Multiobjective genetic algorithms applied to heat transfer problems

In the present work, the multi-objective optimization by genetic algorithms is investigated and applied to heat transfer problems. Firstly, the work aims to compare different reproduction processes employed by genetic algorithms and two new promising processes are suggested. Secondly, in this work two heat transfer problems are studied under the multi-objective point of view. Specifically, the two cases studied are the wavy fins and the corrugated wall channel. Both these cases have already been studied by a single objective optimizer. Therefore, this work aims to extend the previous works in a more comprehensive study.

Industrial ecology applied to ELV management. Material and energy recovery from ASR

This PhD thesis reports on car fluff management, recycling and recovery. Car fluff is the residual waste produced by car recycling operations, particularly from hulk shredding. Car fluff is known also as Automotive Shredder Residue (ASR) and it is made of plastics, rubbers, textiles, metals and other materials, and it is very heterogeneous both in its composition and in its particle size. In fact, fines may amount to about 50%, making difficult to sort out recyclable materials or exploit ASR heat value by energy recovery. This 3 years long study started with the definition of the Italian End-of-Life Vehicles (ELVs) recycling state of the art. A national recycling trial revealed Italian recycling rate to be around 81% in 2008, while European Community recycling target are set to 85% by 2015. Consequently, according to Industrial Ecology framework, a life cycle assessment (LCA) has been conducted revealing that sorting and recycling polymers and metals contained in car fluff, followed by recovering residual energy, is the route which has the best environmental perspective. This results led the second year investigation that involved pyrolysis trials on pretreated ASR fractions aimed at investigating which processes could be suitable for an industrial scale ASR treatment plant. Sieving followed by floatation reported good result in thermochemical conversion of polymers with polyolefins giving excellent conversion rate. This factor triggered ecodesign considerations. Ecodesign, together with LCA, is one of the Industrial Ecology pillars and it consists of design for recycling and design for disassembly, both aimed at the improvement of car components dismantling speed and the substitution of non recyclable material. Finally, during the last year, innovative plants and technologies for metals recovery from car fluff have been visited and tested worldwide in order to design a new car fluff treatment plant aimed at ASR energy and material recovery.

The Efficiency of Microcredit Applied to Social Exclusion.

Microcredit has been a tool to alleviate poverty since long. This research is aimed to observe the efficiency of microcredit in the field of social exclusion. The development of questionnaires and use of existing tools was used to observe the tangible and intangible intertwining of microcredit and by doing so the effort was concentrated to observe whether microcredit has a direct effect on social exclusion or not. Bangladesh was chosen for the field study and 85 samples were taken for the analysis. It is a time period research and one year time was set to receive the sample and working on the statistical analysis. The tangible aspect was based on a World Bank questionnaire and the social capital questionnaire was developed through different well observed tools. The borrowers of Grameen Bank in Bangladesh, is the research sample whish shows a strong correlation between their tangible activity and social life. There are significant changes in tangible aspect and social participation observed from the research. Strong correlation between the two aspects was also found taking into account that the borrowers themselves have a vibrant social life in the village.

Generalized Differential Quadrature Finite Element Method applied to Advanced Structural Mechanics

Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

Operational research applied to regional healthcare system

In this thesis we focus on optimization and simulation techniques applied to solve strategic, tactical and operational problems rising in the healthcare sector. At first we present three applications to Emilia-Romagna Public Health System (SSR) developed in collaboration with Agenzia Sanitaria e Sociale dell'Emilia-Romagna (ASSR), a regional center for innovation and improvement in health. Agenzia launched a strategic campaign aimed at introducing Operations Research techniques as decision making tools to support technological and organizational innovations. The three applications focus on forecast and fund allocation of medical specialty positions, breast screening program extension and operating theater planning. The case studies exploit the potential of combinatorial optimization, discrete event simulation and system dynamics techniques to solve resource constrained problem arising within Emilia-Romagna territory. We then present an application in collaboration with Dipartimento di Epidemiologia del Lazio that focuses on population demand of service allocation to regional emergency departments. Finally, a simulation-optimization approach, developed in collaboration with INESC TECH center of Porto, to evaluate matching policies for the kidney exchange problem is discussed.

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.