Polytechnic University of Turin

About: Polytechnic University of Turin is a education organization based out in Turin, Piemonte, Italy. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 11553 authors who have published 41395 publications receiving 789320 citations. The organization is also known as: POLITO & Politecnico di Torino.

Predicting loss in magnetic steels under arbitrary induction waveform and with minor hysteresis loops

Abstract: We have studied ways of predicting power losses in soft magnetic laminations for generic time dependence of the periodic magnetic polarization J(t). We found that, whatever the frequency and the induction waveform, the loss behavior can be quantitatively assessed within the theoretical framework of the statistical loss model. The prediction requires a limited set of preemptive experimental data, depending on whether or not the arbitrary J(t) waveform is endowed with local slope inversions (i.e., minor hysteresis loops) in its periodic time behavior. In the absence of minor loops, such data reduce, for any peak polarization value J/sub p/, to the loss figures obtained under sinusoidal J(t) at two different frequency values. In the presence of minor loops of semiamplitude J/sub m/, the two-frequency loss experiment should be carried out for both peak polarization values J/sub p/ and J/sub m/. Additional knowledge of the quasi-static major loop, to be used for modeling hysteresis loss, does improve the accuracy of the prediction method. A more general approach to loss in soft magnetic laminations is obtained in this way, the only limitation apparently being the onset of skin effect at high frequencies.

Generalized stochastic Petri nets: a definition at the net level and its implications

Abstract: The class of Petri nets obtained by eliminating timing from generalized stochastic Petri net (GSPN) models while preserving the qualitative behavior is identified. Structural results for those nets are derived, obtaining the first structural analysis of Petri nets with priority and inhibitor arcs. A revision of the GSPN definition based on the structural properties of the models is presented. It is shown that for a (wide) class of nets, the definition of firing probabilities of conflicting immediate transitions does not require the information on reachable markings. Identification of the class of models for which the net-level specification is possible is also based on the structural analysis results. The procedure for the model specification is illustrated by means of an example. It is also shown that a net-level specification of the model associated with efficient structural analysis techniques can have a substantial impact on model analysis. >

DogOnt - Ontology Modeling for Intelligent Domotic Environments

Abstract: Home automation has recently gained a new momentum thanks to the ever-increasing commercial availability of domotic components In this context, researchers are working to provide interoperation mechanisms and to add intelligence on top of them For supporting intelligent behaviors, house modeling is an essential requirement to understand current and future house states and to possibly drive more complex actions In this paper we propose a new house modeling ontology designed to fit real world domotic system capabilities and to support interoperation between currently available and future solutions Taking advantage of technologies developed in the context of the Semantic Web, the DogOnt ontology supports device/network independent description of houses, including both "controllable" and architectural elements States and functionalities are automatically associated to the modeled elements through proper inheritance mechanisms and by means of properly defined SWRL auto-completion rules which ease the modeling process, while automatic device recognition is achieved through classification reasoning