Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to mimic the basic Darwinian concepts of natural selection. They are highly robust and efficient for most engineering optimising studies. Although a late entrant in the materials arena, GAs based studies are increasingly making their presence felt in many different aspects of this discipline. In recent times, GAs have been successfully used in numerous problems in the areas of atomistic material design, alloy design, polymer processing, powder compaction and sintering, ferrous production metallurgy, continuous casting, metal rolling, metal cutting, welding, and so on. The present review attempts to present the state of the art in this area. It includes three broad sections given as: fundamentals of genetic algorithms, genetic algorithms in materials design, and genetic algorithms in materials processing. The first section provides the reader with the basic concepts and the intricacies associated with this novel tec...

Genetic algorithms in materials design and processing

Delamination detection in composites through guided wave field image processing

Free vibration and elastic buckling of beams made of functionally graded materials (FGMs) containing open edge cracks are studied in this paper based on Timoshenko beam theory. The crack is modeled by a massless elastic rotational spring. It is assumed that the material properties follow exponential distributions along beam thickness direction. Analytical solutions of natural frequencies and critical buckling load are obtained for cracked FGM beams with clamped-free, hinged-hinged, and clamped-clamped end supports. A detailed parametric study is conducted to study the influences of crack depth, crack location, total number of cracks, material properties, beam slenderness ratio, and end supports on the free vibration and buckling characteristics of cracked FGM beams.

Flexural Vibration and Elastic Buckling of a Cracked Timoshenko Beam Made of Functionally Graded Materials

Genetic algorithms (GAs) are a tool used to solve high-complexity computational problems. Apart from modelling the phenomena occurring in Nature, they help in optimization, simulation, modelling, design and prediction purposes in science, medicine, technology, and everyday life. They can be adapted to the given task, be joined with other ones (this leads to combined or hybrid methods), and can work in parallel on many processors. The uses of GAs reported in literature represent a wide variety of approaches and led to solving of numerous computational problems of high complexity. In materials science and related fields of science and technology the GAs open possibilities for materials design, studies of their properties, or production at industrial scale. Here, the recent use of GAs in various domains connected to materials science, solid state physics and chemistry, crystallography, biology, and engineering is reviewed. The listed examples taken from recent literature show how broad the use of these metho...

Genetic Algorithms, a Nature-Inspired Tool: Survey of Applications in Materials Science and Related Fields

A new computational tool is developed for the accurate detection and identification of cracks in structures, to be used in conjunction with non-destructive testing of specimens. It is based on the solution of an inverse problem. Based on some measurements, typically along part of the boundary of the structure, that describe the response of the structure to vibration in a chosen frequency or a combination of frequencies, the goal is to estimate whether the structure contains a crack, and if so, to find the parameters (location, size, orientation and shape) of the crack that produces a response closest to the given measurement data in some chosen norm. The inverse problem is solved using a genetic algorithm (GA). The GA optimization process requires the solution of a very large amount of forward problems. The latter are solved via the extended finite element method (XFEM). This enables one to employ the same regular mesh for all the forward problems. Performance of the method is demonstrated via a number of numerical examples involving a cracked flat membrane. Various computational aspects of the method are discussed, including the a priori estimation of the ill-posedness of the crack identification problem. Copyright © 2007 John Wiley & Sons, Ltd.

XFEM‐based crack detection scheme using a genetic algorithm

A spectral finite element with embedded delamination for modeling of wave scattering in composite beams

An efficient strategy for identification of delamination in composite beams and connected structures is presented A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems

https://iopscience.iop.org/article/10.1088/0964-1726/11/6/311/pdf

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An identification procedure and sensitivity studies on single and multiple delaminations in laminated composite beams are presented. A Spectral Finite Element Model (SEM) based on the Fast Fourier Transform (FFT) is employed. A single damaged spectral element is used to model a uniform composite beam segment with a single delamination, irrespective of its length, by only specifying the delamination location and size. A damage force indicator is used to stimulate the identification procedure. In a realistic identification task, the advantage of the proposed procedure is that only two measurement nodes are sufficient as opposed to several measurement nodes in a standard finite element model with a single delamination. For multiple delaminations, the computation time to perform the identification task shows cubic polynomial complexity and hence is tractable for health monitoring of large skeletal structures. Sensitivity of a damage force indicator with respect to variations in delamination location and size ...

Identification of Delamination in a Composite Beam Using a Damaged Spectral Element

A hierarchical Genetic Algorithm (GA) is implemented in a high performance spectral finite element software foridentification of delaminations in laminated composite beams. In smart structural health monitoring, the num-ber of delaminations (or any other modes of damage) as well as their locations and sizes are no way completelyknown. Only known are the healthy structural configuration (mass, stiffness and damping matrices updatedfrom previous phases of monitoring) , sensor measurements and some information about the load environment.To handle such enormous complexity, a hierarchical GA is used to represent heterogeneous population consistingof damaged structures with different number of delaminations and their evolution process to identify the correctdamage configuration in the structures under monitoring. We consider this similarity with the evolution processin heterogeneous population of species in nature to develop an automated procedure to decide on what possibledamaged configuration might have produced the deviation in the measured signals. Computational efficiency ofthe identification task is demonstrated by considering a single delamination. The behaviour of fitness functionin GA, which is an important factor for fast convergence, is studied for single and multiple delaminations.Several advantages of the approach in terms of computational cost is discussed. Beside tackling different othertypes of damage configurations, further scope of research for development of hybrid soft-computing modules arehighlighted.Keywords: Spectral finite element, Damaged spectral element, Waveguide, delamination, GA, Heterogeneouspopulation, Identification, Structural health monitoring

A. Nag

Papers

A spectral finite element with embedded delamination for modeling of wave scattering in composite beams

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

Identification of Delamination in a Composite Beam Using a Damaged Spectral Element

Identification of delaminations in composite: structural health monitoring software based on spectral estimation and hierarchical genetic algorithm