Papers by Foek Tjong Wong
Journal of physics, Sep 1, 2020
This paper focuses on optimizing truss structures while propose best PSO variants. Truss optimiza... more This paper focuses on optimizing truss structures while propose best PSO variants. Truss optimization is one way to make the design efficient. There are three types of optimization, size optimization, shape optimization, and topology optimization. By combining size, shape and topology optimization, we can obtain the most efficient structure. Metaheuristics have the ability to solve this problem. Particle swarm optimization (PSO) is metaheuristic algorithm which is frequently used to solve many optimization problems. PSO mimics the behavior of flocking birds looking for food. But PSO has three parameters that can interfere with its performance, so this algorithm is not adaptive to diverse problems. Many PSO variants have been introduced to solve this problem, including linearly decreasing inertia weight particles swarm optimization (LDWPSO) and bare bones particles swarm optimization (BBPSO). The metaheuristic method is used to find the solution, while DSM s used to analyze the structure. A 10-bar truss structure and a 39-bar truss structure are considered as case studies. The result indicates that BBPSO beat other two algorithms in terms of best result, consistency, and convergence behaviour in both cases. LDWPSO took second place for the three categories, leaving PSO as the worst algorithm that tested.
IOP Conference Series: Earth and Environmental Science, 2021
Castellated beams are commonly used in steel construction. This study will focus on castellated b... more Castellated beams are commonly used in steel construction. This study will focus on castellated beams with circular-shaped openings, which are known as cellular beams. Cost optimization of cellular beams is needed to maintain cost efficiency. The optimization considers the selection of a root beam, the diameter of holes, and the total number of holes in the beam as the variables. Four metaheuristic algorithms are used to optimize the design, namely, the particle swarm optimization (PSO), differential evolution (DE), symbiotic organisms search (SOS), and artificial bee colony (ABC). A four-meter span beam with a 50 kN point live load in the middle of the beam and a 5 kN/m uniformly-distributed dead load are taken as the case study. The results indicate that the SOS algorithm yields the best optimization results in terms of the average, consistency, and convergence behavior with a 30 out of 30 success rates.
IOP Conference Series: Earth and Environmental Science, 2020
Structural design optimization has become an extremely challenging and more complex task for most... more Structural design optimization has become an extremely challenging and more complex task for most real-world practical applications. A huge number of design variables and complex constraints have contributed to the complexity and nonlinearity of the problems. Mathematical programming and gradient-based search algorithms cannot be used to solve nonlinear problems. Thus, researchers have extensively conducted many experimental studies to address the growing complexity of these problems. Metaheuristic algorithms, which typically use nature as a source inspiration, have been developed over past decades. As one of the widely used algorithms, particle swarm optimization (PSO) has been studied and expanded to deal with many complex problems. Particle swarm optimization and its variants have great accuracy in finding the best solution while maintaining its fast convergence behavior. This study aims to investigate PSO and its variants to solve a set of complex structural optimization problem...
Journal of Physics: Conference Series, 2020
A systematic approach of optimization is needed to achieve an optimal design of large and complex... more A systematic approach of optimization is needed to achieve an optimal design of large and complex truss structures. In the last three decades, several researchers have developed and applied various metaheuristic optimization methods to the design of truss structures. This paper investigates a new metaheuristic algorithm called symbiotic organisms search (SOS) for member sizing optimization of relatively large steel trusses. The case studies include a 120-bar dome truss and a 942-bar tower truss. The structural analyses are carried out using the standard finite element method. The profiles of the truss members are circular hollow structural sections selected from a set of the American Institute of Steel Construction standard profiles. The design results using the SOS are then compared to those obtained using other metaheuristic methods, namely the particle swarm optimization, differential evolution, and teaching-learning-based optimization. The comparison shows the superior performan...
Civil Engineering Dimension, Mar 3, 2011
During the last two decades, a large variety of mesh-free methods have been introduced as alterna... more During the last two decades, a large variety of mesh-free methods have been introduced as alternatives to the conventional finite element method (FEM). However, the acceptance in professional practices seems to be slow due to their implementation complexities. Recently, a convenient implementation of the element-free Galerkin method using Kriging interpolation (KI), which can be viewed as an enhancement of the FEM, was proposed. This method is subsequently referred to as Kriging-based FEM (K-FEM). In this method, field variables are approximated by "element-by-element" piecewise KI. Layers of finite elements around each element are adopted as its domain of influence (DOI). The distinctive advantage of the proposed method is its inheritance of the computational procedure of the FEM. Any existing FE code can be easily extended to K-FEM; thus, it has a higher chance to be accepted in the practice. This paper presents overview of the K-FEM. The formulation of KI and the concept of layered-element DOI are reviewed. The two-dimensional elastostatics problem is unitized as a vehicle to convey the concepts. Several examples are presented to demonstrate the reliability of the K-FEM.
