• Journal of Power System Engineering
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• v.21 no.3
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• pp.85-92
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• 2017

Global air traffic is forecast to grow at an average annual rate of around 5% in the next 20 years. The continuous growth of air traffic and raised environmental awareness put increasing pressure on aero engine manufacturers to reduce fuel burn and emissions. NEWAC are a new integrated program of the European Union with focus on innovative core engine concepts to achieve this problem. In this paper, Within NEWAC, active core engine configurations will be investigated. the investigation is focused on the optimal design of the CAC heat exchanger for active core. For optimal design of he CAC heat exchanger, the HTFS of basic design of heat exchanger are analyzed so as to proceed an optimization routines based on Response Surface Method(RSM) and Design of Experiment(DOE). As a result, CAC heat exchanger optimized by 1.0314 lb/s mass flow rate and 3.9058 mm TP of tube layout and 206.8181 mm height of heat exchanger and 918 tube number for heat transfer and pressure drop. We confirm the design optimization using RSM and DOE is useful on complex structure of heat exchanger.

• International Journal of High-Rise Buildings
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• v.5 no.4
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• pp.319-326
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• 2016

The ingenuity of structural engineers in the field of tall and super-tall buildings has led to some of the most remarkable inventions. During this evolution of structural engineering concepts in the last 100 years, the technical challenges that engineers encountered were extraordinary and the advances were unprecedented. However, as the accomplishments of structural engineers are progressing, the desire for taller and safer structures is also increasing. The diagrid structural system is part of this evolving process as it develops a new paradigm for tall building design combining engineering efficiency and new architectural expression. The first appearances of this type of tall buildings have already been constructed and the interest of both engineering and architectural communities is growing mainly due to the many advantages compared to other structural systems. This paper presents a simple approach on optimizing member sizes for the diagonals of steel diagrid tall buildings. The optimizing method is based on minimizing the volume of the diagonal elements of a diagrid structure. The constraints are coming from the stiffness-based design, limiting the tip deflection of the building to widely accepted regulative limits. In addition, the current paper attempts to open the discussion on the important topic of optimization and robustness for tall buildings and also studies the future of the diagrid structural system.

• Smart Structures and Systems
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• v.13 no.4
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• pp.711-730
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• 2014

In this paper the system dynamic influences in actuators with variable stiffness as contemporary used in robotics for safety and efficiency reasons are investigated. Therefore, different configurations of serial and parallel elasticities are modeled by dynamic equations and linearized transfer functions. The latter ones are used to identify the characteristic behavior of the different systems and to study the effect of the different elasticities. As such actuation concepts are often used to reach energy-efficient operation, a power consumption analysis of the configurations is performed. From the comparison of this with the system dynamics, strategies to select and control stiffness are derived. Those are based on matching the natural frequencies or antiresonance modes of the actuation system to the frequency of the trajectory. Results show that exclusive serial and parallel elasticity can minimize power consumption when tuning the system to the natural frequencies. Antiresonance modes are an additional possibility for stiffness control in the series elastic setup. Configurations combining both types of elasticities do not provide further advantages regarding power reduction but an input parallel elasticity might enable for more versatile stiffness selection. Yet, design and control effort increase in such solutions. Topologies incorporating output parallel elasticity showed not to be beneficial in the chosen example but might do so in specific applications.

• Steel and Composite Structures
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• v.8 no.5
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• pp.343-359
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• 2008

In the present study, an efficient method for the optimum design of three-dimensional (3D) steel framed structures is proposed. In this method, in addition to choosing the best position of columns based on architectural requirements, the optimum cross-sectional dimensions of elements are determined. The preliminary design variables are considered as the number of columns in structural plan, which are determined by a direct optimization method suitable for discrete variables, without requiring the evaluation of derivatives. After forming the geometry of structure, the main variables of the cross-sectional dimensions are evaluated, which satisfy the design constraints and also achieve the least-weight of the structure. To reduce the number of finite element analyses and the overall computational time, a new third order approximate function is introduced which employs only the diagonal elements of the higher order derivatives matrices. This function produces a high quality approximation and also, a robust optimization process. The main feature of the proposed techniques that the higher order derivatives are established by the first order exact derivatives. Several examples are solved and efficiency of the new approximation method and also, the proposed method for the best position of columns in 3D steel framed structures is discussed.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.382-388
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• 2011

