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This paper presents the problem formulation and design of compliant grip-and-move manipulators. Each manipulator is composed of two identical path generating compliant mechanisms such that it can grip an object and convey it from one point to another. The integration of both gripping and moving behaviors within a simple mechanism is accomplished by the use of compliant mechanisms, which generate paths that are symmetric. The automated synthesis of these symmetric path generating mechanisms is by a structural topology optimization approach. The problem of topology optimization of continuum structures is solved using a multiobjective genetic algorithm coupled with a morphological representation of geometry that efficiently defines the variable structural geometry, upon a finite element grid. A graph-theoretic chromosome encoding together with compatible crossover and mutation operators are then applied to form an effective evolutionary optimization procedure. Two designs have been created and are presented in this paper, and some concluding remarks and future work are put forward.

An integrated finite element analysis–evolutionary algorithm simulation approach is proposed in this work to model the density characteristics of the three-dimensional printing, specifically for selective laser sintering process. The approach consists of modeling sintering phenomenon by finite element analysis simulation, which is further fed into an evolutionary algorithm cluster comprising genetic programming. The integrated approach is useful to model the functional relationship of density characteristic of selective laser sintering–fabricated components with respect to laser power, scan velocity and scan spacing. Performance of the proposed model is evaluated against the actual results obtained from the literature. We find that our proposed finite element analysis–evolutionary algorithm model is able to model the selective laser sintering process very well, which can be used to complement the analytically and experimentally obtained results. For the validation of the robustness of the model, we also conducted sensitivity and parametric analyses and investigated the specific influence, and variation, of each of the input process parameters on the density of the selective laser sintering–fabricated component. It was found that scan spacing has the least influence, whereas scan velocity has the highest influence on the density of the selective laser sintering–fabricated component. Non-linear relationships unveiled between the process parameters highlight the capability of the model in simulating the density characteristic of the complex selective laser sintering process in uncertain input conditions. [ABSTRACT FROM AUTHOR]

A novel computational approach is proposed to investigate the shear modulus of graphene nanostructures. In this approach, the factors that affect the shear modulus of graphene structures are analysed using an integrated artificial intelligence (AI) cluster comprising molecular dynamics (MD) and gene expression programming. The MD-based-AI approach has the ability to formulate the explicit relationship of shear modulus graphene nanostructure with respect to aspect ratio, temperature, number of atomic planes and vacancy defects. In addition, the shear modulus of graphene predicted using an integrated MD-based-AI model is in good agreement with that of experimental results obtained from the literature. The sensitivity and parametric analysis were further conducted to find out specific influence and variation of each of the input system parameters on the shear modulus of two graphene structures. It was found that the number of defects has the most dominating influence on the shear modulus of graphene nanostructure. [ABSTRACT FROM PUBLISHER]

An integrated computational approach is proposed to investigate the compressive strength of boron nitride nanotubes (BNNTs). In this approach, an artificial intelligence (AI) cluster comprising of multi-gene genetic programming and molecular dynamics (MD) simulation technique, was specifically designed to formulate the explicit relationship of compressive strength of BNNTs with respect to system aspect ratio (AR), temperature and vacancy defects. It was found that the novel MD based AI model is able to model the compressive strength of BNNTs very well, which is in good agreement with that of experimental results obtained from the literature. Additionally, we also conducted sensitivity and parametric analysis to find out specific influence and variation of each of the input system parameters on the compressive strength of BNNTs. It was found that the AR has the most dominating influence on the compressive strength of BNNTs. [ABSTRACT FROM AUTHOR]