A Parameter Database And Information System For Duncan-Chang's Model

Duncan-Chang's model can represent the non-linearity of soil mechnical behavior. It has a few number of parameters, material constants and adequate physical meaning. So this model becomes one of the most widely used constitutive models. However, great difficulty exists in deciding Duncan-Chang's model parameters exactly. How to determine the model parameters properly is one of the most puzzled questions for numerical analysis in Geotechnical Engineering. The difference between calculation result and practical cases do lie in parameters.The state-of-the-art of model parameters was summarized. According to the management and analysis of about 500 groups of model parameters published in more than 100 vended literatrues, the research of the manufacture process of datasheets and forms and system's main construction, this thesis suggested and established a Duncan-Chang's model parameter database and information system (DCPDIS) which bases on Visual Foxpro language platform. DCPDIS precessed several functions, such as: managing Duncan-Chang's model parameter unitely; scaning and history inquiring about fortime engineering's Duncan-Chang's model parameter information, which affords references for the future; completing and modifing the DCPDIS through function buttons, such as add, modify, save and delete; in addition, users can acquire help from the searches fuction in"system help"module, and this module can link to the whole content of referenced literatures.The establishment of DCPDIS has practical merit in pushing on the digital process of Geoengineering and making the precious data accumulated in engineering practice before to be exploited and applied ulteriorly. Through the information known to query and forecast the information unknown, this will largestly accelerate the engineering process, make benefits both in finacial and labor aspects. At the same time, the data in database can be useful for Geotechnical Engineering study, such as offering stylebook for study of Neural Network model, statistical stylebook for study of probability distributing.