Being aware of the risk in advance necessitates intricate processes but is feasible. Although previous studies have demonstrated high accuracy, their performance still leaves room for improvement. A self-organizing feature map (SOM) based neurofuzzy model is developed in this study to provide another alternative for forecasting corporate financial distress. The model is designed to yield high prediction accuracy, as well as reference rules for evaluating corporate financial status. As a database, the study collects all financial reports from listed construction companies during the latest decade, resulting in over 1000 effective samples. The proportion of "failed" and "non-failed" companies is approximately 1:2. Each financial report is comprised of 25 ratios which are set as the input variable s. The proposed model integrates the concepts of pattern classification, fuzzy modeling and SOM-based optimization to predict corporate financial distress. The results exhibit a high accuracy rate at 85.1%. This model outperforms previous tools. A total of 97 rules are extracted from the proposed model which can be also used as reference for construction practitioners. Users may easily identify their corporate financial status by using these rules.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.254-260
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• 2017

The service life of civil infrastructure needs to be maintained or extended through appropriate inspections and maintenance planning, which results from the optimization process. A multi-objective optimization process can lead to more rational and flexible trade-off solutions rather than a single-objective optimization for the service life management of civil infrastructure. Recent investigations on the service life management of civil infrastructure were generally based on minimizing the life-cycle cost analysis and maximizing the structural performance. Various objectives for service life management have been developed using novel probabilistic concepts and methods over the last few decades. On the other hand, an increase in the number of objectives in a multi-objective optimization problem can lead to difficulties in computational efficiency, visualization, and decision making. These difficulties can be overcome using the objective reduction approach to identify the redundant and essential objectives. As a result, the efficiency in computational efforts, visualization, and decision making can be improved. In this paper, the multi-objective optimization using the objective reduction approach was applied to the service life management of concrete bridges. The results showed that four initial objectives can be reduced by two objectives for the optimal service life management.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.205-210
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• 2022

With the rapid development of the social economy and the continuous improvement of living standards, a favorable environment has been provided for the rapid development of the tourism industry. The highly developed Internet technology has provided people with more convenient online travel. With the rapid development of online tourism, tourism-related Internet businesses are also developing rapidly. This study first introduces the research background and significance of the study, and suggests the necessity of Ctrip's business model optimization study based on the development of social economy such as online tourism development hotspots and business model research issues. Ctrip explains the current status of research inside and outside the online travel industry and business model, in-depth introduction and analysis of related concepts and theories such as online travel and OTA business models, and expands them based on expert research. Several aspects such as insufficient Ctrip's existing business model, high current operating costs, major factors affecting suppliers, and slow development of new business were suggested, and alternatives were suggested to solve these problems. Ctrip maintained a sustainable competitive edge, including Ctrip's business model optimization strategy for value creation and innovation and Internet business model optimization strategy for customer value chains.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.3
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• pp.29-42
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• 2008

Semantic Web society initially focused only on data but has gradually moved toward knowledge. Recently rule beyond ontology has emerged as a key element of the Semantic Web. All of these activities are obviously aiming at making data and knowledge on the Web sharable and reusable between various entities around the world. If one of ultimate visions of the Semantic Web is to increase human's decision making quality assisted by machines, there is a missing but important part to be shared and reused. It is knowledge about constraints on data and concepts represented by ontology which should be emphasized more. In this paper, we propose Semantic Web Constraint Language (SWCL) based on OWL and show how effective SWCL can be in representing and solving an internet shopper's decision making problem by an implementation of a shopping agent in the Semantic Web environment.