Simulació numèrica de fenòmens de transferència de calor i dinàmics de fluids transitoris

The work carried out during the 4 year research activity can be barely classified in two main lines. On the one hand, a considerable effort is taken to address issues related with the verification of multi-dimensional and transient solutions that are obtained by numerical simulations. Within the studied cases, we can consider cases of piston-cylinder ows within geometries similar to those of hermetic reciprocating compressors.This issue is mentioned in Part I. On the other hand, numerical simulations of different phenomena have been performed. More emphasis has been given to the natural convection ow within enclosures. This is explained in Part II. The case extensively studied has been the natural convection ow. The natural convection ow within enclosures has attracted the attention of many researchers due to its potential to model numerous applications of engineering interest, such as cooling of electronic devices, air ow in buildings, heat transfer in solar collectors, among others. The natural convection studies corresponding to the parallelepipedic enclosures can be classified into two elementary classes: i) heating from a horizontal wall (heating from below); ii) heating from a vertical wall. The characteristic example of the former case is the Rayleigh-B_enard ow, however this research is on the cavities heated from the side. This configuration is referred commonly as the differentially heated cavity.

Compression-based Image Registration

Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images