Copertina

TOaCNN: Adaptive Convolutional Neural Network for Multidisciplinary Topology Optimization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chadha, Khaish Singh, Kumar, Prabhat
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

PyTOaCNN: Topology optimization using an adaptive convolutional neural network in Python
di: Chadha, Khaish Singh, et al.
Pubblicazione: (2024)

GO-GAN: Geometry Optimization Generative Adversarial Network for Achieving Optimized Structures with Targeted Physical Properties
di: Padmaprabhan, A., et al.
Pubblicazione: (2025)

SoRoTop: a hitchhiker's guide to topology optimization MATLAB code for design-dependent pneumatic-driven soft robots
di: Kumar, Prabhat
Pubblicazione: (2024)

TOPress3D: 3D topology optimization with design-dependent pressure loads in MATLAB
di: Kumar, Prabhat
Pubblicazione: (2024)

Topology optimization of contact-aided compliant mechanisms for tracing multi-kink paths
di: Kumar, Prabhat, et al.
Pubblicazione: (2024)

Normalized field product approach: A parameter-free density evaluation method for close-to-binary solutions in topology optimization with embedded length scale
di: Singh, Nikhil, et al.
Pubblicazione: (2024)

TOPress: a MATLAB implementation for topology optimization of structures subjected to design-dependent pressure loads
di: Kumar, Prabhat
Pubblicazione: (2023)

Partitioned Surrogates and Thompson Sampling for Multidisciplinary Bayesian Optimization
di: Baars, Susanna, et al.
Pubblicazione: (2024)

PyHexTop: a compact Python code for topology optimization using hexagonal elements
di: Agarwal, Aditi, et al.
Pubblicazione: (2023)

VoroTO: Multiscale Topology Optimization of Voronoi Structures using Surrogate Neural Networks
di: Padhy, Rahul Kumar, et al.
Pubblicazione: (2024)

Graph Neural Network-Based Topology Optimization for Self-Supporting Structures in Additive Manufacturing
di: Tabarraei, Alireza, et al.
Pubblicazione: (2025)

PyTOPress: Python code for topology optimization with design-dependent pressure loads
di: Saxena, Shivajay, et al.
Pubblicazione: (2024)

A Dual Physics-Informed Kolmogorov-Arnold Neural Network Framework for Continuum Topology Optimization
di: Zhang, Junyuan, et al.
Pubblicazione: (2026)

Neural Level Set Topology Optimization Using Unfitted Finite Elements
di: Mallon, Connor N., et al.
Pubblicazione: (2023)

Enhancing Smart Grids with Internet of Energy: Deep Reinforcement Learning and Convolutional Neural Network
di: Ruzbahani, Ali Mohammadi
Pubblicazione: (2024)

A Novel Shortest Path Query Algorithm Based on Optimized Adaptive Topology Structure
di: Fang, Xiao, et al.
Pubblicazione: (2024)

TOFLUX: A Differentiable Topology Optimization Framework for Multiphysics Fluidic Problems
di: Padhy, Rahul Kumar, et al.
Pubblicazione: (2025)

MOTO: Topology Optimization for Large Deformations via an Implicit Material Point Method
di: Padhy, Rahul Kumar, et al.
Pubblicazione: (2026)

A Multi-Period Topology and Design Optimization Approach for District Heating Networks
di: Wack, Yannick, et al.
Pubblicazione: (2024)

Option Pricing with Convolutional Kolmogorov-Arnold Networks
di: Li, Zeyuan, et al.
Pubblicazione: (2024)

Transformer-based Topology Optimization
di: Lutheran, Aaron, et al.
Pubblicazione: (2025)

Latent Space Diffusion for Topology Optimization
di: Lutheran, Aaron, et al.
Pubblicazione: (2025)

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization
di: Yang, Shaoliang, et al.
Pubblicazione: (2026)

Superstructure Optimization with Embedded Neural Networks for Sustainable Aviation Fuel Production
di: Klimek, Alexander, et al.
Pubblicazione: (2025)

Variational Quantum Latent Encoding for Topology Optimization
di: Tabarraei, Alireza
Pubblicazione: (2025)

Multi-Patch Isogeometric Convolution Hierarchical Deep-learning Neural Network
di: Zhang, Lei, et al.
Pubblicazione: (2024)

Synthetic Data for Discriminating Serotonergic Neurons using Convolutional Neural Networks
di: Corradetti, Daniele, et al.
Pubblicazione: (2024)

Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions
di: Rane, Chinmay, et al.
Pubblicazione: (2023)

Adaptive Coordinate Transforms for Neural Operators
di: Liu, Chaoyu, et al.
Pubblicazione: (2026)

Stress-constrained Topology Optimization for Metamaterial Microstructure Design
di: Chen, Yanda, et al.
Pubblicazione: (2026)

NITO: Neural Implicit Fields for Resolution-free Topology Optimization
di: Nobari, Amin Heyrani, et al.
Pubblicazione: (2024)

Gaussian Ensemble Topology (GET): A New Explicit and Inherently Smooth Framework for Manufacture-Ready Topology Optimization
di: Ma, Xinyu, et al.
Pubblicazione: (2025)

Data-Driven Topology Optimization for Multiscale Biomimetic Spinodal Design
di: Deng, Shiguang, et al.
Pubblicazione: (2025)

Yield and Buckling Stress Limits in Topology Optimization of Multiscale Structures
di: Christensen, Christoffer Fyllgraf, et al.
Pubblicazione: (2025)

A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty
di: Singh, Pratyush Kumar, et al.
Pubblicazione: (2024)

A Generative Adversarial Graph Neural Network for Synthetic Time Series Data
di: Gregnanin, Marco, et al.
Pubblicazione: (2026)

Convolutional Hierarchical Deep Learning Neural Networks-Tensor Decomposition (C-HiDeNN-TD): a scalable surrogate modeling approach for large-scale physical systems
di: Guo, Jiachen, et al.
Pubblicazione: (2024)

The Statistical Significance of the Inclusion of Graph Neural Networks in the Financial Time Series Forecasting Problem
di: Gregnanin, Marco, et al.
Pubblicazione: (2026)

Physics-Informed Transformer for Real-Time High-Fidelity Topology Optimization
di: Lutheran, Aaron, et al.
Pubblicazione: (2026)

Comparative Analysis of Compliance-Matrix Induced Norms in Structural Topology Optimization
di: Nayak, Jyotiranjan, et al.
Pubblicazione: (2026)