• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.908-912
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• 2013

Because of their longer operating times and larger size relative to conventional fans, the cooling fans mounted in buses consume larger amounts of energy. Most of the cooling fans mounted in a bus are connected to the engine by a viscous clutch. A viscous cooling fan's speed is determined by its fluid temperature, which is affected by the air flow through the radiator. The fan does not react immediately to the coolant temperature and in doing so causes unnecessary energy consumption. Therefore, the fuel economy of buses using viscous fans can be improved by changing to an electric cooling fan design, which can be actively controlled. In addition, electric power consumption is increased by using electric cooling fans. Thus, when electric fans are applied in conjunction with the alternator management system (AMS), the fuel economy is further enhanced. In this study, simulations were performed to predict coolant temperature and cooling fan speeds. Simulations were performed for both viscous and electric cooling fans, and power consumption was calculated. Additionally, fuel economy was calculated applying both the alternator management system and the electric cooling fan.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.4
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• pp.380-386
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• 2020

This paper represents an analysis of the economic impact of firing natural gas/diesel and natural gas/by-product oil mixtures in diesel engine power plants. The objects of analysis is a power plant with electricity generation capacity (300 kW). Using performance data of original diesel engines, the fuel consumption characteristics of the duel fuel engines were simulated. Then, economic assessment was carried out using the performance data and the net present value method. A special focus was given to the evaluation of fuel cost saving when firing natural gas/diesel and natural gas/by-product oil mixtures instead of the pure diesel firing case. Analyses were performed by assuming fuel price changes in the market as well as by using current prices. The analysis results showed that co-firing of natural gas/diesel and natural gas/by-product oil would provide considerable fuel cost saving, leading to meaningful economic benefits.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.3
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• pp.44-51
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• 2021

PIP is an abbreviation of 'Performance Improvement Package', which is a package that can improve performance by applying some design changes to existing aircraft. Boeing provides PIP applicable to B777-200, and Airbus provides PIP applicable to A350-900 as standard. PIP provided by Boeing and Airbus is a separate task, but it is expected to reduce fuel consumption by reducing drag through aerodynamic improvements. The PIP applied to the A350-900 includes work such as increasing Winglet Height and re-twisting Outboard Wing. This study is to verify the effect of PIP application of the A350-900 aircraft and use it as basic data for economic analysis. The aerodynamic improvement studies and expected effects of the PIP application were examined, and the actual flight data of the PIP-applied and the non-applied aircraft were compared to confirm the PIP application effect. This paper provides empirical results for the aviation industry on the PIP application efficiency as a method of improving fuel efficiency and reducing carbon emission.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.1 s.139
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• pp.57-63
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• 2005

This paper introduces basic research of optimum routing assessment system as voyage support purpose which can obtain safe and efficient route. In view point of safety, the prediction of ship motion should be evaluated in the condition of rough weather This part includes general seakeeping estimation based on 3 dimensional panel method and parametric roil prediction. For increasing voyage efficiency, ETA(Estimated Time of Arrival) and fuel consumption should be calculated considering speed reduction and power increase due to wave effects based on added resistance calculation and ship performance characteristics. Basically, the weather forecast is assumed to be prepared previously to operate this system. The idea of these factors in this system will be helpful to escape from dangerous voyage situation by wave conditions and to make optimum route planning based on ETA and fuel consumption.

• Fire Science and Engineering
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• v.30 no.2
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• pp.92-97
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• 2016

The present study has been conducted to estimate the chemical flame height based on fuel consumption in fire field model. The calculation algorithms based on cumulative fraction of HRRPUL and fuel concentration along the z axis were applied to the results predicted by Fire Dynamics Simulator (FDS) version 6.3.2 and the mean chemical flame height was obtained by time averaging of instantaneous flame height with the algorithms. The mean flame height calculated by fuel concentration was quite well matched with that of cumulative value of HRRPUL within 10% over-prediction. This study contribute to a more detailed understanding of fire behavior and quantitative evaluation of flame height in the computational fire model.

• Korean Journal of Agricultural Science
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• v.43 no.1
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• pp.116-126
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• 2016

The objective of this study is to predict the fuel efficiency of an agricultural tractor. The fuel efficiency of the tractor during rotary tillage was predicted using numerical modeling. A numerical model was developed using Simulation X. Based on tractor power flow, numerical modeling consisted of an engine, transmission, PTO (power take off), and hydraulics. The specifications of major components utilized in the numerical model were the same as those of a 71 kW tractor (field test tractor). The load that was inputted for fuel efficiency prediction into the simulation model was obtained from a field test. Fuel efficiency predictions were conducted by comparing field test results and simulation results. In addition, it was performed by dividing the rotary tillage and steering section. Main results are as follows: first, t-values of engine torque were measured to be 0.31 in the rotary tillage and 0.92 in the steering section. Second, t-values of fuel consumption were measured to be 0.51 and 5.41 in the rotary tillage and the steering section, respectively. Finally, t-values of fuel efficiency were measured to be 1.72 and 40 in the rotary tillage and the steering section, respectively. The results show no significant differences with t-values of less than 5% in the rotary tillage. But, it shows significant differences in the steering section. Therefore, simulation for accurate fuel efficiency prediction requires a suitable algorithm or detailed design of the simulation model in the steering section.

• Journal of ILASS-Korea
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• v.23 no.1
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• pp.36-41
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• 2018

Fuel wall film effects power output and cycle deviation by changing the amount of fuel flowing into cylinder in PFI gasoline engines. Reduction of wall film can reduce fuel consumption and improve combustion stability. In this research, the effects of injection strategies including injection pressure and dual injection system is investigated for reducing wall film formation. The CONVERGE software is used for numerical analysis tool and O'Rourke film splash model was used for wall film prediction model. Compared with the reference case wall film decreased with increase of injection pressures, and the film formation reduced when the dual injection system was used.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.4
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• pp.447-453
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• 2016

The reduction technologies of exhaust gas from both the off-road engine and on-road vehicles are important. It is possible to apply various combustion technologies with engines after the application of a treatment technology to this field. In this study, main injection timing, pilot injection timing, and exhaust gas recirculation (EGR) rate were selected as the experimental parameters whose effects on the emission of exhaust gases and on the fuel consumption characteristics were to be determined. In the experiment, the emission of nitrogen oxide (NOx) and Smoke, and the Torque at the same fuel consumption level, were measured. The experimental data were analyzed using the Taguchi method with an L9 orthogonal array. Additionally, analysis of variation (ANOVA) was used to confirm the influence of each parameter. Consequently, the level of each parameter was selected based on the signal-to-noise ratio data (main injection timing, 3; pilot injection timing, 3; EGR rate, 2), and the results of the Taguchi prediction were verified experimentally (error: NOx, 10.3 %; Smoke, 6.6 %; brake-specific fuel consumption (BSFC), 0.6 %).

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.98-103
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• 2019

Integrity prediction of the operation equipment of naval vessels is essential to maintain the efficiency of the operation performance in urgent situations. Recently, the integrated condition assessment system(ICAS) was introduced and maintained to improve operational performance. This technology is related with ICAS, and it must be localized through extensive research. In this paper, we present the results of applying the data-driven model to the predictability methods of diesel generators, which are naval vessel operation equipment.