Analys av ett mikronät vid Ihushi Development Center i Tanzania

Denna studie omfattar en undersökning om hur ett hybridnät har fungerat, i detta fall Ihushi Development Center som ligger I Tanzania. De mätningar som har gjorts, har följt en standard för att kunna universellt användas vid en fortsatt studie eller direkt kunna användas för att jämföras med andra hybridnät med liknande uppsättning och förutsättningar. Under arbetets gång så har en ny modell tagits fram för att smidigt kunna analysera rådata och uträkning av de nödvändiga parametrarna. Detta underlättar även kommande arbeten kring detta hybridnät. Det har också blivit en typ av simulering då det har funnits många olika typer av utspridda och kontinuerliga fel som har behövts hanteras. Dessa värden har då behövts uppskattats utifrån olika källor och metoder, för att sedan användas. Det har sedan räknats ut effektiviteter och prestanda på olika delar i systemet som sedan kommenteras och kan direkt användas för en utvärdering i en framtida studie. Dessa resultat har bitvis jämförts med tidigare utvärdering men då det saknats information från föregående rapport så har en fullständig jämförelse och slutsats inte varit möjlig.

Contribution to the diffuse radiation modelling in Évora, Portugal

Solar radiation data is crucial for the design of energy systems based on the solar resource. Since diffuse radiation measurements are not always available in the archive data series, either due to the inexistence of measuring equipment, shading device misplacement or missing data, models to generate these data are needed. In this work, one year of hourly and daily horizontal solar global and diffuse irradiation measurements in Évora are used to establish a new relation between the diffuse radiation and the clearness index. The proposed model includes a fitting parameter, which was adjusted through a simple optimization procedure to minimize the Least Square Error as compared to measurements. A comparison against several other fitting models presented in the literature was also carried out using the Root Mean Square Error as statistical indicator, and it was found that the present model is more accurate than the previous fitting models for the diffuse radiation data in Évora.

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Search for squarks and gluinos in events with jets and missing transverse energy using 2.1 fb(-1) of p(p)over-bar collision data at root s=1.96 TeV - D phi Collaboration

A data sample corresponding to an integrated luminosity of 2.1 fb(-1) collected by the D phi detector at the Fermilab Tevatron Collider was analyzed to search for squarks and gluinos produced in p (p) over bar collisions at a center-of-mass energy of 1.96 TeV. No evidence for the production of such particles was observed in topologies involving jets and missing transverse energy, and 95% C.L. lower limits of 379 GeV and 308 GeV were set on the squark and gluino masses, respectively, within the framework of minimal supergravity with tan beta = 3, A(0) = 0, and mu < 0. The corresponding previous limits are improved by 54 GeV and 67 GeV. (c) 2008 Elsevier B.V. All rights reserved.

Performance of the CMS missing transverse momentum reconstruction in pp data at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)