Infrastructure Engineering - Research Publications

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    Computational Modelling for Managing Pathways to Cartilage Failure.
    Miramini, S ; Smith, DW ; Gardiner, BS ; Zhang, L ; Connizzo, BK ; Han, L ; Sah, RL (Springer Cham, 2023)
    Over several decades the perception and therefore description of articular cartilage changed substantially. It has transitioned from being described as a relatively inert tissue with limited repair capacity, to a tissue undergoing continuous maintenance and even adaption, through a range of complex regulatory processes. Even from the narrower lens of biomechanics, the engagement with articular cartilage has changed from it being an interesting, slippery material found in the hostile mechanical environment between opposing long bones, to an intriguing example of mechanobiology in action. The progress revealing this complexity, where physics, chemistry, material science and biology are merging, has been described with increasingly sophisticated computational models. Here we describe how these computational models of cartilage as an integrated system can be combined with the approach of structural reliability analysis. That is, causal, deterministic models placed in the framework of the probabilistic approach of structural reliability analysis could be used to understand, predict, and mitigate the risk of cartilage failure or pathology. At the heart of this approach is seeing cartilage overuse and disease processes as a 'material failure', resulting in failure to perform its function, which is largely mechanical. One can then describe pathways to failure, for example, how homeostatic repair processes can be overwhelmed leading to a compromised tissue. To illustrate this 'pathways to failure' approach, we use the interplay between cartilage consolidation and lubrication to analyse the increase in expected wear rates associated with cartilage defects or meniscectomy.
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    Structural Health Monitoring of Bridges Using Advanced Non-destructive Testing Technique
    Maizuar, M ; Zhang, L ; Miramini, S ; Mendis, P ; Duffield, C ; Wang, CM ; Ho, JCM ; Kitipornchai, S (Springer, Singapore, 2020-01-01)
    This paper presents an integrated framework for structural health monitoring of bridges by using advanced non-destructive testing (NDT) technique in conjunction with computational modelling. First, the structural characteristics of the Eltham Trestle Bridge under train loading were monitored using the combination of the 3D optical measurement system and IBIS-S. The results demonstrate that, in conjunction with computational modelling, the NDT can capture the structural health conditions of the bridge by analysing the natural frequencies and deformation profiles of the critical members of the bridges. Then, the developed framework also takes into account the impact of extreme events (e.g. truck impacts and earthquakes) by using a reliability-based model. Finally, using the Montague Street Bridge as a case study, it shows that proposed framework has the capability of predicting the residual life of a bridge subject to both progressive deterioration and extreme events throughout its service life.
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    Automation in structural health monitoring of transport infrastructure
    Zhang, L ; Herath, N ; Raja, BNK ; Chen, S ; Miramini, S ; Duffield, C (Springer Singapore, 2021-01-01)
    Roads are among the most important assets in the world. Road structure improvements make a crucial contribution to economic development and growth and bring important social benefits. Automation in structural health monitoring allow the accurate prediction of ongoing damage caused by long-term traffic loading. This permits optimal road structure management and ensures the longevity and safety of road structures. This chapter discusses a variety of advanced automation techniques in structural health monitoring of road structures, such as data acquisition, data processing, and life-cycle assessment. It demonstrates that the implementation of automation in road asset management can increase the productivity and extend the service life of road structures, and enhance the durability of crucial road structures and increase transport infrastructure sustainability.
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    Infrared Thermography for Detecting Subsurface Defects of Concrete Structures
    Khan Raja, BN ; Miramini, S ; Duffield, C ; Zhang, L ; Wang, CM ; Ming, C ; Kitipornchai, S (Springer Singapore, 2020-12-23)
    Delamination is one of the serious types of deterioration in reinforced concrete structures. It could cause concrete spalling, exposed steel bars, and ultimately affects the structural integrity of concrete structures. Infrared thermography (IRT) is a non-destructive technique which could potentially detect the delamination by capturing thermal contrast (∆T) on concrete surface caused by the heat flow disruption within the concrete due to subsurface anomalies. However, the optimum time and environmental conditions for IRT data collection are still unclear. In this study, an experimentally validated numerical model was developed to investigate the effect of a range of environmental conditions and defect characteristics on the IRT inspection outcomes. The results show that, under direct solar irradiation, the total heat flux input plays an important role in the development of thermal contrast ∆T instead of flux rate. Furthermore, delamination depth and size are two critical parameters that affect IRT results.