• Steel and Composite Structures
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• 제25권6호
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• Earthquakes and Structures
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• 제12권3호
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• pp.309-319
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• 2017

A new method is suggested for the retrofitting of torsionally sensitive buildings. The main objective is to eliminate the torsional component from the first two natural modes of the structure by properly modifying its stiffness distribution via selective strengthening of its vertical elements. Due to the multi-parameter nature of this problem, state-of-art optimization schemes together with an ad-hoc software implementation were used for quantifying the required stiffness increase, determine the required retrofitting scheme and finally design and analyze the required composite sections for structural rehabilitation. The performance of the suggested method and its positive impact on the earthquake response of such structures is demonstrated through benchmark examples and applications on actual torsionally sensitive buildings.

• 한국산업융합학회 논문집
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• 제11권3호
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• pp.127-134
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• 2008

This study is to develop the structure analysis and optimization algorithm of the strut supported temporary structure for underground constructions. Developed algorithm performs the analysis and the optimization of each strut, wale, and H pile of temporary structures separately. The design variables of nonlinear optimization consist of the cross-sections of temporary structures such as strut, wale, and H pile and the solution of the nonlinear programming is searched using for the method of successive unconstranint minimization technique. The weight of the structure is used for the object function of nonlinear programming. the constraints are derived from the specification of the temporary structures as compressive axial, bending, shear, composite stress and serviceability. The structural analysis is performed based on the elastoplastic beam theory. This developed program can be used to evaluate the applicability, convergence, and effectiveness of the temporary structures.

• Steel and Composite Structures
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• 제42권1호
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• pp.139-149
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• 2022

To simplify the design and reduce the construction cost of traditional multi-girder structural systems, twin I-girder structures are widely used in many countries in recent years. Due to the concern on post-fracture redundancy, however, twin girder bridges are currently classified as fracture critical structures in AASHTO specifications for highway bridges. To investigate the after-fracture behavior of such structures, a composite steel and concrete twin girder specimen was built and an artificial fracture through the web and the bottom flange was created on one main girder. The static loading test was performed to investigate its mechanical performance after a severe fracture occurred on the main girder. Applied load and vertical displacement curves, and the applied load versus strain relationships at key sections were measured. To investigate the load distribution and transfer capacities between two steel girders, the normal strain development on crossbeams was also measured during the loading test. In addition, both shear and normal strains of studs were also measured in the loading test to explore the behavior of shear connectors in such bridges. The functions and structural performance of structural members and possible load transfer paths after main girder fractures in such bridges were also discussed. The test results indicate in this study that a typical twin I-girder can resist a general fracture on one of its two main girders. The presented results can provide references for post-fracture performance and optimization for the design of twin I-girder bridges and similar structures.

• Steel and Composite Structures
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• 제42권6호
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• pp.855-864
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• 2022

Due to limited resources, and increasing speed of development, the optimal use of available resources has become the most important challenge of human societies. In the last few decades, many researchers have focused their research on solving various optimization problems, providing new optimization methods, and improving the performance of existing optimization methods. Echolocation Search Algorithm (ESA) is an evolutionary optimization algorithm that is based on mimicking the mechanism of the animals such as bats, dolphins, oilbirds, etc in food finding to solve optimization problems. In this paper, the ability of ESA for solving truss size optimization problems with continuous variables is investigated. To examine the efficiency of ESA, three benchmark examples are considered. The numerical results exhibit the effectiveness of ESA for solving truss optimization problems.

• Structural Engineering and Mechanics
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• 제61권3호
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• pp.325-334
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• 2017

In the present study, a numerical model for probability analysis of optimal design of fatigue non-uniform crack growth behaviour of a cracked aluminium 2024 T3 plate repaired with a bonded composite patch is investigated. The proposed 3D numerical model has advanced in literatures, which gathers in a unique study: problems of reliability, optimization, fatigue, cracks and repair of plates subjected to tensile loadings. To achieve this aim, a finite element modelling is carried out to determine the evolution of the stress intensity factor at the crack tip Paris law is used to predict the fatigue life for a give n crack. To have an optimal volume of our patch satisfied the practical fatigue life, a procedure of optimization is proposed. Finally, the probabilistic analysis is performed in order to a show that optimized patch design is influenced by uncertainties related to mechanical and geometrical properties during the manufacturing process.

• Steel and Composite Structures
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• 제14권2호
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• pp.121-132
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• 2013

This paper deals with multiobjective optimization of symmetrically laminated composite angle-ply annular sector plates subjected to axial uniform pressure load and thermal load. The design objective is the maximization of the weighted sum of the critical buckling load and fundamental frequency. The design variable is the fibre orientations in the layers. The performance index is formulated as the weighted sum of individual objectives in order to obtain the optimum solutions of the design problem. The first-order shear deformation theory is used for the mathematical formulation. Finally, the effects of different weighting factors, annularity, sector angle and boundary conditions on the optimal design are investigated and the results are compared.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2003년도 춘계학술발표대회 논문집
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• pp.161-164
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• 2003

Almost all buildings/infrastructures made of composite materials are fabricated without proper design. Unlike airplane or automobile parts, prototype test is impossible. One cannot destroy 10 story buildings or 100-meter long bridges. People try to build 100-story buildings or several thousand meter long bridges. In order to realize "composites in construction", the following subjects must be studied in detail, for his design: Concept optimization, Simple method of analysis, Folded plate theory, Size effects in failure, and Critical frequency. Unlike the design procedure with conventional materials, his design should include material design, selection of manufacturing methods, and quality control methods, in addition to the fabrication method.on method.

• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.334-340
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• 2013

This paper deals with the optimization of blade stiffened composite panels. The main objective of the research is to make response surfaces for the constraints. The response surface for warping thermal deformation was previously made for a fixed dimension composite structure. In this study, the dimensions of the blade stiffener were treated as design variables. This meant that a new response surface technique was required for the constraints. For the response surfaces, the lamination parameters, linear thermal expansions and dimensions of the structures were used as variables. A genetic algorithm was adopted as an optimizer, and an optimal result, which satisfied two constraints, was obtained. As a result, a new response surface was obtained, for predicting warping thermal deformation.

• 한국항공우주학회지
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• 제47권7호
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• pp.535-540
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• 2019

MDO(Multi-disciplinary Optimization)를 위한 서로 다른 모델 간의 결합은 계산 프레임 워크의 복잡성을 크게 증가시키는 동시에 CPU 시간과 메모리 사용을 증가시킨다. 이러한 어려움을 극복하기 위해 POD(Proper Orthogonal Decomposition)와 RBF(Radial Basis Function)를 사용하여 복합 샌드위치 구조가 항공기 날개 스킨 재료로 사용될 때 복합재와 샌드위치 코어의 두께를 결정하는 최적화 문제의 해를 구했다. POD와 RBF를 사용하여 날개 형상과 하중 데이터에 대한 대리 모델을 만들었으며 대리 모델에 의해 얻어진 목적 함수 및 제약 함수 값을 사용하여 최적해를 구하였다.