This research uses Microsoft SQL Server as a database management system and uses Python to establish analytical models including ACI, CEB, GL2000, B3, B4, and B4-TW. Unlike traditional database analysis method, which uses Excel and Access, Python and SQL can do data screening, data mining and data analysis much more efficiently.
This website is the first created webpage that includes both cloud-based shrinkage & creep database and online calculation modules internationally. Its database currently includes 4 decades of test data from Taiwan, JSCE data from Japan and NU data from all over the globe; test data from China is now collecting and organizing.
This website is designed to be extremely user-friendly and can get the hang of it at the first glance. There are two major functions provided. First, users can input essential data needed for analysis and obtain shrinkage or creep’s prediction curve immediately. Second, users can enter the maximum and minimum value of certain parameters interested in, and all corresponding data points form the selected database will be outputted in scatter graph in a few seconds.