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Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.

The purpose of this study is to develop a method to reduce the computation time necessary for the automated optimal design of dual-band wearable antennas. In particular, the authors investigated if this can be achieved by the use of a hierarchical optimization paradigm combined with a simplified human body model. The geometry of the antenna under consideration is described via eight geometrical parameters which are automatically adjusted with the use of an evolutionary algorithm to improve the impedance matching of an antenna located in the proximity of a human body. Specifically, the antennas were designed to operate in the ISM band which covers two frequency ranges: 2.4-2.5 GHz and 5.7-5.9 GHz.

During the studies on the automated design of wearable antennas using evolutionary computing, the authors observed that not all design parameters exhibit equal influence on the objective function. Therefore, it was hypothesized that to reduce the computation effort, the design parameters can be activated sequentially based on their influence. Accordingly, the authors’ computer code has been modified to include this feature.

The authors’ novel hierarchical multi-parameter optimization method was able to converge to a better solution within a shorter time compared to an equivalent method not exploiting automatic activation of an increasing number of design parameters. Considering a significant computational cost involved in the calculation of the objective function, this exhibits a convincing advantage of their hierarchical approach, at least for the considered class of antennas.

The described method has been developed for the design of single- or dual-band wearable antennas. Its application to other classes of antennas and antenna environments may require some adjustments of the objective functions or parameter values of the evolutionary algorithm. It follows from the well-recognized fact that all optimization methods are to some extent application-specific.

Computation load involved in the automated design and optimization can be significantly reduced compared to the non-hierarchical approach with a heterogeneous human body model.

To the best of the authors’ knowledge, the described application of hierarchical paradigm to the optimization of wearable antennas is fully original, as well as is its combination with simplified body models.

This paper aims to deal with the optimal shape design of a class of permanent magnet motors by minimizing multiple objectives according to an original interpretation of Pareto optimality. The proposed method solves a many-objective problems characterized by five objective functions and five design variables with evolution strategy algorithms, classically used for single- and multi-objective (two objective functions) optimization problems.

Two approaches are proposed in the paper: the All-Objectives (AO) and the Many-Objectives (MO) optimization approach. The former is based on a single-objective optimization of a preference function, i.e. a normalized weighted sum. In contrast, in the MO a multi-objective optimization algorithm is applied to the minimization of a weight-free preference function and simultaneously to a maximization of the distance of the current solution from the prototype. The optimizations are based on an equivalent circuit model of the Permanent Magnet (PM) motor, but the results are assessed by means of finite element analyses (FEAs).

An extensive study of the solutions obtained by means of the different optimization approaches is provided by means of post-processing analyses. Both the approaches find non-dominated solutions with respect to the prototype that are substantially improving the initial solution. The points of strength along with the weakness points of each solution with respect to the prototype are analysed in depth.

The paper gives a good guide to the designers of electric motors, focussed on a shape design optimization.

Considering simultaneously five objective functions in an automated optimal design procedure is challenging. The proposed approach, based on a well-known and established optimization algorithm, but exploiting a new concept of degree of conflict, can lead to new results in the field of automated optimal design in a many-objective context.

The purpose of this paper is to present a methodology based on an optimizer linked with electric finite element method (FEM) for automating the optimized design of power transformer insulation system structures.

The proposed methodology combines two stages to obtain the optimized design of transformer insulation system structures. First, an analytical calculation is carried out with the optimizer to search a candidate solution. Then, the candidate solution is numerically checked in detail to validate its consistency. Otherwise, these two steps are iteratively repeated until the optimizer finds a candidate solution according to the objective function.

The solutions found applying the proposed methodology reduce the inter-electrode distances compared to those insulation designs referenced in the literature for the same value of safety margin.

The proposed methodology explores a wide range of insulation system structures in an automated way which is not possible to do with the classical trial-and-error approach based on personal expertise.

