Computational mechanics, Finite element technology, Structural optimization, Design automation.
Automation in Structural Design
Structural design can be classified into several design tasks. These tasks need different degrees of human intuition. Those design tasks that require little human intuition and can be systematically written as algorithms may be easily delegated to computers. In contrast, other design tasks that require a lot of human intuition and do not have clear algorithms cannot be done without designers’ experiences. Although it may seem that some of the heuristic design tasks are not difficult and can be handled quite easily even by engineers, in practice, these easy tasks unfortunately prevent the whole design process from being completely automated. In this research area, artificial intelligence (AI) and other advanced computing technologies will be used to remove these hindrances, created by heuristic design tasks, in order that complete structural design automation can be developed.
Advanced Finite Element Analysis
It can be safely said that the finite element method (FEM) is currently the best method for solving mechanical problems. The method has been continuously developed and its progress is quite noticeable. Nevertheless, the development of FEM has been mainly concentrated on the theoretical part of the method. It is now time to integrate new computing technologies with FEM in order that advanced finite element analysis can be performed with ease. In this research area, advanced computing technologies, such as new programming technologies, artificial intelligence, information technologies, and database technologies, will be used to improve the performance and usability of FEM.
Doctoral Theses Supervised | |
2020: | Vo, Duy. Geometrically nonlinear multi-patch isogeometric analysis of beams: Timoshenko and Euler-Bernoulli beam theories. |
2019: | Shakya, Alin. Truss topology optimization with a prescribed maximum number of elements. |
2019: | Suttakul, Pana. Effective out-of-plane rigidities and weight efficiency of thin 2D-lattice plates. |
2016: | Theerakittayakorn, Kasem. Investigation of effective elastic properties of frame-like periodic cellular solids by strain-energy-based homogenization. |
2010: | Nimtawat, Anan. Layout design of beam-slab floors using a genetic algorithm. |
2009: | Chaichanasiri, Ekachai. A study on mechanical behavior of bone surrounding a dental implant by finite element contact analysis. |
2008: | Soparat, Preecha. Analysis of crack growth in concrete by the element-free Galerkin method. |
Master Theses Supervised | |
2019: | Chorn, Vithearin. An isogeometric conforming Kirchhoff plate element using rational Bézier basis functions. |
2019: | Hou, Phirun. A hybrid particle-swarm-teaching-learning-based algorithm for truss topology optimization. |
2019: | Nghi, Duong Huu. Truss topology optimization by a statistical firefly algorithm. |
2017: | Vo, Duy. A 2D field-consistent rational Bézier beam element for large displacement analysis. |
2016: | Lean, Chantrea. Truss optimization using symbolic finite element solutions. |
2015: | Sam, Pisith. Symbolic-numerical object-oriented finite element programming. |
2015: | Petprakob, Wasuwat. Beam-slab floor optimization using genetic and particle swarm optimization algorithms. |
2010: | Chantarapanich, Nattapon. Determination of the correction angle for the treatment of early state knee osteoarthritis by the high tibial osteotomy. |
2009: | Kahatadeniya, Kanchana Suranga. Determination of the critical failure surface for slope stability analysis using ant colony optimization. |
2005: | Vu, Long Nhu. A 2D field-consistent beam element for large displacement analysis using the total Lagrangian formulation. |
2004: | Nimityongskul, Nont. An ant colony optimization algorithm for sizing optimization of structures. |
2003: | Somprasert, Chantima. An object-oriented model for combined implementation of the finite element and meshless methods. |
2001: | Thanyakriengkrai, Yupaporn. Neural networks for structural design optimization using genetic algorithms. |
2001: | Thitawat, Vasan. Stability and bifurcation analysis of crack patterns in quasi-brittle materials. |
2000: | Soparat, Preecha. A mixed finite element formulation for analysis of cracking localization in quasi-brittle materials. |
2000: | Meesomklin, Konlakarn. A novel penalty scheme in genetic algorithms for structural design optimization. |
1998: | Petcherdchoo, Aruz. Analysis of cracking localization in quasi-brittle materials using the smeared crack approach. |
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