Physics Informed Neural Networks for Linear Elasticity Eigenvalue Problem
December, 2025- PINNs
- Linear Elasticity
From a 1,000-Year-Old Tree to the Stage: The Making of a Taiwan Sacred Wood Violin
367 個小時的琢磨，從大雪山深處一塊帶著裂痕的千年神木，到登上舞台響起琴音的那一刻。這不只是一把樂器的誕生，更是一場傳統工藝的突破。本片記錄了首演前與時間賽跑的極限製作過程，以及運用機器學習進行音色分析與醫學 CT 掃描建模的研究歷程。
影片連結physics-based modeling of instruments often relies on the FEM. However, it is computationally expensive and not flexible. This research proposes a neural network-based surrogate model for predicting the full-field displacement distribution and eigenfrequencies of violin plates. The proposed method does not require high-end GPUs and exhibits strong generalization capabilities and computational efficiency.
