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The next frontier involves using benchmarks and simulation data to train AI systems. Researchers have developed , a deep-learning framework that uses a crack index to discover crack-free designs before a part is ever built. The system optimizes the design's shape, balancing weight and functionality, while avoiding the stress concentrations that lead to cracking. PATO demonstrates that a deep understanding of superposition-based failure criteria can be embedded directly into the generative design process. superposition benchmark crack free