In the present paper, the dynamic force-moment equilibrium equations, driving power and energy equations are analyzed to formulate the equation for fuel economy(km/liter) equivalent to the driving distance (km) divided by the fuel volume (liter) of the vehicle, a selected model of gasoline powered KIA K3 (1.6v). In addition, the effects of the dynamic parameters such as speed of vehicle (V), vehicle total weight(M), rolling resistance ($C_r$) between tires and road surface, inclined angle of road (${\theta}$), as well as the aerodynamic parameters such as drag coefficient ($C_d$) of vehicle, air density(${\rho}$), cross-sectional area (A) of vehicle, wind speed ($V_w$) have been analyzed. And the possibility of alternative materials such as lightweight metal alloys, fiber reinforced plastic composite materials to replace the conventional steel and casting iron materials and to reduce the weight of the vehicle has been investigated by Ashby's material index method. Through studies, the following results were obtained. The most influencing parameters on the fuel economy at high speed zone (100 km/h) were V, the aerodynamic parameters such as $C_d$, A, ${\rho}$, and $C_r$ and M. While at low speed zone (60 km/h), they are, in magnitude order, dynamic parameters such as V, M, $C_r$ and aerodynamic ones such as $C_d$, A, and ${\rho}$, respectively.
Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.
Kumaran, K. Manikanda;Chinnadurai, M.;Manikandan, S.;Murugan, S. Palani;Elakiya, E.
KSII Transactions on Internet and Information Systems (TIIS)
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v.15
no.7
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pp.2377-2398
/
2021
In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.
Won, Taeyeon;Eo, Yang Dam;Sung, Hong ki;Chong, Kyu soo;Youn, Junhee
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.38
no.6
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pp.573-581
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2020
Using CCTV images and weather parameters, a method for estimating PM (Particulate Matter) index was proposed, and an experiment was conducted. For CCTV images, we proposed a method of estimating the PM index by applying a deep learning technique based on a CNN (Convolutional Neural Network) with ROI(Region Of Interest) image including a specific spot and an full area image. In addition, after combining the predicted result values by deep learning with the two weather parameters of humidity and wind speed, a post-processing experiment was also conducted to calculate the modified PM index using the learned regression model. As a result of the experiment, the estimated value of the PM index from the CCTV image was R2(R-Squared) 0.58~0.89, and the result of learning the ROI image and the full area image with the measuring device was the best. The result of post-processing using weather parameters did not always show improvement in accuracy in all cases in the experimental area.
Journal of the Korea institute for structural maintenance and inspection
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v.26
no.2
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pp.28-36
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2022
As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.
With the construction of Seoul National University (SNU), the Mt. Gwanak watershed has undergone some urbanization. As with other campus catchments, data related to the water cycle is extremely limited. Therefore, this study began by collecting hydrological and meteorological data using Atmos-41, a complex meteorological observation instrument. The observation results of Atmos-41 were validated by analyzing the statistical characteristics and confidence intervals based on the monthly variability of data from the Korea Meteorological Administration. Results of the previous research were used to validate the simulated surface runoff and infiltration using the Storm Water Management Model (SWMM). The potential evapotranspiration (PET) simulated by the SWMM was rectified by comparing it to the Atmos-41 observation data. Multiple regression analysis was employed to adjust for the fluctuations in precipitation, relative humidity, and wind speed because the calculated SWMM PET tends to be underestimated during periods of low temperatures. R2 increased from 0.54 to 0.80 when compared to the Atmos-41 PET. The rate of change in the water cycle as a consequence of the SNU's construction resulted in a 15.7% increase in surface runoff, a 14.2% decrease in infiltration rate, and a 1.6% decrease in evaporation.
