• Title/Summary/Keyword: Artificial ground

Search Result 776, Processing Time 0.03 seconds

Mode-Matching Analysis for Complex Antenna Factors of Circular Top-Hat EMI Monopole Antennas (모드 정합법에 의한 원판 부착형 EMI 모노폴 안테나의 복소 안테나 인자 해석)

  • 정운주;김기채
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.14 no.10
    • /
    • pp.1024-1029
    • /
    • 2003
  • This paper presents the complex antenna factor of a top-hat EMI monopole antenna for measuring time domain electromagnetic fields. The approach is facilitated by adding a artificial parallel ground plane above the monopole antenna. This allows use of cylindrical harmonic field expansions in each of three subregions enclosed by the two ground plane. The results show that the complex antenna factor of the top-hat monopole antenna does not diverge at low frequencies. When compared with a monopole antenna, the top-hat monopole antenna has broadband characteristics. In order to verify the availability of the mode-matching method, the input impedance of the antenna were compared with experiments.

Delay Tolerant Packet Forwarding Algorithm Based on Location Estimation for Micro Aerial Vehicle Networks

  • Li, Shiji;Hu, Guyu;Ding, Youwei;Zhou, Yun
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.14 no.3
    • /
    • pp.1377-1399
    • /
    • 2020
  • In search and rescue mission, micro aerial vehicles (MAVs) are typically used to capture image and video from an aerial perspective and transfer the data to the ground station. Because of the power limitation, a cluster of MAVs are required for a large search area, hence an ad-hoc wireless network must be maintained to transfer data more conveniently and fast. However, the unstable link and the intermittent connectivity between the MAVs caused by MAVs' movement may challenge the packet forwarding. This paper proposes a delay tolerant packet forwarding algorithm based on location estimation for MAV networks, called DTNest algorithm. In the algorithm, ferrying MAVs are used to transmit data between MAVs and the ground station, and the locations of both searching MAVs and ferrying MAVs are estimated to compute the distances between the MAVs and destination. The MAV that is closest to the destination is selected greedy to forward packet. If a MAV cannot find the next hop MAV using the greedy strategy, the packets will be stored and re-forwarded once again in the next time slot. The experiment results show that the proposed DTNest algorithm outperforms the typical DTNgeo algorithm in terms of packet delivery ratio and average routing hops.

Motion Analysis of Power Tiller for Stability Improvement (III) -Verification of a Mathematical Model of Motion for Power Tiller-Trailer System- (동력경운기(動力耕耘機)의 안정성(安定性) 향상(向上)을 위한 주행(走行) 및 선회(旋回)에 관(關)한 연구(硏究) (III) -동력경운기(動力耕耘機)-트레일러 시스템 운동(運動)모델의 검증(檢證)-)

  • Park, K.J.;Ryu, K.H.;Chung, C.J.;Kim, K.U.;Yoo, S.N.
    • Journal of Biosystems Engineering
    • /
    • v.13 no.2
    • /
    • pp.1-8
    • /
    • 1988
  • A scale model of power tiller-trailer system with the same kinematic characteristics was constructed one eighth of the actual size to validate the effectiveness of mathematical model of motion. The parameters for the scale model of power tiller-trailer system were measured by a series of laboratory experiments. Validation tests for the: scale model was conducted under several ground and operating conditions. The tests were performed on artificial ground surfaces with several kind, of slope and obstacle. The travel path of the scale model was photographed successively in three directions. The travel paths obtained from both the film analysis and the simulation model appeared to be consistent with each other. It was concluded that the simulation model could be used to predict the motion of actual power tiller-trailer system if the parameters for actual power tiller and trailer are provided.

  • PDF

Experimental Study of Runoff Induced by Infiltration Trench (침투 트렌치로 인한 유출 양상의 실험 연구)

  • Lee, Sangho;Cho, Heeho;Lee, Jungmin;Park, Jaehyun
    • Journal of Korean Society on Water Environment
    • /
    • v.24 no.1
    • /
    • pp.107-117
    • /
    • 2008
  • Infiltration facilities are effective instruments to mitigate flood and can increase base runoff in urban watersheds. In order to analyze effects of infiltration trenches physical model experiments were conducted. The physical model facility consists of two soil tanks, artificial rainfall generators, tensiometers, and piezometers. The experiment was conducted by nine times and each case differed in rainfall intensity, rainfall duration and the type of ground surface. Measured quantities in the experiments are as follows: surface runoff, subsurface runoff, trench pipe runoff, groundwater level, water content, etc. The following resulted from the model experiment: The volume of subsurface runoff at trench watershed was maximum 78.3% compared with rainfall. This value is bigger than that of ordinary rate of subsurface runoff, and shows a groundwater recharge effect of trench. The time of runoff passing through the trench became earlier and the volume of runoff became larger with the increase of inflow into the trench, while trench exfiltration into ground became relatively smaller. The results of this study presented above show that infiltration trenches are effective instruments to increase base runoff during dry periods.

