• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.102-107
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• 2004

Performance based design is a recent evolutionary step in the process of designing fire protection systems. In essence, it is a logical design process resulting in a solution that achieves a specified performance. Sometimes the prescriptive solutions presented in various codes and standards are too expensive or inflexible. Often the solutions do not and enables optimization of a solution for cost and function. In this study, performance based design was carried out to determine the extent of passive fire protection for oil terminal facilities. The results of performance based design were compared with those of prescriptive code based design. Performance based design is not always more economic than prescriptive code based design but provides more reliable and effective design that is fit for the purpose.

• Smart Structures and Systems
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• v.21 no.4
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• pp.435-448
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• 2018

This paper reports the development of a theoretically rigorous method for permanent way engineers to assess the condition of railway ballast under a concrete sleeper with the potential to be extended to a smart system for long-term health monitoring of railway ballast. Owing to the uncertainties induced by the problems of modeling error and measurement noise, the Bayesian approach was followed in the development. After the selection of the most plausible model class for describing the damage status of the rail-sleeper-ballast system, Bayesian model updating is adopted to calculate the posterior PDF of the ballast stiffness at various regions under the sleeper. An obvious drop in ballast stiffness at a region under the sleeper is an evidence of ballast damage. In model updating, the model that can minimize the discrepancy between the measured and model-predicted modal parameters can be considered as the most probable model for calculating the posterior PDF under the Bayesian framework. To address the problems of non-uniqueness and local minima in the model updating process, a two-stage hybrid optimization method was developed. The modified evolutionary algorithm was developed in the first stage to identify the important regions in the parameter space and resulting in a set of initial trials for deterministic optimization to locate all most probable models in the second stage. The proposed methodology was numerically and experimentally verified. Using the identified model, a series of comprehensive numerical case studies was carried out to investigate the effects of data quantity and quality on the results of ballast damage detection. Difficulties to be overcome before the proposed method can be extended to a long-term ballast monitoring system are discussed in the conclusion.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.281-290
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• 2003

Co Evolutionary Structural Design(CESD) Framework is presented, which can deal with the load design and structural topology design simultaneously. The load design here is the exploration algorithm that finds the critical load patterns of the given structure. In general, the load pattern is a crucial factor in determining the structural topology and being selected from the experts어 intuition and experience. However, if any of the critical load patterns would be excluded during the process of problem formation, the solution structure might show inadequate performance under the load pattern. Otherwise if some reinforcement method such as safety factor method would be utilized, the solution structure could result in inefficient conservativeness. On the other hand, the CESD has the ability of automatically finding the most critical load patterns and can help the structural solution evolve into the robust design. The CESD is made up of a load design discipline and a structural topology design discipline both of which have the fully coupled relation each other. This coupling is resolved iteratively until the resultant solution can resist against all the possible load patterns and both disciplines evolve into the solution structure with the mutual help or competition. To verify the usefulness of this approach, the 10 bar truss and the jacket type offshore structure are presented. SORA(Sequential Optimization & Reliability Assessment) is adopted in CESD as a probabilistic optimization methodology, and its usefulness in decreasing the computational cost is verified also.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.537-547
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• 2001

The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.52.1-52.1
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• 2017

Galaxy clusters are the most massive gravitationally bound systems and thus probably the most recent objects to form. One of promising routes to understand the assembly history of galaxy clusters is to measure observable quantities of components in clusters that are sensitive to the evolutionary state of the cluster. Recent deep observations on the nearby clusters show distinct diffuse intracluster light (ICL), that the light from stars are not bound any individual cluster galaxy, however until now this component has not been well studied due to its faint nature, with typical brightness of ~100 times fainter than the sky background. As shown in galaxy cluster simulation studies, the ICL abundance increases during various dynamical exchanges of galaxies such as the disruption of dwarf galaxies, major mergers between galaxies and the tidal stripping of galaxies. Thus, the ICL is an effective tool to measure the evolutionary stage of galaxy clusters. Moreover, the investigation of the ICL evolution mechanism will allow us understand the galaxy evolution process therein. In this pilot study, we target the Coma cluster, where the existing ICL studies are limited only in the central region. With large and uniform deep optical images from the Subaru telescope, available only recently (Okabe et al. 2014), we are developing a robust ICL measurement technique, extracting the ICL surface brightness and color profiles, which will allow us to study the origin of the ICL and its connection to the evolutionary history of the Coma cluster. For the next phase, we plan to utilize the plenty of spectroscopy data from the MMT telescope to compare ICL properties with the star formation history of the brightest cluster galaxies (BCG), and discuss the ICL formation mechanism of the Coma cluster by comparing the distribution of cluster galaxies with the distribution of diffuse light inside the Coma cluster.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.347-355
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• 2020

An Isolation-with-Migration (IM) model is used to estimate extant population sizes, the splitting time of populations split away from their common ancestral populations, and migration rates between the extant populations. An evolutionary model such as IM models is estimated by analyzing DNA sequences sampled from the extant populations in the model. When a true model includes an unsampled 'ghost' population without data, the unsampled population is often ignored from the evolutionary model to infer. In this paper, we conduct a simulation study to investigate the effect of an unsampled population on the estimation of the size of the sampled population. When there exists an unsampled population that shares migrations with the sampled population, the size estimation of the sampled population was biased. However, the size estimation was improved if an evolutionary model, including the unsampled population, was estimated.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.231-241
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• 2018

This is a study of reputation from the perspective of evolutionary psychology. To start a theory building process in PR, Tall Puppy scale is examined using dominance hierarchy and reputation hierarchy. Tall Puppy scale is a measure toward highly successful, thus famous people. when they fall. The result showed that Koreans have negative attitude toward famous people 8times more and prefer their fall than Austrailians. The number one variable to explain the psychology of reputation hierarchy was self-esteem. It was strongly correlated with reputation hierarchy attitude. People with higher self-esteem were more generous about famous figures when people with low self-esteem prefer more the fall of tall puppies. A discussion for reputation hierarchy theory is followed.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.361-371
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• 2000

This paper treats a genetic algorithm for ship scheduling problem in set packing formulation. We newly devised a partition based representation of solution and compose initial population using a domain knowledge of problem which results in saving calculation cost. We established replacement strategy which makes each individual not to degenerate during evolutionary process and applied adaptive mutate operator to improve feasibility of individual. If offspring is feasible then an improve operator is applied to increase objective value without loss of feasibility. A computational experiment was carried out with real data and showed a useful result for a large size real world problem.

• Journal of Technology Innovation
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• v.12 no.1
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• pp.135-160
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• 2004

We witness now the changing techno-economic paradigm and the emerging learning economy. Reflecting on these changes, the group of Evolutionary Economists study recently the theory on regional innovation system, but their research results are still now not theoretically ‘systemized’. Moreover, they often indeed speak of the ‘social capital’, but do not investigate that. This paper tries to systemize their empirical findings and theoretical results and integrate the discussions on social capital in fields of sociology into a mathematical model. This study emphasizes the role of social capital in the innovating process.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.209-225
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• 2013

A procedure employing a Teaching-Learning Based Optimization (TLBO) method is developed to design discrete pin jointed structures. TLBO process consists of two parts: the first part represents learning from teacher and the second part illustrates learning by interaction among the learners. The results are compared with those obtained using other various evolutionary optimization methods considering the best solution, average solution, and computational effort. Consequently, the TLBO algorithm works effectively and demonstrates remarkable performance for the optimization of engineering design applications.