HPC與UHPC收縮行為之實驗研究

Abstract

良好的混凝土工程設計應統籌考慮強度、變形與耐久性三個方面，但在工程設計中，混凝土的體積穩定性和耐久性問題常常被忽視，大壩、橋樑、道路路面等工程由於收縮變形過大而導致結構開裂影響結構的安全性和耐久性。由於對混凝土強度的需求和強塑劑的發展，高性能混凝土(HPC)和超高性能混凝土(UHPC)中水膠比不斷減小、水泥用量不斷增加，混凝土的收縮過大成為制約混凝土工程發展的瓶頸之一。飛灰、高爐石粉等屬於工業生產過程中的副產物，在HPC中使用飛灰等礦物摻料，有利於環境保護、節能減碳。單摻或複摻膨脹劑和鋼纖維對UHPC的物理性能、力學性能、收縮行為的影響也是本研究的重要內容。 本研究以單摻或複摻0~40%的飛灰、0~20%的高爐石粉或偏高嶺土為參數，進行了HPC的工作性能、力學性能、自體收縮、乾燥收縮等宏觀性能實驗和粉末衍射實驗(XRD)、掃描電鏡實驗(SEM)等微觀性能實驗。研究表明隨著礦物摻料摻量的增加，HPC的凝結時間變長、坍落度增加、乾燥收縮減小、Ca(OH)2的衍射峰強度減小、界面過渡區更緻密。隨著飛灰摻量的減小、高爐石粉和偏高嶺土摻量的增加，HPC的抗壓強度逐漸提高。摻入飛灰和高爐石粉有助於減小HPC的自體收縮，但摻入細度較大的偏高嶺土則增加了HPC的自體收縮。複摻高爐石粉和飛灰HPC、複摻偏高嶺土和飛灰HPC的乾燥收縮低於單摻同摻量飛灰HPC，單摻偏高嶺土HPC的乾燥收縮稍少於同摻量高爐石粉HPC。複摻高爐石粉和飛灰HPC、複摻偏高嶺土和飛灰HPC的自體收縮高於單摻同摻量飛灰HPC。單摻偏高嶺土HPC的自體收縮顯著高於同摻量高爐石粉HPC。 本研究以單摻或複摻0~6%的膨脹劑摻量、0~3%的鋼纖維體積摻量為參數，進行了UHPC的工作性能、力學性能、自體收縮、乾燥收縮等宏觀性能實驗和XRD實驗、SEM實驗、熱重分析實驗、孔結構分析實驗等微觀性能實驗，研究表明隨著膨脹劑摻量的增加，UHPC可以在保持較好工作性能和力學性能的情況下，顯著減小自體收縮，Ca(OH)2的衍射峰強度、吸熱峰強度、10nm~50nm孔隙體積均下降或減少，增加C-S-H凝膠、鈣礬石等生成物結晶的數量。摻入鋼纖維會增強UHPC的抗壓強度、降低流動性、減少UHPC的自體收縮和乾燥收縮。複摻膨脹劑和鋼纖維可不同程度地減少UHPC的自體收縮和乾燥收縮。 本研究採用B4 TW2020、Eurocode 2、JSCE、CEB MC10、ACI 209R、B4、GL2000等收縮預測模型(其中7種用於乾燥收縮，4種用於自體收縮)以及礦物摻料修正係數kSCM、相對誤差RE、擬合度R2new等參數對13組HPC的乾燥收縮、自體收縮進行了預測分析。採用B4 TW2020、Eurocode 2、JSCE、CEB MC10、FHWA、Yoo、Lee、JonassonH、DilgerW等收縮預測模型(其中4種用於乾燥收縮，9種用於自體收縮)結合膨脹劑和鋼纖維修正係數kEF、相對誤差RE、擬合度R2new對11組UHPC的乾燥收縮、自體收縮進行了預測分析。kSCM*B4和GL2000對HPC乾燥收縮的預測誤差、kSCM*CEB和B4 TW2020對HPC自體收縮的預測誤差相對較小。kEF*B4 TW2020和JSCE對UHPC乾燥收縮的預測誤差、kEF*B4 TW2020等5種模型對UHPC自體收縮的預測誤差相對較小。

