• Architectural research
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• v.14 no.1
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• pp.19-26
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• 2012

The technique of integrated design optimization is proposed to design spatial structures. Various element technologies such as topology optimization, layout editing and size optimization processes are used in an integrated manner to improve the performance of spatial structures. In order to demonstrate the present technique, a unit spatial structure is optimized and numerical results are described here.

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.3-51
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• 2005

Optimization methods are presented for design of shells and spatial structures. The effectiveness of using optimization techniques are demonstrated by the following examples: 1. Shape design of ribbed shells. 2. Shape design of membrane structures. 3. Optimization of single-layer spatial truss against buckling. 4. Application of heuristic methods to optimization of space frames. The readers may first see the numerical results to find that is possible by optimization. In the appendix, overview of structural optimization in architectural design is presented, and effectiveness of optimization is demonstrated by small examples. Each chapter is a part of a published paper, or translation from a Japanese article. So there might be some difficulties for understanding the details: inconsistency of the story, etc., which the author hope not to lead to major difficulties for understanding the concepts and results.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.133-149
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• 2017

As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.246-253
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algorithm are searching methods for optimum values. The object of this reserch is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic one, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.59-66
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• 2010

This study presents the topology optimization technique by density method to determine the initial shape of space truss structures. Most initial shape design is performed by designer's previous experiences and trial and error method instead of the application of reasonable optimization method. Thus, the reasonable and economical optimization methods are needed to be introduced for the initial shape design. Therefore, we set design domain for cantilever space truss structure as an example model. And topology optimization is used to obtain optimum layout for them, and then size optimization method is used to find the optimum member size. Therefore, the reasonable initial optimal shapes of spatial truss structures can be obtained through the topology and size optimization using density method.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.367-378
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• 2022

In this study, combined size and shape optimization of spatial truss tower structures are presented by using new optimization algorithms named Rao-1, and Rao-2. The nodal displacements, allowable stress and buckling for compressive members are taken into account as structural constraints for truss towers. The discrete and continuous design variables are used as design variables for size and shape optimization. To show the efficiency of the proposed optimization algorithm, 25-bar, and 39-bar 3D truss towers are solved for combined size and shape optimization. The 72-bar, and 160-bar 3D truss towers are solved only by size optimization. The optimal results obtained from this study are compared to those given in the literature to illustrate the efficiency and robustness of the proposed algorithm. The structural analysis and the optimization process are coded in MATLAB programming.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.290-299
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• 2008

We propose the query optimization technique using query classification in hybrid spatial DBMS. In our approach, user queries should to be classified into three types: memory query, disk query, and hybrid query. Specialty, In the hybrid query processing, the query predicate is divided by comparison between materialized view creating conditions and user query conditions. Then, the deductions of the classified queries' cost formula are used for the query optimization. The optimization is mainly done by the selection algorithm of the smallest cost data access path. Our approach improves the performance of hybrid spatial DBMS than traditional disk-based DBMS by $20%{\sim}50%$.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.97-104
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• 2016

In this paper, we propose spatial information based simulator for user experience optimization and minimize real space complexity. We focus on developing simulator how to design virtual space model and to implement virtual character using real space data. Especially, we use expanded events-driven inference model for SVM based on machine learning. Our simulator is capable of feature selection by k-fold cross validation method for optimization of data learning. This strategy efficiently throughput of executing inference of user behavior feature by virtual space model. Thus, we aim to develop the user experience optimization system for people to facilitate mapping as the first step toward to daily life data inference. Methodologically, we focus on user behavior and space modeling for implement virtual space.

• Spatial Information Research
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• v.21 no.2
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• pp.23-33
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• 2013

W ith the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of 'query merging' that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm's distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS.

• Journal of Korean Association for Spatial Structures
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• v.21 no.1
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• pp.61-70
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• 2021

This paper describes a novel zero-stress member selecting method for sizing optimization of truss structures. When a sizing optimization method with static constraints is implemented, the member stresses are affected sensitively with changing the variables. However, because some truss members are unaffected by specific loading cases, zero-stress states are experienced by the elements. The zero-stress members could affect the computational cost and time of sizing optimization processes. Feature selection approaches can be then used to eliminate the zero-stress member from the whole variables prior to the process of optimization. Several numerical truss examples are tested using the proposed methods.