• Steel and Composite Structures
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• v.19 no.4
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• pp.995-1009
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• 2015

This study presents design optimization of spot welded structures to attain maximum strength by using the Nelder-Mead (Simplex) method. It is the main idea of the algorithm that the simulation run is executed several times to satisfy predefined convergence criteria and every run uses the starting points of the previous configurations. The material and size of the sheet plates are the pre-assigned parameters which do not change in the optimization cycle. Locations of the spot welds, on the other hand, are chosen to be design variables. In order to calculate the objective function, which is the maximum equivalent stress, ANSYS, general purpose finite element analysis software, is used. To obtain global optimum locations of spot welds a methodology is proposed by modifying the Nelder-Mead (Simplex) method. The procedure is applied to a number of representative problems to demonstrate the validity and effectiveness of the proposed method. It is shown that it is possible to obtain the global optimum values without stacking local minimum ones by using proposed methodology.

• Journal of Auto-vehicle Safety Association
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• v.11 no.1
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• pp.23-29
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• 2019

Recently, use of composite materials has been increasing for body structures and chassis parts in the car industry because of weight reduction effect and excellent mechanical thermal characteristics. However, application of composite materials in brake system is very difficult because it is hard to obtain enough brake performance due to low heat storage capacity of the composite materials. In this paper, we will present new carbon ceramic composite disc with high flow characteristic. To obtain this characteristic, new vent structures were designed by using ARIZ method and substance-field model analysis. The flow effect of these vent structures on the brake performance was verified by pugh matrix and cooling test. The test results show improvement of cooling performance up to $30^{\circ}C$. Finally, These results will improve brake the reliability of the brake performance for the high performance vehicles and electric vehicles.

• Earthquakes and Structures
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• v.6 no.1
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• pp.19-43
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• 2014

A risk assessment framework for evaluating building structures is implemented in this study. This framework allows considering sources of uncertainty both on structural capacity and seismic demand. In particular randomness on seismic load, incident angle, material properties, floor mass and structural damping are considered; in addition the choice of fibre modelling versus plastic hinge model is also considered as a source of uncertainty. The main objective of this work is to study the contribution of these sources of uncertainty on the fragilities of steel and steel-reinforced concrete composite 3D building structures. The fragility curves are expressed in the form of a two-parameter lognormal distribution where vertical statistics in conjunction with metaheuristic optimization are implemented for calculating the two parameters.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.93-100
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• 2012

In this paper, the deterministic optimal design for the tail plane made of composite materials is conducted under the deterministic loading condition and compared with that of the metallic materials. Next, the reliability analysis with five random variables such as loading and material properties of unidirectional prepreg is conducted to examine the probability of failure for the deterministic optimal design results. The MATLAB programing is used for reliability analysis combined with FEA S/W(COMSOL) for structural analysis. The laminated composite is assumed to the equivalent orthotropic material using classical laminated plate theory. The response surface methodology and importance sampling technique are adopted to reduce computational cost with satisfying the accuracy in reliability analysis. As a result, structural weight of composite materials is lighter than that of metals in deterministic optimal design. However, the probability of failure for the deterministic optimal design of the tail plane structures is too high to be neglected. The sensitivity of each variable is also estimated using probabilistic sensitivity analysis to figure out which variables are sensitive to failure. The computational cost is considerably reduced when response surface methodology and importance sampling technique are used. The study of the computationally inexpensive method for reliability-based design optimization will be necessary in further work.

• Steel and Composite Structures
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• v.42 no.4
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• pp.489-499
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• 2022

This paper proposes a numerical optimization method to design the mesoscale architecture of textile composite for simultaneously enhancing mechanical and thermal properties, which compete with each other making it difficult to design intuitively. The base cell of the periodic warp and fill yarn system is served as the design space, and optimal fibre yarn geometries are found by solving the optimization problem through the proposed method. With the help of homogenization method, analytical formulae for the effective material properties as functions of the geometry parameters of plain-woven textile composites were derived, and they are used to form the inverse homogenization method to establish the design problem. These modules are then put together to form a multiobjective optimization problem, which is formulated in such a way that the optimal design depends on the weight factors predetermined by the user based on the stiffness and thermal terms in the objective function. Numerical examples illustrate that the developed method can achieve reasonable designs in terms of fibre yarn paths and geometries.

