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Today, banks are the main consumers and generators of credit scores on their customers. This has been further enhanced since 2004, when the Basel Committee1 published a review of the agreement of 1998 to regulate minimum capital requirements: Basel 2. The Web site of the Bank for International Settlements reports that “The changes aimed at rewarding and encouraging continued improvements in risk measurement and control”. One of the major changes on risk measurement involved the insolvency risk, accelerating the development and the adoption of credit scoring methods.

In this work, we propose to extend an efficient strategy for robust optimization when a large number of uncertainties is considered, in order to include multi-criteria decision making tools. This strategy is based on ANOVA analysis for reducing the stochastic dimension and a massive use of metamodels for predicting the sensitivity indexes in the design variables plan. This approach is applied to the optimization under uncertainty of horizontal ground heat exchangers, used in Ground Source Heat Pumps (GSHPs) for heating and cooling of buildings. System efficiency is maximized taking into account several uncertain parameters, such as the heat conductivity of the ground around the tubes, the velocity inside the tubes and the depth of installation.

In the last decades renewable energy production has been growing exponentially. In this sector, electricity generation through wind turbines has become relevant. The aim of research is to enhance efficiency and energy production. In this article, in fact, the optimization analysis of a 3 MW horizontal axis wind turbine (HAWT) blade is presented. The aerodynamic performances are evaluated through an in house BEM code, developed by Airworks s.r.l., which is coupled with modeFrontier® in order to manage incoming data and post process results obtained in an automatic way. Airfoil type, section length, chord and twist distributions have been taken as input parameters. Power coefficient and annual energy production are the output variables used to judge the aerodynamic performance of the resulting blade. Several runs have been done in order to collect information and find the best design for the blade.

In this work an approach is presented for the analysis of the effects of geomet-ric tolerances in fluid dynamic behaviour of manufactured components. The Tensorial-expanded Chaos Collocation method coupled to Fictitious Domain Method has been used to solve Fluid Dynamic problems with geometric uncertainties. The main advantage of the Tensorial-expanded Chaos Collocation method is its non-intrusive formulation, so existing deterministic solvers can be used. The Least-Squares Spectral Element Method has been employed for the analysis of the deterministic differential problems obtained by Tensorial-expanded Chaos Collocation. This algorithm exploits a Fictitious Domain approach, so it is particularly suitable to solve differential problems defined on stochastic domains. The capabilities of the Tensorial-expanded Chaos Collocation method combined to the Ficti-tious Domain-Least- Squares Spectral Element Method are demonstrated by a numerical experiment.

La ricerca riguarda lo studio fluidodinamico del moto dell'aria attraverso un sistema di filtrazione meccanica di sostanze solide in sospensione utilizzato nelle cappe aspiranti delle cucine industriali. Il filtro in esame è ampiamente diffuso sul mercato per via della sua semplice geometria e della praticità d'uso e manutenzione; il dispositivo è costituito da due lamiere di acciaio inossidabile opportunamente tagliate e ripiegate in modo tale da formare dei canali di passaggio per l'aria con dei spostamenti solo lungo due direzioni e per tale motivo definito filtro "a labirinto". Le prestazioni del filtro sono state studiate sia per via numerica tramite l'uso di un software commerciale di termofluidodinamica computazionale, sia sperimentalmente attraverso dei test effettuati nel laboratorio del dipartimento. Nel presente lavoro verranno quindi esposti i modelli numerici scelti per definire le condizioni al contorno delle simulazioni CFD e verrà presentato l'apparato di prova realizzato ed utilizzato al fine di ricavare i campi di velocità tramite la tecnica di velocimetria laser Doppler. Infine verranno confrontati i risultati che si sono ottenuti, che mettono bene in evidenza la non stazionarietà del problema; si è riscontrata un'instabilità marcata e una non simmetria del deflusso in uscita dal filtro dovuta ad un'espansione improvvisa (PSE, Planar Sudden Expansion) della sezione di passaggio.

E' stata sviluppato una nuova ed innovativa geometria di filtro basata su moto elicoidale

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In this paper Chaos Collocation method coupled to Fictitious Domain approach has been applied to one- and two-dimensional elliptic problems defined on random domains in order to demonstrate the accuracy and convergence of the methodology. Chaos Collocation method replaces a stochastic process with a set of deterministic problems, which can be separately solved, so that the big advantage of Chaos Collocation is that it is non-intrusive and existing deterministic solvers can be used. For the analysis of differential problems obtained by Chaos Collocation, Fictitious Domain method with Least-Squares Spectral Element approximation has been employed. This algorithm exploits a fictitious computational domain, where the boundary constraints, immersed in the new simple shaped domain, are enforced by means of Lagrange multipliers. For this reason its main advantage lies in the fact that only a Cartesian mesh, that represents the enclosure, needs to be generated. Excellent accuracy properties of developed method are demonstrated by numerical experiments.

This chapter introduces the capability of the numerical multi-dimensional approach to solve complex problems in finance. It is well known how, with the growth of computational resource, scientists have developed numerical algorithms for the resolution of complex systems, in order to find the relations between the different components. One important field in this research is focused on the mimic of nature behavior to solve problems. In this chapter two technologies based on these techniques, self-organizing maps and multi-objectives genetic algorithm, have been used to solve two important fields in finance: the country risk assessment and the time series forecasting. The authors, through the examples in the chapter, would like to demonstrate how a multi-dimensional approach based on the mimic of nature could be useful to solve modern complex problems in finance.