Fatigue damage assessment of reinforced concrete slabs using integrated dynamic testing and simulation / Adiza Jamadin

Adiza , Jamadin (2020) Fatigue damage assessment of reinforced concrete slabs using integrated dynamic testing and simulation / Adiza Jamadin. Undergraduates thesis, Universiti Malaya.

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Abstract

Assessment of existing fatigued structures is an important aspect of civil engineering infrastructure. This is critical in most loaded civil engineering structures such as bridges that are constantly subjected to dynamic loading, causing fatigue in the materials over time. Bridge deck slabs are one of the most structural elements susceptible to different cyclic loads, requiring regular checks for damage to fatigue. In order to understand the deterioration, fatigue carrying capacity and residual strength, the serviceability of the slab under the fatigue loads was not fully explored. Therefore, this research is designed to use vibration-based techniques to investigate the integrity of fatigued RC slabs. The objective of the study was to develop an integrated technique to evaluate the serviceability of fatigued RC slab structures including their dynamic characteristics, stiffness reduction, fatigue carrying capacity and residual strength through an integrated dynamic test and finite element (FE) model and update. Static, fatigue and dynamic testing of RC slabs were involved in the experimental program. A series of investigations have been carried out and have been divided into three phases. Phase one identified the dynamic characteristics of RC slabs at different levels of fatigue damage, including natural frequencies, mode shapes and damping ratios. The parameters of the test include the different number of fatigue loads at 1 million, 1.5 million and 2 million; and the different level of damage at undamaged, fatigued and damaged condition. The dynamic characteristics of RC slabs have been studied at different levels of fatigue damage. The natural frequencies show the drop from 38.6 Hz to 36 Hz and to 29.2 Hz due to the increase in the level of fatigue damage. It can be concluded that the dynamic behavior was significantly influenced by the RC slabs experiencing fatigue loads. Phase two of the FE modeling developed to represent the identical behavior of the RC slabs tested. The FE model was then correlated and updated using parametric optimization against experimental data to reflect the actual condition of RC slabs. It has been shown that, compared to the initial models, the updated FE models have a small error of 0.22 percent for the first mode and thus better improvements in terms of agreement on natural frequencies. It can be seen that the natural frequencies of the updated FE models were close to the experimental data measured with a minimum percentage of 0.26% and a maximum of 2.74% for the first mode. RC slabs ' efficiency would be reduced–making it necessary to evaluate fatigue carrying capacity. Phase three observed the RC slabs ' fatigue carrying capacity through the structural stiffness change. It also concluded that the dynamic behavior was significantly influenced by the RC slabs experiencing a loss in stiffness. The maximum decrease of 70.26 percent in structural stiffness was observed from undamaged to the highest fatigued state in the first mode. The relationship between stiffness, load cycles and natural frequency dynamic response is thus established. The residual strength of the RC slabs was observed in this phase. The decrease in residual strength justifies the loss of the damaged RC slabs ' stiffness, which is accounted for by the Young's modulus and moment of inertia. The strength capacity can be estimated theoretically through the relationship of these parameters. Compared to the updated model, the results are verified and a good agreement with a maximum error is 0.52%. An efficient method of assessing fatigue damage that integrates the dynamic testing and simulation on concrete structure introduced in this thesis provides a comprehensive technique and therefore has a very good potential for predicting future structural performance in service.

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