• International Journal of Highway Engineering
• /
• v.15 no.6
• /
• pp.69-78
• /
• 2013

PURPOSES : In this study blast furnace slag, an industrial byproduct, was used with an activating chemicals, $Ca(OH)_2$ and $Na_2SiO_3$ for carbon capture and sequestration as well as strength development. METHODS : This paper presents the optimized mixing design of Carbon-Capturing and Sequestering Activated Blast-Furnace Slag Mortar. Design of experiments in order to the optimized mixing design was applied and commercial program (MINITAB) was used. Statistical analysis was used to Box-Behnken (B-B) method in response surface analysis. RESULTS : The influencing factors of experimental are water ratio, Chemical admixture ratio and Curing temperature. In the results of response surface analysis, to obtain goal performance, the optimized mixing design for Carbon-Capturing and Sequestering Activated Blast-Furnace Slag Mortar were water ratio 40%, Chemical admixture ratio 58.78% and Curing temperature of $60^{\circ}C$. CONCLUSIONS : Compared with previous studies of this experiment is to some extent the optimal combination is expected to be reliable.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.26 no.3
• /
• pp.205-213
• /
• 2023

An optimal design of a simple beam-shaped flexure hinge mount supporting an optical mirror is presented. An optical mirror assembly is an opto-mechanically coupled system as the optical and mechanical behaviors interact. This side-supporting mount is flexible in the radial direction and rigid for the remaining degrees of freedom to support the mirror without transferring thermal load. Through thermo-elastic, optical and eigenvalue analysis, opto-mechanical performance was predicted to establish the objective functions for optimization. The key design parameters for this flexure are the thickness and length. To find the optimal values of design parameters, response surface analysis was performed using the design of experiment based on nested FCD. Optimal design candidates were derived from the response surface analysis, and the optimal design shape was confirmed through Opto-mechanical performance validation analysis.

• Journal of the Korean Society of Safety
• /
• v.21 no.6 s.78
• /
• pp.74-81
• /
• 2006

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Arch Bridge. Component reliabilities of girders have been evaluated using the response surfaces of the design variables at the selected critical sections based on the maximum shear and negative moment locations. Response Surface Method(RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to be obtained by Monte-Carlo Simulations or by First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system composed of girders is changed into parallel series connection system. The upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significantly reduced time and efforts compared with the previous permutation method or system reliability analysis method.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.295-300
• /
• 2007

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Arch Bridge. Component reliabilities of girders have been evaluated using the response surfaces of the design variables at the selected critical sections based on the maximum shear and negative moment locations. Response Surface Method (RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to be obtained by Monte-Carlo Simulations or by First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system composed of girders is changed into parallel series connection system. The upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significant]y reduced time and efforts compared with the previous permutation method or system reliability analysis method.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.7 no.4
• /
• pp.135-141
• /
• 2008

Independent suspension axle and final reduction gear for special-purpose vehicles such as a armored vehicles are almost imported in Germany etc. so, developing them is necessary to save cost. In severe condition (open fields, water surface driving, obstacle pass), special-purpose vehicles must work well. Drop box, axle and final reduction gear performed static analysis. We know that is possible weight reduction. The purpose of this paper is to find out the optimal shape of final reduction gear's case by means of response surface methodology. The response surface method is the statistical method which can be applied to the non-sensitivity based optimization. The response surface which is constructed by the least square method contains only the polynomial terms so that the global maximum and minimum points are easily obtained.

• Computational Structural Engineering
• /
• v.7 no.1
• /
• pp.109-116
• /
• 1994

In this paper, various reliability analysis methods for calculating a probability of failure are investigated for their accuracy and efficiency. Crude Monte Carlo method is used as a basis for the comparison of various numerical results. For the sampling methods, Importance Sampling method and Directional Simulation method are considered for overcoming a drawback of Crude Monte Carlo method. For the approximate methods, conventional Rackwitz-Fiessler method. 3-parameter Chen-Lind method, and Rosenblatt transformation method are compared on the basis of First order reliability method. As a Second-order reliability method, Curvature-Fitting paraboloid method, Point-fitting paraboloid method, and Log-likelihood function method are explored in order to verify the accuracy of the reliability calculation results. These methods mentioned above would have some difficulty unless the limit state equation is expressed explicitly in terms of random design variables. Thus, there is a need to develop some general reliability methods for the case where an implicit limit state equation is given. For this purpose, Response surface method is used where the limit state equation is approximated by regression analysis of the response surface outcomes resulted from the structural analysis. From the application of these various reliability methods to three examples, it is found that Directional Simulation method and Response Surface method are very efficient and recommendable for the general reliability analysis problem cases.

• Structural Engineering and Mechanics
• /
• v.21 no.5
• /
• pp.507-518
• /
• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• Proceedings of the KSME Conference
• /
• 2004.11a
• /
• pp.510-515
• /
• 2004

A proton exchange membrane fuel cells(PEMFC) operate at low temperature, allowing for faster startups and immediate response to change in the demand for power, and also deliver high power density. To maximize economical efficiency in PEMPC, it is necessary to the optimization. Response surface method(RSM) has non-gradient and fast convergency characteristics. Sampling points are extracted by design of experiments using Central Composite Method. In this paper, it is shown that the optimization is required for the design study of the PEMFC.

• Smart Structures and Systems
• /
• v.25 no.6
• /
• pp.679-691
• /
• 2020

To identify the bridge information from the response of test vehicles passing on it (also known as the indirect approach) has aroused the interest of many researchers thanks to its economy, easy implementation and less disruption to traffic. The surface roughness of bridge remains an obstacle for such method as it contaminates the vehicle response severely and thereby renders many vehicle-response-based bridge identification methods ineffective. This study aims to eliminate such effect with the responses of two different test vehicles. The proposed method can estimate the surface profile of a bridge based on the acceleration data of the vehicles running on the bridge successively, and obtain the normalized contact point response, which proves to be relatively immune to surface roughness. The frequencies and mode shapes of bridge can be further extracted from the normalized contact point acceleration with spectral analysis and Hilbert transform. The effectiveness of the proposed method is verified numerically with a three-span continuous bridge. The influence of measurement noise is also examined.

• Structural Engineering and Mechanics
• /
• v.56 no.4
• /
• pp.549-567
• /
• 2015

A first-order moment method (FORM) reliability analysis is commonly used for structural stability analysis. It requires the values and partial derivatives of the performance to function with respect to the random variables for the design. These calculations can be cumbersome when the performance functions are implicit. A Gaussian process (GP)-based response surface is adopted in this study to approximate the limit state function. By using a trained GP model, a large number of values and partial derivatives of the performance functions can be obtained for conventional reliability analysis with a FORM, thereby reducing the number of stability analysis calculations. This dynamic renewed knowledge source can provide great assistance in improving the predictive capacity of GP during the iterative process, particularly from the view of machine learning. An iterative algorithm is therefore proposed to improve the precision of GP approximation around the design point by constantly adding new design points to the initial training set. Examples are provided to illustrate the GP-based response surface for both structural and non-structural reliability analyses. The results show that the proposed approach is applicable to structural reliability analyses that involve implicit performance functions and structural response evaluations that entail time-consuming finite element analyses.