Area Extraction of License Plates Using an Artificial Neural Network

  • Kim, Hyun-Yul;Lee, Seung-Kyu;Lee, Geon-Wha;Park, Young-rok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.7 no.4
    • /
    • pp.212-222
    • /
    • 2014
  • In the current study, the authors propose a method for extracting license plate regions by means of a neural network trained to output the plate's center of gravity. The method is shown to be effective. Since the learning pattern presentation positions are defined by random numbers, a different pattern is submitted to the neural network for learning each time, which enables it to form a neural network with high universality of coverage. The article discusses issues of the optimal learning surface for a license plate covered by the learning pattern, the effect of suppression learning of the number and pattern enlargement/reduction and of concentration value conversion. Results of evaluation tests based on pictures of 595 vehicles taken at an under-ground parking garage demonstrated detection rates of 98.5%, 98.7%, and 100%, respectively.

Landslide Detection using Wireless Sensor Networks (사면방재를 위한 무선센서 네트워크 기술연구)

  • Kim, Hyung-Woo;Lee, Bum-Gyo
    • 한국방재학회:학술대회논문집
    • /
    • 2008.02a
    • /
    • pp.369-372
    • /
    • 2008
  • Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes comprising a sensing part and a communication part are developed to detect ground movement. Sensing part is designed to measure inclination angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15.1) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of experimental studies was performed at a small-scale earth slope equipped with an artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope starts to move. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

  • PDF

Development of a Rock Slope Analysis Software Considering Ground Water Level (지하수의 영향을 고려한 사면 해석 소프트웨어 개발)

  • Yang Hyung-Sik;Ha Tae-Wook;Kim Won-Beom;Choi Mi-Jin;Lee Jine-Haeng
    • Tunnel and Underground Space
    • /
    • v.15 no.3 s.56
    • /
    • pp.213-222
    • /
    • 2005
  • In this study, an artificial neural network was used to predict stability of weak rock slopes with various discontinuities and underground water conditions. Input data were provided by UDEC analyses on 108 cases of representative conditions of different slope heights, angles, discontinuity angles and water levels. The verification shows high correlation $(r^2-=0.97)$ between analyses and predictions. The program was able to predict safety factors with the same accuracy from unlearned data sets.

Development of Knowledge-based Study on Optimized NATM Lining Design System (지식기반형 NATM 라이닝 최적 설계 시스템 개발)

  • Song, Ju-Sang;Yoo, Chung-sik
    • Journal of the Korean Geosynthetics Society
    • /
    • v.17 no.4
    • /
    • pp.251-265
    • /
    • 2018
  • This paper concerns the development of an optimized NATM secondary lining design system for a subsea tunnel. The subsea tunnel is normally laid down under the sea water and submarine ground which consists of soil or rock. The design system is the series of process which can predict lining member forces by ANN (artificial neural network system), analyze suitable section for the designated ground, construction and tunnel conditions. Finally, this lining design system aims to be connected for designing the subsea tunnel automatically. The lining member forces are predicted based on the ANN which was calculated by a FEM (finite element analysis) and it helps designers determine its lining dimension easily without any further FEM calculations.

Seismic Fragility Analysis of Curved Bridge under High Frequency Earthquakes (고주파 지진에 의한 곡선 교량의 지진 취약도 분석)

  • Jeon, Juntai;Ju, Bu-Seog;Son, Hoyoung
    • Journal of the Society of Disaster Information
    • /
    • v.16 no.4
    • /
    • pp.806-812
    • /
    • 2020
  • Purpose: This is aimed to evaluate the seismic fragility of curved bridge structure with I-shape girder subjected to 12 high frequency ground motions based on Gyeongju earthquake. Method: The linear elastic finite element model of curved bridge with I-Shape cross section was constructed and them linear elastic time history analyses were performed using the 12 artificial ground motions. Result: It was found that displacement response(LS1, LS2) was failed after PGA 0.1g and the stress response also showed failure after PGA 0.2g. Conclusion: The curved bridge with I-shape girder was sensitive to high frequency earthquakes.

Deep neural network for prediction of time-history seismic response of bridges

  • An, Hyojoon;Lee, Jong-Han
    • Structural Engineering and Mechanics
    • /
    • v.83 no.3
    • /
    • pp.401-413
    • /
    • 2022
  • The collapse of civil infrastructure due to natural disasters results in financial losses and many casualties. In particular, the recent increase in earthquake activities has highlighted on the importance of assessing the seismic performance and predicting the seismic risk of a structure. However, the nonlinear behavior of a structure and the uncertainty in ground motion complicate the accurate seismic response prediction of a structure. Artificial intelligence can overcome these limitations to reasonably predict the nonlinear behavior of structures. In this study, a deep learning-based algorithm was developed to estimate the time-history seismic response of bridge structures. The proposed deep neural network was trained using structural and ground motion parameters. The performance of the seismic response prediction algorithm showed the similar phase and magnitude to those of the time-history analysis in a single-degree-of-freedom system that exhibits nonlinear behavior as a main structural element. Then, the proposed algorithm was expanded to predict the seismic response and fragility prediction of a bridge system. The proposed deep neural network reasonably predicted the nonlinear seismic behavior of piers and bearings for approximately 93% and 87% of the test dataset, respectively. The results of the study also demonstrated that the proposed algorithm can be utilized to assess the seismic fragility of bridge components and system.