2026 ASEE Annual Conference & Exposition

Use of computational tools, such as engineering simulations, is transforming the healthcare industry through In Silico testing methods. In Silico allows for safer, faster, and cheaper development for applications like drug delivery and medical devices. This industry trend has great implications for university curricula which are already overflowing.

This paper presents the Ansys Academic Healthcare SimLab app, a web-based educational simulation tool that enables biomedical engineering and medical students to explore computational modeling without requiring deep expertise in simulation software. Developed using Dash and PyAnsys, the app addresses the challenge of introducing early-year students to complex simulation workflows by automating geometry generation, meshing, solver setup, and post-processing while maintaining pedagogical focus on interpreting results and understanding physical phenomena. The app's browser-based interface enables remote learning and reduces barriers associated with traditional simulation software training, making these advanced computational tools more accessible.

Key learning objectives for this application include: (1) utilize computational thinking in biomedical contexts, (2) understand the relationship between input parameters and physiological outcomes, (3) implement simulation workflows through an accessible interface, and (4) critically analyze theoretical predictions using computational results.

The accompanying learning activity guides students through three biomedical domains—cardiovascular, respiratory, and bioelectrical systems—where they can modify parameters, run simulations powered by Ansys Fluent and Discovery tools, and compare analytical models with computational results. The app's modular structure supports multiple implementation scenarios including lab replacements, project-based learning, pre/post-class assignments, and inquiry-based "what-if" exploration.

This paper will cover details on implementation details including deployment options, integration with course curricula, student assessment strategies through built-in quizzes, and customization approaches for different institutional contexts. Situational factors affecting tool adoption include software licensing requirements, computational resources, instructor familiarity with simulation tools, and curriculum alignment.