Executive Summary : | Fatigue is very common mode of failure in many engineering applications and accounts for nearly 90% of all failures, including some catastrophic events. Therefore it is crucial to consider and understand fatigue crack initiation and growth and design materials which are able to withstand high temperatures and are resistant to fatigue among other extreme enviromental factors. For example, in jet engines in modern aircrafts and turbine blades used in power generation industry, the efficiency increases significantly with rise in operating temperatures. Over the last 70 years, many high temperature, fatigue resistant materials have been designed for such applications, which include steel, titanium alloys and nickel based superalloys. Recently, High Entropy Alloys (HEAs) have been developed which are composed of atleast 4-5 metals to create materials of certain favourable characteristics, which include high toughness, high melting point, lightweight, low cost and high conductivity. Due to these properties, they have been found to be ideal candidates for use in jet engines and turbine blades which are exposed to severe fatigue loading. The reason for the recent growth in the field of HEAs is the development of new computational techniques, which can simulate and predict the properties of a potential alloy before experiments are done. This eliminates the need for a trial and error process and accelerates material development. In this project, we will aim to develop a computational tool to predict the initiation and growth of cracks in HEAs under low cycle fatigue. We will utilize a technique called Discrete Dislocation Dynamics (DDD) which is a popular physics-based mesoscale modelling technique used to predict the evolution of a (3D) network of dislocations under varying external conditions such as temperature and applied stress among others. It avoids the use of phenomenological variables typically used in continuum models such as the Crystal Plasticity Finite Element method. Meanwhile, it is also not limited in the length and time scales that characterize Molecular Dynamics simulations. Thus, it stands at the right lengthscale to model fatigue cracks and failure. In this project, we will couple DDD with a dislocation representation of cracks to demonstrate a meshless method of predicting fatigue crack growth. This will also enable us to study interaction between crack growth and crystal deformation using DDD. To the knowledge of the PI, such models do not exist presently. Moreover, the various primary mechanisms by which such cracks propagate at the microscale will also be revealed. Since fatigue failure is a microstructure sensitive phenomenon, this will accelerate fatigue resistant material design. A detailed methodology and work plan is provided in the Technical Document. |