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Research Article

Development of AI-based Prediction and Assessment Program for Tunnelling Impact
Chungsik Yoo1
,
SYED AIZAZ HAIDER2*
,
Jaewon Yang3
,
TABISH ALI4
,
,
,
1Member, Professor, School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus, Cheoncheon-dong, Jangan-gu, Suwan-si, Gyeonggi-do, Korea
2Member, Graduate Student, School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus, Cheoncheon-dong, Jangan-gu, Suwan-si, Gyeonggi-do, Korea
3Member, Graduate Student, School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus, Cheoncheon-dong, Jangan-gu, Suwan-si, Gyeonggi-do, Korea
4Member, Graduate Student, School of Civil and Environmental Engineering, Sungkyunkwan Univ. Natural Sciences Campus, Cheoncheon-dong, Jangan-gu, Suwan-si, Gyeonggi-do, Korea
* Corresponding Author
30 December 2019. pp. 39-52
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Abstract

In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

Keywords
Artificial intelligence
Artificial neural network
Numerical analysis
Tunnelling
Impact assessment

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Information
  • Publisher :Korean Geosythetics Society
  • Publisher(Ko) :한국지반신소재학회
  • Journal Title :Journal of the Korean Geosynthetics Society
  • Journal Title(Ko) :한국지반신소재학회 논문집
  • Volume : 18
  • No :4
  • Pages :39-52
  • Received Date : 2019-04-02
  • Revised Date : 2019-08-17
  • Accepted Date : 2019-11-14
  • DOI :https://doi.org/10.12814/jkgss.2019.18.4.039
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