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Fatigue life of a component is influenced by multiple factors like material, manufacturing, load & geometric variations and due to this there is a huge scatter in both test & predicted life through simulations. There are different methods available to account for these variations while predicting fatigue life. However, whenever a fatigue simulation engineer tries to correlate predictions with test outcomes, he/she will face a challenge as to: How to account for scatter in test? How to compare predicted life through simulations with test data? How much difference between test outcome and predictions is acceptable? To address these challenges, authors have suggested two approaches in this paper – 1. Sample to Sample approach and 2. Statistical approach. This paper suggests a set of criteria under both these approaches to conclude confidently that the prediction model is able to match the test outcomes.

Aluminum casting parts generally have inherent internal defects such as porosity which lowers the fatigue strength of such castings. Accounting for such a fatigue strength reduction for Aluminum casted parts is the primary purpose of this paper. Authors have used Murakami et al [1] approach to calculate porosity correction factor for fatigue. The actual material S-N curve is modified using fatigue factors to account for the fatigue strength reduction due to presence of porosity. This approach was then validated on one of the fatigue failure cases on Aluminum casted housing. There was a close match between the test data and proposed approach for fatigue prediction. With this approach, engineers will be able to do fatigue predictions in presence of material defects like porosity with simple porosity correction factor, rather than using complex modeling of porosity in FEA or using detailed fracture mechanics methods.

Real-world bolted connections are subjected to axial, bending and transverse working loads which are mostly difficult to ascertain purely by hand calculations and Free body diagrams (FBDs). VDI 2230 document which is largely followed across the industry for bolted joint assessments, assumes that this load data is readily available to the users. However, that is not always the case. Present work tries to address this aspect of bolted joint assessment by providing physics-based guidelines to ascertain these loads by using Finite Element Tools. Bolted joint phenomenon like Prying effect may be obvious in simple cases, however quantifying this effect in real life problems is quite challenging. Authors have suggested simple, but effective method, to quantify this effect by using Finite Element Analysis (FEA).

The three parameter Ramberg-Osgood (RO) method finds popular usage for extracting complete stress-strain curve from limited data which is usually available. The currently popular practice of assuming the plasticity to set in only at the Yield point provides computational advantage by separating the complete nonlinear curve, obtained from RO method, into elastic and plastic regions. It is shown, with an example problem, that serious errors are committed by using this method if one compares the obtained results with results of complete stress-strain curve. In the present work we propose a simple Taylor series based approach based on RO method to overcome the above deficiency. This method is found to be computationally efficient. The proposed method is applicable for stress-strain curves of materials for which RO method provides a good approximation.