Suitable engineering design of concrete should coordinately consider strength, deformation, and durability. However, in engineering design, the volume stability and durability of concrete are often overlooked, leading to structural cracking in projects such as dams, bridges, and road surfaces due to excessive shrinkage deformation, which affects the safety and durability of the structure. Due to the demand for concrete strength and the development of superplasticizer, the water cement ratio in high-performance concrete (HPC) and ultra-high performance concrete (UHPC) continues to decrease, and the amount of cement used in these concrete continues to increase. The excessive shrinkage of concrete has become one of the bottlenecks restricting the development of concrete engineering. Fly ash, ground granulated blast-furnace slag (GGBS), and other waste materials in industrial production processes are beneficial for environmental protection, energy conservation, and carbon reduction when used in HPC. The influence of single or binary addition of an expansive agent and steel fibers on the physical properties, mechanical properties and shrinkage behavior of ultra-high performance concrete is also an important topic that needs to be studied. This study conducted macroscopic performance experiments on HPC with single or binary content of 0~40% fly ash, 0~20% GGBS or metakaolin, including workability, mechanical properties, autogenous shrinkage, and drying shrinkage, as well as microstructural experiments of X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results showed that with the content of supplementary cementitious materials, the setting time of HPC increased, slump of HPC increased, drying shrinkage of HPC decreased, the diffraction peak intensity of Ca(OH)2 decreased, and the interface transition zone became denser. With the decrease content of fly ash and the increase content of GGBS and metakaolin, the compressive strength of HPC gradually increased. The addition of fly ash and GGBS helps to reduce the autogenous shrinkage of HPC, but the addition of finer metakaolin increased the autogenous shrinkage of HPC. The drying shrinkage of HPC mixed with GGBS and fly ash, as well as HPC mixed with metakaolin and fly ash, was lower than that of HPC mixed with the same content of fly ash. The drying shrinkage of HPC mixed with single metakaolin was slightly lower than that of HPC mixed with the same content of GGBS. The autogenous shrinkage of HPC with mixed GGBS and fly ash, mixed metakaolin and fly ash was higher than that of HPC with the same content of fly ash. The autogenous shrinkage of HPC with single metakaolin was significantly higher than that of HPC with the same content of GGBS. In this study, the macro performance experiments such as workability, mechanical properties, autogenous shrinkage, dry shrinkage, XRD experiments, SEM experiments, TG analysis experiments, and Mercury intrusion porosimetry experiments, etc. of UHPC were carried out with the expansion agent dosage of 0%-6%, and the steel fibers dosage of single or binary addition of 0%-3%. The research shows that with the increase of expansion agent dosage, UHPC could significantly reduce autogenous shrinkage while maintaining good workability and mechanical properties, the diffraction peak of Ca(OH)2, endothermic peak of Ca(OH)2, and 10nm ~50nm pore volume all decreased, and the quantity of C-S-H gel and ettringite crystals was increased. Adding steel fibers enhanced the compressive strength of UHPC and reduced its flowability, drying shrinkage and autogenous shrinakge. The addition of expansion agents and steel fibers could decrease drying shrinkage and autogenous shrinakge of UHPC. This study predicted and analyzed the drying shrinkage and autogenous shrinkage of 13 groups of HPC using several shrinkage prediction models, including B4 TW2020, Eurocode 2, JSCE, CEB MC10, ACI 209R, B4, GL2000 (7 models for drying shrinkage, 4 models for autogenous shrinkage), as well as parameters such as kSCM coefficient, relative error RE, and fitting degree R2new. Several shrinkage prediction models, including B4 TW2020, Eurocode 2, JSCE, CEB MC10, FHWA, Yoo, Lee, JonassonH, and DilgerW (4 models for drying shrinkage, 9 models for autogenous shrinkage), as well as parameters such as kEF coefficient, relative error RE, and fitting degree R2new, were used to predict and analyze the drying shrinkage and autogenous shrinkage of 11 groups of UHPC. The shrinkage prediction results could provide reference for predicting drying shrinkage and autogenous shrinkage in HPC and UHPC related engineering. The prediction errors of kSCM*B4 and GL2000 for HPC drying shrinkage, kSCM*CEB and B4 TW2020 for HPC autogenous shrinkage were relatively small. The prediction errors of kEF*B4 TW2020 and JSCE for UHPC drying shrinkage, kEF*B4 TW2020 and other 4 models for UHPC autogenous shrinkage were relatively small.