• Steel and Composite Structures
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• v.45 no.4
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• pp.579-590
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• 2022

One of the biggest problems in structural steel calculation is the design of structures using the lowest possible material weight, making this a slow and costly process. To achieve this objective, several optimization methods have been developed and tested. Nevertheless, a method that performs very efficiently when applied to different problems is not yet available. Based on this assumption, this work proposes a hybrid metaheuristic algorithm for geometric and dimensional optimization of space trusses, called Simulated Squirrel Search Algorithm, which consists of an association of the well-established neighborhood shifting algorithm (Simulated Annealing) with a recently developed promising population algorithm (Squirrel Search Algorithm, or SSA). In this study, two models are tried, being respectively, a classical model from the literature (25-bar space truss) and a roof system composed of space trusses. The structures are subjected to resistance and displacement constraints. A penalty function using Fuzzy Logic (FL) is investigated. Comparative analyses are performed between the Squirrel Search Algorithm (SSSA) and other optimization methods present in the literature. The results obtained indicate that the proposed method can be competitive with other heuristics.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• Journal of Korean Society of Steel Construction
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• v.15 no.4 s.65
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• pp.389-401
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• 2003

The purpose of this study is to develop an algorithm, which can be designed the optimal sections of the composite framed structures constituted with the beams and the columns consisted of H type of steel section and concrete considering the reliability index. The optimized problem or the composite framed structures is formulated with the objective function and the constraints taking the section sizes as the design variables. The objective functions are constituted by the total costs of constructions. Also, the constraints are derived by considering the reliability index of section stress and allowable stress. The algorithm optimized the section of the composite framed structures utilizes the SUMT method using the modified Newton-Raphson direction method. The optimizing algorithm developed in this study is applied to the numerical examples with respecting a one-bay, one-story composite framed structure and a one-bay five-story one for the practical utilization of design on the composite framed structures using the reliability indices$({\beta})$ three and zero. In addition, their numerical results are compared and analyzed to examine the possibility of optimization the applicability, and the convergence this algorithm.

• Composites Research
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• v.22 no.3
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• pp.66-73
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• 2009

Total thickness, areal density and mass moment of inertia of materials are important material factors for structural characteristics. In this work, a material-structural optimization was performed up to the maximum ballistic limit of multi-layered composite structures under high impact velocity followed by the investigation of the influence of these factors on an impact absorption performance. A unified model combined with Florence's and Awerbuch-Bonder's models was used in optimizing the multi-layered composite structure consisting of CMC, rubber, aluminum and Al-foam. Total thickness, areal density and mass moment of inertia were used for the optimization constraint. As shown in the results, the ballistic limit determined from a newly developed unified model was closely similar to the finite clement analysis. Additionally, the ballistic limit and impact absorption energy obtained by the optimized structure were improved approximately 16.8% and 26.7%, respectively comparing with a not optimized multi-layered structure.

• Steel and Composite Structures
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• v.48 no.5
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• pp.531-545
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• 2023

Composite dowels are implemented as a powerful alternative to headed studs for the efficient combination of Ultra High-Performance Concrete (UHPC) with high-strength steel in novel composite structures. They are required to provide sufficient shear resistance and ensure the transmission of tensile forces in the composite connection in order to prevent lifting of the concrete slab. In this paper, the load bearing capacity of puzzle-shaped and clothoidal-shaped dowels encased in UHPC specimen were investigated based on validated experimental test data. Considering the influence of the embedment depth and the spacing width of shear dowels, the characteristics of UHPC square plate on the load bearing capacity of composite structure, 240 numeric models have been constructed and analyzed. Three artificial intelligence approaches have been implemented to learn the discipline from collected experimental data and then make prediction, which includes Artificial Neural Network-Particle Swarm Optimization (ANN-PSO), Adaptive Neuro-Fuzzy Inference System (ANFIS) and an Extreme Learning Machine (ELM). Among the factors, the embedment depth of composite dowel is proved to be the most influential parameter on the load bearing capacity. Furthermore, the results of the prediction models reveal that ELM is capable to achieve more accurate prediction.