This paper presents an innovative two-level modeling approach for accurately simulating the inductance matrix of induction machines (IMs) under fault conditions. The first level uses Finite Element Method (FEM) simulations to extract the inductance matrix $L(\theta)$ of the healthy machine, achieving high spatial resolution with minimal computational resources. The second level enables the introduction of rotor asymmetry faults using tensor algebra, thus eliminating the need for repeated FEM simulations. This approach enhances the efficiency of fault simulations, making it suitable for real-time diagnostic applications. The model is validated through both steady-state and transient analysis, demonstrating its effectiveness in reproducing fault-related harmonics and offering significant improvements in computational performance compared to traditional time-stepping FEM models.

The rapid integration of generative artificial intelligence (AI) into higher education raises questions about its pedagogical value and its role in sustainability-oriented learning. This study investigates the use of AI in a Challenge-Based Learning (CBL) engineering hackathon (INDUSHack) focused on the Sustainable Development Goals (SDGs), examining patterns of AI adoption, perceived benefits and risks, and its contribution to SDG integration in project design. A descriptive exploratory design was employed, collecting questionnaire data from 60 undergraduate participants and complementing these with expert committee evaluations of project outcomes. Results indicate widespread AI use, primarily for idea generation, information synthesis, and project structuring. Participants reported perceived improvements in efficiency, creativity, and the clarity of SDG alignment; however, difficulties persisted in translating sustainability concepts into measurable, technically grounded criteria. The findings suggest that while AI can support learning processes and sustainability framing in CBL environments, its effective use requires structured guidance and critical AI literacy to ensure meaningful integration of SDGs.