• Environmental Engineering Research
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• v.25 no.4
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• pp.488-497
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• 2020

The present study investigates the feasibility of nitrogenous heterocyclic compounds (NHCs) (Pyridine-Quinoline) degradation by catalytic wet peroxidation (CWPO) in the presence of nanoscale zerovalent iron supported on granular activated carbon (nFe⁰/GAC) using statistical optimization technique. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the process parameters of CWPO process such as initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of pyridine (Py) and quinolone (Qn) were chosen as the main variables, and total organic carbon (TOC) removal and total Fe leaching were selected as the investigated response. The optimization of process parameters by desirability function showed the ~85% of TOC removal with process condition of initial solution pH 3.5, catalyst dose of 0.55 g/L, hydrogen peroxide concentration of 0.34 mmol, initial concentration of Py 200 mg/L and initial concentration of Qn 200 mg/L. Further, for TOC removal the analysis of variance results of the RSM revealed that all parameter i.e. initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of Py and initial concentration of Qn were highly significant according to the p values (p < 0.05). The quadratic model was found to be the best fit for experimental data. The present study revealed that BBD was reliable and effective for the determination of the optimum conditions for CWPO of NHCs (Py-Qn).

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.163-172
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• 2007

ESC has been used as a tool for evaluating overall performance of firms. ESC focuses mainly on building a balanced viewpoint comprising perspectives and their metrics. It is, therefore, difficult to value overall strategic achievements of a company derived by consolidating various perspectives and metrics. Because of the absence of a method for consolidating ESC metrics and computing total score based on these metrics, it is difficult to evaluate whole strategic performance and find core obstacle parts of performance. In this paper, we suggest a method of normalizing a numerical value of metrics with different units, and calculating the total score of ESC metrics. We conduct a case study of evaluating the effectiveness of CRM to illustrate the applicability and feasibility of the suggested method.

• Advances in materials Research
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• v.5 no.2
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• pp.67-80
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• 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.

• Journal of Navigation and Port Research
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• v.35 no.2
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• pp.121-130
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• 2011

The localization of vehicle is an important part of an unmanned vehicle control problem. Pseudolite ultrasonic system(PUS) is the method to find an absolute position with a high accuracy by using ultrasonic sensor. And Gyro is the inertial sensor to measure yaw angle of vehicle. PUS can be able to estimate the position of mobile robot precisely, in which errors are not accumulated. And Gyro is a more faster measure method than PUS. In this paper, we suggest a more accuracy method of calculating PUS which is numerical analysis approach named Newtonian method. And also propose the fusion method to increase the accuracy of estimated angle on moving vehicle by using PUS and Gyro integrated system by Kalman filtering. To control the 4WS unmanned vehicle, the trajectory following algorithm is suggested. And the new concept arbitration of goal controller is suggested. This method considers the desirability function of vehicle state. Finally, the performances of Newtonian method and designed controller were verified from the experimental results with the 4WS vehicle scaled 1/10.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• Structural Engineering and Mechanics
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• v.70 no.4
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• pp.395-405
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• 2019

In the present work, the effects of cutting parameters on surface roughness parameters (Ra), tool wear parameters (VBmax), tool vibration (Vy) and material removal rate (MRR) during hard turning of AISI 4140 steel using coated carbide tool have been evaluated. The relationships between machining parameters and output variables were modeled using response surface methodology (RSM). Analysis of variance (ANOVA) was performed to quantify the effect of cutting parameters on the studied machining parameters and to check the adequacy of the mathematical model. Additionally, Multi-objective optimization based desirability function was performed to find optimal cutting parameters to minimize surface roughness, and maximize productivity. The experiments were planned as Box Behnken Design (BBD). The results show that feed rate influenced the surface roughness; the cutting speed influenced the tool wear; the feed rate influenced the tool vibration predominantly. According to the microscopic imagery, it was observed that adhesion and abrasion as the major wear mechanism.

• Journal of Environmental Science International
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• v.30 no.5
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• pp.399-406
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• 2021

The dissolution of ionized gas in dielectric barrier plasma, similar to the principle of ozone generation, is a major performance-affecting factor. In this study, the plasma gas dissolving performance of a gas mixing-circulation plasma process was evaluated using an experimental design methodology. The plasma reaction is a function of four parameters [electric current (X₁), gas flow rate (X₂), liquid flow rate (X₃) and reaction time (X₄)] modeled by the Box-Behnken design. RNO (N, N-Dimethyl-4-nitrosoaniline), an indictor of OH radical formation, was evaluated using a quadratic response surface model. The model prediction equation derived for RNO degradation was shown as a second-order polynomial. By pooling the terms with poor explanatory power as error terms and performing ANOVA, results showed high significance, with an adjusted R² value of 0.9386; this indicate that the model adequately satisfies the polynomial fit. For the RNO degradation, the measured value and the predicted values by the model equation agreed relatively well. The optimum current, gas flow rate, liquid flow rate and reaction time were obtained for the highest desirability for RNO degradation at 0.21 A, 2.65 L/min, 0.75 L/min and 6.5 min, respectively.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.561-578
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• 2020

The present work addresses the surface integrity and chip morphology in finish hard turning of AISI D3 steel under nanofluid assisted minimum quantity lubrication (NFMQL) condition. The surface integrity aspects include microhardness, residual stress, white layer formation, machined surface morphology, and surface roughness. This experimental investigation aims to explore the feasibility of low-cost multilayer (TiCN/Al2O3/TiN) coated carbide tool in hard machining applications and to assess the propitious role of minimum quantity lubrication using graphene nanoparticles enriched eco-friendly radiator coolant based nano-cutting fluid for machinability improvement of hardened steel. Combined approach of central composite design (CCD) - analysis of variance (ANOVA), desirability function analysis, and response surface methodology (RSM) have been subsequently employed for experimental investigation, predictive modelling and optimization of surface roughness. With a motivational philosophy of "Go Green-Think Green-Act Green", the work also deals with economic analysis, and sustainability assessment under environmental-friendly NFMQL condition. Results showed that machining with nanofluid-MQL provided an effective cooling-lubrication strategy, safer and cleaner production, environmental friendliness and assisted to improve sustainability.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1480-1487
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• 2012

Recently, the safety of the coal-mining tunnels has been improved greatly, but accidents occur continually. Most tunnel support failures occur because the fish plate part that connects the I-beams is unable to withstand ground pressure. In the case of XX coal mine, the arch part of tunnel support bends to the upper direction. In such a case, excessive horizontal load as well as vertical load acts on the tunnel support. Horizontal load is caused by the sudden loosing of underground rock mass or the leakage of underground water, so it is fairly complex to predict horizontal loading on a tunnel support. To predict the horizontal load on this component is defined as the problem that determines the horizontal load conditions in wedges of tunnel support. This is an optimization problem in which maximum bending stress and horizontal load are considered by an objective function and design variables, respectively. Therefore, in this study, design of experiments and optimization algorithm were applied to identify the horizontal load in tunnel support.