Civil Engineering Dimension, Mar 16, 2009
An enhancement of the finite element method with Kriging shape functions (K-FEM) was recently pro... more An enhancement of the finite element method with Kriging shape functions (K-FEM) was recently proposed. In this method, the field variables of a boundary value problem are approximated using 'element-by-element' piecewise Kriging interpolation (el-KI). For each element, the interpolation function is constructed from a set of nodes within a prescribed domain of influence comprising the element and its several layers of neighbouring elements. This paper presents a numerical study on the accuracy and convergence of the el-KI in function fitting problems. Several examples of functions in two-dimensional space are employed in this study. The results show that very accurate function fittings and excellent convergence can be attained by the el-KI..
DOAJ (DOAJ: Directory of Open Access Journals), Mar 1, 2017
A major difficulty in formulating a finite element for shear-deformable beams, plates, and shells... more A major difficulty in formulating a finite element for shear-deformable beams, plates, and shells is the shear locking phenomenon. A recently proposed general technique to overcome this difficulty is the discrete shear gap (DSG) technique. In this study, the DSG technique was applied to the linear, quadratic, and cubic Timoshenko beam elements. With this technique, the displacement-based shear strain field was replaced with a substitute shear strain field obtained from the derivative of the interpolated shear gap. A series of numerical tests were conducted to assess the elements performance. The results showed that the DSG technique works perfectly to eliminate the shear locking. The resulting deflection, rotation, bending moment, and shear force distributions were very accurate and converged optimally to the corresponding analytical solutions. Thus the beam elements with the DSG technique are better alternatives than those with the classical selective-reduced integration.
Civil Engineering Dimension, Oct 18, 2019
A tapered beam is a beam that has a linearly varying cross section. This paper presents an analyt... more A tapered beam is a beam that has a linearly varying cross section. This paper presents an analytical derivation of the solutions to bending of a symmetric tapered cantilever Timoshenko beam subjected to a bending moment and a concentrated force at the free end and a uniformly-distributed load along the beam. The governing differential equations of the Timoshenko beam of a variable cross section are firstly derived from the principle of minimum potential energy. The differential equations are then solved to obtain the exact deflections and rotations along the beam. Formulas for computing the beam deflections and rotations at the free end are presented. Examples of application are given for the cases of a relatively slender beam and a deep beam. The present solutions can be useful for practical applications as well as for evaluating the accuracy of a numerical method
Procedia Engineering, 2017
The Scopus Author Ide nt ifie r ass ign s a unique number to g roups of documents written by the ... more The Scopus Author Ide nt ifie r ass ign s a unique number to g roups of documents written by the same author via an algorithm that matches authorshi p based on a X ce rtain criteria. Ifa document cannot be confid entl y matched with an author identifier, it is grou ped separately. In this case, you may see more than one entry for the same author.
Asian Journal of Civil Engineering, Apr 24, 2018
In the construction industry, determining project schedules has become one of the most critical s... more In the construction industry, determining project schedules has become one of the most critical subjects among project managers. These schedules oftentimes result in significant resource fluctuations that are costly and impractical for the construction company. Thus, construction managers are required to adjust the resource profile through a resource leveling process. In this paper, a novel optimization model is presented for resource leveling, called the ''modified symbiotic organisms search'' (MSOS). MSOS is developed based on the standard symbiotic organisms search, but with an improvement in the parasitism phase to better tackle complex optimization problems. A case study is employed to investigate the performance of the proposed optimization model in coping with the resource leveling problem. The experimental results show that the proposed model can find a better quality solution in comparison with existing optimization models.
International Journal of Computational Methods, Oct 12, 2018
Kriging-based finite element method (K-FEM) is an enhancement of the FEM through the use of Krigi... more Kriging-based finite element method (K-FEM) is an enhancement of the FEM through the use of Kriging interpolation in place of the conventional polynomial interpolation. In this paper, the K-FEM is developed for static, free vibration, and buckling analyses of Timoshenko beams. The discrete shear gap technique is employed to eliminate shear locking. The numerical tests show that a Kriging-Based beam element with cubic basis and three element-layer domain of influencing nodes is free from shear locking. Exceptionally accurate displacements, bending moments, natural frequencies, and buckling loads and reasonably accurate shear force can be achieved using a relatively course mesh.
