Efficient meta-heuristic mesh adaptation strategies for NURBS upper–bound limit analysis of curved three-dimensional masonry structures

• Published in: Computers & structures Vol. 236; p. 106271
• Main Authors: Grillanda, Nicola, Chiozzi, Andrea, Milani, Gabriele, Tralli, Antonio
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.08.2020; Elsevier BV
• Subjects: Adaptation; Algorithms; Bearing capacity; Collapse load; Environment models; Failure mechanisms; Finite element method; Genetic algorithm; Genetic algorithms; Heuristic; Heuristic methods; Limit analysis; Load bearing elements; Masonry; Masonry vaults; Meta-heuristic algorithms; NURBS; Particle swarm optimization; Prey predator algorithm; Three dimensional analysis; Upper bounds; Vaults; Meta-heuristic algorithms; Masonry vaults; Genetic algorithm; Limit analysis; Masonry; Prey predator algorithm; NURBS
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2020.106271

•Adaptive NURBS-based limit analysis allows fast assessment of general masonry structures.•Several meta-heuristic mesh adaptation schemes are proposed for the analysis of masonry vaults.•A new, specifically tailored, Prey Predator Algorithm (PPA) is presented.•The high efficiency of the proposed schemes is illustrated by means of numerical examples. We propose a new adaptive NURBS upper-bound limit analysis approach for the assessment of general three-dimensional curved masonry structures, based on different meta-heuristic mesh adaptation schemes. The method, which can easily be integrated within CAD modeling environments, allows to establish the actual failure mechanism and load bearing capacity of a masonry structure by iteratively adjusting a tentative pattern of yield lines, defined upon a suitable initial mesh of NURBS rigid elements, by means of a suitable meta-heuristic algorithm which searches for the minimum collapse load multiplier, thus enforcing the upper-bound theorem of limit analysis. In particular, we investigate and discuss the efficiency of several meta-heuristic algorithms in delivering the optimal solution: a specifically devised Prey Predator Algorithm (PPA) is compared with the Particle Swarm Optimization (PSO) Algorithm, the Firefly Algorithm (FA) and a suitable Genetic Algorithm (GA). Four masonry vaults have been chosen as case studies. In particular, the modified PPA proves to be the most efficient mesh-adjustment scheme for the proposed adaptive NURBS-based limit analysis procedure.