The Construction And Application Of The Database Bank Management System For Concrete Durability Test

Under the circumstances that concrete durability has become more and more important at present, it's urgent how to improve the investigation efficiency of concrete durability. Lots of projects and study data show that the durability of concrete is influenced non-linear by test equipments, ingredients, experience, performance of materials etc. These make concrete confect and predicting performance fallen behind, In engineerings, many concrete parameters of long-term value, such as stress, strength calculation and imitate true analysis, are very important, but measure these values is time-consuming. Therefore, how to handle to these data and analysis, then applied estimate model to processing the predict of performance, having the theories with realistic meaning.Launching on method and means of concrete durability research, we developed Concrete Durability Database Management System (Ab. CDurDBMS). Based on enough experiment data, BP Neural Networks is applied to predict concrete performance and a quantitative model is setup to analyse factors. BP Neural Networks is a system modeled on the human brain. It is composed of a great deal of neurons. Each neuron is linked to certain of its neighbors with varying coefficients of connectivity that represent the strengths of these connections. Learning is accomplished by adjusting these strengths to cause the overall network to output appropriate results. Concrete carbonation and reinforcing steel bar rust are complexly dynamic process. On the design of concrete durability, we should predict carbonation depth and steel corrosion extent in future according to concrete constitution and surrounding. But the mechanism how factors impact on carbonation and steel corrosion is not certain. The system introduces Gray Model, GM(n,h)-one differential equation is setup. The model is good at predicting uncertain process and quantifying factors. Applied in practice, the CDurDBMS has been proved convenient for researcher to collect information and handle experiment data. It provides an efficient approach to manage and standardize experiment data. Adopting prediction models of BP Neural Network and GM(n,h), obtained parameters of performance may be quoted by similar experiments. So experiment times would be lessened, and work intension can be reduced. Grey connection analysis can be used to analyse quantitatively effecting factors and pick-up main factor, the conclusion obtained is accordant to qualitative analysis.