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Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of electromagnetic problems which may be sensitive to parameter variations. The purpose of this paper is to propose a robust objective function for topological design problems.

In this paper, a robust objective function for topology optimization is defined on an uncertainty set using the worst case analysis. The robustness of a topological design is defined as the worst response due to the variations of the location of the topology change. The approach is based on the definition of a topological gradient.

The robust topology optimization (RTO) was applied to eddy current crack reconstruction problems. The numerical applications showed that this method can provide more reliable results for the reconstruction in the presence of significant noise in the measured signal.

The RTO may be applied to some more complicated design problems; however large computational costs may result.

This paper has defined a robustness metric for topology design and a robust design model is proposed for topology optimization problems.

The conventional starting point for the design of an electrical machine (or any low-frequency electromagnetic device) is known as “sizing”. In this process, a simple magnetic circuit is used to estimate the main geometric parameters. This does not work for many devices, particularly where eddy currents and non-linearity dominate. The purpose of this paper is to investigate an approach using a neural network trained on a large database of existing designs as a general sizing system.

The approach is based on a combination of a radial basis function neural network and a database of stored performances of electrical machines. The network is trained based on a set of typical performance requirements for a machines design problem. The resulting design is analyzed using finite elements to determine if the design performance is acceptable.

The number of neurons in the network was varied to determine the approximation and generalization capabilities. The finite element analysis showed that the network produced initial design parameters which resulted in an appropriate performance.

The research has looked at only one class of machine. Further work is needed on a range of machines to determine how effective the approach can be.

The approach can provide a good initial design and thus can reduce overall design time significantly.

The paper proposes a novel, fast and effective generalized approach to sizing low frequency electromagnetic devices.

This paper discusses the possibility of automating the design of electromagnetic devices. Several paradigms currently exist to accelerate the design process, search the design space and examine the effects of tolerances on various parameters. Amongst these are semantic networks, response surfaces, interval mathematics and sensitivity analysis. This paper explores all of these and also suggests what is needed in the future in order to create a true computer based design system.

To present a general synthesis method in the design of variable comb drive MEMS capacitors which can provide specified capacitance versus position profiles while give large tuning range.

By carefully choosing design parameters and constraint conditions, the design process is implemented as the solution of a constraint optimization problem. An electric field analysis software based on the finite element method and an optimization software based on the evolutionary stochastic search are chosen to work together to implement the system.

The results verify that the shape of a variable MEMS capacitor has a great influence on the capacitance versus distance profile and demonstrates that a specific geometry of the MEMS capacitor can be found to match a desired capacitance‐distance profile.

The analytical expression for the capacitance formed between the fixed and the movable fingers is somewhat inaccurate. The results are not compared to measurement because no device has been fabricated.

A very successful numerical simulation example and guidance for MEMS designers to develop MEMS devices with variable electrode shapes.

This paper proposes a systematic way for the design of MEMS tunable capacitors with variable shape. The approach can be used to design MEMS devices with variable electrode shapes to satisfy specific requirements.

The purpose of this paper is to develop a novel multi‐objective optimization algorithm which takes into account the uncertainty in design parameters by using a reduced resolution for their representation, thus implementing a simple form of robustness. Additionally, the number of function evaluations should be minimized.

The proposed approach is based on an elitist evolutionary algorithm coupled with a reduction in the number of significant figures used to represent design parameters. In effect, this becomes a filter in the optimization process and allows the system to avoid extremely sharp optima within the search space. By reducing the resolution of the search and maintaining a full archive of previous solutions, the number of evaluations of the objective functions, each of which may require an expensive numerical solution, is reduced.

The algorithm was tested both on an algebraic test function and on two TEAM Workshop Problems (22 and 25). The results demonstrated that it is stable; can emerge from deceptive fronts; and find optimal solutions which match those previously published at a relatively low‐computational cost.

The originality of this paper lies in the concept of using a low‐resolution representation of the design parameters. This results in a finite size search space and increases the speed of the algorithm while avoiding non‐manufacturable solutions.

The inverse problem related to eddy current testing (ECT) is often formulated as a shape optimization problem. The purpose of this paper is to propose a methodology for determining the optimal parameters of a sensor system for more accurate reconstruction of the crack shape.

In this paper, an objective function is formulated using the shape sensitivity information computed from the ECT data. The design of a non‐destructive testing (NDT) sensor is carried out through optimizing the sensor parameters under such a criterion.

The methodology proposed results in modifications to the original sensor geometry which makes it more sensitive to the depth changes in a crack. A square wave form of excitation is used in order to provide more information on the size of the crack at different depths, essentially through the superposition of a range of excitation frequencies, each of which has a different depth of penetration. The newly designed ECT sensor system is suitable for dealing with the natural crack problem.

While the methodology is general and has been shown to work in a simulated environment, the result is not verified by the experiments because the newly designed device has not actually been fabricated.

This paper has demonstrated the possibility of designing a sensor probe using computer aided design tools without extensive physical testing. The design process is novel and based on a sensitivity approach. This is shown to be very efficient and effective and the solution of the inverse problem demonstrates a very fast convergence.

This paper aims to investigate the electroporation phenomenon in a single cell exposed to ultra short (μs) and high voltage (kV) electric pulses.

The problem is addressed by two complementary approaches. First, numerical simulations based on an asymptotic approximation derived from the Smoluchowski theory are used to calculate the pore generation, growth and size evolution at the membrane of a spherical cell model, immersed in a suspension medium and consisting of cytoplasm and membrane. The numerical calculations are solved using the finite difference method. Second, an in vitro experiment with LLC-MK2 cells is carried out in which electroporation was monitored with molecules of propidium iodide. This part also comprehended the design and manufacturing of a portable electric pulse generator capable of providing rectangular pulses with amplitude of 1,000 V and duration in the range of 1-μs to 100-μs. The pulse generator is composed of three modules: a high voltage DC source, a control module, and an energy storage and high voltage switching.

The numerical simulations considered a 5-μm radius cell submitted to a 500 kV/m rectangular electric pulse for 1-μs. The results indicate the formation of around 3,500 pores at the cell membrane, most of them, around 950, located at the poles of the cell aligned to the applied electric pulse, with radii sizes varying from 0.5-nm to 13-nm. The in vitro experiment considered exposition of LLC-MK2 cells to pulses of 200 V, 500 V, and 700 V, and 1-μs. Images from fluorescence microscopy exhibit the LLC-MK2 cells with intense red, a strong evidence of the electroporation.

The work presents a thorough study of the electroporation phenomenon combining two complementary approaches, a rigorous numerical simulation and a detailed in vitro experiment.

The paper aims to present a new methodology for hybrid genetic algorithms (GA) in the solution of electromagnetic optimization problems.

This methodology can be seen as a local search operator which uses local quadratic approximations for each objective and constraint function in the problem. In the local search phase, these approximations define an associated local search problem that is efficiently solved using a formulation based on linear matrix inequalities.

The paper illustrates the proposed methodology comparing the performance of the hybrid GA against the basic GA in two analytical problems and in the well‐known TEAM benchmark Problem 22. For the analytical problems, 30 independent runs for each algorithm were considered whereas for Problem 22, ten independent runs for each algorithm were taken.

For the analytical problems, the hybrid GA enhanced both the convergence speed, in terms of the number of function evaluations, and the accuracy of the final result. For Problem 22, the hybrid GA was able to reach a better solution, with a better value of the standard deviation with less CPU time.

The paper could be useful both for device designers and researchers involved optimization in computational electromagnetics.

The hybrid GA proposed enhanced the convergence speed, in terms of the number of function evaluations, representing a faster and robust algorithm for practical optimization problems.