Journal of Korean Society of Coastal and Ocean Engineers
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v.34
no.6
/
pp.335-345
/
2022
Climate change is accelerating worldwide due to the recent rise in global temperature, and the intensity of typhoons is increasing due to the rise in seawater temperature around the Korean Peninsula. An increase in typhoon intensity is expected to increase not only wind damage, but also coastal damage caused by storm surge. Accordingly, in this study, a study of the method of reducing storm surges was conducted for the purpose of disaster prevention in order to respond to the increasing damage from storm surges. Storm surges caused by typhoons can be expected to be affected by structures located on the track of typhoon, and the effects of storm surges were studied by the eastern coast and the barrier island along the coast of the Gulf of Mexico in the United States. This study focused on this aspect and conducted related research, considering that storm surges in the southern coastal area of the Korean Peninsula could be directly or indirectly affected by Jeju Island, which is located on the track of typhoon. In order to analyze the impact of Jeju Island on storm surges, simulations were performed in various situations using a numerical analysis model. The results of using Jeju Island are thought to be able to be used to study new disaster prevention structures that respond to super typhoons.
HanJoo Lee;Minkyu Jee;Hakdong Kim;Taeheul Jun;Cheongwon Kim
Journal of Broadcast Engineering
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v.28
no.3
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pp.285-292
/
2023
Recently, the impact of fine dust on health has become a major topic. Fine dust is dangerous because it can penetrate the body and affect the respiratory system, without being filtered out by the mucous membrane in the nose. Since fine dust is directly related to the industry, it is practically impossible to completely remove it. Therefore, if the concentration of fine dust can be predicted in advance, pre-emptive measures can be taken to minimize its impact on the human body. Fine dust can travel over 600km in a day, so it not only affects neighboring areas, but also distant regions. In this paper, wind direction and speed data and a time series prediction model were used to predict the concentration of fine dust in Seoul, and the correlation between the concentration of fine dust in Seoul and the concentration in each region was confirmed. In addition, predictions were made using the concentration of fine dust in each region and in Seoul. The lowest MAE (mean absolute error) in the prediction results was 12.13, which was about 15.17% better than the MAE of 14.3 presented in previous studies.
KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.4A
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pp.507-515
/
2008
In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.
Exploration of asteroids' internal structure is essential for understanding their evolutional history. It also provides a fundamental information about the history of coalescence and collision of the solar system. Among several models of the internal structures, the rubble-pile model, confirmed by the near-Earth asteroid (25143) Itokawa by Hayabusa mission [1], is now widely regarded as the most common to asteroids with size ranging from 200 m to 10 km [2]. On the contrary, monolithic and core-mantle structures are also possible for small asteroids [3]. It is, however, still challenging to look through the interior of a target object using remote-sensing devices. In this presentation, we introduce our ongoing research conducted at Seoul National and propose an idea to infer the internal structure of Apophis using available instruments. Itokawa's research provides an important benchmark for Apophis exploration because both asteroids have similar size and composition [4][5]. We have conducted research on Itokawa's evolution in terms of collision and space weathering. Space weathering is the surface alteration process caused by solar wind implantation and micrometeorite bombardment [6]. Meanwhile, resurfacing via a collision acts as a counter-process of space weathering by exposing fresh materials under the matured layer and lower the overall degree of space weathering. Therefore, the balance of these two processes determine the space weathering degrees of the asteroid. We focus on the impact evidence on the boulder surface and found that space weathering progresses in only 100-10,000 years and modifies the surface optical properties (Jin & Ishiguro, KAS 2020 Fall Meeting). It is important to note that the timescale is significantly shorter than the Itokawa's age, suggesting that the asteroid can be totally processed by space weathering. Accordingly, our result triggers a further discussion about why Itokawa indicates a moderately fresh spectrum (Sq-type denotes less matured than S-type). For example, Itokawa's smooth terrains show a weaker degree of space weathering than other S-type asteroids [7]. We conjecture that the global seismic shaking caused by collisions with >1 mm-sized interplanetary dust particles induces granular convection, which hinders the progression of space weathering [8]. Note that the efficiency of seismic wave propagation is strongly dependent on the internal structure of the asteroid. Finally, we consider possible approaches to investigate Apophis's internal structure. The first idea is studying the space weathering age, as conducted for Itokawa. If Apophis indicates a younger age, the internal structure would have more voids [9]. In addition, the 2029 close encounter with Earth provides a rare natural opportunity to witness the contrast between before and after the event. If the asteroid exhibits a slight change in shape and space weathering degree, one can determine the physical structure of the internal materials (e.g., rubble-pile monolithic, thick or thin regolith layer, the cohesion of the materials). We will also consider a possible science using a seismometer.
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