Dual HRKAN framework (DPIKAN-TO) for topology optimization with one network predicting displacements and another handling sensitivity-based design updates.
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7 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
A fused gather-GEMM-scatter CUDA kernel achieves 4.6-7.3x end-to-end speedup and 3.2-4.9x lower energy for matrix-free 3D SIMP topology optimization on RTX 4090 compared to three-stage baselines.
An LLM acting as real-time controller for SIMP topology optimization parameters outperforms fixed schedules and heuristics, delivering 5.7-18.1% lower compliance on 2D and 3D benchmarks.
Method for generating minimum-weight structurally robust shell objects from 3D models using Laplacian parametrization to ensure intersection-free inner boundaries during stress-based thickness optimization.
IterSIMP-σ integrates multimodal LLMs for proposing spatial density interventions in stress-aware SIMP topology optimization, yielding comparable but statistically non-significant performance gains over rule-based baselines on 2D and 3D benchmarks.
A sequential topology optimization approach uses SIMP results to initialize level-set refinement via signed distance function transfer on 3D meshes, achieving comparable compliance with up to 4.6x speedup on benchmarks.
citing papers explorer
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A Dual Physics-Informed Kolmogorov-Arnold Neural Network Framework for Continuum Topology Optimization
Dual HRKAN framework (DPIKAN-TO) for topology optimization with one network predicting displacements and another handling sensitivity-based design updates.
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Matrix-Free 3D SIMP Topology Optimization with Fused Gather-GEMM-Scatter Kernels
A fused gather-GEMM-scatter CUDA kernel achieves 4.6-7.3x end-to-end speedup and 3.2-4.9x lower energy for matrix-free 3D SIMP topology optimization on RTX 4090 compared to three-stage baselines.
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Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization
An LLM acting as real-time controller for SIMP topology optimization parameters outperforms fixed schedules and heuristics, delivering 5.7-18.1% lower compliance on 2D and 3D benchmarks.
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Structural Design Using Laplacian Shells
Method for generating minimum-weight structurally robust shell objects from 3D models using Laplacian parametrization to ensure intersection-free inner boundaries during stress-based thickness optimization.
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IterSIMP-{\sigma}: Evaluating LLM-Assisted Spatial Interventions in Stress-Aware Topology Optimization
IterSIMP-σ integrates multimodal LLMs for proposing spatial density interventions in stress-aware SIMP topology optimization, yielding comparable but statistically non-significant performance gains over rule-based baselines on 2D and 3D benchmarks.
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Sequential topology optimization: SIMP initialization for level-set boundary refinement
A sequential topology optimization approach uses SIMP results to initialize level-set refinement via signed distance function transfer on 3D meshes, achieving comparable compliance with up to 4.6x speedup on benchmarks.
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