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An inverse finite element algorithm is established to extract the tensile constitutive properties such as Young's modulus, yield strength and true stress–true strain diagram of a material in a virtually non-destructive manner. Standard test methods for predicting mechanical properties require the removal of large size material samples from the in-service component, which is impractical. To circumvent this situation, a new dumb-bell shaped miniature specimen has been designed and fabricated which can be used for evaluation of properties for a material or component. Also test fixtures were developed to perform a tension test on this proposed miniature specimen in a testing machine. The studies have been conducted in low carbon steel, die steel and medium carbon steel. The output from the miniature test, namely, load–elongation diagram, is obtained and used for the proposed inverse finite element algorithm to find the material properties. Inverse finite element modelling is carried out using a 2D plane stress analysis. The predicted results are found to be in good agreement with the experimental results.

The objective of this paper is to delineate a method for determining the yield strength of a material in a virtually nondestructive manner. Conventional test methods for predicting the yield strength require the removal of large material samples from the in-service component, which is impractical. In this paper, the power of neural networks in predicting the yield strength from the data obtained by conducting tension test on newly developed dumb-bell-shaped miniature specimen is demonstrated using the self-organizing capabilities of the ANN. The input to the neural network is the breakaway load obtained from the miniature test, and the output obtained from the model is yield strength value. The value of the yield strength estimated by neural network is found to be in good agreement (<5% error) with that of the actual value from the standard test. The neural network models are convenient and powerful tools for practical applications in solving various problems in engineering.

The present paper describes the method for evaluation of yield strength and fracture toughness of three materials, namely, linepipe steel, aluminum (Al) alloy, and gray cast iron using miniature specimen test. Conventional standard test methods consume more material and money and may damage the integrity of the in-service component. Miniature specimen tests overcome all these demerits. A method is outlined to predict the yield strength and fracture toughness from the miniature test through the empirical relations. The validation of results has been carried out by conducting standard tensile and fracture toughness tests according to ASTM standards. Further, the finite element method has been used to simulate the miniature test. A close agreement is observed between the results of the miniature test and standard tests.