A B S T R A C T In this study, the effects of plasticity-induced crack closure and overloads were investigated using thermoelastic stress analysis (TSA) in aluminum alloy 2024. The amplitude of the stress intensity factors were evaluated during crack growth by fitting a Muskhelishvili-type description of the crack tip stress fields to the TSA data using the multipoint overdeterministic method. A new method to directly measure the extent of the crack tip plastic zone is proposed based on the phase difference between the TSA and forcing signals. The presence of crack tip plasticity was clearly identified and correlated with changes in the stress intensity factor values obtained from the TSA data both during constant amplitude loading as well as single and multiple overloads. Immediately post-overload the plastic zone increased in size by up to 50% whereas the amplitude of the stress intensity factor and the crack growth rate decreased until the crack grew through the plastic region created by the overload when the pre-overload value of the crack growth was re-attained. The experimental data of mode I stress intensity factor, crack growth rate and radius of crack tip plastic zone obtained from thermoelastic data in the region affected by the overload were used to estimate the exponent in the Wheeler crack growth model which was found to be a function of percentage overload and the number of cycles of overload. a = crack length A = thermoelastic calibration constant C = Paris empirical constant C ε = specific heat at constant strain C p = specific heat at constant pressure e = surface emissivity K I = mode I stress intensity factor K II = mode II stress intensity factor m = wheeler empirical exponent n = Paris empirical exponent N = number of cycles Q = heat input r p = radius of crack tip plastic region R = ratio of σ min to σ max S = thermoelastic signal S max = maximum thermoelastic signal per row of pixels T = absolute temperature α = linear coefficient of thermal expansionCorrespondence: Amol Patki.

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The achievement of high levels of confidence in finite element models involves their validation using measured responses such as static strains or vibration mode shapes. A huge amount of data with a high level of information redundancy is usually obtained in both the detailed finite element prediction and the full-field measurements so that achieving a meaningful validation becomes a challenging problem. In order to extract useful shape features from such data, image processing and pattern recognition techniques may be used. One of the most commonly adopted shape feature extraction procedures is the Fourier transform in which the original data may be expressed as a set of coefficients (coordinates) of the decomposition kernels (bases) in the feature space. Localised effects can be detected by the wavelet transform. The acquired shape features are succinct and therefore simplify the model validation, based on the full-field data, allowing it to be achieved in a more effective and efficient way. In this paper, full-field finite element strain patterns of a plate with a centred circular hole are considered. A special set of orthonormal shape decomposition kernels based on the circular Zernike polynomials are constructed by the Gram-Schmidt orthonormalization process. It is found that the strain patterns can suitably be represented by only a very small number of shape features from the derived kernels.

This study focuses on the mechanical response of a particle-reinforced restorative dental composite (Renew™) under proportional transverse confinement to understand the effects of stress multiaxiality on its mechanical and failure behaviors. We describe the confining ring technique as an experimental tool to introduce multiaxial compressive stress states in dental composites that realistically mimic three-dimensional stress states commonly experienced by dental restorations in the oral cavity. Effect of initial radial misfit between confining ring and specimen is analyzed through computational finite element simulations, and an analytical treatment of problem is also provided to compute the confining stress during elasto-plastic expansion of confining ring. Experimental results suggest that inelastic response of Renew composite is significantly influenced by hydrostatic stress component, and pressure-dependent yield functions are required to analyze plastic deformations and internal damage accumulation process.

This study explores the use of a generic shape descriptor for quantitative comparisons between the full-field strain data acquired from virgin and damaged composite panels using digital image correlation. These descriptors are capable of decomposing images with 10 3 to 10 6 pixels into a feature vector with less than a few hundred elements. Strain distributions in four composite specimens with incremental impact damage and a virgin specimen, all subject to a tensile load, were decomposed using the newly developed Fourier-Zernike descriptors. Pearson's correlation coefficient, cosine similarity and Euclidean distance were employed to compare quantitatively the feature vectors evaluated for the strain distributions in the four damaged specimens with the strain distribution in the virgin specimen. The deviation of the Pearson correlation coefficient from unity was found to be an effective damage indicator, which could be evaluated automatically and without the need for subjective assessment of the damage.

Abstract. It is good practice to validate analytical and numerical models used in stress analysis for engineering design by comparison with measurements obtained from real components either in-service or in the laboratory. In reality, this critical step is often neglected or reduced to placing a single strain gage at the predicted hot-spot of stress. Modern techniques of optical analysis allow full-field maps of displacement, strain and, or stress to be obtained from real components with relative ease and at modest cost. However, validations continued to be performed only at predicted and, or observed hot-spots and most of the wealth of data is ignored. It is proposed that image decomposition methods, commonly employed in techniques such as fingerprinting and iris recognition, can be employed to validate stress analysis models by comparing all of the key features in the data from the experiment and the model. Image decomposition techniques such as Zernike moments and Fourier transforms have been used to decompose full-field distributions for strain generated from optical techniques such as digital image correlation and thermoelastic stress analysis as well as from analytical and numerical models by treating the strain distributions as images. The result of the decomposition is 10 1 to 10 2 image descriptors instead of the 10 5 or 10 6 pixels in the original data. As a consequence, it is relatively easy to make a statistical comparison of the image descriptors from the experiment and from the analytical/numerical model and to provide a quantitative assessment of the stress analysis.

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