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.

Cascading events triggering industrial accidents: quantitative assessment of NaTech and domino scenarios

The so called cascading events, which lead to high-impact low-frequency scenarios are rising concern worldwide. A chain of events result in a major industrial accident with dreadful (and often unpredicted) consequences. Cascading events can be the result of the realization of an external threat, like a terrorist attack a natural disaster or of “domino effect”. During domino events the escalation of a primary accident is driven by the propagation of the primary event to nearby units, causing an overall increment of the accident severity and an increment of the risk associated to an industrial installation. Also natural disasters, like intense flooding, hurricanes, earthquake and lightning are found capable to enhance the risk of an industrial area, triggering loss of containment of hazardous materials and in major accidents. The scientific community usually refers to those accidents as “NaTechs”: natural events triggering industrial accidents. In this document, a state of the art of available approaches to the modelling, assessment, prevention and management of domino and NaTech events is described. On the other hand, the relevant work carried out during past studies still needs to be consolidated and completed, in order to be applicable in a real industrial framework. New methodologies, developed during my research activity, aimed at the quantitative assessment of domino and NaTech accidents are presented. The tools and methods provided within this very study had the aim to assist the progress toward a consolidated and universal methodology for the assessment and prevention of cascading events, contributing to enhance safety and sustainability of the chemical and process industry.

Design methods and geometric modelling of scaffolds for bone tissue engineering

Every year, thousand of surgical treatments are performed in order to fix up or completely substitute, where possible, organs or tissues affected by degenerative diseases. Patients with these kind of illnesses stay long times waiting for a donor that could replace, in a short time, the damaged organ or the tissue. The lack of biological alternates, related to conventional surgical treatments as autografts, allografts, e xenografts, led the researchers belonging to different areas to collaborate to find out innovative solutions. This research brought to a new discipline able to merge molecular biology, biomaterial, engineering, biomechanics and, recently, design and architecture knowledges. This discipline is named Tissue Engineering (TE) and it represents a step forward towards the substitutive or regenerative medicine. One of the major challenge of the TE is to design and develop, using a biomimetic approach, an artificial 3D anatomy scaffold, suitable for cells adhesion that are able to proliferate and differentiate themselves as consequence of the biological and biophysical stimulus offered by the specific tissue to be replaced. Nowadays, powerful instruments allow to perform analysis day by day more accurateand defined on patients that need more precise diagnosis and treatments.Starting from patient specific information provided by TC (Computed Tomography) microCT and MRI(Magnetic Resonance Imaging), an image-based approach can be performed in order to reconstruct the site to be replaced. With the aid of the recent Additive Manufacturing techniques that allow to print tridimensional objects with sub millimetric precision, it is now possible to practice an almost complete control of the parametrical characteristics of the scaffold: this is the way to achieve a correct cellular regeneration. In this work, we focalize the attention on a branch of TE known as Bone TE, whose the bone is main subject. Bone TE combines osteoconductive and morphological aspects of the scaffold, whose main properties are pore diameter, structure porosity and interconnectivity. The realization of the ideal values of these parameters represents the main goal of this work: here we'll a create simple and interactive biomimetic design process based on 3D CAD modeling and generative algorithmsthat provide a way to control the main properties and to create a structure morphologically similar to the cancellous bone. Two different typologies of scaffold will be compared: the first is based on Triply Periodic MinimalSurface (T.P.M.S.) whose basic crystalline geometries are nowadays used for Bone TE scaffolding; the second is based on using Voronoi's diagrams and they are more often used in the design of decorations and jewellery for their capacity to decompose and tasselate a volumetric space using an heterogeneous spatial distribution (often frequent in nature). In this work, we will show how to manipulate the main properties (pore diameter, structure porosity and interconnectivity) of the design TE oriented scaffolding using the implementation of generative algorithms: "bringing back the nature to the nature".

Quantitative risk analysis as a tool in process design

La Quantitative Risk Analysis costituisce un valido strumento per la determinazione del rischio associato ad un’installazione industriale e per la successiva attuazione di piani di emergenza. Tuttavia, la sua applicazione nella progettazione di un lay-out richiede la scelta di un criterio in grado di valutare quale sia la disposizione ottimale al fine di minimizzare il rischio. In tal senso, le numerose procedure esistenti, sebbene efficaci, risultano piuttosto faticose e time-consuming. Nel presente lavoro viene dunque proposto un criterio semplice ed oggettivo per comparare i risultati di QRA applicate a differenti designs. Valutando l’area racchiusa nelle curve iso-rischio, vengono confrontate dapprima le metodologie esistenti per lo studio dell’effetto domino, e successivamente, viene applicata al caso di serbatoi in pressione una procedura integrata di Quantitative Risk Domino Assessment. I risultati ottenuti dimostrano chiaramente come sia possibile ridurre notevolmente il rischio di un’attività industriale agendo sulla disposizione delle apparecchiature, con l’obiettivo di limitare gli effetti di possibili scenari accidentali.

Modelling, simulation and optimization of maintenance considerations on condition based maintenance

Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.

Automatic Design of Boolean Networks for Modelling Differentiation Trees

Real living cell is a complex system governed by many process which are not yet fully understood: the process of cell differentiation is one of these. In this thesis work we make use of a cell differentiation model to develop gene regulatory networks (Boolean networks) with desired differentiation dynamics. To accomplish this task we have introduced techniques of automatic design and we have performed experiments using various differentiation trees. The results obtained have shown that the developed algorithms, except the Random algorithm, are able to generate Boolean networks with interesting differentiation dynamics. Moreover, we have presented some possible future applications and developments of the cell differentiation model in robotics and in medical research. Understanding the mechanisms involved in biological cells can gives us the possibility to explain some not yet understood dangerous disease, i.e the cancer. Le cellula è un sistema complesso governato da molti processi ancora non pienamente compresi: il differenziamento cellulare è uno di questi. In questa tesi utilizziamo un modello di differenziamento cellulare per sviluppare reti di regolazione genica (reti Booleane) con dinamiche di differenziamento desiderate. Per svolgere questo compito abbiamo introdotto tecniche di progettazione automatica e abbiamo eseguito esperimenti utilizzando vari alberi di differenziamento. I risultati ottenuti hanno mostrato che gli algoritmi sviluppati, eccetto l'algoritmo Random, sono in grado di poter generare reti Booleane con dinamiche di differenziamento interessanti. Inoltre, abbiamo presentato alcune possibili applicazioni e sviluppi futuri del modello di differenziamento in robotica e nella ricerca medica. Capire i meccanismi alla base del funzionamento cellulare può fornirci la possibilità di spiegare patologie ancora oggi non comprese, come il cancro.

A Bootstrap Test for the Probability of Ruin in the Compound Poisson Risk Process

In this article we propose a bootstrap test for the probability of ruin in the compound Poisson risk process. We adopt the P-value approach, which leads to a more complete assessment of the underlying risk than the probability of ruin alone. We provide second-order accurate P-values for this testing problem and consider both parametric and nonparametric estimators of the individual claim amount distribution. Simulation studies show that the suggested bootstrap P-values are very accurate and outperform their analogues based on the asymptotic normal approximation.

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.

Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study

Background Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. Methods We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT. Results The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes. Conclusions The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.

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.