École Polytechnique de Montréal

About: École Polytechnique de Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 8015 authors who have published 18390 publications receiving 494372 citations.

Feature identification: a novel approach and a case study

Abstract: Feature identification is a well-known technique to identify subsets of a program source code activated when exercising a functionality. Several approaches have been proposed to identify features. We present an approach to feature identification and comparison for large object-oriented multi-threaded programs using both static and dynamic data. We use processor emulation, knowledge filtering, and probabilistic ranking to overcome the difficulties of collecting dynamic data, i.e., imprecision and noise. We use model transformations to compare and to visualise identified features. We compare our approach with a naive approach and a concept analysis-based approach using a case study on a real-life large object-oriented multi-threaded program, Mozilla, to show the advantages of our approach. We also use the case study to compare processor emulation with statistical profiling.

Power Oscillations Damping in DC Microgrids

Abstract: This paper proposes a new control strategy for damping of power oscillations in a multisource dc microgrid. A parallel combination of a fuel cell (FC), a photovoltaic system, and a supercapacitor (SC) is used as a hybrid power conversion system (HPCS). The SC compensates for the slow transient response of the FC stack. The HPCS controller comprises a multiloop voltage controller and a virtual impedance loop for power management. The virtual impedance loop uses a dynamic droop gain to actively damp the low-frequency oscillations of the power sharing control unit. The gain of the virtual impedance loop is determined using a small-signal analysis and the pole placement method. The Mesh analysis is employed to further study the stability of low-frequency modes of the overall dc microgrid. Moreover, based on the guardian map theorem, a robust stability analysis is carried out to determine a robustness margin for the closed-loop system. The main advantage of the proposed method is its robustness against uncertainties imposed by microgrid parameters. This feature provides DG units with plug-and-play capability without needing the exact values of microgrid parameters. The performance of the proposed control scheme is verified using hardware-in-the-loop simulations carried out in OPAL-RT technologies.

Localization of Hopf bifurcations in fluid flow problems

Abstract: We are concerned with the precise localization of Hopf bifurcations in various fluid flow problems. This is when a stationary solution loses stability and often becomes periodic in time. The difficulty is to determine the critical Reynolds number where a pair of eigenvalues of the Jacobian matrix crosses the imaginary axis. This requires the computation of the eigenvalues (or at least some of them) of a large matrix resulting from the discretization of the incompressible Navier-Stokes equations. We thus present a method allowing the computation of the smallest eigenvalues, from which we can extract the one with the smallest real part. From the imaginary part of the critical eigenvalue we can deduce the fundamental frequency of the time-periodic solution. These computations are then confirmed by direct simulation of the time-dependent Navier-Stokes equations.

A kinematic theory of rapid human movements: Part III. Kinetic outcomes.

Abstract: This paper describes the kinematic and kinetic properties of simple rapid movements using a single and unique framework based on a delta-lognormal law (Plamondon 1993a,b, 1995a,b). Predictions concerning isotonic measurements are made using the properties of acceleration profiles, as described by the first time derivative of the delta-lognormal law. Predictions dealing with isometric measurements are directly analyzed using the delta-lognormal law, after demonstrating the experimental equivalence between isometric forces and virtual velocity profiles. The theory is also used to make statistical predictions about the variability of numerous kinematic and kinetic variables. The overall approach can be viewed as if, at some level of representation, the central nervous system were planning, executing and evaluating simple rapid movements in terms of momentum and energy instead of forces. The unifying perspective provided by the theory constitutes a powerful tool with which to study and analyze movements under numerous experimental conditions, using a single analytical law.