Modelling coupled physical-biogeochemical processes in ice-covered oceans

The last decades have seen a large effort of the scientific community to study and understand the physics of sea ice. We currently have a wide - even though still not exhaustive - knowledge of the sea ice dynamics and thermodynamics and of their temporal and spatial variability. Sea ice biogeochemistry is instead largely unknown. Sea ice algae production may account for up to 25% of overall primary production in ice-covered waters of the Southern Ocean. However, the influence of physical factors, such as the location of ice formation, the role of snow cover and light availability on sea ice primary production is poorly understood. There are only sparse localized observations and little knowledge of the functioning of sea ice biogeochemistry at larger scales. Modelling becomes then an auxiliary tool to help qualifying and quantifying the role of sea ice biogeochemistry in the ocean dynamics. In this thesis, a novel approach is used for the modelling and coupling of sea ice biogeochemistry - and in particular its primary production - to sea ice physics. Previous attempts were based on the coupling of rather complex sea ice physical models to empirical or relatively simple biological or biogeochemical models. The focus is moved here to a more biologically-oriented point of view. A simple, however comprehensive, physical model of the sea ice thermodynamics (ESIM) was developed and coupled to a novel sea ice implementation (BFM-SI) of the Biogeochemical Flux Model (BFM). The BFM is a comprehensive model, largely used and validated in the open ocean environment and in regional seas. The physical model has been developed having in mind the biogeochemical properties of sea ice and the physical inputs required to model sea ice biogeochemistry. The central concept of the coupling is the modelling of the Biologically-Active-Layer (BAL), which is the time-varying fraction of sea ice that is continuously connected to the ocean via brines pockets and channels and it acts as rich habitat for many microorganisms. The physical model provides the key physical properties of the BAL (e.g., brines volume, temperature and salinity), and the BFM-SI simulates the physiological and ecological response of the biological community to the physical enviroment. The new biogeochemical model is also coupled to the pelagic BFM through the exchange of organic and inorganic matter at the boundaries between the two systems . This is done by computing the entrapment of matter and gases when sea ice grows and release to the ocean when sea ice melts to ensure mass conservation. The model was tested in different ice-covered regions of the world ocean to test the generality of the parameterizations. The focus was particularly on the regions of landfast ice, where primary production is generally large. The implementation of the BFM in sea ice and the coupling structure in General Circulation Models will add a new component to the latters (and in general to Earth System Models), which will be able to provide adequate estimate of the role and importance of sea ice biogeochemistry in the global carbon cycle.

An equilibrium approach to modelling social interaction

The aim of this work is to put forward a statistical mechanics theory of social interaction, generalizing econometric discrete choice models. After showing the formal equivalence linking econometric multinomial logit models to equilibrium statical mechanics, a multi- population generalization of the Curie-Weiss model for ferromagnets is considered as a starting point in developing a model capable of describing sudden shifts in aggregate human behaviour. Existence of the thermodynamic limit for the model is shown by an asymptotic sub-additivity method and factorization of correlation functions is proved almost everywhere. The exact solution for the model is provided in the thermodynamical limit by nding converging upper and lower bounds for the system's pressure, and the solution is used to prove an analytic result regarding the number of possible equilibrium states of a two-population system. The work stresses the importance of linking regimes predicted by the model to real phenomena, and to this end it proposes two possible procedures to estimate the model's parameters starting from micro-level data. These are applied to three case studies based on census type data: though these studies are found to be ultimately inconclusive on an empirical level, considerations are drawn that encourage further refinements of the chosen modelling approach, to be considered in future work.

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

Slope stability analysis by multi-temporal DEMs and 3D modelling: The 2002 and 2007 Stromboli landslide events

Natural hazard related to the volcanic activity represents a potential risk factor, particularly in the vicinity of human settlements. Besides to the risk related to the explosive and effusive activity, the instability of volcanic edifices may develop into large landslides often catastrophically destructive, as shown by the collapse of the northern flank of Mount St. Helens in 1980. A combined approach was applied to analyse slope failures that occurred at Stromboli volcano. SdF slope stability was evaluated by using high-resolution multi-temporal DTMMs and performing limit equilibrium stability analyses. High-resolution topographical data collected with remote sensing techniques and three-dimensional slope stability analysis play a key role in understanding instability mechanism and the related risks. Analyses carried out on the 2002–2003 and 2007 Stromboli eruptions, starting from high-resolution data acquired through airborne remote sensing surveys, permitted the estimation of the lava volumes emplaced on the SdF slope and contributed to the investigation of the link between magma emission and slope instabilities. Limit Equilibrium analyses were performed on the 2001 and 2007 3D models, in order to simulate the slope behavior before 2002-2003 landslide event and after the 2007 eruption. Stability analyses were conducted to understand the mechanisms that controlled the slope deformations which occurred shortly after the 2007 eruption onset, involving the upper part of slope. Limit equilibrium analyses applied to both cases yielded results which are congruent with observations and monitoring data. The results presented in this work undoubtedly indicate that hazard assessment for the island of Stromboli should take into account the fact that a new magma intrusion could lead to further destabilisation of the slope, which may be more significant than the one recently observed because it will affect an already disarranged deposit and fractured and loosened crater area. The two-pronged approach based on the analysis of 3D multi-temporal mapping datasets and on the application of LE methods contributed to better understanding volcano flank behaviour and to be prepared to undertake actions aimed at risk mitigation.

