• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.153-160
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• 2010

This paper deals with the topology optimized design of the riser support structures for floating production storage and offloading units (FPSOs) under global and local loading conditions. For a preliminary study and validation of the numerical approach, a simplified plate under static loading is first evaluated with the representative topology optimization methods, the Homogenization Design Method (HDM) and Density Method (DM) or Simple Isotropic Material with Penalization (SIMP). In the context of the corresponding riser support structures, the design problem is formulated such that structure shapes based on design domain variables are determined by minimizing the compliance subject to a mass target, considering the stress criterion. An initial design model is generated based on an actual FPSO riser support configuration. The topology optimization results present improved design performances under various loading conditions, while staying within the allowable limit of the offshore area.

• Wind and Structures
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• v.20 no.4
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• pp.489-508
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• 2015

In this paper, a novel methodology is proposed to obtain optimum location of outriggers. The method utilizes genetic algorithm (GA) for shape and size optimization of outrigger-braced tall structures. In spite of previous studies (simplified methods), current study is based on exact modeling of the structure in a computer program developed on Matlab in conjunction with OpenSees. In addition to that, exact wind loading distribution is calculated in accordance with ASCE 7-10. This is novel since in previous studies wind loading distributions were assumed to be uniform or triangular. Also, a new penalty coefficient is proposed which is suitable for optimization of tall buildings. Newly proposed penalty coefficient improves the performance of GA and results in a faster convergence. Optimum location and number of outriggers is investigated. Also, contribution of factors like central core and outrigger rigidity is assessed by analyzing several design examples. According to the results of analysis, exact wind load distribution and modeling of all structural elements, yields optimum designs which are in contrast of simplified methods results. For taller frames significant increase of wind pressure changes the optimum location of outriggers obtained by simplified methods. Ratio of optimum location to the height of the structure for minimizing weight and satisfying serviceability constraints is not a fixed value. Ratio highly depends on height of the structure, core and outriggers stiffness and lateral wind loading distribution.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1015-1018
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• 2006

In this paper, new topology optimization technique is proposed. It mainly uses the strain energy distributions induced by the mode shapes associated with natural frequencies of the structure and so we can implicitly consider the dynamic characteristics of the structure in the topology optimization process. The strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. The resizing algorithm devised from the optimality criteria method is used to update the hole size of the cell existing in each finite element. The cantilever beam problem is adopted to test the proposed techniques. From numerical test, it is found to be that the optimum topology of the cantilever produced by the proposed technique has a hugh increase of natural frequency value and the technique is very effective to maximize the fundamental frequency of the structure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.645-653
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• 2017

Thermal and flow modeling and fin structure optimization were performed to reduce the weight of an electrical device with a staggered fin. First, a numerical model for thermal and flow characteristics was suggested, and then, the model was verified experimentally. Using the verified model, improvement in cooling performance of the cooling system through the staggered fins was predicted. As a result, 87.5% of total heat generated was dissipated through the cooling fins, and a thermal island was observed in the rotor because of low velocity of the internal air flow through the air gap. In addition, it was confirmed that the staggered fin improves the cooling performance but it also increases the total pressure drop within the cooling system, by maximizing the leading edge effect. Based on this analysis result, the effect of each design parameter on the thermal and flow characteristics was analyzed to select the main optimal design parameters, and multi-objective optimization was performed by considering the cooling performance and the fin weight. In conclusion, the optimized fin structure improved the cooling performance by 7% and reduced the fin weight by 28% without any compromise of the pressure drop.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.424-433
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• International Journal of High-Rise Buildings
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• v.3 no.4
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• pp.285-296
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• 2014

The objective of optimization is to present a design process that minimizes the total material consumption while satisfying current codes and specifications. In the research an optimization formulation for RC shear wall structures is proposed. And based on conceptual design methodology, an optimization process is investigated. Then optimal design techniques and specific explanations are introduced for residential buildings with shear wall structure, especially for that with a rectangular layout. An example of 30-story building is presented to illustrate the effectiveness of the proposed optimal design process. Furthermore, the influence of aspect ratio on the concrete consumption and the steel consumption of the superstructure are analyzed for this typical RC shear wall structure; and their relations are obtained by regressive analysis. Finally, the optimal material consumption is suggested for the residential building with RC shear wall structure and with rectangular layout. The relation and the data suggested can be used for guiding the design of similar RC shear wall structures.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1011-1016
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• 2004

All the loads in the real world are dynamic loads and it is well known that structural optimization under dynamic loads is very difficult. Thus the dynamic loads are often transformed to the static loads using dynamic factors. However, due to the difference of load characters, there can be considerable differences between the results from static and dynamic analyses. When the natural frequency of a structure is high, the dynamic analysis result is similar to that of static analysis due to the small inertia effect on the behavior of the structure. However, if the natural frequency is low, the inertia effect should not be ignored. Then, the behavior of the dynamic system is different from that of the static system. The difference of the two cases can be explained from the relationship between the homogeneous and the particular solutions of the differential equation that governs the behavior of the structure. Through various examples, the difference between the dynamic analysis and the static analysis are shown. Also the optimization results considering dynamic loads are compared with static loads.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.7
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• pp.424-424
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• Steel and Composite Structures
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• v.47 no.3
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• pp.339-353
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• 2023

The primary objective of the current study is to optimize and evaluate the seismic performance of steel momentresisting frame (MRF) structures considering soil-structure interaction (SSI) effects. The structural optimization is implemented in the context of performance-based design in accordance with FEMA-350 at different confidence levels from 50% to 90% by taking into account fixed- and flexible-base conditions using an efficient metaheuristic algorithm. Nonlinear response-history analysis (NRHA) is conducted to evaluate the seismic response of structures, and the beam-on-nonlinear Winkler foundation (BNWF) model is used to simulate the soil-foundation interaction under the MRFs. The seismic performance of optimally designed fixed- and flexible-base steel MRFs are compared in terms of overall damage index, seismic collapse safety, and interstory drift ratios at different performance levels. Two illustrative examples of 6- and 12-story steel MRFs are presented. The results show that the consideration of SSI in the optimization process of 6- and 12-story steel MRFs results in an increase of 1.0 to 9.0 % and 0.5 to 5.0 % in structural weight and a slight decrease in structural seismic safety at different confidence levels.