École nationale supérieure de l'aéronautique et de l'espace

About: École nationale supérieure de l'aéronautique et de l'espace is a based out in . It is known for research contribution in the topics: CMOS & Pixel. The organization has 126 authors who have published 114 publications receiving 1550 citations. The organization is also known as: SUPAERO & École Nationale Supérieure de l'Aéronautique et de l'Espace (SUPAERO).

Shock wave instability and the carbuncle phenomenon: same intrinsic origin?

Abstract: The theoretical linear stability of a shock wave moving in an unlimited homogeneous environment has been widely studied during the last fifty years. Important results have been obtained by Dyakov (1954), Landau & Lifchitz (1959) and then by Swan & Fowles (1975) where the fluctuating quantities are written as normal modes. More recently, numerical studies on upwind finite difference schemes have shown some instabilities in the case of the motion of an inviscid perfect gas in a rectangular channel. The purpose of this paper is first to specify a mathematical formulation for the eigenmodes and to exhibit a new mode which was not found by the previous stability analysis of shock waves. Then, this mode is confirmed by numerical simulations which may lead to a new understanding of the so-called carbuncle phenomenon.

Shock wave numerical structure and the carbuncle phenomenon

Abstract: Since the development of shock-capturing methods, the carbuncle phenomenon has been reported to be a spurious solution produced by almost all currently available contact-preserving methods. The present analysis indicates that the onset of carbuncle phenomenon is actually strongly related to the shock wave numerical structure. A matrix-based stability analysis as well as Euler finite volume computations are compared to illustrate the importance of the internal shock structure to trigger the carbuncle phenomenon

Control of the transition to chaos in neural networks with random connectivity

Abstract: The occurrence of chaos in recurrent neural networks is supposed to depend on the architecture and on the synaptic coupling strength. It is studied here for a randomly diluted architecture. We produce a bifurcation parameter independent of the connectivity that allows a sustained activity and the occurrence of chaos when reaching a critical value. Even for weak connectivity and small size, we find numerical results in accordance with the theoretical ones previously established for fully connected infinite sized networks. Moreover the route towards chaos is numerically checked to be a quasiperiodic one, whatever the type of the first bifurcation is. In the discussion, we connect these results to some recent theoretical results about highly diluted networks. Hints are provided for further investigations to elicit the role of chaotic dynamics in the cognitive processes of the brain.