• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• Composites Research
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• v.26 no.4
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• pp.265-272
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• 2013

Fiber-reinforced plastic (FRP) is applied to fabricate the main structures of composite boats. Most of them are made from molds. These products deform after releasing from the mold and they also deform in high temperature environment. Therefore, experimental investigation and evaluation of deformation of laminated composite structures under various manufacturing and working conditions are necessary. The specimens of L-shape and curveshape were made from unsaturated polyester resin and fiberglass material. Input factors (independent variables) are percentage of hardener and manufacturing temperature and four levels of working temperature and output factor is the deformation which is measured on these specimens. From the results, it was observed that the higher the hardener rate and temperature, the lower the deformation. When the working temperature increased, the specimens showed great variations for the initial deformation values. Besides, the values of deformation or input factors could be predicted by regression equations.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.573-580
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• 2006

The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2254-2259
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• 2011

The introduction of Personal Rapid Transit (PRT) has been widely discussed in the Korean transportation research field. However, there is no robust criterion to derive the throughput of cars and passengers at PRT stations, which plays a primary role in determining the overall capacity of PRT systems. The present study provided a methodology to rigorously compute the capacity for simple-serial PRT stations with a single platform, considering three decisive factors, i.e., the demand level of incoming cars and outgoing passengers, the station structure, and the operation strategy. A micro-level simulator was developed for the analysis of station capacity. And, by using this, station capacities were presented for various combinations of the decisive factors. In particular, the relationship between capacity and station structure was investigated in detail. Station structure is represented by the numbers of platform berths, input queue berths, and output queue berths. Moreover, both waive rate and waiting time, which represent the level of passenger service, were taken into account when the station throughput was computed.

• Korean Institute of Interior Design Journal
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• v.13 no.3
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• pp.197-204
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• 2004

This study aims at the development of a cost management system in building interior projects. Renovation and remodeling is activated and expanded much more being compared with new building construction at present. After Interior project proceeding must get out of simple estimate and assumption, then its be needed a formal work process and computerized cost management. Proceeding a building interior project management was proceed in the office and the field. Cost break down, especially, depend on the field manger and used fiend managing money because its not checked by cost manager in office manger. For this study, cost factors are defined in terms of cost break-down interior works which consist of materials and labors. A data model for cost factors was developed, and a relational database is used to realize cost data management based upon this data model. Data input and output are achieved by internet from both of wired PC and mobile phone. This system can timely display a number of needed reports for cost management that identifies cash flow and predicts budget for cost break-down works in interior projects.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1483-1493
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• 2016

Multiple parallel inverters have multiple resonant frequencies that are influenced by many factors. This often results in stability and power quality problems. This paper develops a multiple input multiple output model of grid-connected inverter systems using a closed-loop transfer function. The influence factors of the resonant characteristics are analyzed with the developed model. The analysis results show that the resonant frequency is closely related to the number, type and composition ratio of the parallel inverters. To suppress resonance, a scheme based on virtual impedance is presented, where the virtual impedance is emulated in the vicinity of the resonance frequency. The proposed scheme needs one inverter with virtual impedance control, which reduces the design complexity of the other inverter controllers. Simulation and experimental tests are carried out on two single phase converter-based setups. The results validate the correctness of the model, the analytical results and the resonant suppressing scheme.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.15-20
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• 2006

In this study, we had investigated several input factors and output factors, to maintain safety management, of domestic shipping companies, and then had analyzed the efficiency of performance of performance about each shipping companies' safety management system from 1998 year to 2004 year using DEA method As the result of analysis, the annual mean efficiency of total companies tended downward every year. Analysis was that the cause was increase of the cost of repairing ship, the cost of ship's stores and idle day of ship.

• Journal of Communications and Networks
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• v.5 no.2
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• pp.104-115
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• 2003

It is well known that Multiple Input Multiple Output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial and temporal correlation introduced by the radio environment. In this paper, we examine how MIMO capacity is influenced by a number of factors e.g., a) temporal correlation b) various combinations of low/high spatial correlations at either end, c) combined spatial and temporal correlations. In all cases, we compare the channel capacity that would be achievable under independent fading. We investigate the behaviour of "capacity fades," examine how often the capacity experiences the fades, develop a method to determine level crossing rates and average fade durations and relate these to antenna numbers. We also evaluate the influence of channel correlation on the capacity autocorrelation and assess the fit of a Gaussian random process to the temporal capacity sequence. Finally we note that the particular spatial correlation structure of the MIMO channel is influenced by a large number of factors. For simplicity, it is desirable to use a single overall correlation measure which parameterizes the effect of correlation on capacity. We verify this single parameter concept by simulating a large number of different spatially correlated channels.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.225-230
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• 1992

In this paper, a new learning fuzzy logic controller(LFLC) is presented. The proposed controller is composed of the main control part and the learning part. The main control part is a fuzzy logic controller(FLC) based on linguistic rules and fuzzy inference. For the learning part, artificial neural network(ANN) is added to FLC so that the controller may adapt to unknown plant and environment. According to the output values of the ANN part, which is learned using error back-propagation algorithm, scale factors of the FLC part are determined. These scale factors transfer the range of values of input variables into corresponding universe of discourse in the FLC part in order to achieve good performance. The effectiveness of the proposed control strategy has been demonstrated through simulations involving the control of an unknown robot manipulator with load disturbance.