Soil-structure interaction during tunnelling in urban area: observations and 3D numerical modelling

This work illustrates a soil-tunnel-structure interaction study performed by an integrated,geotechnical and structural,approach based on 3D finite element analyses and validated against experimental observations.The study aims at analysing the response of reinforced concrete framed buildings on discrete foundations in interaction with metro lines.It refers to the case of the twin tunnels of the Milan (Italy) metro line 5,recently built in coarse grained materials using EPB machines,for which subsidence measurements collected along ground and building sections during tunnelling were available.Settlements measured under freefield conditions are firstly back interpreted using Gaussian empirical predictions. Then,the in situ measurements’ analysis is extended to include the evolving response of a 9 storey reinforced concrete building while being undercrossed by the metro line.In the finite element study,the soil mechanical behaviour is described using an advanced constitutive model. This latter,when combined with a proper simulation of the excavation process, proves to realistically reproduce the subsidence profiles under free field conditions and to capture the interaction phenomena occurring between the twin tunnels during the excavation. Furthermore, when the numerical model is extended to include the building, schematised in a detailed manner, the results are in good agreement with the monitoring data for different stages of the twin tunnelling. Thus, they indirectly confirm the satisfactory performance of the adopted numerical approach which also allows a direct evaluation of the structural response as an outcome of the analysis. Further analyses are also carried out modelling the building with different levels of detail. The results highlight that, in this case, the simplified approach based on the equivalent plate schematisation is inadequate to capture the real tunnelling induced displacement field. The overall behaviour of the system proves to be mainly influenced by the buried portion of the building which plays an essential role in the interaction mechanism, due to its high stiffness.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Modelling the dynamic response of rockfall protection barriers

Mountainous areas are prone to natural hazards like rockfalls. Among the many countermeasures, rockfall protection barriers represent an effective solution to mitigate the risk. They are metallic structures designed to intercept rocks falling from unstable slopes, thus dissipating the energy deriving from the impact. This study aims at providing a better understanding of the response of several rockfall barrier types, through the development of rather sophisticated three-dimensional numerical finite elements models which take into account for the highly dynamic and non-linear conditions of such events. The models are built considering the actual geometrical and mechanical properties of real systems. Particular attention is given to the connecting details between the structural components and to their interactions. The importance of the work lies in being able to support a wide experimental activity with appropriate numerical modelling. The data of several full-scale tests carried out on barrier prototypes, as well as on their structural components, are combined with results of numerical simulations. Though the models are designed with relatively simple solutions in order to obtain a low computational cost of the simulations, they are able to reproduce with great accuracy the test results, thus validating the reliability of the numerical strategy proposed for the design of these structures. The developed models have shown to be readily applied to predict the barrier performance under different possible scenarios, by varying the initial configuration of the structures and/or of the impact conditions. Furthermore, the numerical models enable to optimize the design of these structures and to evaluate the benefit of possible solutions. Finally it is shown they can be also used as a valuable supporting tool for the operators within a rockfall risk assessment procedure, to gain crucial understanding of the performance of existing barriers in working conditions.

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

Computational Modelling of Cardiac Electrophysiology: from Cell to Bedside

Heart diseases are the leading cause of death worldwide, both for men and women. However, the ionic mechanisms underlying many cardiac arrhythmias and genetic disorders are not completely understood, thus leading to a limited efficacy of the current available therapies and leaving many open questions for cardiac electrophysiologists. On the other hand, experimental data availability is still a great issue in this field: most of the experiments are performed in vitro and/or using animal models (e.g. rabbit, dog and mouse), even when the final aim is to better understand the electrical behaviour of in vivo human heart either in physiological or pathological conditions. Computational modelling constitutes a primary tool in cardiac electrophysiology: in silico simulations, based on the available experimental data, may help to understand the electrical properties of the heart and the ionic mechanisms underlying a specific phenomenon. Once validated, mathematical models can be used for making predictions and testing hypotheses, thus suggesting potential therapeutic targets. This PhD thesis aims to apply computational cardiac modelling of human single cell action potential (AP) to three clinical scenarios, in order to gain new insights into the ionic mechanisms involved in the electrophysiological changes observed in vitro and/or in vivo. The first context is blood electrolyte variations, which may occur in patients due to different pathologies and/or therapies. In particular, we focused on extracellular Ca2+ and its effect on the AP duration (APD). The second context is haemodialysis (HD) therapy: in addition to blood electrolyte variations, patients undergo a lot of other different changes during HD, e.g. heart rate, cell volume, pH, and sympatho-vagal balance. The third context is human hypertrophic cardiomyopathy (HCM), a genetic disorder characterised by an increased arrhythmic risk, and still lacking a specific pharmacological treatment.