The main goal of this paper is to show the constant growth of recent research work on automated optimal design of low‐frequency electromagnetic systems by reviewing the current literature on the topic.

Fostered by the development of new technologies, micro-electro-mechanical systems (MEMS) are massively present on board of vehicles, within information equipment, as well as in medical and healthcare equipment. The purpose of this paper is to approach here the shape design of MEMS in terms of the optimization of a vector objective function, subject to a set of constraints. Objectives and constraints are non-linear, dependent on the unknown device shape. When multiple objective functions should be optimized simultaneously, the set of solutions minimizing the degree of conflict (Pareto front) can be searched for.

This paper proposes an automated optimal design method based on connecting the MATLAB surrogate modeling (SUMO) toolbox with COMSOL Multiphysics finite element analysis tool, and the evolutionary algorithm NSGA-II as well.

The efficiency of the optimization method proposed is approximately doubled in terms of runtime (5 vs 10 h for the referred platform), when compared with the same computational job without using surrogate models. This way, a cost-effective and accurate approximation of the Pareto front, trading off drive and levitation force components in a comb-drive electrostatic microactuator, was found.

More in-depth models of MEMS devices could be obtained by simulating multi-domain physical processes, i.e. encompassing a coupled-field analysis in the multiphysics sense.

Under this framework, the proposed approach lays the ground for a very general method devoted to the optimal shape design of any MEMS configuration; in fact, the application of multiobjective optimizations to these kind of devices is quite new.

Seeks to determine the optimal shape design of an induction heating device.

Presents, through a case study, the optimal shape design of a multiple coil inductor for surface heating. Resorts to a procedure of automated optimal design, based on evolutionary optimisation and processing both continuous‐valued and discrete‐valued variables.

Demonstrates that it is possible to solve the design problem routinely using an optimisation tool (OptiNet) that is built to work seamlessly with a coupled electromagnetic‐thermal simulation.

Every design criterion that is likely to be of interest to a designer of industrial applications can be described to the system and optimised in a reasonable time frame.

The paper reports recent experiences of the authors in the automated optimal design of devices and systems for induction heating. The results presented have been obtained in the frame of a long‐lasting cooperation between Laboratory of Electroheat, University of Padova and Electromagnetic Devices CAD Laboratory, University of Pavia. In particular, two case studies are discussed; in both cases, the shape design of the inductor is carried out in a systematic way, by minimizing user‐defined objective functions depending on design variables and subject to bounds and constraints. When the design problem is characterized by many objectives which are in mutual conflict, the non‐dominated set of solutions is identified.

The paper deals with research activities to develop optimization workflows implying computational fluid dynamics (CFD) modelling. The purpose of this paper is to present an industrial and fully-automated optimal design tool, able to handle objectives, constraints, multi-parameters and multi-points optimization on a given CATIA CAD. The work is realized on Rapid And CostEffective Rotorcraft compound rotorcraft in the framework of the Fast RotorCraft Innovative Aircraft Demonstrator Platform (IADP) within the Clean Sky 2 programme.

The proposed solution relies on an automated CAD-CFD workflow called through the optimization process based on surrogate-based optimization (SBO) techniques. The SBO workflow has been specifically developed.

The methodology is validated on a simple configuration (bended pipe with two parameters). Then, the process is applied on a full compound rotorcraft to minimize the flow distortion at the engine entry. The design of the experiment and the optimization loop act on seven design parameters of the air inlet and for each individual the evaluation is performed on two operation points, namely, cruise flight and hover case. Finally, the best design is analyzed and aerodynamic performances are compared with the initial design.

The adding value of the developed process is to deal with geometric integration conflicts addressed through a specific CAD module and the implementation of a penalty function method to manage the unsuccessful evaluation of any individual.

Discusses the automated shape design of the electrodes supplying an arrangement for high‐voltage test. Obtains results that are feasible for industrial applications by means of an optimisation algorithm able to process discrete‐valued design variables.