TY - JOUR
T1 - Integration of information technology into geotechnical engineering practice
T2 - concept and development
AU - Yoo, Chungsik
N1 - Publisher Copyright:
© Springer Science+Business Media Dordrecht 2012.
PY - 2013/6
Y1 - 2013/6
N2 - Information Technology (IT) has been extensively used to predict, visualize, and analyze physical parameters in order to expedite routine geotechnical design procedures. This paper presents an example of the combined technique of IT and numerical analysis for routine geotechnical design projects. The proposed approach involves the development of ANN(s) using a calibrated finite element model(s) for use as a prediction tool and implementation of the developed ANN(s) into a GIS platform for visualization and analysis of spatial distribution of predicted results. A novel feature of the proposed approach is an ability to expedite a routine geotechnical design process that otherwise requires significant time and effort in performing numerical analyses for different design scenarios. A knowledge-based underground excavation design system that utilizes artificial neural networks (ANNs) as prediction tools is also introduced. Practical implications of the use of IT in geotechnical design are discussed in great detail.
AB - Information Technology (IT) has been extensively used to predict, visualize, and analyze physical parameters in order to expedite routine geotechnical design procedures. This paper presents an example of the combined technique of IT and numerical analysis for routine geotechnical design projects. The proposed approach involves the development of ANN(s) using a calibrated finite element model(s) for use as a prediction tool and implementation of the developed ANN(s) into a GIS platform for visualization and analysis of spatial distribution of predicted results. A novel feature of the proposed approach is an ability to expedite a routine geotechnical design process that otherwise requires significant time and effort in performing numerical analyses for different design scenarios. A knowledge-based underground excavation design system that utilizes artificial neural networks (ANNs) as prediction tools is also introduced. Practical implications of the use of IT in geotechnical design are discussed in great detail.
KW - Artificial neural network
KW - Geographic information system
KW - Information technology
KW - Numerical analysis
KW - Soft ground improvement
KW - Underground construction
UR - https://www.scopus.com/pages/publications/85028159903
U2 - 10.1007/s10706-012-9587-1
DO - 10.1007/s10706-012-9587-1
M3 - Article
AN - SCOPUS:85028159903
SN - 0960-3182
VL - 31
SP - 965
EP - 978
JO - Geotechnical and Geological Engineering
JF - Geotechnical and Geological Engineering
IS - 3
ER -