Numerical optimization,modeling and system evaluation of a thermophotovoltaic hybrid panel

Photovoltaic (PV) solar panels generally produce electricity in the 6% to 16% efficiency range, the rest being dissipated in thermal losses. To recover this amount, hybrid photovoltaic thermal systems (PVT) have been devised. These are devices that simultaneously convert solar energy into electricity and heat. It is thus interesting to study the PVT system globally from different point of views in order to evaluate advantages and disadvantages of this technology and its possible uses. In particular in Chapter II, the development of the PVT absorber numerical optimization by a genetic algorithm has been carried out analyzing different internal channel profiles in order to find a right compromise between performance and technical and economical feasibility. Therefore in Chapter III ,thanks to a mobile structure built into the university lab, it has been compared experimentally electrical and thermal output power from PVT panels with separated photovoltaic and solar thermal productions. Collecting a lot of experimental data based on different seasonal conditions (ambient temperature,irradiation, wind...),the aim of this mobile structure has been to evaluate average both thermal and electrical increasing and decreasing efficiency values obtained respect to separate productions through the year. In Chapter IV , new PVT and solar thermal equation based models in steady state conditions have been developed by software Dymola that uses Modelica language. This permits ,in a simplified way respect to previous system modelling softwares, to model and evaluate different concepts about PVT panel regarding its structure before prototyping and measuring it. Chapter V concerns instead the definition of PVT boundary conditions into a HVAC system . This was made trough year simulations by software Polysun in order to finally assess the best solar assisted integrated structure thanks to F_save(solar saving energy)factor. Finally, Chapter VI presents the conclusion and the perspectives of this PhD work.

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

Convergence results for stochastic particle systems with social interaction

We consider stochastic individual-based models for social behaviour of groups of animals. In these models the trajectory of each animal is given by a stochastic differential equation with interaction. The social interaction is contained in the drift term of the SDE. We consider a global aggregation force and a short-range repulsion force. The repulsion range and strength gets rescaled with the number of animals N. We show that for N tending to infinity stochastic fluctuations disappear and a smoothed version of the empirical process converges uniformly towards the solution of a nonlinear, nonlocal partial differential equation of advection-reaction-diffusion type. The rescaling of the repulsion in the individual-based model implies that the corresponding term in the limit equation is local while the aggregation term is non-local. Moreover, we discuss the effect of a predator on the system and derive an analogous convergence result. The predator acts as an repulsive force. Different laws of motion for the predator are considered.

MicroRNAs may mediate the down-regulation of neurokinin-1 receptor in chronic bladder pain syndrome

Bladder pain syndrome (BPS) is a clinical syndrome of pelvic pain and urinary urgency-frequency in the absence of a specific cause. Investigating the expression levels of genes involved in the regulation of epithelial permeability, bladder contractility, and inflammation, we show that neurokinin (NK)1 and NK2 tachykinin receptors were significantly down-regulated in BPS patients. Tight junction proteins zona occludens-1, junctional adherins molecule -1, and occludin were similarly down-regulated, implicating increased urothelial permeability, whereas bradykinin B(1) receptor, cannabinoid receptor CB1 and muscarinic receptors M3-M5 were up-regulated. Using cell-based models, we show that prolonged exposure of NK1R to substance P caused a decrease of NK1R mRNA levels and a concomitant increase of regulatory micro(mi)RNAs miR-449b and miR-500. In the biopsies of BPS patients, the same miRNAs were significantly increased, suggesting that BPS promotes an attenuation of NK1R synthesis via activation of specific miRNAs. We confirm this hypothesis by identifying 31 differentially expressed miRNAs in BPS patients and demonstrate a direct correlation between miR-449b, miR-500, miR-328, and miR-320 and a down-regulation of NK1R mRNA and/or protein levels. Our findings further the knowledge of the molecular mechanisms of BPS, and have relevance for other clinical conditions involving the NK1 receptor.

