Matěj Lepš

New approach to optimization of reinforced concrete beams

The present paper outlines an application of genetic algorithm based strategies to a class of optimization tasks associated with the design of steel reinforced concrete structures. In this particular case, the principal design objective is to minimize the total cost of a structure. The resulting structure, however, should not only be marked with a low price but also comply with all strength and serviceability requirements for a given level of the applied load. To solve such a complex optimization problem with a number constraints calls for an efficient and yet reliable optimization technique. Here, the problem is addressed with the help of the augmented simulated annealing method. As an example, a simple continuous steel reinforced beam is analyzed to assess applicability of the proposed approach.

Applying genetic algorithms to selected topics commonly encountered in engineering practice

A carefully selected group of optimization problems is addressed to advocate application of genetic algorithms in various engineering optimization domains. Each topic introduced in the present paper serves as a representative of a larger class of interesting problems that arise frequently in many applications such as design tasks, functional optimization associated with various variational formulations, or a number of problems linked to image evaluation. No particular preferences are given to any version of genetic algorithms, but rather lessons learnt up-to-date are effectively combined to show the power of the genetic algorithm in effective search for the desired solution over a broad class of optimization problems discussed herein.

A competitive comparison of different types of evolutionary algorithms

Abstract This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in civil engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA) [Comp. Meth. Appl. Mech. Eng. 190 (13–14) (2000) 1629], the differential evolution (DE) in its original fashion developed by Storn and Price [R. Storn, On the usage of differential evolution for function optimization, NAPHIS, 1996] and simplified real-coded differential genetic algorithm (simplified atavistic differential evolution, SADE) [O. Hrstka, A. Kucerova, Search for optimization methods on multi-dimensional real domains, Contributions to Mechanics of Materials and Structures, CTU Reports 4, 2000, pp. 87–104]. Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems––the reinforced concrete beam layout and the periodic unit cell problem, respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, IASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.

Soft computing-based calibration of microplane M4 model parameters: Methodology and validation

Abstract Constitutive models for concrete based on the microplane concept have repeatedly proven their ability to well-reproduce non-linear response of concrete on material as well as structural scales. The major obstacle to a routine application of this class of models is, however, the calibration of microplane-related constants from macroscopic data. The goal of this paper is twofold: (i) to introduce the basic ingredients of a robust inverse procedure for the determination of dominant parameters of the M4 model proposed by Bažant et al. (2000) based on cascade artificial neural networks trained by evolutionary algorithm and (ii) to validate the proposed methodology against a representative set of experimental data. The obtained results demonstrate that the soft computing-based method is capable of delivering the searched response with an accuracy comparable to the values obtained by expert users.

Minimum-Weight Truss Reinforcement of a Composite Beam to Increase the Free-Vibrations Fundamental Eigenfrequency

In this contribution, we design a minimum-weight truss reinforcement of a thin-walled composite beam, such that the fundamental free-vibrations eigenfrequency of the beam is increased to a specific value. The reinforcement structure is designed using techniques of topology optimization and produced using additive manufacturing, in order to achieve economical design and minimize manual interventions in the fabrication process. Finally, an experimental validation of theoretical outcomes is performed on an additively manufactured prototype.

Study on Multi-Objective Reconstruction of Random Media

This paper deals with a reconstruction of random media via multi-objective optimization. Two statistical descriptors, namely a two-point probability function and a two-point lineal path function, are repetitively evaluated for the original medium and the reconstructed image to appreciate the improvement in the optimization progress. Because of doubts of the weights setting in the weighted-sum method, purely multi-objective optimization routine Non-dominated Sorting Genetic Algorithm~II is utilized. Three operators are compared for creating new offspring populations that satisfy a prescribed volume fraction constraint. The main contribution is in the testing of the proposed methodology on several benchmark images.

Microplane model parameters estimation using neural networks

Concrete is one of the most frequently used material in Civil Engineering. Nevertheless, as a highly heterogeneous material, it shows very complex non-linear behavior, which is extremely difficult to describe by a sound constitutive law. As a consequence, a numerical simulation of response of complex concrete structures still remains a very challenging and demanding topic.