Unveiling the Resistance Mechanisms in Reinforced Cementitious Materials
Project Description
Innovative cementitious materials, such as Engineered Cementitious Composites (ECC) and Ultra-High Performance Fiber Reinforced Concrete (UHPFRC), have increasingly become integral to the construction industry due to their superior structural properties. These materials are often used in conjunction with reinforcement bars (rebar) to enhance structural performance. However, the internal resistance mechanisms of these advanced materials remain largely unknown, posing a challenge to optimizing their application in construction.

This research project aims to address this gap by employing a multifaceted approach that combines experiments, simulations, and advanced sensing technologies, such as fiber optic sensing and digital image correlation. Through this investigation, we aim to provide valuable insights into the fundamental behavior of reinforced cementitious materials, ultimately contributing to the advancement of construction practices and the development of more resilient infrastructure.
Supervisor
ZHANG, Shenghan
Quota
3
Course type
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
1. Assisting in experimental design
2. Supporting the execution of experiments
3. Learning to use advanced sensing technologies
4. Conducting basic numerical analysis
Applicant's Learning Objectives
1. Gain Hands-on Experience in Experimental Procedures: Acquire practical skills in conducting experiments, including the mixing design of cementitious materials (such as SHCC or UHPFRC), preparing samples, and collecting data.

2. Familiarize with Advanced Sensing Technologies: Learn to operate and interpret data from advanced sensing technologies relevant to the field of study, including fiber optic sensing and digital image correlation.

3. Enhance Skills in Numerical Analysis: Cultivate proficiency in using numerical methods (such as Abaqus) and software (such as Python) for data analysis, including interpreting results and drawing conclusions.
Complexity of the project
Moderate