A novel design update framework for topology optimization with quantum annealing: Application to truss and continuum structures

2024-06-27

Computer Methods in Applied Mechanics and Engineering

AI Summary

Topology optimization suffers from high combinatorial complexity and susceptibility to local optima. Method: This paper proposes a quantum-annealing-integrated structural design update framework applicable to both truss and continuum structures. Quantum annealing is embedded within an iterative optimization loop; binary variable mapping and constraint encoding strategies are devised for compatibility with D-Wave hardware; and sensitivity analysis, the method of moving asymptotes (MMA), and adaptive threshold projection are synergistically coupled for efficient solution. Contribution/Results: On multiple benchmark problems, the proposed method improves convergence stability by over 35% and increases the global optimum attainment rate by a factor of 2.1 compared to conventional approaches. This work presents the first systematic validation of quantum-inspired optimization for engineering structural topology design, demonstrating its feasibility and effectiveness.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Constraint Optimization
• Machine Learning: Quantum Machine Learning

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Web Mining and Content Analysis: Bridging structured and unstructured data
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Problem

• Structural Optimization
• Quantum Computing
• Design Optimization

Innovation

• Quantum Annealing
• Structural Design Optimization
• QUBO Model