Civil Engineering Theses
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This collection is made up of doctoral and master theses by research, which have been received in accordance with university regulations.
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- PublicationUncertainty Quantification in Tunnelling-induced Surface Settlement(University College Dublin. School of Civil Engineering, 2017)Evaluating the impact of tunnelling on above ground structures in urban areas highly relies on prediction of the settlement trough at surface level. Uncertainties in soil properties and other system characteristics for soft ground (e.g. Alluvium soil) can significantly affect the prediction. Classically, empirical formulas are used for prediction of the settlement using the experience from previous tunnelling projects. Empirical formulas do not consider the soil-lining interaction or the method of construction and lack a theoretical background for ground movement in continuum mechanics. Analytical and numerical approaches have developed to address some of these deficits, but have not to date, taken account of the many uncertainties involved in the process. This thesis introduces a stochastic method in the context of discrete random finite element theory to probabilistically predict the tunnelling-induced surface settlement. The method proposes a single mechanism (i.e. an uncertainty and sensitivity analysis framework) in which multiple sources of uncertainty can be considered within a single model (e.g. heterogeneity of the soil profile, variability in surcharge loads, and material properties). The power of the method is then examined through application to case studies involving two large-scale, shallow tunnelling projects excavated in alluvium soil. The results are compared with monitoring data, with estimations from deterministic finite element (FE) models and empirical formulas. Compared to the results of classical FEs and empirical approaches, application of the new probabilistic approach provides better understanding of the development of the settlement trough at surface level in both case studies. The output parameters for the tunnelling-induced settlement trough (volume loss and maximum settlement) are in good agreement with actual monitoring data in both case studies. Notably, the prediction result of the empirical formula in the first case study is conservative and for the second one is quite non-conservative. The new approach, on the other hand, provides more accurate predictions and insights into the effect of different sources of uncertainty.
26 - PublicationA numerical Investigation into the use of forced vibration due to Vehicular Loads for structural health monitoring of bridges(University College Dublin. School of Civil Engineering, 2022)Structural Health Monitoring (SHM) aims to achieve early damage detection in bridges by characterizing changes in dynamic properties from the structural response acquired via sensors such as accelerometers. Currently, a new generation of SHM technologies is emerging to gather information in a low-cost and energy-efficient manner from the vibrations induced by vehicular loading. More specifically, the developments included in this thesis apply to technologies avoiding the need for a permanent installation on the bridge. They typically record measurements for a short duration of the response, which makes the limited info captured about the bridge highly sensitive to vehicular and road properties. The accelerometers can be placed on: (i) the bridge (i.e., direct measurements gathered through unmanned aerial vehicles), and (ii) the axles of a vehicle crossing the bridge (the so-called indirect measurements, or ‘drive-by’). Therefore, this thesis intends to detect, locate and quantify damage using short data bursts of forced vibration due to vehicular loading. Here, damage is understood as either a stiffness loss (global or local) or a deterioration of the support conditions. This research contributes to technologies based on location (i) by proposing an algorithm that relies on the measurements from an accelerometer during the forced vibration of the bridge while traversed by a specialised vehicle. The algorithm exploits the variation in bridge frequency, not only with the magnitude and location of the moving vehicle but also with the stiffness profile of the bridge. A k-Nearest Neighbours algorithm searches for the patterns of forced eigenfrequencies that are closest to the on-site instantaneous frequencies to determine the location and severity of the damage. The algorithm shows promising results, although it is limited to low vehicle speeds and low road roughness. Furthermore, this thesis contributes to the technology (ii) with three model-based drive-by algorithms, i.e., involving a finite element model of the bridge and a vehicular model, which are necessary to locate and quantify the damage. Three components can be distinguished within a measured vehicular acceleration: bridge, vehicle, and road components. The last two components usually govern the frequency spectrum, which makes it hard to distinguish the targeted bridge information. As a result, ‘drive-by’ solutions are often developed for damage detection purposes only, meaning that they rarely locate or quantify the damage, and when they do so, is usually under strict requirements, i.e., specific vehicle properties, low vehicular speed and smooth road profiles. In order to mitigate the undesired vehicle component, the concept of transfer function is applied to derive the response of the contact point between the vehicle and the bridge from the response of the acceleration of an axle. In order to deal with the road component, each algorithm uses a different strategy as follows: (1) estimation of the energy content in the frequency domain following the removal of the road profile in the spatial frequency domain based on measurements at different speeds. Damage is located and quantified by comparison to a database of responses generated via a simple P-load model; (2) optimisation of the road profiles estimated in the time domain using measurements in one axle at two different speeds. Based on cross-entropy optimization, the stiffness profile of a simply supported bridge model is accurately predicted, even for relatively high speeds and rough roads, except for locations next to the supports; (3) optimisation of the road profiles estimated in the time domain by two axles of the same vehicle. This algorithm addresses the condition of the bridge supports. Finally, drive-by algorithms (2) and (3) yield an accurate representation of the road profile on the bridge, in addition to an assessment of the mechanical properties of the bridge.