Process-based modelling of lichens and bryophytes and their role in global biogeochemical cycles

This thesis presents a process-based modelling approach to quantify carbon uptake by lichens and bryophytes at the global scale. Based on the modelled carbon uptake, potential global rates of nitrogen fixation, phosphorus uptake and chemical weathering by the organisms are estimated. In this way, the significance of lichens and bryophytes for global biogeochemical cycles can be assessed. The model uses gridded climate data and key properties of the habitat (e.g. disturbance intervals) to predict processes which control net carbon uptake, namely photosynthesis, respiration, water uptake and evaporation. It relies on equations used in many dynamical vegetation models, which are combined with concepts specific to lichens and bryophytes, such as poikilohydry or the effect of water content on CO2 diffusivity. To incorporate the great functional variation of lichens and bryophytes at the global scale, the model parameters are characterised by broad ranges of possible values instead of a single, globally uniform value. The predicted terrestrial net uptake of 0.34 to 3.3 Gt / yr of carbon and global patterns of productivity are in accordance with empirically-derived estimates. Based on the simulated estimates of net carbon uptake, further impacts of lichens and bryophytes on biogeochemical cycles are quantified at the global scale. Thereby the focus is on three processes, namely nitrogen fixation, phosphorus uptake and chemical weathering. The presented estimates have the form of potential rates, which means that the amount of nitrogen and phosphorus is quantified which is needed by the organisms to build up biomass, also accounting for resorption and leaching of nutrients. Subsequently, the potential phosphorus uptake on bare ground is used to estimate chemical weathering by the organisms, assuming that they release weathering agents to obtain phosphorus. The predicted requirement for nitrogen ranges from 3.5 to 34 Tg / yr and for phosphorus it ranges from 0.46 to 4.6 Tg / yr. Estimates of chemical weathering are between 0.058 and 1.1 km³ / yr of rock. These values seem to have a realistic order of magnitude and they support the notion that lichens and bryophytes have the potential to play an important role for global biogeochemical cycles.

Experimental characterization and modelling of a servo-pneumatic system for a knee loading apparatus

The new knee test rig developed in University of Bologna used pneumatic cylinder as actuator system. Specific characterization and modelling about the pneumatic cylinder and the related devices are needed in better controlling the test rig. In this thesis, an experimental environment for the related device is set up with data acquisition system using Real-time Windows Target, Simulink, MatLab. Based on the experimental data, a fitted model for the pneumatic cylinder friction is found.

Outdoor production of Isochrysis galbana (T-iso) in industrial scale photobioreactors and modelling of its photosynthesis and respiration rate

Isochrysis galbana is a widely-used strain in aquaculture in spite of its low productivity. To maximize the productivity of processes based on this microalgae strain, a model was developed considering the influence of irradiance, temperature, pH and dissolved oxygen concentration on the photosynthesis and respiration rate. Results demonstrate that this strain tolerates temperatures up to 35ºC but it is highly sensitive to irradiances higher than 500 µE·m-2·s-1 and dissolved oxygen concentrations higher than 11 mg·l-1. With the researcher group of the “Universidad de Almeria”, the developed model was validated using data from an industrial-scale outdoor tubular photobioreactor demonstrating that inadequate temperature and dissolved oxygen concentrations reduce productivity to half that which is maximal, according to light availability under real outdoor conditions. The developed model is a useful tool for managing working processes, especially in the development of new processes based on this strain and to take decisions regarding optimal control strategies. Also the outdoor production of Isochrysis galbana T-iso in industrial size tubular photobioreactors (3.0 m3) has been studied. Experiments were performed modifying the dilution rate and evaluating the biomass productivity and quality, in addition to the overall performance of the system. Results confirmed that T-iso can be produced outdoor at commercial scale in continuous mode, productivities up to 20 g·m-2·day-1 of biomass rich in proteins (45%) and lipids (25%) being obtained. The utilization of this type of photobioreactors allows controlling the contamination and pH of the cultures, but daily variation of solar radiation imposes the existence of inadequate dissolved oxygen concentration and temperature at which the cells are exposed to inside the reactor. Excessive dissolved oxygen reduced the biomass productivity to 68% of maximal, whereas inadequate temperature reduces to 63% of maximal. Thus, optimally controlling these parameters the biomass productivity can be duplicated. These results confirm the potential to produce this valuable strain at commercial scale in optimally designed/operated tubular photobioreactors as a biotechnological industry.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Misleading Population Estimates: Biases and Consistency of Visual Surveys and Matrix Modelling in the Endangered Bearded Vulture

