Parameter estimation in a growth model for a biological population

The motivating problem concerns the estimation of the growth curve of solitary corals that follow the nonlinear Von Bertalanffy Growth Function (VBGF). The most common parameterization of the VBGF for corals is based on two parameters: the ultimate length L∞ and the growth rate k. One aim was to find a more reliable method for estimating these parameters, which can capture the influence of environmental covariates. The main issue with current methods is that they force the linearization of VBGF and neglect intra-individual variability. The idea was to use the hierarchical nonlinear model which has the appealing features of taking into account the influence of collection sites, possible intra-site measurement correlation and variance heterogeneity, and that can handle the influence of environmental factors and all the reliable information that might influence coral growth. This method was used on two databases of different solitary corals i.e. Balanophyllia europaea and Leptopsammia pruvoti, collected in six different sites in different environmental conditions, which introduced a decisive improvement in the results. Nevertheless, the theory of the energy balance in growth ascertains the linear correlation of the two parameters and the independence of the ultimate length L∞ from the influence of environmental covariates, so a further aim of the thesis was to propose a new parameterization based on the ultimate length and parameter c which explicitly describes the part of growth ascribable to site-specific conditions such as environmental factors. We explored the possibility of estimating these parameters characterizing the VBGF new parameterization via the nonlinear hierarchical model. Again there was a general improvement with respect to traditional methods. The results of the two parameterizations were similar, although a very slight improvement was observed in the new one. This is, nevertheless, more suitable from a theoretical point of view when considering environmental covariates.

Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

Modelling and Design of Advanced Reliable Circuits and Devices for Energy Efficiency

Reliable electronic systems, namely a set of reliable electronic devices connected to each other and working correctly together for the same functionality, represent an essential ingredient for the large-scale commercial implementation of any technological advancement. Microelectronics technologies and new powerful integrated circuits provide noticeable improvements in performance and cost-effectiveness, and allow introducing electronic systems in increasingly diversified contexts. On the other hand, opening of new fields of application leads to new, unexplored reliability issues. The development of semiconductor device and electrical models (such as the well known SPICE models) able to describe the electrical behavior of devices and circuits, is a useful means to simulate and analyze the functionality of new electronic architectures and new technologies. Moreover, it represents an effective way to point out the reliability issues due to the employment of advanced electronic systems in new application contexts. In this thesis modeling and design of both advanced reliable circuits for general-purpose applications and devices for energy efficiency are considered. More in details, the following activities have been carried out: first, reliability issues in terms of security of standard communication protocols in wireless sensor networks are discussed. A new communication protocol is introduced, allows increasing the network security. Second, a novel scheme for the on-die measurement of either clock jitter or process parameter variations is proposed. The developed scheme can be used for an evaluation of both jitter and process parameter variations at low costs. Then, reliability issues in the field of “energy scavenging systems” have been analyzed. An accurate analysis and modeling of the effects of faults affecting circuit for energy harvesting from mechanical vibrations is performed. Finally, the problem of modeling the electrical and thermal behavior of photovoltaic (PV) cells under hot-spot condition is addressed with the development of an electrical and thermal model.

