Modelling and simulation tools are valuable resources for engineers in many different fields. The broad goal across engineering models is usually the same: to provide realistic predictions of what will occur in actual application conditions. In the surface enhancement world, we have been using assorted models for a long time. Shot peening providers have correlated Almen intensity to estimate residual stress values in alloys for many years, which is, in fact, a type of model. The sophistication of models has grown substantially over the past 15 years, and there are now many different options available to owners of the processes and outside engineers interested in using the processes on their components.
Many of the recent advancements in modelling of engineering processes have come from using the finite element method to simulate application of the surface enhancement treatments to a component. The finite element method permits local assessment of surface enhancement process effects quickly and efficiently. It also has the benefit of often providing easily interpreted graphical charts depicting the results of the modelling efforts. Many options and combinations of finite element models for surface enhancement processes are available. The different options typically use various assumptions, conditions, and input requirements, and often have distinctive levels of complexity and other resource requirements. Most of the relevant surface enhancement process models combine intensity and coverage into predictions of residual stress depth and magnitude. Models can be based on dynamic events, such as the physical impact a surface sustains from shot media or a pressure spike from laser peening, or on a static analysis, such as the residual stresses generated by known processes for known materials.
In my experience, the eigenstrain method of finite element modelling in a static analysis provides the greatest and most efficient benefits for me as an engineer and our customers. Eigenstrain modelling allows for evaluation of residual stress fields in complex geometries, locates peak compensating stresses, predicts the amount of deformation that will occur, and permits multi-loading simulations to evaluate expected in-service improvements from processing.
Eigenstrain refers to internal permanent strain in the material, which in our case, is the strain created by laser peening. However, the term and modelling are applicable to other processes as well. Residual stresses generated in a processed material are generated by plastic strains from the laser peening process (eigenstrains) and elastic strains from the material response to the laser peened area. Model calibrations are usually based on measured residual stress data, but they can also be developed via dynamic finite element modelling. Once these laser-peened material models are developed, they become independent of specific component geometry and, for the most part, thickness. These calibrated models are then loaded into a library and used in specific application development. When inserted into the processed area on a part geometry of interest, the residual stress field equilibrates to the part geometry. This method reduces the development cycle for customers by decreasing time and cost that may otherwise be associated with iterative testing and demonstration of the process.
While modelling of surface enhancement processes has many advantages, there are some challenges associated with implementing it. The upfront effort required by organizations to obtain modelling capabilities often has significant costs associated with it. Usually there are substantial upfront costs to acquire commercial finite element modelling software. There are other resource concerns including who will be using the software and what the training costs associated with their technical needs are. Once the Finite Element Analysis (FEA) capability has been established, development of models, such as an eigenstrain library, can begin but often requires additional data that must be either experimentally determined or harvested from technical libraries or other sources. While these challenges are not insurmountable, they can pose significant hurdles to wider adoption of surface enhancement process modelling. 
The importance of modelling in the surface enhancement world is expected to only increase as customers look to new and improved ways to reduce their part life cycle costs. A key aspect of this growth is not only that the surface enhancement providers develop the modelling capability, but that the capability expands to engineers designing the components. The technological flow path thus far has largely been from the academic level to process suppliers and technical firms. Ultimately, the modelling capability needs to reach design engineers, where it allows conscientious, up-front application of the surface enhancement technologies to improve on part design.

For questions contact: stan@mfn.li

Author: Stan Bovid