• Title/Summary/Keyword: Society of Civil Engineers

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Mechanism of Sedimentation in Bangkok Bar Channel and Estimation of Sedimentation Volume in the Channel

  • Ichiro Deguchi;Toru Aswaragi;Masanobu Ono;Sucharit Koontanakulvong
    • Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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    • 1993.07a
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    • pp.122-123
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    • 1993
  • Bangkok Bar Channel is a unique approach channel to Bangkok(on Toi)Harbor that is the representative river port constructed along the river mouth of Chao Praya River. Various facilities are scattered along the both sides of the river between the river mouth and the bridge located about 50km upward. The construction of the channel began in 1951 and was completed in 1954. (omitted)

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Prediction of Wave Transmission Characteristics of Low Crested Structures Using Artificial Neural Network

  • Kim, Taeyoon;Lee, Woo-Dong;Kwon, Yongju;Kim, Jongyeong;Kang, Byeonggug;Kwon, Soonchul
    • Journal of Ocean Engineering and Technology
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    • v.36 no.5
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    • pp.313-325
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    • 2022
  • Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10-3, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.

Ground Subsidence Risk Analysis on Correlation between Rainfall and Rainfall intensity (강우량과 강우강도에 따른 지반함몰 상관관계 분석)

  • Choi, Chang-Ho;Kim, Jin-Young;Kang, Jae-Mo;Lee, Sung-Yeol;Baek, Won-Jin
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.3
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    • pp.75-83
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    • 2022
  • Recent settlements and sinkhole openings in urban areas have caused social problems such as damage to roads and structures, fear of the public, and loss of property. Several studies have demonstrated that surface subsidence and sinkhole opening are greatly affected by rainfall and rainfall intensity in urban areas. In this paper, we analyzed the relationship with the characteristics of recorded rainfall data using the ground subsidence database reported in major cities. The correlations were found using sedimentation and precipitation data from 2010 to 2014. The duration and intensity of a given precipitation have evolved to obtain an effect on ground sedimentation rate (SR). The results show that the relationship between SR and precipitation is asymptotic and can be modeled by a hyperbolic equation. Through this study, it is possible to predict the occurrence of ground subsidence due to precipitation in advance.