Location

Arlington, Virginia

Session Start Date

8-11-2008

Session End Date

8-16-2008

Abstract

Geotechnical engineering deals with complicated and highly variable set of engineering principles. A typical geotechnical engineering project comprises site characterization, foundation / soil treatment design, execution, monitoring and quality control systems. Unlike some other civil engineering designs, highly variable soil conditions make a geotechnical designs an iterative and repetitive process which in-turn make these designs cost and time intensive. Economy and optimization of geotechnical designs are dependent on comprehensive site characterization and evaluation of multiple alternatives. Availability of up-to-date data sets of geotechnical case histories covering entire spectrum; from techniques / technologies to results can help reduce both cost and time of future geotechnical projects. Knowledge from case histories can be used to develop geotechnical constitutive and analytical models with the help of information technology; such models can lead us to many progressive and futuristic limits of geotechnical engineering. The authors of the paper intend to propose architectural development of “Geotechnical Information System (GTIS)”. The GTIS system covering fundamental geotechnical concepts, data of case histories such as; techniques, technologies employed, monitoring and quality control systems, results / effectiveness of techniques, will provide a framework for the following: • increased understanding of world-wide geotechnical issues by sharing lessons learnt which will help minimize barriers of uncertainty • enhancement of investigation and design procedures • development of economical and efficient technologies • identification of areas for collaborative research • development of “Geotechnical Artificial Intelligence Systems (GTAIS)”

Department(s)

Civil, Architectural and Environmental Engineering

Appears In

International Conference on Case Histories in Geotechnical Engineering

Meeting Name

Sixth Conference

Publisher

Missouri University of Science and Technology

Publication Date

8-11-2008

Document Version

Final Version

Rights

© 2008 Missouri University of Science and Technology, All rights reserved.

Document Type

Article - Conference proceedings

File Type

text

Language

English

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Aug 11th, 12:00 AM Aug 16th, 12:00 AM

From Case Histories to Conceptual Models

Arlington, Virginia

Geotechnical engineering deals with complicated and highly variable set of engineering principles. A typical geotechnical engineering project comprises site characterization, foundation / soil treatment design, execution, monitoring and quality control systems. Unlike some other civil engineering designs, highly variable soil conditions make a geotechnical designs an iterative and repetitive process which in-turn make these designs cost and time intensive. Economy and optimization of geotechnical designs are dependent on comprehensive site characterization and evaluation of multiple alternatives. Availability of up-to-date data sets of geotechnical case histories covering entire spectrum; from techniques / technologies to results can help reduce both cost and time of future geotechnical projects. Knowledge from case histories can be used to develop geotechnical constitutive and analytical models with the help of information technology; such models can lead us to many progressive and futuristic limits of geotechnical engineering. The authors of the paper intend to propose architectural development of “Geotechnical Information System (GTIS)”. The GTIS system covering fundamental geotechnical concepts, data of case histories such as; techniques, technologies employed, monitoring and quality control systems, results / effectiveness of techniques, will provide a framework for the following: • increased understanding of world-wide geotechnical issues by sharing lessons learnt which will help minimize barriers of uncertainty • enhancement of investigation and design procedures • development of economical and efficient technologies • identification of areas for collaborative research • development of “Geotechnical Artificial Intelligence Systems (GTAIS)”