Date of Award
Master of Science in Civil Engineering (MSCE)
Civil and Environmental Engineering
The self-sensing ability of cementitious materials with conductive particles for Structural Health Monitoring (SHM) gained a lot of interest in the last few decades. Based on previous literature it is known, that various materials and sensors have been developed, but still are not commonly used in practice, since the materials used for the conductive phase can be extremely costly and difficult to disperse within the cementitious matrix, which especially accounts for nanoscale materials such as carbon nanotubes (CNTs). Recently, a new approach of creating a conductive and self-sensing concrete containing latex-CNTs thin film-coated aggregates has been developed and investigated with experimental methods. This method enables a less costly and less complex dispersion of the CNTs by spray-painting the coating on coarse and fine aggregates.
The objective of this thesis was to develop a numerical method to predict the piezoresistive behavior of the developed cementitious composite. Nowadays, to avoid costly and time consuming experiments, numerical simulations are an important tool to address such problems. Within a first step, significant parameter for creating a representative microstructure and numerical finite element model had to be identified. The electro-mechanical simulations were conducted for cementitious composites in the mortar-scale by applying a tensile strain to the microstructure. After generation a random microstructure and performing preliminary simulations for a coupled mechanical-electrical physics it was realized, that interfacial debonding must be applied to achieve a fractural change in resistivity (FCR), which is an indicator for the strainsensing ability of a cement-based composite. Afterwards, the numerical simulation was validated with experimental data, which showed an extremely high correlation of the FCR of both studies.
Finally, a parameter study was performed, where the effect of variation of the volume fraction of the conductive coated aggregates, the coating thickness and electrical conductivity on the FCR was investigated. First results showed, that the electrical resistivity of the composite was significantly reduced compared to the plane mortar. The result provided by the parameter study showed, that the change of volume fraction of aggregates and coating thickness has the largest impact on the FCR and sensing ability of the composite. The change of the initial electrical conductivity of the coating does not lead to a considerable FCR. This was traced back to the large difference in conductivity between cement matrix and coating and the high volume fraction of conductive material, which is well above the percolation threshold of nanoscale conductive materials.
Ackermann, Kay Christian, "SELF-SENSING CONCRETE FOR STRUCTURAL HEALTH MONITORING OF SMART INFRASTRUCTURES" (2018). Open Access Master's Theses. Paper 1285.