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Found 4 papers, 0 papers with code
An Adaptive and Scalable ANN-based Model-Order-Reduction Method for Large-Scale TO Designs
Most models are trained to work with the design problem similar to that used for data generation and require retraining if the design problem changes.
An adaptive artificial neural network-based generative design method for layout designs
In recent years, machine learning methods such as artificial neural networks have been used increasingly to speed up the design process.
BIG-bench Machine Learning
Generative Adversarial Network
+1
Accelerating gradient-based topology optimization design with dual-model neural networks
In this work, neural networks are used as efficient surrogate models for forward and sensitivity calculations in order to greatly accelerate the design process of topology optimization.
Deep learning based inverse method for layout design
Layout design with complex constraints is a challenging problem to solve due to the non-uniqueness of the solution and the difficulties in incorporating the constraints into the conventional optimization-based methods.
