• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.537-551
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• 2017

In this paper, a two-phase flow solver $HiFoam^{(R)}$ has been developed based on the $OpenFOAM^{(R)}$ to predict resistance of a ship in calm water. The VOF method of $OpenFOAM^{(R)}$ was reviewed and a simple flux limiter was introduced to enhance the robustness of the solver. The procedure for predicting ship motion was modified by introducing Quasi-Steady Fluid-Body Interaction (QS-FBI) with least square regression to improve the efficiency. Other minor factors were considered as well in terms of the efficiency and robustness. The HiFoam was applied to KCS and JBC simulations to validate its efficiency and accuracy by comparing the results to experimental data and STAR-CCM+. The $HiFoam^{(R)}$ was also applied to various ships and it showed good agreements to the experimental data.

• Journal of applied mathematics & informatics
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• v.11 no.1_2
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• pp.59-80
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• 2003

An incomplete factorization method for preconditioning symmetric positive definite matrices is introduced to solve normal equations. The normal equations are form to solve linear least squares problems. The procedure is based on a block incomplete Cholesky factorization and a multilevel recursive strategy with an approximate Schur complement matrix formed implicitly. A diagonal perturbation strategy is implemented to enhance factorization robustness. The factors obtained are used as a preconditioner for the conjugate gradient method. Numerical experiments are used to show the robustness and efficiency of this preconditioning technique, and to compare it with two other preconditioners.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.1
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• pp.53-61
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• 2008

In this research, the layout and geometry of U-type ribs in the part, including significant process conditions, are automatically optimized to reduce part warpage with robustness in consideration. The optimization procedure are based on an iterative redesign methodology integrated with computer aided injection molding simulation, Taguchi's Design of Experiment(DOE), and a direct search-based optimization method. The robustness of a design alternative is efficiently measured by introducing composite noise factor and Taguchi's signal-to-noise ratio. As a solution search methodology, the modified design space reduction method based on orthogonal arrays is employed to exploit an optimal robust design alternative. To illustrate the proposed methodology, a case study is performed on simulation results, where an optimal robust design alternative is obtained with a moderate number of iterations.

• Transactions of Materials Processing
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• v.12 no.5
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• pp.465-472
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• 2003

Engineering design can be viewed as a decision making process, which involves the nonlinear tradeoffs task among the multiple conflicting attributes and considers the robustness of design. In order to obtain best engineering design, methodology for accurate assessment of his/her preference about the multiple attributes is required. Conventionally, intuitive procedures based on lottery questions are used to elicit the designer's preference structure: however, they can lead to inconsistent and inexact preference results due to the rank reversal problems derived from the designer's big cognitive burden. In this paper, alternatively, a design methodology based on multiattribute utility function through the pairwise comparison among alternatives is presented. The proposed procedure is applied to an actual injection mold design with the aid of the CAE simulation and the result is discussed.

• Structural Engineering and Mechanics
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• v.78 no.4
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• pp.485-496
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• 2021

So far analytical methods on collapse assessment of three-dimensional (3-D) steel frames have mainly focused on a single-column-removal scenario. However, the collapse of the Federal Building in the US due to car bomb explosion indicated that the loss of multiple columns may occur in the real structures, wherein the structures are more vulnerable to collapse. Meanwhile, the General Services Administration (GSA) in the US suggested that the removal of side columns of the structure has a great possibility to cause collapse. Therefore, this paper analytically deals with the robustness of 3-D steel frames in a two-side-column-removal (TSCR) scenario. Analytical method is first proposed to determine the collapse resistance of the frame during this column-removal procedure. The reliability of the analytical method is verified by the finite element results. Moreover, a design-based methodology is proposed to quickly assess the robustness of the frame due to a TSCR scenario. It is found the analytical method can reasonably predict the resistance-displacement relationship of the frame in the TSCR scenario, with an error generally less than 10%. The parametric numerical analyses suggest that the slab thickness mainly affects the plastic bearing capacity of the frame. The rebar diameter mainly affects the capacity of the frame at large displacement. However, the steel beam section height affects both the plastic and ultimate bearing capacity of the frame. A case study on a six-storey steel frame shows that the design-based methodology provides a conservative prediction on the robustness of the frame.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.570-574
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• 1987

The robust servo controller is designed by the procedure of LQG/LTR method in the continuous-time domain. This design results is equivalently converted to the discrete-time suboptimal LQG in order to implement by the microcomputer system. The LTP, condition of the discrete-time LQG is analyzed and approved by the experiments against the uncertainty of real plant, the discretized LQG /LTR control shows the good robustness.

• Advances in aircraft and spacecraft science
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• v.3 no.2
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• pp.211-224
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• 2016

The present study aims to investigate the shimmy stability behavior of a single wheeled nose landing gear system. The system is supposed to be equipped with an electromechanical actuator capable to control the shimmy vibrations. A Proportional-Integrative-Derivative (PID) controller, tuned by using the Particle Swarm Optimization (PSO) procedure, is here proposed to actively damp the shimmy vibration. Time-history results for some test cases are reported and commented. Stochastic analysis is last presented to assess the robustness of the control system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.255-259
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• 1996

This paper presents active vibration control of a rotating cantilevered beam using piezoceramic actuators. A governing equation of motion is obtained by the Hamilton's principle and expressed in the state space representation. Subsequently, an H$_{\infty}$ control which is robust to system uncertainties is synthesized through the loop shaping design procedure. Computer simulations for the steady-state vibration control are undertaken in order to demonstrate the effectiveness and robustness of the proposed control methodology..y.

• Journal of computational fluids engineering
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• v.8 no.3
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• pp.12-20
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• 2003

A numerical procedure for the calculation of solidification and melting phase change using PISO algorithm is presented. In case of phase change problem, the coupling between velocity/pressure/temperature and liquid fraction is important. The converged temperature and liquid fraction solution which satisfies the energy balance is acquired by applying enthalpy method into inner iteration in matrix solver. And a modified PISO algorithm version is introduced to properly solve the coupling between velocity/pressure/temperature and liquid fraction. A comparison of the proposed procedure with a standard iterative method shows improvement both in terms of computing speed and robustness.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.575-582
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• 2019

The problem of selecting variables in the presence of outliers is considered. Variable selection and outlier detection are not separable problems because each observation affects the fitted regression equation differently and has a different influence on each variable. We suggest a simultaneous method for variable selection and outlier detection in a linear regression model. The suggested procedure uses a sequential method to detect outliers and uses all possible subset regressions for model selections. A simplified version of the procedure is also proposed to reduce the computational burden. The procedures are compared to other variable selection methods using real data sets known to contain outliers. Examples show that the proposed procedures are effective and superior to robust algorithms in selecting the best model.