSO (DPSO) using 12 well-known scalable test problems, with dimensionality ranging from two to fifty. A total of 588 test functions is considered and more than 500,000 optimization runs are performed and evaluated. The results are discussed based on the probability of success of random PSO versus DPSO. Finally, a comparison of random PSO to DPSO is shown for the hull-form optimization of the DTMB 5415 model. In summary, test functions show the robustness of DPSO, which outperforms random PSO with odds of 30/1 for low-dimensional problems (indicatively N ≤ 30) and 5/1 for high-dimensional problems (N > 30). The hull-form SBDO (N = 11) shows how DPSO outperforms PSO with odds of 20/1. The use of DPSO in the SBDO context is therefore advised, especially if computationally expensive analyses are involved in the optimization

Towards the high-fidelity multidisciplinary design optimization of a 3d composite material hydrofoil

The development of a multidisciplinary design optimization (MDO) architecture for high-fidelity fluid-structure interaction (FSI) problems is presented with preliminary application to a NACA 0009 3D hydrofoil in metal and carbon-fiber reinforced plastic materials. The MDO methodology and FSI benchmark solution are presented and discussed. The computational cost of the MDO is reduced by performing a design space dimensionality reduction beforehand and integrating into the architecture a variable level of coupling between disciplines, a surrogate model, and an adaptive sampling technique. The optimization is performed using a heuristic global derivative-free algorithm. The MDO method is demonstrated by application to an analytical test problem. Current stage of research includes preliminary test problem optimization, validation of the hydrofoil FSI against experimental data, and design space assessment and dimensionality reduction for the hydrofoil model

Design-space assessment and dimensionality reduction: An off-line method for shape reparameterization in simulation-based optimization

A method based on the Karhunen–Loève expansion (KLE) is formulated for the assessment of arbitrary design spaces in shape optimization, assessing the shape modification variability and providing the definition of a reduced-dimensionality global model of the shape modification vector. The method is based on the concept of geometric variance and does not require design-performance analyses. Specifically, the KLE is applied to the continuous shape modification vector, requiring the solution of a Fredholm integral equation of the second kind. Once the equation is discretized, the problem reduces to the principal component analysis (PCA) of discrete geometrical data. The objective of the present work is to demonstrate how this method can be used to (a) assess different design spaces and shape parameterization methods before optimization is performed and without the need of running simulations for the performance prediction, and (b) reduce the dimensionality of the design space, providing a shape reparameterization using KLE/PCA eigenvalues and eigenmodes. A demonstration for the hull-form optimization of the DTMB 5415 model in calm water is shown, where three design spaces are investigated, namely provided by free-form deformation, radial basis functions, and global modification functions

Optimized DBD plasma actuator system for the suppression of flow separation over a NACA0012 profile

We address the problem of controlling the unsteady flow separation over an aerofoil, using plasma actuators. Despite the complexity of the dynamics of interest, we show how the problem of controlling flow separation can be formulated as a simple output regulation problem, so that a simple control strategy may be used. Different configurations are tested, in order to identify optimal positions of the actuator/sensor pairs along the aerofoil, as well as the corresponding references for the available real-time velocity measurements. A multi- objective deterministic particle swarm optimization algorithm is applied to identify the set of non dominated configurations considering as objectives the time-averaged input signal and the drag- to-lift ratio. Accurate numerical simulations of incompressible flows around a NACA0012 profile at Reynolds Re = 20, 000 and angle of attack 15◦ illustrate the effectiveness of the proposed approach, in the presence of complex nonlinear dynamics, which are neglected in the control design. Fast flow reattachment is achieved, along with both stabilisation and increase/reduction of the lift/drag, respectively. A major advantage of the presented method is that the chosen controlled outputs can be easily measured in realistic applications

Multi-objective hull-form optimization of a swath configuration via design-space dimensionality reduction, multi-fidelity metamodels, and swarm intelligence

A multi-objective simulation-based design optimization (SBDO) is presented for the resistance reduction and displacement increase of a small water-plane area twin hull (SWATH). The geometry is realized as a parametric model with the CAESESQR software, using 27 design parameters. Sobol sampling is used to realize design variations of the original geometry and provide data to the design-space dimensionality reduction method by Karhunen-Lo`eve expan- sion. The hydrodynamic performance is evaluated with the potential flow code WARP, which is used to train a multi-fidelity metamodel through an adaptive sampling procedure based on prediction uncertainty. Two fidelity levels are used varying the computational grid. Finally, the SWATH is optimized by a multi-objective deterministic version of the particle swarm optimiza- tion algorithm. The current SBDO procedure allows for the reduction of the design parameters from 27 to 4, resolving more than the 95% of the original geometric variability. The metamodel is trained by 117 coarse-grid and 27 fine-grid simulations. Finally, significant improvements are identified by the multi-objective algorithm, for both the total resistance and the displacement

A kinematic coupling mechanism with binary electromagnetic actuators for high-precision positioning

Rather than working in a continuous range of motion, binary actuators can only maintain two positions. This lack of flexibility is compensated by high accuracy, repeatability, and reliability. These features make binary-actuated mechanisms appealing for space exploration systems, repetitive pick & place tasks, and biomedical applications. This paper introduces a novel class of binary-actuated mechanisms driven by electromagnets. As these systems rely on the extreme positions of their binary actuators for positioning, the proposed design aims to increase repeatability with a kinematic coupling. By inverting the polarity of its electromagnets, the configuration of the mechanism can be changed from a discrete state to another one. Thus, when the actuation is known, the pose of the system can be accurately computed without any external feedback. A sensorless design simplifies both the control and the architecture of the proposed design, as well as reducing manufacturing and maintenance costs. The conceptual design of the proposed class of mechanisms is described through two examples with three and four configurations, and alternative designs with higher mobility are discussed. Then, a kinematic synthesis procedure is discussed. Finally, the advantages of asymmetric and irregular designs are outlined. Overall, the proposed mechanisms are suited to a wide range of applications that require a rapid, accurate and interchangeable positioning of sensors and tools