• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.90-101
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• 2016

This study was initiated to develop an algorithm for traffic condition adaptive optimal traffic signal control for isolated intersections based on the vehicle trajectory data. The algorithm determines the optimal cycle length, phase lengths, phase sequences using the data collected under V2X communication environment every second. In addition, the algorithm utilizes a traditional feature of the actuated signal control, gap-out, using traditional detector systems to consider the mixture of normal vehicles and vehicles equipped with the V2X communication function. The performance of the algorithm was compared with that of the fixed signal timing plan which was optimized with Synchro under a microscopic traffic simulation-based test bed. As a result, the overall performance, including average delay, average stop delay, the number of stops, and average speed, are improved apparently. In addition, the amount of improvement get bigger as the traffic volume in the intersection as well as the number of vehicles equipped with the V2X communication function increase.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.5
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• pp.85-90
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• 2010

As the environmental regulation of vehicle emission is strengthened, investigations for $NO_x$ and PM reduction strategies are popularly conducted. Two current available technologies for continuous $NO_x$ reduction onboard diesel vehicles are Selective Catalytic Reduction (SCR) using aqueous urea and lean $NO_x$ trap (LNT) catalysts. The experiments were conducted to investigate the $NO_x$ reduction performance of SCR system which can control the ratio of $NO/NO_2$, temperature and SV(space velocity), and the model gas was used which is similar to a diesel exhaust gas. The maximum reduction efficiency is indicated when the $NO:NO_2$ ratio is 1:1 and the SV is 30,000 $h^{-1}$ in $300^{\circ}C$. Generally, ammonia slip from SCR reactors are rooted to incomplete conversion of $NH_3$ over the SCR. In this research, slip was occurred in 6cases (except low SV and $NO:NO_2$ ratio is 1:1) after SCR. Among 6 case of slip occurrence, the maximum conversion efficiency is observed when SV is 60,000 $h^{-1}$ in $400^{\circ}C$.

• Transactions on Electrical and Electronic Materials
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• v.6 no.2
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• pp.35-38
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• 2005

Pb(Zr$_{0.8}$Ti$_{0.2}$)O$_{3}$ powders, prepared by the sol-gel method, were mixed with an organic vehicle and the PZT thick films were fabricated by the screen-printing techniques on Pt/Ah03 substrates. The structural properties were examined as a function of sintering temperature. The particle size distribution of the PZT powder derived from the sol-gel process is uniform with the mean particle size of about 2.6 m. As a result of the DTA, the formation of the polycrystalline perovskite phase was observed at around $890^{circ}$CC. In the X-ray diffraction analysis, all PZT thick films showed a perovskite polycrystalline structure without a pyrochlore phase. The perovskite crystallization temperature of PZT thick films was about $890^{circ}$C. The average thickness of the PZT thick films was approximately 80-90 m.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.781-790
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• 2007

Hybrid electric vehicles(HEV) combined with more than one power sources have great potential to improve fuel economy and reduce pollutant emissions. The Integrated Starter Generator(ISG) HEV researched in this paper is a two energy sources vehicle, with a conventional internal combustion engine(ICE) and an energy storage system(batteries). In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming(DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. A fuel-economy-only case and a fuel & emissions case can be achieved by changing specific weighting factors. The simulation results of the fuel-economy-only case show that there is a 45.1% fuel saving potential for this ISG HEV compared to a conventional transit bus. The test results present a 39.6% improvement in fuel economy which validates the simulation results. Compared to the fuel-economy-only case, the fuel & emissions case further reduces the pollutant emissions at a cost of 3.2% and 4.5% of fuel consumption with respect to the simulation and test result respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.546-552
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• 2010