Fluid dynamic analysis and modelling of industrial chemical equipment

The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.

Electrothermal characterization and nonlinear modelling of GaN transistors for telecommunication circuit design

This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

New mechanisms for modelling the motion of the human ankle complex

The relevance of human joint models was shown in the literature. In particular, the great importance of models for the joint passive motion simulation (i.e. motion under virtually unloaded conditions) was outlined. They clarify the role played by the principal anatomical structures of the articulation, enhancing the comprehension of surgical treatments, and in particular the design of total ankle replacement and ligament reconstruction. Equivalent rigid link mechanisms proved to be an efficient tool for an accurate simulation of the joint passive motion. This thesis focuses on the ankle complex (i.e. the anatomical structure composed of the tibiotalar and the subtalar joints), which has a considerable role in human locomotion. The lack of interpreting models of this articulation and the poor results of total ankle replacement arthroplasty have strongly suggested devising new mathematical models capable of reproducing the restraining function of each structure of the joint and of replicating the relative motion of the bones which constitute the joint itself. In this contest, novel equivalent mechanisms are proposed for modelling the ankle passive motion. Their geometry is based on the joint’s anatomical structures. In particular, the role of the main ligaments of the articulation is investigated under passive conditions by means of nine 5-5 fully parallel mechanisms. Based on this investigation, a one-DOF spatial mechanism is developed for modelling the passive motion of the lower leg. The model considers many passive structures constituting the articulation, overcoming the limitations of previous models which took into account few anatomical elements of the ankle complex. All the models have been identified from experimental data by means of optimization procedure. Then, the simulated motions have been compared to the experimental one, in order to show the efficiency of the approach and thus to deduce the role of each anatomical structure in the ankle kinematic behavior.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

Nonlinear Characterization and Modelling of GaN HEMTs for Microwave Power Amplifier Applications

Semiconductors technologies are rapidly evolving driven by the need for higher performance demanded by applications. Thanks to the numerous advantages that it offers, gallium nitride (GaN) is quickly becoming the technology of reference in the field of power amplification at high frequency. The RF power density of AlGaN/GaN HEMTs (High Electron Mobility Transistor) is an order of magnitude higher than the one of gallium arsenide (GaAs) transistors. The first demonstration of GaN devices dates back only to 1993. Although over the past few years some commercial products have started to be available, the development of a new technology is a long process. The technology of AlGaN/GaN HEMT is not yet fully mature, some issues related to dispersive phenomena and also to reliability are still present. Dispersive phenomena, also referred as long-term memory effects, have a detrimental impact on RF performances and are due both to the presence of traps in the device structure and to self-heating effects. A better understanding of these problems is needed to further improve the obtainable performances. Moreover, new models of devices that take into consideration these effects are necessary for accurate circuit designs. New characterization techniques are thus needed both to gain insight into these problems and improve the technology and to develop more accurate device models. This thesis presents the research conducted on the development of new charac- terization and modelling methodologies for GaN-based devices and on the use of this technology for high frequency power amplifier applications.

Maternal Smoking Impact on the Delivery Cost: a population-based study in the Emilia-Romagna region

This doctoral thesis is devoted to the study of the causal effects of the maternal smoking on the delivery cost. The interest of economic consequences of smoking in pregnancy have been studied fairly extensively in the USA, and very little is known in European context. To identify the causal relation between different maternal smoking status and the delivery cost in the Emilia-Romagna region two distinct methods were used. The first - geometric multidimensional - is mainly based on the multivariate approach and involves computing and testing the global imbalance, classifying cases in order to generate well-matched comparison groups, and then computing treatment effects. The second - structural modelling - refers to a general methodological account of model-building and model-testing. The main idea of this approach is to decompose the global mechanism into sub-mechanisms though a recursive decomposition of a multivariate distribution.

