• Geomechanics and Engineering
• /
• 제7권2호
• /
• pp.149-164
• /
• 2014

One of the most advanced classes of techniques for ground response analysis is based on the use of Transfer Functions. They represent the ratio of Fourier spectrum of amplitude motion at the free surface to the corresponding spectrum of the bedrock motion and they are applied in frequency domain usually by FFT method. However, Fourier spectrum only shows the dominant frequency in each time step and is unable to represent all frequency contents in every time step and this drawback leads to inaccurate results. In this research, this process is optimized by decomposing the input motion into different frequency sub-bands using Wavelet Multi-level Decomposition. Each component is then processed with transfer Function relating to the corresponding component frequency. Taking inverse FFT from all components, the ground motion can be recovered by summing up the results. The nonlinear behavior is approximated using an iterative procedure with nonlinear soil properties. The results of this procedure show better accuracy with respect to field observations than does the Conventional method. The proposed method can also be applied to other engineering disciplines with similar procedure.

• 지식경영연구
• /
• 제21권1호
• /
• pp.27-40
• /
• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• Wind and Structures
• /
• 제32권4호
• /
• pp.355-369
• /
• 2021

Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

• 한국소음진동공학회논문집
• /
• 제12권6호
• /
• pp.461-468
• /
• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Advances in materials Research
• /
• 제5권2호
• /
• pp.67-80
• /
• 2016

The objective of the present work is to optimize process parameters namely, cutting speed, feed rate, and depth of cut in milling of AISI 304 stainless steel. In this work, experiments were carried out as per the Taguchi experimental design and an $L_{27}$ orthogonal array was used to study the influence of various combinations of process parameters on surface roughness (Ra) and material removal rate (MRR). As a dynamic approach, the multiple response optimization was carried out using grey relational analysis (GRA) and desirability function analysis (DFA) for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. The optimum process parameters found to be cutting speed at 63 m/min, feed rate at 600 mm/min, and depth of cut at 0.8 mm. Analysis of variance (ANOVA) was employed to classify the significant parameters affecting the responses. The results indicate that depth of cut is the most significant parameter affecting multiple response characteristics of GFRP composites followed by feed rate and cutting speed. The experimental results for the optimal setting show that there is considerable improvement in the process.

• 산업식품공학
• /
• 제21권3호
• /
• pp.256-266
• /
• 2017

This study was designed to optimize ethanol extraction process of unfertilized corn silk (UCS) to maximize phytochemical contents and bioactivities. The response surface methodology (RSM) with central composite design (CCD) was employed to obtain the optimal extraction conditions. The influence of ethanol concentration, extraction temperature and extraction time on total polyphenol contents, total flavonoid contents, maysin contents, 2,2-diphenyl-1-picrylhydrazyl(DPPH) radical scavenging activities and tyrosinase inhibition were analyzed. For all dependable variables, the most significant factor was ethanol concentration followed by extraction temperature and extraction time. The following optimum conditions were determined by simultaneous optimization of several responses with the Derringer's desirability function using the numerical optimization function of the Design-Expert program: ethanol concentration 80.45%, extraction temperature $53.49^{\circ}C$, and extraction time 4.95 h. Under these conditions, the predicted values of total polyphenol contents, total flavonoid contents, maysin contents, DPPH radical scavenging activity and tyrosinase inhibition were $2758.74{\mu}g\;GAE/g$ dried sample, $1520.81{\mu}g\;QUE/g$ dried sample, 810.26 mg/100g dried sample, 56.86% and 43.49%, respectively, and the overall desirability (D) was 0.74.

• 한국산업융합학회 논문집
• /
• 제26권5호
• /
• pp.895-905
• /
• 2023

Mud tanks used for storing and supplying mud in mud supply systems are essential to secure structural stability according to the mud loads inside the tank. In terms of structural stability of the mud tank can be ensured by increasing the thickness of the structure. However, increasing the thickness may cause a problem of increasing production costs. In addition, this increases the weight of the tank, which can cause problems with the trailer loading weight limitation during transportation. To satisfy both these problems and structural stability, the mud tank should be optimally designed. Therefore, this study conducted an optimum design in consideration of the load of the mud tank through the structural analysis and response surface optimization method in ANSYS.

• Smart Structures and Systems
• /
• 제15권3호
• /
• pp.897-911
• /
• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 2006년 추계학술발표대회 개요집
• /
• pp.104-106
• /
• 2006

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2000년도 춘계학술대회논문집
• /
• pp.619-624
• /
• 2000

Design of experiments based on Taguchi's orthogonal array is utilized for exploring the design space and for building response surface models of insulator and isolator database in order to facilitate the effective solution of multi-objective optimization commonly occurred in NVH problems. Response surface models, called engineering database of design space, provide an efficient means to rapidly model the trade-off among many conflicting NVH goals in automotive. In the design of insulator and isolator in automotive interior part, it is important not only to construct effective matrices of NVH but also to build up engineering database of current products. The experimental design especially based on orthogonal array and the nonlinear optimization algorithms are successfully used together to obtain the optimal design of insulator and isolator. The $2^{nd}$ order response surface models of absorption coefficient and insertion loss are constructed by using modified Taguchi's $L_{12}2^13^7$ orthogonal array and successfully used in optimal design of insulator and isolator.