• Steel and Composite Structures
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• v.25 no.6
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.263-274
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• 2010

Business survey index(BSI) is an economic forecasting index made on the basis of the past achievement of the company and enterpriser's plan and decision for the future. Even the index is very popular in economic situations, only a little research result is known to the public. In the paper we investigate statistical properties of BSI. We define population BSI in the finite population and estimate it unbiasedly. Also we derive the variance of the estimated BSI and its unbiased estimator. In addition, confidence interval of the estimated BSI is proposed. We asserte that confidence interval of the estimated BSI is more reasonable than the relative standard error.

• Transactions of Materials Processing
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• v.28 no.4
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• pp.203-211
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• 2019

In this study, the weight of type IV pressure vessel is optimized through the burst pressure condition using the finite element analysis (FEA) based on the genetic algorithm (GA). The optimization design variables include the thickness of composite layers and the winding angles. The optimized design variables are validated using the numerical simulations for the pressure vessel. Consequently, the weight is decreased by about 6.5% as compared to the previously reported results for Type III pressure vessel. Additionally, a method which reduces the entire optimization time is proposed. In the original method, the population size is constant across all generations. However, the proposed method could reduce the workload through the reduction of the population size by half for every 25 generations. Thus, the proposed method is observed to increase the weight by about 0.1%, however, the working time for the optimization could be decreased by about 46.5%.

• Animal cells and systems
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• v.6 no.1
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• pp.19-22
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• 2002

Life table studies were conducted in the laboratory for the eulophid gregarious pupal parasitoid, Tetrastichus sp., on Hyphantria cunea Drury at a constant temperature of 28.2$\pm$2$^{\circ}C$, 50-60% RH to evaluate their impact on the host and their potential biological control. Development of immature stage took 20.1$\pm$2.7 d: adult females lived for 23.2$\pm$2.2 (range, 16-27)d and produced a mean of 53.6$\pm$26.6 adult progeny per female, with a sex ratio of 1: 9.5 (M:F). The intrinsic rate of natural increase (r$_{m}$) was 0.178/ female/day; the net reproductive rate (R$_{o}$), 46.74; the capacity for increase (r$_{c}$) 0.177; the finite rate of increase (λ) 1.19/female/day; thus each female contributed 46.74 individuals to the population in a mean generation time of 21.6 d. Biological factors in determining the life history trait variation of the parasitoid were discussed.d.d.d.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.651-659
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• 2002

Component Mode Synthesis (CMS) is a dynamic substructuring technique to get an approximate eigensolutions of large degree-of-freedom structures divisible into several components. But, In practice. most of large structures are modeled by different teams of engineers. and their respective finite element models often require different mesh resolutions. As a result, the finite element substructure models can be non-conforming and/or incompatible. In this work, A hybrid version of component mode synthesis using a localized lagrange multiplier to treat the non-conforming mesh problem was derived. Evolution Strategies (ESs) is a stochastic numerical optimization technique and has shown a robust performance for solving deterministic problems. An ESs conducts its search by processing a population of solutions for an optimization problem based on principles from natural evolution. An optimization example for raising the first natural frequency of a plate structure using beam stiffeners was presented using hybrid component mode synthesis and robust evolution strategies (RES) optimization technique. In the example. the design variables are the positions and lengths of beam stiffeners.

• Geomechanics and Engineering
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• v.9 no.6
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• pp.689-707
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• 2015

Progressive increase in population causing land scarcity, which is forcing construction industry to build multistory buildings having underground basements. Normally, basements are constructed for parking facility. This research work evaluates important factors which have caused the collapse of pile-anchor system at under construction five star hotel. 21 m deep excavation is carried out, to have five basements, after installation of 600 mm diameter cast in-situ contiguous concrete piles at plot periphery. To retain piles and backfill, soil anchors are installed as pit excavation is proceeded. Before collapse, anchors are designed by federal highway administration procedure and four anchor rows are installed with three strands per anchor in first row and four in remaining. However, after collapse, system is modeled and analyzed in plaxis using mohr-coulomb method. It is investigated that in-appropriate evaluation of soil properties, additional surcharge loads, lesser number of strands per anchor, shorter grouted body length and shorter pile embedment depth caused large deformations to occur which governed the collapse of east side pile wall. To resume work, old anchors are assumed to be standing at one factor of safety and then system is analyzed using finite element approach. Finally, it is concluded to use four strands per anchor in first new row and five strands in remaining three with increase in grouted and un-grouted body lengths.

• International Journal of Railway
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• v.8 no.1
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• pp.15-20
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• 2015

As a result of the current population concentrations in urban centers, demand for intercity transportation is increasing rapidly. Railway transportation is becoming popular as an intercity transportation because of its timely service, travel speeds and transport efficiency. Among the many railway systems, the innovative and environmentally friendly maglev system has been rated very highly as the next-generation intercity railway system. Linear induction motors are widely used for the propulsion of maglev trains because of their light weight and low construction costs. The urban maglev that was recently completed in Incheon airport site employs a 110km/h class linear induction motor. However, this system was designed to meet requirements for inner-city operations and is not suitable as an intercity transportation system, which requires medium to high speeds. Therefore, this study deals with the characteristics and designs of linear induction motors used for the propulsion of maglev trains that can be used as intercity trains. Rail car specifications for high-speed trains have been presented, and the characteristics of linear induction motors that can be used for the propulsion of these trains have been derived using the finite element method (FEM).

• Journal of the Korean institute of surface engineering
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• v.52 no.1
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• pp.43-51
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• 2019

The environmental pollution which is global warming and abnormal climate is caused by increasing population and activated economics. To reduce environmental pollution, we have being efforts into reducing $CO_2$ emission and use of energy, resources. Especially, for the sake of light weight and fuel efficiency of automotive industry, many countries have defined the restrict environmental regulation which stipulate high magnitude of reducing $CO_2$ emission. In this study, we have predicted the problem of Mu-cell injection molding through the finite element analysis as a function of temperature controlled by Joule heating or in terms of mold temperature. From the result of finite element analysis, we have determined the optimized process and made the injection mold included electric current heating system with Mu-cell manufacturing. Lastly, we analyzed the surface characteristics of the injection products with mold temperature.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.281-290
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• 2007

Linear estimator, a weighted sum of the sample observation, is commonly adopted to estimate the finite population parameters such as population totals in survey sampling. The weight for a sampled unit is often constructed by multiplying the base weight, which is the inverse of the first-order inclusion probability, by an adjustment term that takes into account of the auxiliary information obtained throughout the population. The linear estimator using the weight adjustment is often more efficient than the one using only the bare weight, but its valiance estimation is more complicated. We discuss variance estimation for a general class of weight-adjusted estimator. By identifying that the weight-adjusted estimator can be viewed as a function of estimated nuisance parameters, where the nuisance parameters were used to incorporate the auxiliary information, we derive a linearization of the weight-adjusted estimator using a Taylor expansion. The method proposed here is quite general and can be applied to wide class of the weight-adjusted estimators. Some examples and results from a simulation study are presented.