Matteo Diez

Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems

Graphical abstractDisplay Omitted HighlightsParametric study of deterministic PSO setting under limited computational resources.Comparison of synchronous and asynchronous implementations.Identification of most significant parameter based on more than 40k optimizations.Identification of most promising and robust setup for simulation-based problems.Hydrodynamic hull-form optimization of a high speed catamaran. Deterministic optimization algorithms are very attractive when the objective function is computationally expensive and therefore the statistical analysis of the optimization outcomes becomes too expensive. Among deterministic methods, deterministic particle swarm optimization (DPSO) has several attractive characteristics such as the simplicity of the heuristics, the ease of implementation, and its often fairly remarkable effectiveness. The performances of DPSO depend on four main setting parameters: the number of swarm particles, their initialization, the set of coefficients defining the swarm behavior, and (for box-constrained optimization) the method to handle the box constraints. Here, a parametric study of DPSO is presented, with application to simulation-based design in ship hydrodynamics. The objective is the identification of the most promising setup for both synchronous and asynchronous implementations of DPSO. The analysis is performed under the assumption of limited computational resources and large computational burden of the objective function evaluation. The analysis is conducted using 100 analytical test functions (with dimensionality from two to fifty) and three performance criteria, varying the swarm size, initialization, coefficients, and the method for the box constraints, resulting in more than 40,000 optimizations. The most promising setup is applied to the hull-form optimization of a high speed catamaran, for resistance reduction in calm water and at fixed speed, using a potential-flow solver.

Recent progress in CFD for naval architecture and ocean engineering

An overview is provided of CFDShip-Iowa modeling, numerical methods and high performance computing (HPC), including both current V4.5 and V5.5 and next generation V6. Examples for naval architecture highlight capability and needs. High fidelity V6 simulations for ocean engineering and fundamental physics describe increased resolution for analysis of physics of fluids. Uncertainty quantification research is overviewed as the first step towards development stochastic optimization.

Multidisciplinary conceptual design optimization of aircraft using a sound-matching-based objective function

The article presents a novel approach to include community noise considerations based on sound quality in the Multidisciplinary Conceptual Design Optimization (MCDO) of civil transportation aircraft. The novelty stems from the use of an unconventional objective function, defined as a measure of the difference between the noise emission of the aircraft under analysis and a reference ‘weakly annoying’ noise, the target sound. The minimization of such a merit factor yields an aircraft concept with a noise signature as close as possible to the given target. The reference sound is one of the outcomes of the European Research Project SEFA (Sound Engineering For Aircraft, VI Framework Programme, 2004-2007), and used here as an external input. The aim of the present work is to address the definition and the inclusion of the sound-matching-based objective function in the MCDO of aircraft.

Formulation and parameter selection of multi-objective deterministic particle swarm for simulation-based optimization

Abstract Global derivative-free deterministic algorithms are particularly suitable for simulation-based optimization, where often the existence of multiple local optima cannot be excluded a priori, the derivatives of the objective functions are not available, and the evaluation of the objectives is computationally expensive, thus a statistical analysis of the optimization outcomes is not practicable. Among these algorithms, particle swarm optimization (PSO) is advantageous for the ease of implementation and the capability of providing good approximate solutions to the optimization problem at a reasonable computational cost. PSO has been introduced for single-objective problems and several extension to multi-objective optimization are available in the literature. The objective of the present work is the systematic assessment and selection of the most promising formulation and setup parameters of multi-objective deterministic particle swarm optimization (MODPSO) for simulation-based problems. A comparative study of six formulations (varying the definition of cognitive and social attractors) and three setting parameters (number of particles, initialization method, and coefficient set) is performed using 66 analytical test problems. The number of objective functions range from two to three and the number of variables from two to eight, as often encountered in simulation-based engineering problems. The desired Pareto fronts are convex, concave, continuous, and discontinuous. A full-factorial combination of formulations and parameters is investigated, leading to more than 60,000 optimization runs, and assessed by three performance metrics. The most promising MODPSO formulation/parameter is identified and applied to the hull-form optimization of a high-speed catamaran in realistic ocean conditions. Its performance is finally compared with four stochastic algorithms, namely three versions of multi-objective PSO and the genetic algorithm NSGA-II.

Community Noise Impact on the Conceptual Design of Innovative Aircraft Configurations

The paper presents recent work to include community noise considerations based on costs in an existing framework for MDO-CD (Multi-Disciplinary Optimization for Conceptual Design) of highly innovative configurations for civil aviation. The paper presents an extension of the formulation used in the code MAGIC (Multidisciplinary Analysis and desiGn of Innovative Configurations), developed by the authors and their collaborators, which comprises models for structures, aerodynamics, aeroelasticity, flight mechanics, and propulsion, along with the recent addition of aeroacoustics and life-cycle costs models. The community noise is treated here as a cost and included in the objective. It should be noted that the cost of noise depends a lot upon government regulation and community perception, and hence is not known during the conceptual design phase. Thus, the paper presents a parametric study of conceptual design based on life-cycle costs, with the cost of noise used as a varying parameter. The paper includes applications to the optimization of innovative configurations, such as the box-wing configuration (Prantl-Plane) proposed by Frediani. The box-wing configuration is particularly interesting because of the greatly reduced induced drag. This implies a reduction of the power required, and hence a reduction of community noise.