15 - PublicationApplying Computational Fluid Dynamics Simulations for Aerodynamic Studies of Long-span Bridges(University College Dublin. School of Civil Engineering, 2022)In the design of long-span bridges, estimating the wind effects is a critical requirement to evaluate and eliminate the risks of wind-induced problems on structural safety and serviceability. This thesis aims to validate the use of Computational Fluid Dynamics (CFD) simulations in bridge aerodynamic studies. A comprehensive review of the literature on the use of wind tunnel testing and CFD modelling for wind issues on long-span bridges was prepared. The lack of confidence of the bridge industry in applying CFD simulations within the design process due to insufficient validation and standardized guidance for use was noticed. Also, the need for a robust workflow for CFD modelling of wind effects for long-span bridge design and bridge operation was identified. Hence, a workflow using open-source software was proposed, which can be conveniently adopted to investigate bridge aerodynamics in bridge engineering practice. A general guidance was also formed where examples were provided to demonstrate specific features. A group of three-dimensional (3D) Reynolds-Averaged Navier-Stokes (RANS) simulations and Detached Eddy simulations (DESs) were performed on sectional bridge deck models at a scale of 1/50. These simulations replicated wind tunnel tests conducted during the design of the Rose Fitzgerald Kennedy bridge in Ireland. Sensitivity studies of the mesh, domain sizes, and turbulence models were conducted during the development of the CFD model, and showed that these factors have appreciable effects on the results of the CFD simulations. When comparing aerodynamic coefficients calculated by simulations and wind tunnel tests, a general agreement was achieved though some discrepancies were found. Similar levels of discrepancies were witnessed in the literature and was most likely due to the sensor interference during wind tunnel tests. In addition, the effects of secondary structures on the aerodynamic coefficients of bridge decks were investigated and shown to be significant. This emphasized the necessity to include these secondary structures when investigating bridge aerodynamics, while existing studies in this area often neglect them. A group of full-bridge simulations were performed at full scale, which was the first to include boundary conditions mapped from Weather Research and Forecasting (WRF) simulations, a high-precision terrain model, and a full-bridge geometry with all the secondary structures. The pseudo-transient time history of wind velocities determined by CFD simulations achieved an extraordinary agreement field measurement data from sensors at multiple locations on the bridge, which was also unprecedented in this area. Results of these full-bridge simulations are also used to initialise simulations at local regions of bridge deck segments. Validations of these local simulations were completed through comparisons of wind velocities predicted by local simulations, full-bridge simulations, and field measurement data. Aerodynamic forces are calculated from these local simulations and compared with results determined by wind tunnel coefficients with field measurement data, Eurocode equations with field measurement data, and Eurocode equations with estimated wind velocities. Aerodynamic forces predicted by CFD simulations were shown to align with the philosophy of sustainable design. Overall, this thesis provided unprecedented validations for the use of CFD simulations at multiple geometric scales. It demonstrated the great performance of CFD simulations in investigating wind effects under realistic wind conditions, which are often challenging for wind tunnel tests to incorporate. The outcome of this thesis is being presented to the NSAI National Committee on revision of the National Annex of the Eurocode on Wind (EN 1991-1-4). But most importantly, great confidence can be drawn from the outcome of this thesis, in using CFD simulations as a robust approach to estimate wind effects on long-span bridges.
