.png){kind=icon}
返回
StructDiffusion: End-to-end intelligent shear wall structure layout generation and analysis using diffusion model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.engstruct.2024.118068.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Shear wall structures are widely used in high-rise buildings. However, the design process of shear wall structures suffers from inefficiencies. This paper introduces StructDiffusion, an end -to -end intelligent system for shear wall layout generation and analysis. The proposed approach tackles the layout design task by employing a novel diffusion model architecture to generate conditional images. Key components of the proposed method include pretrained diffusion models, ControlNet for conditional control, and LoRA for efficient adaptation. Notably, the method allows for architectural plan images and basic textual design conditions as inputs, enabling manipulation of the generated layouts by adjusting attributes such as building height and seismic intensity. To evaluate the quality of the model ' s design swiftly, this paper presents a comprehensive evaluation framework that incorporates perceptual and structural validity metrics. Through experimental analyses, this paper demonstrates the effectiveness of the proposed model in generating layouts, surpassing the capabilities of GAN-based methods. Furthermore, our study investigates model -specific parameter configuration, text -guided capabilities, code compliance, and computational efficiency. StructDiffusion significantly enhances the automation and intelligence of structural engineering workflows. The framework effectively addresses challenges associated with instability, data scarcity, and limitations in assessment. This pioneering application of diffusion models opens up promising avenues for advancing data -driven structural design.
Keyword:
Shear wall layout design
Deep learning
Diffusion model
Automation in structural design
Intelligent structural design
Text guidance generation
期刊
IF:
6.4
论文数:
2.1W
被引数:
8.7W
机构
引用论文
Sensorless Control of Z Source Inverter fed BLDC Motor Drive by FOC - DTC Hybrid Control Strategy Using Fuzzy Logic Controller采用模糊逻辑控制器的foc-dtc混合控制策略的Z源逆变器馈电BLDC电机驱动的无传感器控制
PREAI
分享收藏Self-focusing effects of dispositional self-consciousness, mirror presence, and audience presence.性格自我意识、镜像存在和观众存在的自我聚焦效应。
PREAI
分享收藏A practical shear wall layout optimization framework for the design of high-rise buildings一种实用的高层建筑剪力墙布置优化设计框架.png)
STRUCTURES
OAAI
STRUCTURESIF4.3
OAAI分享收藏Intelligent layout design of curvilinearly stiffened panels via deep learning-based methodMATERIALS & DESIGNOAAI
MATERIALS & DESIGNIF7.9
OAAI分享收藏
查看更多内容