Design for intelligent interaction CAE software: a hybrid recommendation-based approach to improve simulation workflow efficiency

Engineering simulation software, as a core tool in computer-aided engineering (CAE), plays a critical role in supporting industrial design and computational analysis. However, the complexity of its interaction workflows and the cognitive burden on users—especially novices—pose significant challenges to usability and learning efficiency. In response to these limitations, this study proposes the design of an intelligent interactive system for engineering simulation, driven by a hybrid recommendation mechanism. The system aims to reduce users’ cognitive load, streamline the pre-processing phase, and enhance overall simulation workflow efficiency. A mixed-methods approach was adopted, combining a large-scale questionnaire (N = 304) and semi-structured interviews to investigate user satisfaction, interaction preferences, and acceptance of recommendation-based assistance. The results revealed that while traditional CAE interfaces are functional, they impose substantial information overload and learning barriers. To address this, a recommendation-augmented fatigue analysis interaction platform was developed, featuring progressive guidance, context-aware module suggestions, and visual explanations of recommendation logic. A usability evaluation comparing the proposed system with conventional fatigue simulation software demonstrated significant improvements in task efficiency (n = 36), user satisfaction, and perceived control. The findings validate the feasibility and effectiveness of integrating recommendation mechanisms into CAE software from a user-centered perspective. This study contributes a novel design strategy and system prototype for enhancing human–computer interaction in complex engineering domains.