As the demands for the safety and convenience applications of the vehicles increase, the data load for the In-vehicle Network has increased significantly. As a result, a deterministic and fault-tolerant communication system is required to implement the safety critical applications such as X-by-wire systems. FlexRay communication system is a new standard of network communication system which provides the high speed serial communication, time triggered bus and fault tolerant communication between electronic devices. In addition to time-triggered communication, as providing of the event-triggered communication such as CAN, FlexRay protocol is able to manage the restricted communication resource more effectively. This paper presents the development of FlexRay driver which will be applied to the future ECU's communication system. To develop the FlexRay driver, the FlexRay requirement specification and FlexRay specification is analyzed. The developed FlexRay driver is implemented by using MPC5567 microprocessor of the Freescale semiconductor. To verify the developed FlexRay driver, the waveform of the FlexRay driver was measured and compared with the CAN communication system. As a result, the bus load is reduced about 13% compared with the CAN communication system.

• Advances in Traditional Medicine
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• v.6 no.2
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• pp.79-85
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• 2006

In order to study the effect of acupuncture stimulation on bone mineral density (BMD), using the ovariectomized (OVX) rat model, we assessed the degree of osteopenia by dual-energy X-ray absorptiometry, measured the level of locomotor activity using a metabolism measuring system, and performed histological studies of bone tissue. Twenty-four female Wistar rats (8 weeks old, 160 - 180 g)were divided into three groups. Rats in the OVX-A group underwent ovariectomy followed by acupuncture stimulation. The OVX rats in the Vehicle control group were not treated with acupuncture as a control. The rats in the control group received neither ovariectomy nor acupuncture. Acupuncture stimulation for 12 weeks in the OVX-A group inhibited the reduction in BMD of the femoral bones caused by ovariectomy. Moreover, in the two OVX groups, there was no clear difference in the level of locomotor activity between the active and resting phases prior to acupuncture stimulation in each rat, and the pattern of locomotor activity was irregular. After acupuncture stimulation of the OVX-A rats, the pattern of locomotor activity became diphasic with clear active and resting phases, as was observed in the Control group. On histological studies, the continuity of trabecular bone was maintained more favorably and bone mass was higher in the OVX-A group than in the vehicle control group. These results suggest that the increased locomotor activity that had been induced by acupuncture stimulation increased the BMD.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.15-20
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• 2017

This study analyzed the load change of the gear generated by the operation of the vehicle recliner through Finite Element Analysis. The basic model of the recliner used was a commercial product, and the effect of the seat frame was excluded. The load conditions applied to the recliner were set considering gravity, the mass of the seat's back frame, and the weight of a person. The operating mode was set to move the seat back from the vertical to the reclined position. As a result, it was found that the tooth bending amount of the gear rim and wheel increased from the cam rotation angle of 450 degrees, and a change in the contact ratio occurred. Furthermore, excessive torque fluctuations occurred in the ranges of 390 to 450 and 750 to 710 degrees. It was found that this occurred in the region of about 30 degrees before and after the point where the x-axis direction load is larger than the y-direction load. From this torque fluctuation it was determined to likely to cause chattering noise.

• Corrosion Science and Technology
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• v.21 no.6
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• pp.514-524
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• 2022

Carbon emissions from fuel consumption have been pointed by scientists as the cause of global warming. In particular, fossil fuels are known to emit more carbon when burned than other types of fuels. In this regard, International Maritime Organization has announced a regulation plan to reduce carbon dioxide emissions. Therefore, recently, Liquefied Natural Gas propulsion ships are responding to such carbon reduction regulation. However, from a long-term perspective, it is necessary to use carbon-free fuels such as hydrogen and ammonia. Nitrogen oxides might be generated during ammonia combustion. There is a possibility that incompletely burned ammonia is discharged. Therefore, rather than being used as a direct fuel, Ammonia is only used to reduce NO_X such as urea solution in diesel vehicle Selective Catalyst Reduction. Currently, LPG vehicle fuel feed system studies have evaluated the durability of combustion injectors and fuel tanks in ammonia environment. However, few studies have been conducted to apply ammonia as a ship fuel. Therefore, this study aims to evaluate corrosion damage that might occur when ammonia is used as a propulsion fuel on ships.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.