Felipe Orozco^1‡, Brian Alfaro-González^1‡, Yendry Corrales Ureña¹, Karolina Villalobos¹, Angie Sanchez¹, Francisco Bravo¹, José Roberto Vega¹, Orlando Argüello-Miranda^1†*

Journal of Renewable Materials, Vol.5, No.3-4, pp. 199-207, 2017, DOI:10.7569/JRM.2017.634110

Abstract As an outcome of millions of years of evolution, biological systems have developed different methods to interact with their surroundings. Many of these adaptations, such as secretions, light-interacting surfaces, biochemical active compounds, and many other survival strategies, are phenomena occurring at the nanometric scale. In this review, we describe how extracellular nanometric structures are responsible for manipulating energy and matter, creating some of the emergent properties of life. Iridescent colors in birds’ feathers, the manipulation of wettability of insects’ exoskeletons, the adhesive properties of nanopatterned secretions and the ability to polarize light are examples of More >

T. Podoba¹, L. Tomsu¹, K. Vlcek¹, M. Heczko

The International Conference on Computational & Experimental Engineering and Sciences, Vol.15, No.4, pp. 111-122, 2010, DOI:10.3970/icces.2010.015.111

Abstract Surface reconstruction based on chaotic systems or exactly given point clouds is very difficult area. Current algorithms such as Marching Cube or Voronoi Filtering do not use methods based on artificial intelligence. In this paper, we investigate solution of polygonal surface construction based on AI. The main purpose is to generate complex polygonal mesh structures based on strange attractors with fractal structure. Attractors have to be created as 4D objects using quaternion algebra or using methods of AI. Polygonal mesh can have different numbers of polygons because of iterative application of this system. Our main More >

V.C. Mariani¹, V. J. Neckel², L. S. Coelho³

CMES-Computer Modeling in Engineering & Sciences, Vol.68, No.2, pp. 167-184, 2010, DOI:10.3970/cmes.2010.068.167

Abstract In this study an inverse heat conduction problem using two optimization methods to estimate apparent thermal diffusivity at different drying temperatures is solved. Temperature and moisture versus time were obtained numerically using heat and mass transfer equations with drying temperatures in the range between 20°C to 70°C. The solution of the partial differential equation is made with a finite difference method coupled to optimization techniques of Differential Evolution (DE) and Particle Swarm Optimization (PSO) used in inverse problem. Statistical analysis shows no significant differences between reported and estimated curves, and no remarkable differences between results More >

Hossein M. Shodja^{1, 2, 3}, Alireza Hashemian^{2, 4}

The International Conference on Computational & Experimental Engineering and Sciences, Vol.13, No.3, pp. 57-58, 2009, DOI:10.3970/icces.2009.013.057

Abstract Gradient reproducing kernel particle method (GRKPM) is a meshless technique which incorporates the first gradients of the function into the reproducing equation of RKPM. Therefore, in two-dimensional space GRKPM introduces three types of shape functions rather than one. The robustness of GRKPM's shape functions is established by reconstruction of a third-order polynomial. To enforce the essential boundary conditions (EBCs), GRKPM's shape functions are modified by transformation technique. By utilizing the modified shape functions, the weak form of the nonlinear evolutionary Buckley-Leverett (BL) equation is discretized in space, rendering a system of nonlinear ordinary differential equations More >

M. Irízar, L. D. Câmara, A. J. Silva Neto, O. Llanes

CMES-Computer Modeling in Engineering & Sciences, Vol.54, No.1, pp. 1-14, 2009, DOI:10.3970/cmes.2009.054.001

Abstract Modeling of Chromatography allows a better understanding and development of new techniques to be applied at industrial level, although it's relatively complex. The models of this process are represented by systems of partial differential equations with non linear parameters difficult to estimate generally, which constitutes an inverse problem. In general there aren't analytical solutions and therefore numerical methods should be used for their direct solutions. Frequently typical boundary conditions are considered, but it's convenient to study different approaches for those. Evolutionary Computation has been used successfully in many problems of diverse areas for searching in More >

TakehikoNakama¹

CMC-Computers, Materials & Continua, Vol.14, No.1, pp. 35-60, 2009, DOI:10.3970/cmc.2009.014.035

Abstract Random noise perturbs objective functions in practical optimization problems, and genetic algorithms (GAs) have been proposed as an effective optimization tool for dealing with noisy objective functions. In this paper, we investigate GAs in a variety of noisy environments where fitness perturbation can occur in any form-for example, fitness evaluations can be concurrently disturbed by additive and multiplicative noise. We reveal the convergence properties of GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms in noisy environments. We compute the one-step transition probabilities of the Markov chain and… More >

A.Oba¹, Y.Fujii², M.Okuma³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.7, No.1, pp. 51-56, 2008, DOI:10.3970/icces.2008.007.051

Abstract In this paper, the authors present a new evolutionary structural optimization method based on FE modeling using identical cubic elements for optimizing strength and dynamics characteristics of structures. The method is developed from the previous ones([1\hbox {}]-[3\hbox {}]), and carries out the size and topological shape optimization to satify the strength against external force and inertia force of itself and to control the natural frequencies of the structure. The method gives us the lightest structure satisfying the requirement about the strength and dynamic characteristics. The outline of the method is presented first, and a basic More >

Hossein M. Shodja^1,2,3, Alireza Hashemian^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.32, No.1, pp. 17-34, 2008, DOI:10.3970/cmes.2008.032.017

Abstract Gradient reproducing kernel particle method (GRKPM) is a meshless technique which incorporates the first gradients of the function into the reproducing equation of RKPM. Therefore, in two-dimensional space GRKPM introduces three types of shape functions rather than one. The robustness of GRKPM's shape functions is established by reconstruction of a third-order polynomial. To enforce the essential boundary conditions (EBCs), GRKPM's shape functions are modified by transformation technique. By utilizing the modified shape functions, the weak form of the nonlinear evolutionary Buckley-Leverett (BL) equation is discretized in space, rendering a system of nonlinear ordinary differential equations More >

P. Fedelinski¹, R. Gorski¹

CMES-Computer Modeling in Engineering & Sciences, Vol.15, No.1, pp. 31-40, 2006, DOI:10.3970/cmes.2006.015.031

Abstract The aim of the present work is to analyze and optimize plates in plane strain or stress with stiffeners subjected to dynamic loads. The reinforced structures are analyzed using the coupled boundary and finite element method. The plates are modeled using the dual reciprocity boundary element method (DR-BEM) and the stiffeners using the finite element method (FEM). The matrix equations of motion are formulated for the plate and stiffeners. The equations are coupled using conditions of compatibility of displacements and equilibrium of tractions along the interfaces between the plate and stiffeners. The final set of… More >

Y.S. Lian¹, M.S. Liou²

CMES-Computer Modeling in Engineering & Sciences, Vol.8, No.1, pp. 61-72, 2005, DOI:10.3970/cmes.2005.008.061

Abstract This paper focuses on integration of computational methods for design optimization based on data mining and knowledge discovery. We propose to use radial basis function neural networks to analyze the large database generated from evolutionary algorithms and to extract the cause-effect relationship, between the objective functions and the input design variables. The aim is to improve the optimization process by either reducing the computation cost or improving the optimal. Also, it is hoped to provide designers with the salient design pattern about the problem under consideration, from the physics-based simulations. The proposed technique is applied More >