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Innovative Computational Support in Bridge Aesthetics

Author(s):


Medium: journal article
Language(s): English
Published in: Transportation Research Record: Journal of the Transportation Research Board, , n. 1, v. 1549
Page(s): 1-11
DOI: 10.1177/0361198196154900101
Abstract:

Bridge aesthetics, an area of great interest to engineers, is recognized as a difficult area to research because of its subjective nature and ill-defined concepts. An innovative computational decision support tool for use in bridge aesthetics is described. The system contains a knowledge base created by using an extensive literature survey and by completing in-depth knowledge elicitation from leading bridge designers in the United Kingdom and with the support of the Department of Transport. To further validate the knowledge base, the rules elicited from the designers were tested against public opinion through a series of questionnaires. This procedure enabled the construction of a knowledge base that supports many aspects of aesthetics for small- to medium-sized span road bridges. This limited domain was chosen because this form of bridge is currently the most commonly constructed in Britain, yet generally receives little attention in terms of aesthetics because of time and economic constraints. The knowledge base has been incorporated into a system aimed at providing interactive advice on comparative bridge design. The system was developed in Visual C + + to run on a personal computer and to operate in a Windows environment. It is currently undergoing prolonged evaluation in practicing bridge design offices. To date, this evaluation has shown that engineers like the system and would find it useful. Therefore, commercial exploitation is currently being explored. The comments received during the evaluation are also being used to further tailor the system to suit practicing engineers' needs.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/0361198196154900101.
  • About this
    data sheet
  • Reference-ID
    10778583
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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