Student: Afraa Hassan
Supervisor: Dr. Muntasir Billah
Thesis Committee Member(s): Dr. Eltayeb Mohamedelhassan, and Dr. Sam Salem (Graduate Program Coordinator - Session Chair)
Presentation Title: Durable Concrete for Northern Infrastructure with Reduced Drying Shrinkage and Micro-Cracking
Date and time: Wednesday, February 3rd, 2021, between 1:00 and 1:45 P.M.
Time: Feb 3, 2021 01:00 PM Eastern Time (US and Canada)
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Meeting ID: 941 2936 7134
In the Northern regions, durability issues resulting from concrete cracking are a major factor for damages and failures for many types of structures (e.g., buildings, parking garages, basement, bridge decks). The presence of shrinkage cracks in concrete is one of the major issues affecting concrete durability. Loss of moisture, changes in temperature, and hydration process are few reasons that cause shrinkage cracks in concrete. Among all types of shrinkage, drying shrinkage contributes a major portion of shrinkage strain in conventional concrete. Controlling the drying shrinkage effectively can reduce the total shrinkage strain in concrete and subsequently reduce the extent of cracking and improve the durability of concrete structures. Over the last several decades, researchers have investigated the causes and remediation strategies for shrinkage in concrete. Their research combines information on concrete shrinkage, identifying the types and causes of shrinkage in concrete, and explaining the applications and suitability of different types of shrinkage reducing admixtures (SRA). The objective of this exploratory study is to develop a pulp fiber-based concrete to reduce the drying shrinkage and microcracks in concrete. Using superabsorbent cellulose fibers (SCF) derived from water-insoluble, lignin-free Softwood Kraft Pulp fibers in the concrete mix, this study intends to develop a concrete mix with acceptable fresh and hardened properties with low drying shrinkage and cracking. Using the Scanning Electron Microscope (SEM) images the crack growth in different concrete specimens is observed. Free shrinkage tests are conducted to evaluate the effectiveness of SCF in reducing the drying shrinkage of concrete. Test results indicated significantly reduced crack widths and lower drying shrinkage in concrete containing SCFs. Additionally, shrinkage strain of concrete is one of the most important design parameters in many construction applications. Although there exist many shrinkage prediction models, the output from those models varies significantly. Recently, the availability of increased amount of data and computational power and, on the other side, the variety of available analytics algorithms have enabled engineers to move from descriptive statistics and simplistic correlation analyses to more sophisticated machine learning (ML) techniques. Considering the current difficulties of predicting the shrinkage strain of concrete, this research will also develop an ML-based shrinkage prediction model using the globally accepted RILEM data bank consisting of 1869 dataset. Different ML techniques will be used to identify the most accurate model for calculating concrete shrinkage. Shrinkage strains calculated using the ML models will be compared with the existing ACI model, CEB MC 90 model, B3 model, and GL 2000 model. The comparison of this model will give a clear overview of the parameters that affect concrete shrinkage most and help to develop a reliable shrinkage strain prediction model.
Student: Afraa Hassan