Applying erosion damage mapping to asses and quantify off-site effects of soil erosion in Switzerland

In order to fill existing knowledge gaps in the temporal and spatial distribution of soil erosion, its sources and causes, as well as in relation to its off-site impacts, erosion damage mapping of all visible erosion features was carried out at three study sites in Switzerland. The data illustrate that about one-quarter of the cultivated land was affected by water erosion. Observed mean annual soil loss rates are considered rather low (0.7–2.3 t/ha/y) compared to other European countries. However, substantial losses of >70 t/ha were recorded on individual plots. This paper focuses on the spatial aspects of soil erosion, by observing and comparing the study areas in a 1-year period from October 2005 to October 2006. The analyses illustrate that the sites differ considerably in average soil loss rates, but show similar patterns of off-site effects. In about one-third of the damaged plots an external source of surface runoff upslope contributed to the damage (run-on). Similarly, more than 50 per cent of the soil eroded on arable land deposited downslope on adjacent plots, roads, public/private infrastructure, etc., and 20 per cent of it reached open water bodies. Large amounts of eroded soil which deposit off-site, often related to slope depressions, are considered muddy floods and were frequently observed in Switzerland. Mapping, in conclusion, helps to sheds light on some of the important challenges of today, in particular: to comprehensively assess socioeconomic and ecological off-site effects of soil erosion, to attribute off-site impacts to on-site causes, and to raise awareness of all stakeholders involved, in order to improve ongoing discussions on policy formulation and implementation at the national and international levels.

Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed

The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.

Investigation Of Leucine And Glutamic Acid Properties From The Nanoscale To The Macroscale

Aerosols are known to have important effects on climate, the atmosphere, and human health. The extent of those effects is unknown and largely depend on the interaction of aerosols with water in the atmosphere. Ambient aerosols are complex mixtures of both inorganic and organic compounds. The cloud condensation nuclei (CCN) activities, hygroscopic behavior and particle morphology of a monocarboxylic amino acid (leucine) and a dicarboxylic amino acid (glutamic acid) were investigated. Activation diameters at various supersaturation conditions were experimentally determined and compared with Köhler theoretical values. The theory accounts for both surface tension and the limited solubility of organic compounds. It was discovered that glutamic acid aerosols readily took on water both when relative humidity was less than 100% and when the supersaturation condition was reached, while leucine did not show any water activation at those conditions. Moreover, the study also suggests that Köhler theory describes CCN activity of organic compounds well when only surface tension of the compound is taken into account and complete solubility is assumed. Single parameter ¿ was also computed using both CCN data and hygroscopic growth factor (GF). The results of ¿ range from 0.17 to 0.53 using CCN data and 0.09 to 0.2 using GFs. Finally, the study suggests that during the water-evaporation/particle-nucleation process, crystallization from solution droplets takes place at different locations: for glutamic acid at the particles¿ center and leucine at the particles¿ boundary.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Finite element 3D reconstruction of the pulmonary acinus imaged by synchrotron X-ray tomography

The alveolated structure of the pulmonary acinus plays a vital role in gas exchange function. Three-dimensional (3D) analysis of the parenchymal region is fundamental to understanding this structure-function relationship, but only a limited number of attempts have been conducted in the past because of technical limitations. In this study, we developed a new image processing methodology based on finite element (FE) analysis for accurate 3D structural reconstruction of the gas exchange regions of the lung. Stereologically well characterized rat lung samples (Pediatr Res 53: 72-80, 2003) were imaged using high-resolution synchrotron radiation-based X-ray tomographic microscopy. A stack of 1,024 images (each slice: 1024 x 1024 pixels) with resolution of 1.4 mum(3) per voxel were generated. For the development of FE algorithm, regions of interest (ROI), containing approximately 7.5 million voxels, were further extracted as a working subunit. 3D FEs were created overlaying the voxel map using a grid-based hexahedral algorithm. A proper threshold value for appropriate segmentation was iteratively determined to match the calculated volume density of tissue to the stereologically determined value (Pediatr Res 53: 72-80, 2003). The resulting 3D FEs are ready to be used for 3D structural analysis as well as for subsequent FE computational analyses like fluid dynamics and skeletonization.

