This paper presents the review concerning mechanical properties of bone and the miniature specimen test techniques. For developing a realistic understanding of how factors such as moisture content, mineralization, age, species, location, gender, rate of deformation etc. affect the mechanical properties of bone, it is critical to understand the role of these factors. A general survey on existing research work is presented on this aspect. The essential features of miniature specimen test techniques are described, along with the application of small punch test method to evaluate the mechanical behavior of materials. The procedure for the determination of tensile and fracture properties, such as: yield strength, ultimate strength, ductility, fracture toughness etc. using small punch test technique have been described. The empirical equations proposed by various investigators for the prediction of tensile and fracture properties are presented and discussed. In some cases, the predictions of material properties have been essentially made through the finite element simulation. The finite element simulation of miniature specimen test technique is also covered in this review. The use of inverse finite element procedure for the prediction of uniaxial tensile constitutive behaviour of materials is also presented.Keywords: mechanical properties, compact bone, miniature specimen, small punch test, finite element simulation and inverse finite element procedure.

Abstract.Welding is the process of producing permanent joints with the application of pressure and/or heat energy. During welding operation, weldments may be subjected to uneven thermal stresses. These stresses influence the metallurgical structure of the component. Due to this, the strength of the weld joint is reduced. Therefore, vibratory weld treatment during welding has been proposed in the present work to enhance the flexural and impact strength of weldments. However, it is found that the mechanical properties have shown nonlinear behavior with the chosen input parameters. Hence, an efficient Neural Network (NN) based prediction tool is developed to approximate the mechanical properties of weldments without performing the experiments, output values can be predicted for the given input values. Further, an immune based strategy is integrated to the developed prediction tool in order to obtain desired quality welded joints.