SUMMARYThis paper presents an energy-based characterization technique that stochastically identifies the elastic constants of anisotropic materials by modeling the measurement noise and removing its effect unlike conventional deterministic techniques, which deterministically identify the elastic constants directly from noisy measurements. The technique recursively estimates the elastic constants at every acquisition of measurements using Kalman Filter. Owing to the non-linear expression of the measurement model, a Kalman gain has been newly derived and achieves optimal estimation. Since the variances in addition to the means are computed, the proposed technique can not only identify the elastic constants but also describe their certainty as an additional advantage. The validity of the proposed technique and its superiority to the conventional technique were first demonstrated via parametric studies of low-dimensional problems. The proposed technique was then successfully applied to the identification of elastic constants of an anisotropic material.

A B S T R A C T Experimental and analytical investigations for the low cycle-fatigue life prediction ofGlass-Reinforced Polymer (GRP) in Chopped Strand Mat (CSM) form are studied. Based on the theories of modulus degradation and residual strength degradation, a novel model is proposed for the prediction of progressive stiffness loss in terms of tension-tension fatigue load and the number of cycles. The proposed model involves various loadings and environmental variables, which makes the reliable predictions suitable for structural analysts. Experiments were carried out at room and elevated temperatures to evaluate the validity of the proposed prediction model for the characterisation of temperature-dependent behaviour in fatigue. Predictions using the proposed model are in good agreement with the experiments that justify the use of the model to determine the extent of low-cycle fatigue damage accumulation in GRP-CSM at room and elevated temperatures.Keywords fatigue life prediction; Glass fibres; rate dependence; short fibre composite; temperature dependence. I N T R O D U C T I O NA wide range of structures or components are commonly manufactured using fibre-reinforced polymer composites. The requirements that are not just to enhance operational performance but also to reduce the overall cost have caused widespread use of GRP in CSM form particularly in the maritime industry. It is common to get temperatures in excess of 65 • C on boats with white gel coats, while temperatures up to 85 • C have been measured with red gel coats, and well over 95 • C with black gel coats in the tropics. 1 Despite the fact that gel goats are commonly used to attempt for temperature control in composite bodies, mechanical properties of CSM-GRP at elevated temperature have not been thoroughly investigated. There are essentially three types of fatigue beCorrespondence: G. Prusty. haviour prediction model for composites namely, (a) theories based on conventional S-N curves, (b) theories based on changes in elastic modulus and residual strength, and (c) theories based on actual damage mechanisms. Most of the prediction models developed from these theories have been based on residual strength or residual stiffness. Whitney 1 illustrated a residual strength model for both tensile and compressive strength degradation as competing failure modes. An equation for strength degradation model was developed based on a three parameter Power Law. The suggested prediction model is not able to account for the failure mode with delamination. Hence, if delamination played a significant role in the failure mechanism of a particular composite material, the model would be definitely inadequate to get a reliable prediction. Rotem and Nelson 2 proposed a prediction model that relates the residual strength of composite with a temperature-shifting factor by assuming constant residual

A new technique for accurate and fast characterization of exposure tool imaging performance is presented. It is based on optical measurements of a macroscopically large length of test marks printed in a photoresist in a two-step process. In the first step, the line of the specific critical dimension ͑CD͒ is exposed with energy of one-half the nominal energy for a fully formed image. In the second step, the line of the same CD but with a slightly different orientation is exposed with the same energy as in the first step in such a way that its image superimposes the image exposed in the first step. The length of the resulting test mark is linearly proportional to the width of a line printed in a regular exposure process and is inversely proportional to sin͑␣͒, where 2␣ is an angle between two orientations. The coefficient of proportionality is found to be constant for a given resist process over broad ranges of CD variations caused by defocusing, aberrations, exposure dose change, etc. The mark length is measured rapidly with high accuracy by an optical scanning system and the result is then converted into the CD value. A measurement precision ͑3͒ of 0.5 nm is achieved for sub-150 nm CDs. Results of deep ultraviolet exposure tool characterization at CDs down to 100 nm are presented.

This paper presents and reviews an online methodology which characterizes materials using full-field strain measurement. The proposed methodology utilizes the principle of conservation of energy and formulates both the deterministic technique based on the pseudoinverse analysis and the stochastic technique based on the Kalman filter in terms of recursive linear equations. The methodology further describes the derivation the average Frobenius norm and the differential entropy as recursively computable measures enabling the evaluation of the well-posedness of the material characterization problem as well as the uncertainty of the identified constants. Comparative studies have identified that the deterministic identification is a particular case of the stochastic identification, whilst the adequacy and significance of both the average Frobenius norm and the differential entropy was reconfirmed.