Model predictive control in thermal management of multiprocessor systems-on-chip

MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks

Quantum dot-dye hybrid systems for energy transfer applications

In this thesis, we focus on the preparation of energy transfer-based quantum dot (QD)-dye hybrid systems. Two kinds of QD-dye hybrid systems have been successfully synthesized: QD-silica-dye and QD-dye hybrid systems.rn rnIn the QD-silica-dye hybrid system, multishell CdSe/CdS/ZnS QDs were adsorbed onto monodisperse Stöber silica particles with an outer silica shell of thickness 2 - 24 nm containing organic dye molecules (Texas Red). The thickness of this dye layer has a strong effect on the total sensitized acceptor emission, which is explained by the increase in the number of dye molecules homogeneously distributed within the silica shell, in combination with an enhanced surface adsorption of QDs with increasing dye amount. Our conclusions were underlined by comparison of the experimental results with Monte-Carlo simulations, and by control experiments confirming attractive interactions between QDs and Texas Red freely dissolved in solution. rnrnNew QD-dye hybrid system consisting of multishell QDs and organic perylene dyes have been synthesized. We developed a versatile approach to assemble extraordinarily stable QD-dye hybrids, which uses dicarboxylate anchors to bind rylene dyes to QD. This system yields a good basis to study the energy transfer between QD and dye because of its simple and compact design: there is no third kind of molecule linking QD and dye; no spacer; and the affinity of the functional group to the QD surface is strong. The FRET signal was measured for these complexes as a function of both dye to QD ratio and center-to-center distance between QD and dye by controlling number of covered ZnS layers. Data showed that fluorescence resonance energy transfer (FRET) was the dominant mechanism of the energy transfer in our QD-dye hybrid system. FRET efficiency can be controlled by not only adjusting the number of dyes on the QD surface or the QD to dye distance, but also properly choosing different dye and QD components. Due to the strong stability, our QD-dye complexes can also be easily transferred into water. Our approach can apply to not only dye molecules but also other organic molecules. As an example, the QDs have been complexed with calixarene molecules and the QD-calixarene complexes also have potential for QD-based energy transfer study. rn

The electron antineutrino angular correlation coefficient a in free neutron decay: Testing the standard model with the aSPECT-spectrometer

The beta-decay of free neutrons is a strongly over-determined process in the Standard Model (SM) of Particle Physics and is described by a multitude of observables. Some of those observables are sensitive to physics beyond the SM. For example, the correlation coefficients of the involved particles belong to them. The spectrometer aSPECT was designed to measure precisely the shape of the proton energy spectrum and to extract from it the electron anti-neutrino angular correlation coefficient "a". A first test period (2005/ 2006) showed the “proof-of-principles”. The limiting influence of uncontrollable background conditions in the spectrometer made it impossible to extract a reliable value for the coefficient "a" (publication: Baessler et al., 2008, Europhys. Journ. A, 38, p.17-26). A second measurement cycle (2007/ 2008) aimed to under-run the relative accuracy of previous experiments (Stratowa et al. (1978), Byrne et al. (2002)) da/a =5%. I performed the analysis of the data taken there which is the emphasis of this doctoral thesis. A central point are background studies. The systematic impact of background on a was reduced to da/a(syst.)=0.61 %. The statistical accuracy of the analyzed measurements is da/a(stat.)=1.4 %. Besides, saturation effects of the detector electronics were investigated which were initially observed. These turned out not to be correctable on a sufficient level. An applicable idea how to avoid the saturation effects will be discussed in the last chapter.

Properties of cosmic voids in dark energy simulations

The last decade has witnessed the establishment of a Standard Cosmological Model, which is based on two fundamental assumptions: the first one is the existence of a new non relativistic kind of particles, i. e. the Dark Matter (DM) that provides the potential wells in which structures create, while the second one is presence of the Dark Energy (DE), the simplest form of which is represented by the Cosmological Constant Λ, that sources the acceleration in the expansion of our Universe. These two features are summarized by the acronym ΛCDM, which is an abbreviation used to refer to the present Standard Cosmological Model. Although the Standard Cosmological Model shows a remarkably successful agreement with most of the available observations, it presents some longstanding unsolved problems. A possible way to solve these problems is represented by the introduction of a dynamical Dark Energy, in the form of the scalar field ϕ. In the coupled DE models, the scalar field ϕ features a direct interaction with matter in different regimes. Cosmic voids are large under-dense regions in the Universe devoided of matter. Being nearby empty of matter their dynamics is supposed to be dominated by DE, to the nature of which the properties of cosmic voids should be very sensitive. This thesis work is devoted to the statistical and geometrical analysis of cosmic voids in large N-body simulations of structure formation in the context of alternative competing cosmological models. In particular we used the ZOBOV code (see ref. Neyrinck 2008), a publicly available void finder algorithm, to identify voids in the Halos catalogues extraxted from CoDECS simulations (see ref. Baldi 2012 ). The CoDECS are the largest N-body simulations to date of interacting Dark Energy (DE) models. We identify suitable criteria to produce voids catalogues with the aim of comparing the properties of these objects in interacting DE scenarios to the standard ΛCDM model, at different redshifts. This thesis work is organized as follows: in chapter 1, the Standard Cosmological Model as well as the main properties of cosmic voids are intro- duced. In chapter 2, we will present the scalar field scenario. In chapter 3 the tools, the methods and the criteria by which a voids catalogue is created are described while in chapter 4 we discuss the statistical properties of cosmic voids included in our catalogues. In chapter 5 the geometrical properties of the catalogued cosmic voids are presented by means of their stacked profiles. In chapter 6 we summarized our results and we propose further developments of this work.

