Civil and Structural Engineering Computing: 2001
School of Engineering, University of Durham, United Kingdom
This paper reviews the use of computers in geotechnical engineering for purposes other than numerical modelling. Information technology is becoming increasingly important in geotechnical engineering and computers are being used much more for non-computational purposes. Expert judgement and qualitative data processing play an important role in geotechnical engineering. Therefore, this paper reviews the use of computers for storage, exchange and processing of data, often in qualitative form. The use of computers for numerical modelling is not dealt with.
A major use of computers within the geotechnical industry involves geotechnical database systems. Site investigation data can often be voluminous and database systems provide a way of storing and processing these data. A major advance in data management has been the development of a standard format for data exchange developed by the Association of Geotechnical and Geoenvironmental Specialists in the UK. This has had a very significant impact on UK site investigation practice and the AGS format is now widely used as a means of communicating data between and within companies in the UK and as direct input into software applications that require such data. An area of data management and processing where there is scope for improvement in software packages is visualization of the ground model. Geographical information systems could assist with visualisation but have not yet been widely adopted in geotechnical practice.
The paper also covers the use of artificial intelligence (A.I.) techniques, such as knowledge-based (expert) systems, neural networks and genetic algorithms. Knowledge-based systems were first applied to geotechnical engineering in 1985 and neural network applications date from 1991. Systems are reviewed for the most common areas of application: Classification and Parameter Assessment, Foundations and Site Investigation.
Future advances in data processing are likely to come from an integration of knowledge-based system and database technologies. Knowledge-based systems can introduce a greater degree of `intelligence' into the data checking and interpretation. A large number of artificial intelligence (A.I.) systems have now been developed for geotechnical applications. However, many of the systems described are simple prototypes systems and very few are being used commercially at present. The transfer from research into full development seems to be slow in geotechnical engineering.
Finally, the use of the World Wide Web is considered, perhaps the most important aspect of information technology to impinge on professional practice at the present time. The paper focuses on the recent development of GeotechML, a mark-up language for representing geotechnical data on the web. GeotechML is the geotechnical equivalent of Extensible Mark-up language (XML) which will become the main form of data representation used on the World Wide Web. To date, data structures have been defined for ground investigation data, geotechnical entities (structures) and case histories, but further development is underway.
GeotechML will make it possible to search all geotechnical data available on the web. In this way the World Wide Web will become an international repository of geotechnical information, available to the whole community, avoiding the need to establish national or international geotechnical databases.
To assist with data processing and design, the geotechnical engineer could benefit from access to database systems, knowledge-based programs, surface modelling and visualisation tools, conventional calculation software, numerical modelling packages and more. The way forward is to develop an integrated `geotechnical workbench' which provides access to this wide range of software tools. It is suggested that GeotechML could be used as a means of providing a common `Project Model' through which all these packages could interact.