• Proceedings of the KSME Conference
• /
• 2007.05b
• /
• pp.2690-2695
• /
• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• IE interfaces
• /
• v.23 no.3
• /
• pp.257-263
• /
• 2010

Taguchi defined a good quality as 'A correspondence of product characteristic's expected value to the objective value satisfying the minimum variance condition.' For his good quality, he suggested Taguchi Method which is called Robust design which is irrelevant to the effect of these noise factors. Taguchi Method which has many success examples and which is used by many manufacturing industry. But Optimal solution of Taguchi Method is one among the experiments which is not optimal area of experiment point. On the other hand, Response Surface Method (RSM) which has advantage to find optimal solution area experiments points by approximate polynomial regression. But Optimal of RSM is depended on initial point and RSM can not use many factors because of a great many experiment. In this paper, we combine the Taguchi Method and the Response Surface Method with each advantage which is called Taguchi-RSM. Taguchi-RSM has two step, first step to find first solution by Taguchi Method, second step to find optimal solution by RSM with initial point as first step solution. We give example using catapults.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.21 no.3
• /
• pp.15-23
• /
• 2013

Weight reduction of a automobile has been steadily tried in automotive industry to improve fuel efficiency, driving performance and the production profits. Since the weight of BIW takes up a large portion of the total weight of the automobile, reducing the weight of BIW greatly contributes to reducing the total weight of the vehicle. To reduce weight, vehicle manufacturers have tried to apply lightweight materials, such as aluminum and high-strength steel, to the components of BIW instead of conventional steel. In this research, material arrangement of an automotive BIW was optimized by formulating a design problem to minimize weight of the BIW while satisfying design requirements about bending and torsional stiffness and perform a metamodel-based design optimization strategy. As a result of the design optimization, weight of the BIW is reduced by 45.7% while satisfying all design requirements.

• Agricultural and Biosystems Engineering
• /
• v.2 no.2
• /
• pp.63-68
• /
• 2001

The objective of this study was to develop a real-time soil moisture meter using RF impedance. The impedance suchas capacitance and resistance (or conductance) was analyzed using parallel cylinder type capacitance probe(C-probe) and Q-meter (HP4342). The capacitance and conductance of soil increased as volumetric water content increased. The 5 MHz of modified Colpitts type crystal oscillator was designed to detect the capacitance change of the C-probe with moist soil. A third order polynomial regression model was proposed to describe the relationship between RF impedance and volumetric water content. The prototype real time moisture meter consisted of the C-probe, sample container, oscillator, frequency counter and related signal processing units. The calibration equation for measurement of volumetric moisture content of soil was developed and validated. The correlation coefficient and root mean square error between measured volumetric water content by oven method and predicted values by prototype moisture meter for unknown soil samples were 0.984 and 0.032$cm^3$$cm\^3$, respectively.

• Geomechanics and Engineering
• /
• v.20 no.4
• /
• pp.345-358
• /
• 2020

Numerous studies have repeatedly demonstrated the efficiency of using skirts to increase the bearing capacity and to reduce settlement of shallow foundations subjected to static loads. However, no efforts have been made to study the efficiency of using these skirts to reduce settlement produced by machine vibration, although machines are very sensitive to settlement and the foundations of these machines should be designed properly to ensure that the settlement produced due to machine vibration is very small. This research has been conducted to investigate the efficiency of using skirts as a technique to reduce the settlement of a strip foundation subjected to machine vibration. A two-dimensional finite element model has been developed, validated, and employed to achieve the aim of the study. The results of the analyses showed that the use of skirts reduces the settlement produced due to machine vibration. However, the percentage decrease of the settlement is remarkably influenced by the density of the soil and the frequency of vibration, where it rises as the frequency of vibration increases and declines as the soil density rises. It was also found that increasing skirt length increases the percentage decrease of the settlement. Importantly, the results obtained from the analyses have been utilized to derive new dynamic impedance values that implicitly consider the presence of skirts. Finally, novel design equations of dynamic impedance that implicitly account to the effect of the skirts have been derived and validated utilizing a new intelligent data driven method. These new equations can be used in future designs of skirted strip foundations subjected to machine vibration.

• Journal of Power Electronics
• /
• v.17 no.5
• /
• pp.1288-1297
• /
• 2017

The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

• Geomechanics and Engineering
• /
• v.1 no.1
• /
• pp.53-74
• /
• 2009

In recent years, several computer-aided pattern recognition and data mining techniques have been developed for modeling of soil behavior. The main idea behind a pattern recognition system is that it learns adaptively from experience and is able to provide predictions for new cases. Artificial neural networks are the most widely used pattern recognition methods that have been utilized to model soil behavior. Recently, the authors have pioneered the application of genetic programming (GP) and evolutionary polynomial regression (EPR) techniques for modeling of soils and a number of other geotechnical applications. The paper reviews applications of pattern recognition and data mining systems in geotechnical engineering with particular reference to constitutive modeling of soils. It covers applications of artificial neural network, genetic programming and evolutionary programming approaches for soil modeling. It is suggested that these systems could be developed as efficient tools for modeling of soils and analysis of geotechnical engineering problems, especially for cases where the behavior is too complex and conventional models are unable to effectively describe various aspects of the behavior. It is also recognized that these techniques are complementary to conventional soil models rather than a substitute to them.

• Advances in environmental research
• /
• v.2 no.4
• /
• pp.291-308
• /
• 2013

In the present study, an experimental design methodology was used to optimize the adsorptive removal of Basic Yellow 13 (BY13) using Turkish coal powder. A central composite design (CCD) consisting of 31 experiments was employed to evaluate the simple and combined effects of the four independent variables, initial dye concentration (mg/L), adsorbent dosage (g/L), temperature ($^{\circ}C$) and contact time (min) on the color removal (CR) efficiency (%) and optimizing the process response. Analysis of variance (ANOVA) showed a high coefficient of determination value ($R^2=0.947$) and satisfactory prediction of the polynomial regression model was derived. Results indicated that the CR efficiency was not significantly affected by temperature in the range of $12-60^{\circ}C$. While all other variables significantly influenced response. The highest CR (95.14%), estimated by multivariate experimental design, was found at the optimal experimental conditions of initial dye concentration 30 mg/L, adsorbent dosage 1.5 g/L, temperature $25^{\circ}C$ and contact time 10 min.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.19 no.3
• /
• pp.234-238
• /
• 1990

The effects of salt concentration immersion time in a salt solution prior to air dehydration and heating of air temperature during dehydration upon the browning reaction and pyruvic acid content of air dried garlics to a 6.5% moisture content(wet basis) were analyzed by a response surface methodology(RSM), Those values were also predicted by using a second degree polynomial regression model. Heating of air temperature was the most significant factor affecting the both browning reaction and pyruvic acid content. Salt concentration had more influence to browning reaction than immersion time whereas immersion time was more impor-tant factor than salt concentration on a retention of pyruvic acid sugested different processing conditions. While the processing conditions to minimize the browning reaction(O.D=0.009) were 0.3% of salt solution 9 min of immersion time and 5$0^{\circ}C$ of air temperature compared to control(O.D=0.022) of air dehydration at 5$0^{\circ}C$ Pyruvic acid contents were maximized(174 $\mu$mole/g garlic solid) at the 0.1% of salt solution 3 min of immersion time and 5$0^{\circ}C$ of air temperature compared to control(147 $\mu$mole/g garlic solid) of air dehydration at 5$0^{\circ}C$

• International Journal of Air-Conditioning and Refrigeration
• /
• v.16 no.1
• /
• pp.1-8
• /
• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.