• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.14 no.3
• /
• pp.85-91
• /
• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.589-594
• /
• 2007

This paper is shown new method for durability assesment and design have been noticed to be very valuable has been successfully applied to predict concrete structures. This paper provides that a new approach for predicting the corrosion durability of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successive1y by the Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures under chloride attack environments.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.2
• /
• pp.177-183
• /
• 2013

We describe a new method for selecting design variables for shape optimization of high-voltage gas circuit breaker using a Kriging meta-model and a genetic algorithm. Firstly we sample balance design variables using the Latin Hypercube Sampling. Secondly, we build meta-model using the Kriging. Thirdly, we search the optimal design variables using a genetic algorithm. To obtain the more exact design variable, we adopt the boundary shifting method. With the proposed optimization frame, we can get the improved interruption design and reduce the design time by 80%. We applied the proposed method to the optimization of multivariate optimization problems as well as shape optimization of a high - voltage gas circuit breaker.

• The KSFM Journal of Fluid Machinery
• /
• v.12 no.3
• /
• pp.7-12
• /
• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.477-488
• /
• 2000

A distance measure between two Latin-hypercube designs is defined and its expected value is computed. It was computed by using mathematical statistics, numerical analysis (multidimensional numerical integration), Monte-carlo method, and the theory of asymptotic normal distribution. For the comparison of two Latin-hypercube designs with same structure but different randomness, the difference of expected values of response function and information mass of experimental designs are considered. These methods may be useful in comparison between two general experimental designs.

• The KSFM Journal of Fluid Machinery
• /
• v.10 no.3 s.42
• /
• pp.39-46
• /
• 2007

This study presents a numerical procedure to optimize the shape of staggered dimple surface to enhance turbulent heat transfer in a rectangular channel. The RBNN method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer with shear stress transport (SST) turbulence model. The dimple depth-to-dimple print diameter (d/D), channel height-to-dimple print diameter ratio (H/D), and dimple print diameter-to-pitch ratio (D/S) are chosen as design variables. The objective function is defined as a linear combination of heat transfer related term and friction loss related term with a weighting factor. Latin Hypercube Sampling (LHS) is used to determine the training points as a mean of the design of experiment. The optimum shape shows remarkable performance in comparison with a reference shape.

• Steel and Composite Structures
• /
• v.8 no.1
• /
• pp.35-52
• /
• 2008

The paper investigates the seismic performance of a Partially-Restrained (PR) steel-concrete composite frame using the probabilistic approach. The analysed frame was tested at the ELSA laboratory of the Joint Research Centre of Ispra (Italy), while the representative beam-to-column composite connections were tested at the Universities of Pisa, Milan and Trento (Italy). The component modelling of both interior and exterior composite joints is described first, including the experimental-numerical validation. The Latin Hypercube method has been used to draw the probabilistic distribution curves of joints, and then the whole PR composite frame has been analysed. Pushover and incremental dynamic analyses have been carried out using the non-linear FE code SAP2000 version 9.1. The fragility and performance curves of the PR composite frame have been determined for four damage limit states.

• Transactions on Electrical and Electronic Materials
• /
• v.7 no.4
• /
• pp.210-214
• /
• 2006

In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.2
• /
• pp.207-212
• /
• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• International Journal of Reliability and Applications
• /
• v.2 no.1
• /
• pp.27-36
• /
• 2001

This Paper proposes a new methodology for assessing the reliability of an accident management, which Is based on the reliability physics and the scheme to generate dynamic event tree. The methodology consists of 3 main steps: screening; uncertainty propagation; and probability estimation. Sensitivity analysis is used for screening the variables of significance. Latin Hypercube sampling technique and MAAP code are used for uncertainty propagation, and the dynamic event tree generation method is used for the estimation of non-success probability of implementing an accident management strategy. This approach is applied in assessing the non-success probability of implementing a cavity flooding strategy, which is to supply water into the reactor cavity using emergency fire systems during the sequence of station blackout at the reference plant.