Energy and conductance state modeling of power electronic converters for DC microgrids

This document will demonstrate the methodology used to create an energy and conductance based model for power electronic converters. The work is intended to be a replacement for voltage and current based models which have limited applicability to the network nodal equations. Using conductance-based modeling allows direct application of load differential equations to the bus admittance matrix (Y-bus) with a unified approach. When applied directly to the Y-bus, the system becomes much easier to simulate since the state variables do not need to be transformed. The proposed transformation applies to loads, sources, and energy storage systems and is useful for DC microgrids. Transformed state models of a complete microgrid are compared to experimental results and show the models accurately reflect the system dynamic behavior.

EXPLORING CHANGES IN DETRITAL FLOCCULENT LAYER DYNAMICS DUE TO SHIFTS IN MACROPHYTE COMMUNITIES IN THE NORTHERN EVERGLADES

A shift in plant communities of the Water Conservation Areas (WCAs) within the Everglades has been linked to changes in hydrology and high levels of nutrient loading from surrounding agicultural areas. This has resulted in the encroachment of dense cattail stands (Typha domingensis) into areas that had previously been a ridge and slough landscape populated primarily by native sawgrass (Cladium jamaicense). In order to study ecological management solutions in this area, WCA-2A was broken into study plots; several of which became open water areas through the application of herbicide and burning regimens. The open water areas allowed for Chara spp (a submersed algal species) to replace Typha domingensis as the dominant macrophyte. This study investigated the polymer and ionic profiles of Chara spp, Typha domingensis and Cladium jamaicense and their contributions to detrital flocculent (floc) in the study plots where they are the dominant macrophytes. Floc is not only an important food source for aquatic species; it also supports many algal, fungal and bacterial communities. Data gathered in this study indicated that the floc sample from a phosphorus enriched open water study plot (EO1) where Chara spp was the dominant macrophyte may contain cell wall polymers from sources other than Chara spp (most likely Typha domingensis), while the chemical and polymeric profile of the floc of the study plot where Typha domingensis is the dominant macrophyte (EC1) suggests that the floc layer has contributions from algal sources as well as Typha domingensis. Additionally, monoclonal antibodies to Arabinoglalactan protein (AGP) and (1,4)-β-D galactan were identified as possible biomarkers for distinguishing algal dominated floc layers from layers dominated by emergent vegetation. Calcium labeling could be a useful tool for this as well because of the high amount of Ca2+ associated with Chara spp cell walls. When looking into the soluble phosphorus content of the macrophytes and paired floc samples of WCA-2A, it was found that Chara spp may be contributing a greater amount of Ca-bound phosphorus to floc layers where it is the dominant macrophyte when compared to floc layers from study plots dominated by emergent macrophytes. Floc layers also appear to be acting as a nutrient sink for soluble phosphorus. The findings of this study support the overall hypothesis that the shift from native emergent macrophyte communities to submersed macrophyte communities in study sites of the northern Everglades is affecting the polymeric/chemical profile and ionic content of detrital floc layers. The effects of this shift may contribute to changes in complex flocculent community dynamics.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only applications must evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time to changing contexts. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only must applications evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment. How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.

Visualization and stereological characterization of individual rat lung acini by high-resolution X-ray tomographic microscopy

The small trees of gas-exchanging pulmonary airways which are fed by the most distal purely conducting airways are called acini and represent the functional gas-exchanging units. The three-dimensional architecture of the acini has a strong influence on ventilation and particle deposition. Due to the difficulty to identify individual acini on microscopic lung sections the knowledge about the number of acini and their biological parameters like volume, surface area, and number of alveoli per acinus are limited. We developed a method to extract individual acini from lungs imaged by high-resolution synchrotron radiation based X-ray tomographic microscopy and estimated their volume, surface area and number of alveoli. Rat acini were isolated by semiautomatically closing the airways at the transition from conducting to gas-exchanging airways. We estimated a mean internal acinar volume of 1.148mm(3), a mean acinar surface area of 73.9mm(2), and a mean of 8470 alveoli per acinus. Assuming that the acini are similarly sized throughout different regions of the lung, we calculated that a rat lung contains 5470±833 acini. We conclude that our novel approach is well suited for the fast and reliable characterization of a large number of individual acini in healthy, diseased, or transgenic lungs of different species including humans.