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.

Investigation of the lithium ion mobility in cyclic model compounds and their ion conducting properties

Efficient energy storage and conversion is playing a key role in overcoming the present and future challenges in energy supply. Batteries provide portable, electrochemical storage of green energy sources and potentially allow for a reduction of the dependence on fossil fuels, which is of great importance with respect to the issue of global warming. In view of both, energy density and energy drain, rechargeable lithium ion batteries outperform other present accumulator systems. However, despite great efforts over the last decades, the ideal electrolyte in terms of key characteristics such as capacity, cycle life, and most important reliable safety, has not yet been identified. rnrnSteps ahead in lithium ion battery technology require a fundamental understanding of lithium ion transport, salt association, and ion solvation within the electrolyte. Indeed, well-defined model compounds allow for systematic studies of molecular ion transport. Thus, in the present work, based on the concept of ‘immobilizing’ ion solvents, three main series with a cyclotriphosphazene (CTP), hexaphenylbenzene (HBP), and tetramethylcyclotetrasiloxane (TMS) scaffold were prepared. Lithium ion solvents, among others ethylene carbonate (EC), which has proven to fulfill together with pro-pylene carbonate safety and market concerns in commercial lithium ion batteries, were attached to the different cores via alkyl spacers of variable length.rnrnAll model compounds were fully characterized, pure and thermally stable up to at least 235 °C, covering the requested broad range of glass transition temperatures from -78.1 °C up to +6.2 °C. While the CTP models tend to rearrange at elevated temperatures over time, which questions the general stability of alkoxide related (poly)phosphazenes, both, the HPB and CTP based models show no evidence of core stacking. In particular the CTP derivatives represent good solvents for various lithium salts, exhibiting no significant differences in the ionic conductivity σ_dc and thus indicating comparable salt dissociation and rather independent motion of cations and ions.rnrnIn general, temperature-dependent bulk ionic conductivities investigated via impedance spectroscopy follow a William-Landel-Ferry (WLF) type behavior. Modifications of the alkyl spacer length were shown to influence ionic conductivities only in combination to changes in glass transition temperatures. Though the glass transition temperatures of the blends are low, their conductivities are only in the range of typical polymer electrolytes. The highest σ_dc obtained at ambient temperatures was 6.0 x 10-6 S•cm-1, strongly suggesting a rather tight coordination of the lithium ions to the solvating 2-oxo-1,3-dioxolane moieties, supported by the increased σ_dc values for the oligo(ethylene oxide) based analogues.rnrnFurther insights into the mechanism of lithium ion dynamics were derived from 7Li and 13C Solid- State NMR investigations. While localized ion motion was probed by i.e. 7Li spin-lattice relaxation measurements with apparent activation energies E_a of 20 to 40 kJ/mol, long-range macroscopic transport was monitored by Pulsed-Field Gradient (PFG) NMR, providing an E_a of 61 kJ/mol. The latter is in good agreement with the values determined from bulk conductivity data, indicating the major contribution of ion transport was only detected by PFG NMR. However, the μm-diffusion is rather slow, emphasizing the strong lithium coordination to the carbonyl oxygens, which hampers sufficient ion conductivities and suggests exploring ‘softer’ solvating moieties in future electrolytes.rn

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.