Globally Convergent Hybridization of Particle Swarm Optimization Using Line Search-Based Derivative-Free Techniques

The hybrid use of exact and heuristic derivative-free methods for global unconstrained optimization problems is presented. Many real-world problems are modeled by computationally expensive functions, such as problems in simulation-based design of complex engineering systems. Objective-function values are often provided by systems of partial differential equations, solved by computationally expensive black-box tools. The objective-function is likely noisy and its derivatives are often not available. On the one hand, the use of exact optimization methods might be computationally too expensive, especially if asymptotic convergence properties are sought. On the other hand, heuristic methods do not guarantee the stationarity of their final solutions. Nevertheless, heuristic methods are usually able to provide an approximate solution at a reasonable computational cost, and have been widely applied to real-world simulation-based design optimization problems. Herein, an overall hybrid algorithm combining the appealing properties of both exact and heuristic methods is discussed, with focus on Particle Swarm Optimization (PSO) and line search-based derivative-free algorithms. The theoretical properties of the hybrid algorithm are detailed, in terms of limit points stationarity. Numerical results are presented for a specific test function and for two real-world optimization problems in ship hydrodynamics.

Robust Optimization of Aircraft Life-cycle Costs Including the Cost of Community Noise

The paper presents an extension of a formulation for life-cycle-costs-based MDO-CD (Multi-Disciplinary Optimization for Conceptual Design) of aircraft configurations for civil aviation, to take into account the stochastic variation of probabilistic parameters. Specifically, in the formulation used, the community noise is included in the optimization process as a cost. This cost depends a lot, for instance, upon government regulation and community perception, and hence is not necessarily determined when one is performing all the conceptual design computations. Thus, in the formulation presented, the cost of noise is used as a probabilistic design parameter and the optimal design is evaluated as that which minimize the expected value of the aircraft life-cycle-cost. In this preliminary work, the noise produced by the aircraft is evaluated using a simple Noise-Power-Distance model and included in the optimization process. A description of the technique used to estimate the community-noise impact on the life-cycle cost of the aircraft is presented. Applications to the optimization of an aircraft of the A320 category are shown.

A Proposal of PSO Particles' Initialization for Costly Unconstrained Optimization Problems: ORTHOinit

A proposal for particles’ initialization in PSO is presented and discussed, with focus on costly global unconstrained optimization problems. The standard PSO iteration is reformulated such that the trajectories of the particles are studied in an extended space, combining particles’ position and speed. To the aim of exploring effectively and efficiently the optimization search space since the early iterations, the particles are initialized using sets of orthogonal vectors in the extended space (orthogonal initialization, ORTHOinit). Theoretical derivation and application to a simulation-based optimization problem in ship design are presented, showing the potential benefits of the current approach.

Initial Particles Position for PSO, in Bound Constrained Optimization

We consider the solution of bound constrained optimization problems, where we assume that the evaluation of the objective function is costly, its derivatives are unavailable and the use of exact derivative-free algorithms may imply a too large computational burden. There is plenty of real applications, e.g. several design optimization problems, belonging to the latter class, where the objective function must be treated as a ‘black-box’ and automatic differentiation turns to be unsuitable. Since the objective function is often obtained as the result of a simulation, it might be affected also by noise, so that the use of finite differences may be definitely harmful. In this paper we consider the use of the evolutionary Particle Swarm Optimization (PSO) algorithm, where the choice of the parameters is inspired by, in order to avoid diverging trajectories of the particles, and help the exploration of the feasible set. Moreover, we extend the ideas in and propose a specific set of initial particles position for the bound constrained problem.

A Sound-Matching-Based Approach for Aircraft Noise Annoyance Alleviation Via MDO

The paper presents the authors’ most recent advances in the development of a reliable and eective algorithm for the inclusion of community noise consideration within a Multidisciplinary Design Optimization (MDO) framework. The attention is here focused on the possibility to include sound quality issues as an alternative to the classical sound-level-based approach. The improvement of the sound quality could be seen as an additional “degree of freedom” available to the designer to reduce the impact of the air trac on residents’ life. One of the primary objectives of the European Research Project SEFA (Sound Engineering For Aircraft) is the definition of those characteristics that make the aircraft acoustic emissions less annoying. This is done by means of an extensive campaign of psychometric tests, supported by a careful sound engineering work. One of the outcomes of this activity is the synthesis of a target sound, having all the characteristics of “pleasantness” defined. The role of the authors within the project is the development of an algorithm capable to evaluate the feasibility of the target sound matching since the conceptual phase of the design of the aircraft. To accomplish this, a method for the quantitative evaluation of the dierence between the target sound and the acoustic emissions of the aircraft is needed. A careful definition of the “distance” between two sounds is introduced and validated, in order to identify a metric useful to properly build an objective function capable to drive the optimization process toward the target-sound-matching configurations. In this work, the evaluation of the sounds distance is extended to the analysis of non-stationary sounds and applied to match the emissions of recorded sounds in the final approach procedure. Specifically, the distance is evaluated as the L p -norm of the dierence between the current spectrum and target spectrum over the frequency-time domain. In order to evaluate the current spectrum, the computation of airframe noise, fan and compressor noise, buzz-saw and jet noise is performed. Atmospheric attenuation, ground reflection and doppler eect are also taken into account. In this work, an L 2 -distance between current and target spectra is taken as the objective function of an evolutionary algorithm. The static equilibrium of the aircraft is used as a constraint, whereas the variables space used includes both design and procedural parameters. Preliminary numerical results show that the method is capable to eectively drive the optimization process towards those configurations satisfying the sound-matching criterion.