Computational Analysis of Changing Wavelength on Bottom Rib and Side Rib Wavy Microchannel Heat Sinks

As the power capacity of microelectronics continues to increase while their volume and size decrease, many different on-chip methods including microchannel heat sinks (MCHS) are being explored to cool down the temperature of these electronics. Wavy MCHS have been proven to yield better heat transfer performance compared to straight MCHS, while only producing a slightly larger pressure drop. This study investigates the heat transfer performance of MCHS following a vertical wavy design and a horizontal wavy design that have the same cross-sectional area. The simulations show that vortices are produced along the channel in the peaks and troughs of the sinusoidal waves which creates mixing within the coolant to better dissipate the heat via convection. The vertical wavy design produces to long symmetrical vortices that travel along the side of the channel, while the horizontal wavy design produces four smaller symmetrical vortices that form at the top, middle, and bottom of the channel. The results show that the horizontal wavy design performs better than the straight and vertical wavy channel especially with a larger decrease in wavelength along the flow direction. Keywords – Heat Transfer, Wavy Microchannel Heat Sinks, Computational Fluid Dynamics (CFD

Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers

The use of on-body wearable sensors is widespread in several academic and industrial domains. Of great interest are their applications in ambulatory monitoring and pervasive computing systems; here, some quantitative analysis of human motion and its automatic classification are the main computational tasks to be pursued. In this paper, we discuss how human physical activity can be classified using on-body accelerometers, with a major emphasis devoted to the computational algorithms employed for this purpose. In particular, we motivate our current interest for classifiers based on Hidden Markov Models (HMMs). An example is illustrated and discussed by analysing a dataset of accelerometer time series

Effect of the reductant nature on the catalytic removal of N2O on a Fe-zeolite-beta catalyst.

International audienc

Influence of co-cations in the selective catalytic reduction of NO by NH3 over copper exchanged faujasite zeolites

International audienceThe effect of a co-cation (Cs, Ba, Ca, Sr, Ba, La, Ce, Sm, Dy, Yb) on the properties of Cu exchanged faujasite catalysts in the selective catalytic reduction (SCR) of NO by NH3 in an oxidising atmosphere has been studied. Temperature programmed reduction (TPR) by H2 of Cu-faujasite (Cu-FAU) was used as a tool to identify and quantify the nature and location of Cu species. The ‘blocking' of sodalites cages of Cu-FAU by alkali earth or lanthanide ions enhanced the SCR activity at low temperature (LT) and made the reaction fully selective towards N2 in the whole temperature range studied (up to 773 K). The formation of N2O in Cu-FAU zeolites results from the reaction between nitrogen monoxide and ammonia on next-nearest-neighbour (NNN) Cu ions located in sodalite cages

Conception et réalisation d'un centre primaire de soins en Côte d'Ivoire

STRASBOURG-Medecine (674822101) / SudocPARIS-BIUM (751062103) / SudocSTRASBOURG-Sc. et Techniques (674822102) / SudocSudocFranceF

Effect of the reductant nature on the catalytic removal of N2O on a Fe-zeolite-beta catalyst.

International audienc