• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1109-1114
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• 2012

The performance of a system can be affected by various variables such as manufacturing tolerances, uncertainties of material properties, and environmental factors acting on the system. Robust design optimization has attracted much attention in the design of products because it can find the best design solution that minimizes the variance of the response while considering the distribution of the variables. However, the computational cost and accuracy of optimization have thus far been a challenging problem. In this study, robust design optimization using the multiplicative decomposition method is proposed in order to solve these problems. Because the proposed method calculates the mean and variance of the system directly from the kriging metamodel using the multiplicative decomposition method, it can be used to search for a robust optimum design accurately and efficiently. Several mathematical and engineering examples are used to demonstrate the feasibility of the proposed method.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.225-238
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• 2019

Migration velocity analysis (MVA) for creating optimum depth-domain velocities in seismic imaging was applied to marine long-offset multi-channel data, and the effectiveness of the MVA approach was demonstrated by the combinations of conventional data processing procedures. The time-domain images generated by conventional time-processing scheme has been considered to be sufficient so far for the seismic stratigraphic interpretation. However, when the purpose of the seismic imaging moves to the hydrocarbon exploration, especially in the geologic modeling of the oil and gas play or lead area, drilling prognosis, in-place hydrocarbon volume estimation, the seismic images should be converted into depth domain or depth processing should be applied in the processing phase. CMP-based velocity analysis, which is mainly based on several approximations in the data domain, inherently contains errors and thus has high uncertainties. On the other hand, the MVA provides efficient and somewhat real-scale (in depth) images even if there are no logging data available. In this study, marine long-offset multi-channel seismic data were optimally processed in time domain to establish the most qualified dataset for the usage of the iterative MVA. Then, the depth-domain velocity profile was updated several times and the final velocity-in-depth was used for generating depth images (CRP gather and stack) and compared with the images obtained from the velocity-in-time. From the results, we were able to confirm the depth-domain results are more reasonable than the time-domain results. The spurious local minima, which can be occurred during the implementation of full waveform inversion, can be reduced when the result of MVA is used as an initial velocity model.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.139-148
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• 2014

In recent years, computational models using parametric estimation method have been developed and used widely for efficient cost analysis. In this research, by applying experienced data from Guidance and Control Systems in Missile System field, the cost analysis for engineering model and commercial computational model(Price H, HL, M, S) are conducted and its result is analysed, so that the difference between two models and its grounds are apprehended. Comparing the calibrated value of computational model based on the data base of similar equipment and the cost from the engineering estimation, the two results are very close. It means that the credibility of data is enhanced through calibration. Also, for cost analysis of similar components in the future, the method for calibration of the computational models is also examined. When estimating development cost in this research, although many parts have been estimated through uncertain elements, the reliability could have been enhanced by applying computational model which secures objectivity. It is a very reasonable estimation method by utilizing calibration of the computational models based on existing accumulated development data.