On global linearization of planar involutions

Let phi: a"e(2) -> a"e(2) be an orientation-preserving C (1) involution such that phi(0) = 0. Let Spc(phi) = {Eigenvalues of D phi(p) | p a a"e(2)}. We prove that if Spc(phi) aS, a"e or Spc(phi) a (c) [1, 1 + epsilon) = a... for some epsilon > 0, then phi is globally C (1) conjugate to the linear involution D phi(0) via the conjugacy h = (I + D phi(0)phi)/2,where I: a"e(2) -> a"e(2) is the identity map. Similarly, we prove that if phi is an orientation-reversing C (1) involution such that phi(0) = 0 and Trace (D phi(0)D phi(p) > - 1 for all p a a"e(2), then phi is globally C (1) conjugate to the linear involution D phi(0) via the conjugacy h. Finally, we show that h may fail to be a global linearization of phi if the above conditions are not fulfilled.

A Model-Based Approach for Small-Signal Stability Assessment of Unbalanced Power Systems

In this paper, a modeling technique for small-signal stability assessment of unbalanced power systems is presented. Since power distribution systems are inherently unbalanced, due to its lines and loads characteristics, and the penetration of distributed generation into these systems is increasing nowadays, such a tool is needed in order to ensure a secure and reliable operation of these systems. The main contribution of this paper is the development of a phasor-based model for the study of dynamic phenomena in unbalanced power systems. Using an assumption on the net torque of the generator, it is possible to precisely define an equilibrium point for the phasor model of the system, thus enabling its linearization around this point, and, consequently, its eigenvalue/eigenvector analysis for small-signal stability assessment. The modeling technique presented here was compared to the dynamic behavior observed in ATP simulations and the results show that, for the generator and controller models used, the proposed modeling approach is adequate and yields reliable and precise results.

An integer linear programming approach for bilinear integer programming

We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear P. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. (C) 2011 Elsevier B.V. All rights reserved.

Comparison between frequency domain and time domain riser analysis

In the optimization or parametric analyses of risers, several configurations must be analyzed. It is laborious to perform time domain solutions for the dynamic analysis, since they are time-consuming tasks. So, frequency domain solutions appear to be a possible alternative, mainly in the early stages of a riser design. However, frequency domain analysis is linear and requires that nonlinear effects are treated. The aim of this paper is to present a possible way to treat some of these nonlinearities, using an iterative process together with an analytical correction, and compare the results of a frequency domain analysis with the those of a full nonlinear analysis. [DOI: 10.1115/1.4006149]