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Implementation and Optimization of Reverse Suspension Structure Design Model Using Deep Learning.

Xiwen Yu1, Kai Wang2, Shaoxuan Wang3

  • 1School of Arts and Media, Hefei Normal University, Hefei, Anhui 230601, China.

Computational Intelligence and Neuroscience
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Summary
This summary is machine-generated.

This study introduces a novel reverse suspension structure design model using deep learning and the finite element method. The model optimizes architectural design for better building performance and efficiency.

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Area of Science:

  • Architectural Engineering
  • Computational Design
  • Structural Optimization

Background:

  • Material design projects face increasing complexity and diversification.
  • Architects require improved design efficiency and optimized results for building structures.
  • Internet of Things (IoT) offers comprehensive perception and intelligent processing capabilities.

Purpose of the Study:

  • To enhance design efficiency and optimize results in complex material design projects.
  • To develop a reliable reverse suspension structure design model for architectural applications.
  • To improve the performance and construction cycle of building structures.

Main Methods:

  • Constructed a reverse suspension structure design model using the finite element method and simulated annealing algorithm.
  • Employed deep learning for performance correction and shell structure optimization.
  • Utilized geographic information system (GIS) for spatial element matching and calculation.
  • Implemented an index construction strategy for data fusion diagnosis.

Main Results:

  • The deep learning-based reverse suspension structure design model proved reliable through physical suspension experiments.
  • Simulation results showed maximum tensile stress of 3.71 MPa and compressive stress of 14.7 MPa.
  • Maximum deformation differences between compressive and tensile stress were 0.07 and 0.11, respectively, within acceptable error ranges.
  • Evolutionary optimization analysis confirmed uniform load distribution, verifying algorithm feasibility.

Conclusions:

  • The developed reverse suspension structure model offers an accurate and feasible design approach for complex building suspension structures.
  • The model can shorten the creation and improvement cycle for such structures.
  • It optimizes both the performance and construction cycle of building structures.