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  • 學位論文

建置及應用資料庫以發展台灣自充填混凝土收縮預測公式

Developing Taiwan's Self-Compacting Concrete Shrinkage Prediction Formulae Based on the Establishment and Application of Database

指導教授 : 陳振川

摘要


混凝土潛變、收縮相關研究已經於世界各地發展了數十年,而自充填混凝土(SCC)經過近二十多年研究發展已在台灣工程上普遍使用,然而其變形特性仍待深入探討。美國西北大學建立了世界以及日本混凝土體積變形資料庫,台灣大學也在陳振川教授帶領之下也於2001建立第一版屬於台灣本土潛變、收縮資料庫,其內容均以需搗實混凝土為主(VC)。本研究繼續按照NU資料庫之架構與形式,並透過蒐集和整理現今國際最新之自充填混凝土收縮資料。藉由SCC及VC資料庫分析比較發現台灣配比之地方特色。一般台灣自充填混凝土擁有較高砂率以及較多礦物取代以及使用彈性模數較低之砂岩。本研究選用B4模型作為基礎,用來發展適用於台灣自充填混凝土收縮之預測模式。另外本研究以劉庭愷與秦維邑開發之程式為基礎,並根據他們所提供之程式延伸與撰寫,用以進行資料快速分析,大幅縮短原本研究所需時間。 本研究蒐集來自世界各地自充填混凝土潛變、收縮資料並建立成資料庫形式。鑒於自充填混凝土與傳統混凝土差異性,因此在資料建置上新增屬於自充填混凝土特色之參數,如:砂率、坍流度、最大粗骨材粒徑……等。最後本研究也提出專屬自充填混凝土之預測模式,該預測模式在各統計參數指標下也有不錯表現,除此之外也適用於國際及台灣自充填混凝土收縮之預測。

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. However the Self-Compacting concrete (SCC) after near 20 years of research and development, has been widely used in construction, but its deformation characteristics still needs more investigation. Northwestern University (NU) of the USA has established a concrete deformation database which incorporates data from around the world, while National Taiwan University (NTU) began collecting data from Taiwan and established a first-version vibrated concrete (VC) database in 2001. Continuing the early work done at NTU, this study follows the framework and parameters of the NU database to establish Taiwan Self-Compacting Concrete Shrinkage database. Some distinct local chara cteristics of Self-Compacting concrete in Taiwan have been discovered after a comparison between international and Taiwan-only data. The local SCC produced are generally made with high sand ratio, high mineral admixture substitution, as well as low elastic modulus of sandstone aggregate. This study takes Model B4 shrinkage prediction formula as a base to develop Taiwanese local prediction formula. In addition, on effective new tool used for data analysis in this study developed by Ting-Kai Liu and Wei-Yi Chin. This study collects SCC data from all over the world, and establishes a SCC shrinkage database. In view of the difference between SCC and VC, the new parameters such as sand ratio、slump-flow、max aggregate size were included. By showing satisfactory performance in statistical comparisons, this study proposed a SCC shrinkage prediction model, which is suitable for both international and Taiwan SCC database

參考文獻


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