Application of Explicit Computer-Aided Engineering (CAE) Methodology for superior correlation with quasi-static strength-based physical tests under highly non-linear system deformation

Computer-Aided Engineering (CAE) methodologies play a critical role in simulating and correlating structural behavior with the physical tests. Structural analysis in CAE is applied across a wide range of real-world load cases, with fatigue and strength evaluations being widely popular. For strength-based evaluations, CAE provides two primary solution techniques—Implicit and Explicit—each suited to different applications. The Implicit methodology is well suited for quasi-static and linear or mildly nonlinear problems, whereas the Explicit methodology excels in highly nonlinear, dynamic events involving large deformations, fracture, contact, or material failure. Traditionally, Implicit methodology has been the most common and preferred approach for quasi-static strength analysis. While suitable and effective for most cases, this method has limitations when large deformations, excessive permanent sets or material failure are observed in physical tests. Implicit analysis particularly tends to underpredict the key results and cannot model material damage, leading to poor CAE correlation with physical behavior. To address these shortcomings, Explicit analysis has been increasingly explored and adopted for superior correlation with physical tests for its ability to better handle and accurately model highly non-linear behaviors and progressive damage in structural systems. In order to ensure the Explicit analysis methodology effectively captures quasi-static behavior (while maintaining accuracy) by negating the influence of inertia or mass effects, kinetic energy must remain minimal in CAE—ideally less than five percent of the system’s internal or work energy. This paper demonstrates the effective application of Explicit methodology under quasi-static conditions, showing that despite its counterintuitive nature, it provides superior correlation with physical tests by efficiently capturing large deformations, excessive permanent sets, and material damage in highly nonlinear systems while fully honoring quasi-static conditions.