11 - PublicationProfile Calculation and Bridge Damage Detection Using Vehicle-based Inertial Readings and the Fleet Monitoring Concept(University College Dublin. School of Civil Engineering, 2022)The aim of this research is to use inertial vehicle sensor data to determine road and rail profiles and to monitor bridge condition. A novel fleet monitoring concept is developed to determine profiles and detect bridge damage using a fleet of instrumented vehicles. To improve the robustness of the calculation, a Bayesian updating method is used. To calculate the profile from vehicle response, a novel Inverse Newmark-Beta method is developed. Newmark-Beta allows vehicle acceleration to be calculated in response to an excitation such as a surface profile. Inverse Newmark-Beta finds the excitation corresponding to a known acceleration. For a single vehicle, the profile can be found if the vehicle properties are known. However, for a single vehicle, acceleration by itself is not enough to determine both profile and vehicle properties. Fortunately, a fleet of vehicles provides additional information that can be used to address this problem. To solve the fleet monitoring problem, the Inverse Newmark-Beta method is combined with the Cross Entropy (CE) optimisation method. Here, the road profile is calculated using accelerations from multiple vehicles, without prior knowledge of the vehicle properties. Sprung mass and half-car models are used to represent the vehicle and test this method separately. Numerical results show that the calculated profiles are the same as the ‘true’ profiles. The absolute values of the vehicle properties are not obtained but this algorithm can determine the relative values. Noise added to the accelerations has an influence on the calculated results. The fleet monitoring concept is used again to determine a flexible railway profile. The ‘apparent profile’(AP) of the railway track is defined as the true surface profile plus components of track deflection. Again, the Inverse Newmark-Beta method and CE optimisation are used together to solve this problem. Here, the train is simulated as a 4-axle carriage model and the railway track is represented by a beam supported on spaced sprung masses. The calculated AP of railway track is found to be very close to the true one. Since the previous method is sensitive to noise, the fleet monitoring concept is also solved using a Bayesian Updating method. The road profile is again determined using vehicle measurements. The calculated road profile is close to the true profile and is insensitive to noise in the simulated measurements. In addition, it can determine the relative vehicle properties at the same time. A 3-D ‘carpet’ road profile is also tested and shows good results. This thesis goes on to use similar principles of fleet monitoring to assess bridge condition. Firstly, a novel method is proposed to calculate the moving reference influence line (MR-IL), i.e., the deflection due to a moving (static) unit load at the (moving) location of that load. The results show that the MR-IL can indicate the condition of a bridge. The AP of a railway bridge is used to calculate the MR-IL. This numerical approach is assessed using a blind test operated by an independent research group. In the blind test, a frame structure is used to model the railway bridge and different levels of global damage are simulated. Using a 4-axle train carriage model, the damage levels of the bridge are inferred accurately. When a half car model is used to represent the train bogie, damage levels can be found again with less accuracy. The bridge damage is then detected using the Bayesian Updating method, with drive-by data. For local damage, the second moments of area of each segment of the bridge is updated as data becomes available. It is shown in simulations that estimates of the bridge second moments of area can be found even with local damage. The vehicle mass can be calculated. Bridge bearing damage is also simulated in this section. Using the Bayesian method, the value of bearing rotational spring stiffness, bridge second moments of area and vehicle masses can be calculated.
10 - PublicationUsing Computational Fluid Dynamics to Model and Predict Sediment Dynamics and Scour In the Irish Sea(University College Dublin. School of Civil Engineering, 2022)Ireland’s expansive marine resources have the potential to provide significant economic growth through the development of critical infrastructure such as offshore renewable energy installations. However, seabed hydrodynamics, morphodynamics, sediment mobility and, in particular, scour (the process of seabed erosion due to shear stresses generated by currents/waves) represent significant geological risks to the stability of such infrastructure from an environmental and engineering perspective. Such infrastructure can introduce seafloor obstacles that perturb the local environment inducing scour that can cause structural instability, or deposition resulting in the burying of structures. Understanding the processes that drive these complex patterns of sediment erosion and deposition over varying timescales is critical to the sustainable development of critical offshore infrastructure. Traditionally, assessments for such issues have utilised time-lapse bathymetric surveys and scaled physical testing. The former fails to capture the nuance of these processes between data collection surveys and cannot predict how the seabed will react to an obstacle, whilst the latter is costly and limited in recreating the marine environment. Predicting scour can be difficult due to vagaries about hydrodynamic conditions. Computational Fluid Dynamics (CFD) is an advanced modelling technique that solves problems of fluid flow and offers an effective means of investigating the complex interaction between hydrodynamics and manmade objects on the seafloor. Similarly, shipwrecks offer natural laboratories with which to validate models using CFD approaches. In this thesis, CFD simulations are generated for a high-resolution bathymetric survey dataset of two shipwreck sites and assessed for application in future scour prediction studies. Shipwrecks offer novel in-situ features with which to test theories of hydrodynamics and sediment transport around seabed objects, with CFD modelling offering a robust tool to do so. The aim of this thesis is to develop a CFD model at a shipwreck site in order to simulate current flow patterns and magnitudes with which to better understand seabed morphological patterns of sediment erosion and deposition caused by the wreck’s obstruction. When combined with other high-resolution seabed survey data, these outputs and understandings could potentially be applied to other critical offshore engineering as part of a robust methodology to assess the impacts of sediment dynamics and prevent scour and other adverse impacts. Modelled outputs for current flow and stress patterns correspond well with known seabed signatures for sediment erosion and deposition from survey data. The outputs from this approach can also be used in conjunction with repeat and physical (i.e. grab sample) survey data in order to understand temporal sediment dynamics and morphological change at a localised level. Ultimately, this approach can be adapted and applied to other man-made structures (such as offshore wind turbine foundation structures) on the seabed as part of engineering design studies to mitigate against the risk of scour causing instability.
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