Advanced modelling of time domain electromagnetic data with updated hydrogeological interpretations

Several countries have acquired, over the past decades, large amounts of area covering Airborne Electromagnetic data. Contribution of airborne geophysics has dramatically increased for both groundwater resource mapping and management proving how those systems are appropriate for large-scale and efficient groundwater surveying. We start with processing and inversion of two AEM dataset from two different systems collected over the Spiritwood Valley Aquifer area, Manitoba, Canada respectively, the AeroTEM III (commissioned by the Geological Survey of Canada in 2010) and the “Full waveform VTEM” dataset, collected and tested over the same survey area, during the fall 2011. We demonstrate that in the presence of multiple datasets, either AEM and ground data, due processing, inversion, post-processing, data integration and data calibration is the proper approach capable of providing reliable and consistent resistivity models. Our approach can be of interest to many end users, ranging from Geological Surveys, Universities to Private Companies, which are often proprietary of large geophysical databases to be interpreted for geological and\or hydrogeological purposes. In this study we deeply investigate the role of integration of several complimentary types of geophysical data collected over the same survey area. We show that data integration can improve inversions, reduce ambiguity and deliver high resolution results. We further attempt to use the final, most reliable output resistivity models as a solid basis for building a knowledge-driven 3D geological voxel-based model. A voxel approach allows a quantitative understanding of the hydrogeological setting of the area, and it can be further used to estimate the aquifers volumes (i.e. potential amount of groundwater resources) as well as hydrogeological flow model prediction. In addition, we investigated the impact of an AEM dataset towards hydrogeological mapping and 3D hydrogeological modeling, comparing it to having only a ground based TEM dataset and\or to having only boreholes data.

Techniques for Lagrangian modelling of dispersion in geophysical flows

Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.

Analysis and modelling of the performance of technologies for flue gas treatment in Waste-to-Energy processes

Waste management represents an important issue in our society and Waste-to-Energy incineration plants have been playing a significant role in the last decades, showing an increased importance in Europe. One of the main issues posed by waste combustion is the generation of air contaminants. Particular concern is present about acid gases, mainly hydrogen chloride and sulfur oxides, due to their potential impact on the environment and on human health. Therefore, in the present study the main available technological options for flue gas treatment were analyzed, focusing on dry treatment systems, which are increasingly applied in Municipal Solid Wastes (MSW) incinerators. An operational model was proposed to describe and optimize acid gas removal process. It was applied to an existing MSW incineration plant, where acid gases are neutralized in a two-stage dry treatment system. This process is based on the injection of powdered calcium hydroxide and sodium bicarbonate in reactors followed by fabric filters. HCl and SO2 conversions were expressed as a function of reactants flow rates, calculating model parameters from literature and plant data. The implementation in a software for process simulation allowed the identification of optimal operating conditions, taking into account the reactant feed rates, the amount of solid products and the recycle of the sorbent. Alternative configurations of the reference plant were also assessed. The applicability of the operational model was extended developing also a fundamental approach to the issue. A predictive model was developed, describing mass transfer and kinetic phenomena governing the acid gas neutralization with solid sorbents. The rate controlling steps were identified through the reproduction of literature data, allowing the description of acid gas removal in the case study analyzed. A laboratory device was also designed and started up to assess the required model parameters.

Dynamic analysis of the motorcycle chattering behaviour by means of symbolic multibody modelling

Aim of this research is the development and validation of a comprehensive multibody motorcycle model featuring rigid-ring tires, taking into account both slope and roughness of road surfaces. A novel parametrization for the general kinematics of the motorcycle is proposed, using a mixed reference-point and relative-coordinates approach. The resulting description, developed in terms of dependent coordinates, makes it possible to efficiently include rigid-ring kinematics as well as road elevation and slope. The equations of motion for the multibody system are derived symbolically and the constraint equations arising from the dependent-coordinate formulation are handled using a projection technique. Therefore the resulting system of equations can be integrated in time domain using a standard ODE algorithm. The model is validated with respect to maneuvers experimentally measured on the race track, showing consistent results and excellent computational efficiency. More in detail, it is also capable of reproducing the chatter vibration of racing motorcycles. The chatter phenomenon, appearing during high speed cornering maneuvers, consists of a self-excited vertical oscillation of both the front and rear unsprung masses in the range of frequency between 17 and 22 Hz. A critical maneuver is numerically simulated, and a self-excited vibration appears, consistent with the experimentally measured chatter vibration. Finally, the driving mechanism for the self-excitation is highlighted and a physical interpretation is proposed.