| The assessment and prediction of damage in bridges is a necessary part in bridge conservation maintenance and technical reconstruction of today, which is also one of the most heated problems that are being discussed by scientists in engineering area and scholars at home and abroad, and along with the increment of old bridges, the problem attracts more attention. Combining with the character of bridges, the thesis gives a systematic and thorough study on some technical problems of assessment of damage in concrete bridges, which includes:(1) Integrating with the research results in engineering, a systematic analysis for the cause of damaged concrete bridges in our country was given in the thesis, which will consequently lead to some pertinent proposals towards plan, design , construction and administration of bridges as well as lay a foundation for the establishment and decision-making of the assessment system of damaged bridges.(2) According to its character, bridge system can be divided into several multilevel-systems, and thus a hierarchy assessment model is established. On the basis of these research works, a comprehensive grading system for assessment factors is discussed and developed, being prepared for the neural network assessment of damaged concrete bridges.(3) Based on the hierarchy assessment model, a neural network method to assess the damage in bridges is put forward. The scores of assessment factors being made the input value and the score of damage assessment the output value, a multilevel assessment model for bridges came into being, which in turn could come to the final result of the bridge as a whole and get the damage rating according to the given standard. The method, making use of neural network to learn from exiting assessment examples, could undergo assessment instead of expert group with the relationship between assessment result and assessment factors best expressed in the network. As a result, it could not only reduce assessment workload and save resources, but also accumulate experts' experience and get rid of human factors in the course of assessment to make the result sound objective. Simultaneously, the established system is characterized by learning of itself, which can complete assessment through simulating experienced assessment mechanism when there is no expert or has not got enough experts. To conclude from the given examples, each model, after spending little time on training themselves from sample data, could assess the damage degree for existing bridges using trained weighted values and thresholds.(4) Considering such actual difficulties as lacking of engineering data and discrepancy in managing level, four methods for damage assessment are proposed in the thesis based on expert knowledge, which are weighted average method , fuzzy comprehensive evaluation method, generalized quantification method and set pair analysis method to make useful supplements to the neural network method. Disadvantageous effects, caused by dissimilarity of subjective factors such as everyAbstractexpert's knowledge , level, discernment and emphasis on problem, are eliminated to some extent in each method. Furthermore, there are not any complicate mathematic or mechanical calculations, and conclusion can be easily got only by some simple reasoning and comparing from experience. Given examples indicate that it's conclusion accord with the engineering practice quite well.(5) Being a very important factor of concrete bridges, remaining life become much more crucial in process of damage assessment. Accordingly, the thesis proposes four models for predicting the remaining life of concrete bridges, which are regression prediction model, grey prediction model, improved grey model and neural network model. Decision-makers can choose different models in terms of subjective conditions, including knowledge level as well as the quantity and kinds of information mastered, to carry thorough prediction analysis and decision making.(6) Maintenance is a significant part...
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