| dc.description.abstract | Concrete structures, including buildings, bridges, pavements, and offshore structures,
face a wide range of loading conditions, both static and cyclic. When subjected to
fatigue loading, the response of concrete elements can be quite complex and difficult
to predict, primarily due to the inherent heterogeneity of the material. Experiments
are the most effective approach to study fatigue behaviour, utilizing techniques like
acoustic emission to understand internal microcracking. Typically, these experiments
are performed on notched specimens to accurately monitor fracture behavior. However,
fatigue experiments are time-consuming and relatively expensive considering the casting
and curing time in addition to the cycling time during tests. To optimize costs and save
time, it is beneficial to determine the static strength of specimens prior to the experiment.
This knowledge helps in determining load amplitudes for testing and enables the effective
design of experiments.
The theory of critical distances (TCD), due to its appealing characteristics, has been
successfully used in the past to predict the strength of brittle as well as ductile materials,
weakened by the presence of stress risers, under both static and fatigue loading. In this
work, the TCD’s unique features are exploited, and the point method is reformulated
to predict the strength of notched plain concrete beams of different sizes under mode
I quasi-static loading. The presence of fracture process zone, which is responsible for
the post-peak softening behaviour of concrete under tension, is considered through the
concept of an effective elastic crack. A power law is proposed to relate the effective
crack length to the geometrical properties. The material characteristic length, required
for the application of TCD, is correlated with the maximum aggregate size. The resulting
formulation is found to yield satisfactory predictions of static strength of notched plain
concrete beams, wherein the geometric dimensions of the beam, tensile strength, and
maximum aggregate size of the concrete mix are the governing parameters. The proposed
formulation is validated using a probabilistic analysis of various experimental results
available in the literature. Furthermore, the TCD is applied for predicting the static
strength under mixed mode loading. Two alternatives are proposed, one by directly
applying TCD by considering the characteristic length to vary linearly with mode mixity
ratio and the other by converting the mixed mode problem into an equivalent mode I
case using energy equivalence.
Understanding the internal microcracking occurring within concrete is crucial to gain
insight into its behaviour under fatigue conditions. One of the most effective techniques
for achieving this is the use of acoustic emission (AE). This study explores the potential of various methods for analysing AE signals such as average frequency versus rise
angle analysis and intensity analysis for characterisation of the fracture process in plain
concrete under both monotonic and fatigue loading conditions. By applying k-means
clustering to the AE data, four damage mechanisms in plain concrete, namely cement
mortar cracking, aggregate slip, ITZ cracking, and aggregate fracture, are identified.
In addition, parameters extracted from AE signals have shown a promising correlation
with fatigue crack behaviour, with a log-linear relationship between crack propagation
rate and AE parameter rate. Among the different parameters extracted from the AE
waveforms, the AE energy is identified as the most suitable parameter for characterising
fatigue behaviour of concrete. Here, the model parameters as well as their posterior
distributions are estimated using Bayesian regression.
The present study is, thus, an attempt to understand and forecast the response of con crete specimens when subjected to monotonic and fatigue loading utilising the potential
of the theory of critical distances and acoustic emission. Overall, this dissertation aims
to provide valuable insights into the response of concrete to different loading conditions
and contribute to the development of more accurate and reliable methods for predicting
the behaviour of concrete structures under real world loading conditions. | en_US |
