2 citations · 2 across the 6 of their papers we have counts for
7 papers
A comprehensive comparison of neural operators for 3D industry-scale engineering designs
Weiheng Zhong, Qibang Liu, Diab Abueidda +2
Neural operators have emerged as powerful tools for learning nonlinear mappings between function spaces, enabling real-time prediction of complex dynamics in diverse scientific and…
Sequential Neural Operator Transformer for High-Fidelity Surrogates of Time-Dependent Non-linear Partial Differential Equations
Qibang Liu, Seid Koric
Partial differential equations (PDEs) are fundamental to modeling complex and nonlinear physical phenomena, but their numerical solution often requires significant computational re…
Towards Signed Distance Function based Metamaterial Design: Neural Operator Transformer for Forward Prediction and Diffusion Model for Inverse Design
Qibang Liu, Seid Koric, Diab Abueidda +2
The inverse design of metamaterial architectures presents a significant challenge, particularly for nonlinear mechanical properties involving large deformations, buckling, contact,…
Geometry-Informed Neural Operator Transformer
Qibang Liu, Weiheng Zhong, Hadi Meidani +3
Machine-learning-based surrogate models offer significant computational efficiency and faster simulations compared to traditional numerical methods, especially for problems requiri…
Effects of Prompt Length on Domain-specific Tasks for Large Language Models
Qibang Liu, Wenzhe Wang, Jeffrey Willard
In recent years, Large Language Models have garnered significant attention for their strong performance in various natural language tasks, such as machine translation and question…
Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing
Qibang Liu, Pengfei Cai, Diab Abueidda +4
Under some initial and boundary conditions, the rapid reaction-thermal diffusion process taking place during frontal polymerization (FP) destabilizes the planar mode of front propa…
Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier
Jaewan Park, Shashank Kushwaha, Junyan He +4
Metamaterials, synthetic materials with customized properties, have emerged as a promising field due to advancements in additive manufacturing. These materials derive unique mechan…