建置及應用資料庫以發展台灣混凝土潛變預測公式

Developing Taiwan's Concrete Creep Prediction Formulae Based on the Establishment and Application of Database

劉庭愷(Ting-Kai Liu)

指導教授 ： 陳振川

國立臺灣大學/工學院/土木工程學研究所/碩士(2017年)

https://doi.org/10.6342/NTU201703508

摘要

世界針對混凝土潛變收縮已有長期的試驗與研究發展，美國西北大學及日本土木學會分別彙整國際及日本資料以建立混凝土變形資料庫；台灣大學曾於2001年統整台灣混凝土資料，距今已近二十年，本研究首先依國際格式蒐集更新台灣混凝土變形資料，建立「台灣混凝土潛變收縮資料庫」。經透過與國際資料庫分析比較與文獻探討，證實台灣混凝土配比設計時，具有常使用高水泥量、低水灰比、低粒料量∕水泥量比，且使用彈性模數較低之本土粒料的特性。本研究評估選用Model B4潛變預測公式為基礎，針對台灣混凝土獨有之特性進行本土化修正，修正內容主要為本土粒料造成混凝土彈性模數的偏低、高漿體量造成高變形、與低粒料彈性模數對乾燥潛變的影響等，最後提出適用於台灣混凝土的潛變預測公式。另外，台灣資料庫中高爐石與飛灰混凝土之潛變資料量較為不足，故本研究也指出現有公式對高爐石與飛灰混凝土之適用情況、適用範圍，及未來加強實驗研究之建議。
另外，本研究也演進國際上傳統的資料庫建置與分析方式，採用MySQL資料庫管理系統建立資料庫；並使用Python程式語言撰寫分析與後續處理之程式，結果顯示搭配MySQL與Python之資料庫處理程序，執行效率遠優於傳統之方法，原因在於MySQL與Python之效能本身就較傳統的資料庫軟體與程式語言為佳，且兩者之間可利用SQL資料庫語法的可攜帶性，達到良好的整合，Python中各種專業套件也能使許多分析的後續動作自動化。最後，本研究成果除將台灣混凝土資料庫併入世界混凝土資料庫，也奠定世界資料庫發展至雲端化與網頁化之基礎。

關鍵字

混凝土 ； 長期變形 ； 潛變 ； 高爐石粉 ； 飛灰 ； 資料庫

並列摘要

Tests and researches on the creep and shrinkage of concrete have been developed over several decades at various places around the world. Northwestern University (NU) of the USA has established a concrete deformation database which incorporates data from around the world, while the Japan Society of Civil Engineers has established their own such database with date from Japan. National Taiwan University (NTU) began collecting data from Taiwan and established a first-version database in 2001. Continuing the early work done at NTU, this study follows the framework and formula of the NU database in establishing the Taiwan Creep and Shrinkage Database, the purpose of which is in collecting and integrating up-to-date local data on shrinkage and creep. Some distinct local characteristics of concrete in Taiwan have been discovered after a comparison between international and Taiwan-only data. The local concrete produced is generally made with a high amount of cement, low water-to-cement ratio, as well as low elastic modulus of sandstone aggregate. This study takes the Model B4 creep prediction model as a base for the development of a local prediction model for Taiwan. Modifications to the model, where necessary, primarily concern the underestimation of the concrete elastic modulus due to local aggregate, large deformation due to high paste amount, and the influence of low elastic modulus of aggregate to drying creep. Due to the lack of data for slag and fly ash concrete creep in the Taiwan database, suggestions for further experiments are proposed to promote the formulation of prediction formulae.
Rather than traditional methods, this study uses new tools for database establishment and analysis, and combines them in a new procedure. The new procedure involves MySQL, a Database Management System, for database establishment, and Python, a programming language, for programing of analysis models and post-processing tasks. Results show that this new database processing procedure is much more efficient than traditional procedures. This is, first, due to the greater efficiency of MySQL and Python over traditional Database Management Systems and programming languages. Second, SQL (the database programming language behind MySQL) is highly portable, which facilitates integration between MySQL and Python. Third, professional packages in Python allow one to proceed with many steps of analysis and post-processing automatically.
It is foreseen that this study will help to incorporate the Taiwan database into the world concrete deformation database and will help to establish an effective platform based on MySQL and Python. This, in turn, is expected to promote the development of a new era of cloud calculation and user-friendly web systems for deformation prediction.

並列關鍵字

concrete ； prediction ； creep ； slag ； fly ash ； database

參考文獻

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