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.

本網頁使用Microsoft SQL Server做為資料庫管理系統，並使用Python建立分析方法，其中分析方法包含：ACI、CEB、GL2000、B3、B4以及B4-TW等分析模型。有別於傳統資料庫分析，例如Excel及Access;使用Python程式語言可以透過SQL語法的可攜性進行資料篩選、資料分析，效率更勝一般傳統資料庫分析方法。

本網站為國際上第一個完整且雲端化的收縮及潛變資料庫，其資料庫數據包含台灣數十年來的試驗資料、日本JSCE試驗資料和美國NU試驗資料，目前正在進行中國的試驗數據收集與整理。本網站提供兩大功能。1. 僅需輸入不同預測模型之對應參數即可得到該模型的預測曲線；2. 輸入參數的數值區間即可得到資料庫中位於此區間所有的數據分布之散步圖，不論是工程界或學術界皆能輕易上手並使用。