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Nurwin Adam G. Muhammad
1) Department of Civil Engineering, Western Mindanao State University, Zamboanga City 7000, Philippines. 2) Graduate School, Mindanao State University–Iligan Institute of Technology, Philippines, Iligan City 9200
Civil Engineering, Building, Construction & Architecture

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CFD-Based PSO Optimization of Bamboo Roof Trusses Under Wind Loading Nurwin Adam G. Muhammad; Jerson N. Orejudos; Mary Joanne C. Aniñon; Lessandro Estelito O. Garciano
Civil Engineering Journal Vol. 12 No. 5 (2026): May
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2026-012-05-023

Abstract

Bamboo roof trusses are promising for low-carbon housing, but their performance under strong wind is highly influenced by roof geometry. This study developed a coupled computational fluid dynamics (CFD) and particle swarm optimization (PSO) framework to optimize a bamboo Howe roof truss under extreme wind loading. The objective was to reduce the maximum member utilization by finding a roof-truss geometry that responds efficiently to geometry dependent wind effects. For each candidate geometry, ANSYS SpaceClaim and ANSYS Fluent were used to update the roof profile and compute the wind-induced force resultants acting on the roof surfaces. These force resultants, together with roof and ceiling dead loads, were then applied to a MATLAB two-dimensional frame model to calculate member forces, deflections, and utilization ratios. The PSO run converged after 660 objective-function evaluations over 22 iterations using 30 particles per iteration. The optimized truss had a ridge height of hr = 2.079 m, r1 = 0.324, and r2 = 0.487, giving a maximum member utilization of 0.116, small deflection, and a truss volume of approximately 0.05 m³. Compared with the best solution in the first iteration, the optimized design reduced maximum utilization by 37%. The main contribution of this study is the integration of CFD derived wind loading with PSO-based bamboo truss optimization, allowing both wind demand and structural response to be updated during the search process.
Co-Authors Jerson N. Orejudos Lessandro Estelito O. Garciano Mary Joanne C. Aniñon