Conservation strategies for long-lived vertebrates require accurate estimates of parameters relative to the populations' size, numbers of non-breeding individuals (the “cryptic” fraction of the population) and the age structure. Frequently, visual survey techniques are used to make these estimates but the accuracy of these approaches is questionable, mainly because of the existence of numerous potential biases. Here we compare data on population trends and age structure in a bearded vulture (Gypaetus barbatus) population from visual surveys performed at supplementary feeding stations with data derived from population matrix-modelling approximations. Our results suggest that visual surveys overestimate the number of immature (<2 years old) birds, whereas subadults (3–5 y.o.) and adults (>6 y.o.) were underestimated in comparison with the predictions of a population model using a stable-age distribution. In addition, we found that visual surveys did not provide conclusive information on true variations in the size of the focal population. Our results suggest that although long-term studies (i.e. population matrix modelling based on capture-recapture procedures) are a more time-consuming method, they provide more reliable and robust estimates of population parameters needed in designing and applying conservation strategies. The findings shown here are likely transferable to the management and conservation of other long-lived vertebrate populations that share similar life-history traits and ecological requirements.

Biogeochemical processes in a clay formation in situ experiment: Part F - Reactive transport modelling

Reactive transport modelling was used to simulate solute transport, thermodynamic reactions, ion exchange and biodegradation in the Porewater Chemistry (PC) experiment at the Mont Terri Rock Laboratory. Simulations show that the most important chemical processes controlling the fluid composition within the borehole and the surrounding formation during the experiment are ion exchange, biodegradation and dissolution/precipitation reactions involving pyrite and carbonate minerals. In contrast, thermodynamic mineral dissolution/precipitation reactions involving alumo-silicate minerals have little impact on the fluid composition on the time-scale of the experiment. With the accurate description of the initial chemical condition in the formation in combination with kinetic formulations describing the different stages of bacterial activities, it has been possible to reproduce the evolution of important system parameters, such as the pH, redox potential, total organic C. dissolved inorganic C and SO(4) concentration. Leaching of glycerol from the pH-electrode may be the primary source of organic material that initiated bacterial growth, which caused the chemical perturbation in the borehole. Results from these simulations are consistent with data from the over-coring and demonstrate that the Opalinus Clay has a high buffering capacity in terms of chemical perturbations caused by bacterial activity. This buffering capacity can be attributed to the carbonate system as well as to the reactivity of clay surfaces.

Resurgence of HIV infection among men who have sex with men in Switzerland: mathematical modelling study

Background New HIV infections in men who have sex with men (MSM) have increased in Switzerland since 2000 despite combination antiretroviral therapy (cART). The objectives of this mathematical modelling study were: to describe the dynamics of the HIV epidemic in MSM in Switzerland using national data; to explore the effects of hypothetical prevention scenarios; and to conduct a multivariate sensitivity analysis. Methodology/Principal Findings The model describes HIV transmission, progression and the effects of cART using differential equations. The model was fitted to Swiss HIV and AIDS surveillance data and twelve unknown parameters were estimated. Predicted numbers of diagnosed HIV infections and AIDS cases fitted the observed data well. By the end of 2010, an estimated 13.5% (95% CI 12.5, 14.6%) of all HIV-infected MSM were undiagnosed and accounted for 81.8% (95% CI 81.1, 82.4%) of new HIV infections. The transmission rate was at its lowest from 1995–1999, with a nadir of 46 incident HIV infections in 1999, but increased from 2000. The estimated number of new infections continued to increase to more than 250 in 2010, although the reproduction number was still below the epidemic threshold. Prevention scenarios included temporary reductions in risk behaviour, annual test and treat, and reduction in risk behaviour to levels observed earlier in the epidemic. These led to predicted reductions in new infections from 2 to 26% by 2020. Parameters related to disease progression and relative infectiousness at different HIV stages had the greatest influence on estimates of the net transmission rate. Conclusions/Significance The model outputs suggest that the increase in HIV transmission amongst MSM in Switzerland is the result of continuing risky sexual behaviour, particularly by those unaware of their infection status. Long term reductions in the incidence of HIV infection in MSM in Switzerland will require increased and sustained uptake of effective interventions.

Risk attribution of Campylobacter infection by age group using exposure modelling

Knowledge on the relative importance of alternative sources of human campylobacteriosis is important in order to implement effective disease prevention measures. The objective of this study was to assess the relative importance of three key exposure pathways (travelling abroad, poultry meat, pet contact) for different patient age groups in Switzerland. With a stochastic exposure model data on Campylobacter incidence for the years 2002-2007 were linked with data for the three exposure pathways and the results of a case-control study. Mean values for the population attributable fractions (PAF) over all age groups and years were 27% (95% CI 17-39) for poultry consumption, 27% (95% CI 22-32) for travelling abroad, 8% (95% CI 6-9) for pet contact and 39% (95% CI 25-50) for other risk factors. This model provided robust results when using data available for Switzerland, but the uncertainties remained high. The output of the model could be improved if more accurate input data are available to estimate the infection rate per exposure. In particular, the relatively high proportion of cases attributed to 'other risk factors' requires further attention.