Fatigue Strength and Life Prediction of Forged Steel Crankshaft by Using Fracture Mechanics Approach 2013-26-0141

Crankshaft is one of the critical components of an IC engine, failure of which may result in disaster and makes engine useless unless costly repair performed. It possesses intricate geometry and while operation experiences complex loading pattern. In diesel engines, the transient load of cylinder gas pressure is transmitted to crankshaft through connecting rod, which is dynamic in nature with respect to magnitude and direction. However, the piston along with connecting rod and crankshaft illustrate respective reciprocating and rotating system of components. The dynamic load and rotating system exerts repeated bending and shear stress due to torsion, which are common stresses acting on crankshaft and mostly responsible for crankshaft fatigue failure. Hence, fatigue strength and life assessment plays an important role in crankshaft development considering its safety and reliable operation. The present paper is based on comparative studies of two methods of fatigue life assessment of a single cylinder diesel engine crankshaft by using fracture mechanics approach viz. Linear Elastic Fracture Mechanics (LEFM) and recently developed Critical Distance Approach (CDA). These methods predict crack growth, time required for failure and other parameters essential in life assessment. LEFM is an analytical method based on stress intensity factor which characteristics the stress distribution in the vicinity of crack tip, where as CDA is a group of methods predicts failure using stress distance plot. The maximum stress value required for both the methods are obtained using FEA. The present paper provides an insight of LEFM and CDA methods along with its benefits to the designers to correctly assess the life of crankshaft at early stage of design. This paper also gives a detailed overview of failure analysis process including theoretical methods and result integration for predicting life of components as compared to life estimation by means of software.