arXiv subjects

Shuji Moriguchi

Publications and source records attributed to Shuji Moriguchi.

3 recordsLinked to original sources

arXiv2025

An Efficient Quantum Approximate Optimization Algorithm with Fixed Linear Ramp Schedule for Truss Structure Optimization

This study proposes a novel structural optimization framework based on quantum variational circuits, in which the multiplier acting on the cross-sectional area of each rod in a truss structure as an updater is used as a design variable. Specifically, we employ a classical processor for structural analysis with the finite element method, and the Quantum Approximate Optimization Algorithm (QAOA) is subsequently performed to update the cross-sectional area so that the compliance is minimized. The advantages of this framework can be seen in three key aspects. First, by defining design variables as multipliers, rather than simply reducing the design variable to a binary candidate of inclusion or exclusion (corresponding to qubit states, ``0" and ``1"), it provides greater flexibility in adjusting the cross-sectional area of the rod at each iteration of the optimization process. Second, the multipliers acting on rods are encoded with on-off encoding, eliminating additional constraints in the convergence judgement. As a result, the objective function is in a simple format, enabling efficient optimization using QAOA.Third, a fixed linear ramp schedule (FLRS) for variational parameter setting bypasses the classical optimization process, thereby improving the operational efficiency of the framework. In the two structural cases investigated in this study, the proposed approach highlights the feasibility and applicability potential of quantum computing in advancing engineering design and optimization. Numerical experiments have demonstrated the effectiveness of this framework, providing a firm foundation for future research on quantum-assisted optimization methods in engineering fields.

quant-ph↗

arXiv2024

On the performance of sequential Bayesian update for database of diverse tsunami scenarios

Although the sequential tsunami scenario detection framework was validated in our previous work, several tasks remain to be resolved from a practical point of view. This study aims to evaluate the performance of the previous tsunami scenario detection framework using a diverse database consisting of complex fault rupture patterns with heterogeneous slip distributions. Specifically, we compare the effectiveness of scenario superposition to that of the previous most likely scenario detection method. Additionally, how the length of the observation time window influences the accuracy of both methods is analyzed. We utilize an existing database comprising 1771 tsunami scenarios targeting the city Westport (WA, U.S.), which includes synthetic wave height records and inundation distributions as the result of fault rupture in the Cascadia subduction zone. The heterogeneous patterns of slips used in the database increase the diversity of the scenarios and thus make it a proper database for evaluating the performance of scenario superposition. To assess the performance, we consider various observation time windows shorter than 15 minutes and divide the database into five testing and learning sets. The evaluation accuracy of the maximum offshore wave, inundation depth, and its distribution is analyzed to examine the advantages of the scenario superposition method over the previous method. We introduce the dynamic time warping (DTW) method as an additional benchmark and compare its results to that of the Bayesian scenario detection method.

cs.CE↗

arXiv2024

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

This paper presents a novel design update strategy for topology optimization, as an iterative optimization. The key contribution lies in incorporating a design updater concept with quantum annealing, applicable to both truss and continuum structures. To align with density-based approaches in topology optimization, these updaters are formulated through a multiplicative relationship to represent the design material and serve as design variables. Specifically, structural analysis is conducted on a classical computer using the finite element method, while quantum annealing is utilized for topology updates. The primary objective of the framework is to minimize compliance under a volume constraint. An encoding formulation for the design variables is derived, and the penalty method along with a slack variable is employed to transform the inequality volume constraint. Subsequently, the optimization problem for determining the updater is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) model. To demonstrate its performance, the developed design framework is tested on different computing platforms to perform design optimization for truss structures, as well as 2D and 3D continuum structures. Numerical results indicate that the proposed framework successfully finds optimal topologies similar to benchmark results. Furthermore, the results show the advantage of reduced time in finding an optimal design using quantum annealing compared to simulated annealing.

cs.CE↗