IOP Conference Series: Earth and Environmental Science, 2021
Steel deck floor systems can be considered as one of the main components of a structure. As techn... more Steel deck floor systems can be considered as one of the main components of a structure. As technology advances, the role of optimization is used in many aspects of structural designs. Steel deck floor systems are one of many components that are usually optimized to look for its optimum cost but are still able to hold the structure. This study compares the performance of the particle swarm optimization (PSO), artificial bee colony (ABC), differential evolution (DE), and symbiotic organisms search (SOS), that categorized as nature-inspired algorithms, in the optimization of a steel deck floor system. The variables considered are the edge beams, interior beams, and the composite steel deck. The results show that the SOS gives the most optimum cost with a better average and a perfect success rate.
Journal of Physics: Conference Series, 2020
This paper focuses on optimizing truss structures while propose best PSO variants. Truss optimiza... more This paper focuses on optimizing truss structures while propose best PSO variants. Truss optimization is one way to make the design efficient. There are three types of optimization, size optimization, shape optimization, and topology optimization. By combining size, shape and topology optimization, we can obtain the most efficient structure. Metaheuristics have the ability to solve this problem. Particle swarm optimization (PSO) is metaheuristic algorithm which is frequently used to solve many optimization problems. PSO mimics the behavior of flocking birds looking for food. But PSO has three parameters that can interfere with its performance, so this algorithm is not adaptive to diverse problems. Many PSO variants have been introduced to solve this problem, including linearly decreasing inertia weight particles swarm optimization (LDWPSO) and bare bones particles swarm optimization (BBPSO). The metaheuristic method is used to find the solution, while DSM s used to analyze the structure. A 10-bar truss structure and a 39-bar truss structure are considered as case studies. The result indicates that BBPSO beat other two algorithms in terms of best result, consistency, and convergence behaviour in both cases. LDWPSO took second place for the three categories, leaving PSO as the worst algorithm that tested.
IOP Conference Series: Earth and Environmental Science, 2020
Studies on truss design optimization have been conducted extensively over the past decades. One o... more Studies on truss design optimization have been conducted extensively over the past decades. One of the significant current discussions is the reliability aspect of truss design in addition to optimal design. This problem has become more important, especially the sizing and shaping in the optimization of truss structures. Reliability-based design optimization is defined as finding the optimum structure while satisfying the given uncertainty and reliability criteria. This study aims to investigate the performance of metaheuristic algorithm in optimizing the truss structure design and satisfying the reliability constraints. Latin hypercube sampling method was used to model the presence of uncertainty. Symbiotic organisms search was also utilized as a metaheuristic algorithm to solve a modified 15-bar planar truss. The results indicated that reliability design gives a significant result in the shape and size of truss.
IOP Conference Series: Earth and Environmental Science, 2020
Field studies of structural optimization have gained increased attention due to the rapid develop... more Field studies of structural optimization have gained increased attention due to the rapid development of metaheuristic algorithms. One widely known metaheuristic algorithm, Particle Swarm Optimization (PSO), has been extensively used to solve many problems and is reported to have fast convergence behavior and good accuracy. As many problems become more complex, studies have been focused on improving PSO searching capability. This study presents the application of PSO and its variants in optimizing truss structures. The performances of PSO and several PSO variants, namely, linearly decreasing inertia weight PSO (LDW-PSO) and bare bones PSO (BB-PSO), were compared and investigated. All optimization algorithms were tested in 72-bar and 25-bar spatial truss problems. The results indicate that BBPSO was the best algorithm in terms of optimum solution, consistency, and convergence behavior.
International Journal of Computational Methods, 2018
Kriging-based finite element method (K-FEM) is an enhancement of the FEM through the use of Krigi... more Kriging-based finite element method (K-FEM) is an enhancement of the FEM through the use of Kriging interpolation in place of the conventional polynomial interpolation. In this paper, the K-FEM is developed for static, free vibration, and buckling analyses of Timoshenko beams. The discrete shear gap technique is employed to eliminate shear locking. The numerical tests show that a Kriging-Based beam element with cubic basis and three element-layer domain of influencing nodes is free from shear locking. Exceptionally accurate displacements, bending moments, natural frequencies, and buckling loads and reasonably accurate shear force can be achieved using a relatively course mesh.
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Papers by Foek Tjong Wong