4 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
Point-DeepONet: Predicting Nonlinear Fields on Non-Parametric Geometries under Variable Load Conditions
Jangseop Park, Namwoo Kang
Nonlinear structural analyses in engineering often require extensive finite element simulations, limiting their applicability in design optimization and real-time control. Conventi…
Physics-Constrained Graph Neural Networks for Spatio-Temporal Prediction of Drop Impact on OLED Display Panels
Jiyong Kim, Jangseop Park, Nayong Kim +5
This study aims to predict the spatio-temporal evolution of physical quantities observed in multi-layered display panels subjected to the drop impact of a ball. To model these comp…
Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction
Jangseop Park, Namwoo Kang
In engineering design, surrogate models are widely employed to replace computationally expensive simulations by leveraging design variables and geometric parameters from computer-a…
DeepJEB: 3D Deep Learning-based Synthetic Jet Engine Bracket Dataset
Seongjun Hong, Yongmin Kwon, Dongju Shin +2
Recent advances in artificial intelligence (AI) have impacted various fields, including mechanical engineering. However, the development of diverse, high-quality datasets for struc…
Learning Design Preferences through Design Feature Extraction and Weighted Ensemble
Dongju Shin, Sunghee Lee, Namwoo Kang
Design is a factor that plays an important role in consumer purchase decisions. As the need for understanding and predicting various preferences for each customer increases along w…