The book Vortex Methods: Theory and Practice presents a comprehensive account of the numerical technique for solving fluid flow problems. It provides a very nice balance between the theoretical development and analysis of the various techniques and their practical implementation. In fact, the presentation of the rigorous mathematical analysis of these methods instills confidence in their implementation. The book goes into some detail on the more recent developments that attempt to account for viscous effects, in particular the presence of viscous boundary layers in some flows of interest. The presentation is very readable, with most points illustrated with well-chosen examples, some quite sophisticated. It is a very worthy reference book that should appeal to a large body of readers, from those interested in the mathematical analysis of the methods to practitioners of computational fluid dynamics. The use of the book as a text is compromised by its lack of exercises for students, but it could form the basis of a graduate special topics course. Juan Lopez

Vortex Methods: Theory and Practice

We present a simple proof on the formation of flocking to the Cucker-Smale system based on the explicit construction of a Lyapunov functional. Our results also provide a unified condition on the initial states in which the exponential convergence to flocking state will occur. For large particle systems, we give a rigorous justification for the mean-field limit from the many particle Cucker-Smale system to the Vlasov equation with flocking dissipation as the number of particles goes to infinity.

/pdf/a-simple-proof-of-the-cucker-smale-flocking-dynamics-and-25glpyaua7.pdf

A simple proof of the Cucker-Smale flocking dynamics and mean-field limit

In this paper, we extend the cubature Kalman filter (CKF) to deal with nonlinear state-space models of the continuous-discrete kind. To be consistent with the literature, the resulting nonlinear filter is referred to as the continuous-discrete cubature Kalman filter (CD-CKF). We use the Ito-Taylor expansion of order 1.5 to transform the process equation, modeled in the form of stochastic ordinary differential equations, into a set of stochastic difference equations. Building on this transformation and assuming that all conditional densities are Gaussian-distributed, the solution to the Bayesian filter reduces to the problem of how to compute Gaussian-weighted integrals. To numerically compute the integrals, we use the third-degree cubature rule. For a reliable implementation of the CD-CKF in a finite word-length machine, it is structurally modified to propagate the square-roots of the covariance matrices. The reliability and accuracy of the square-root version of the CD-CKF are tested in a case study that involves the use of a radar problem of practical significance; the problem considered herein is challenging in the context of radar in two respects- high dimensionality of the state and increasing degree of nonlinearity. The results, presented herein, indicate that the CD-CKF markedly outperforms existing continuous-discrete filters.

/pdf/cubature-kalman-filtering-for-continuous-discrete-systems-1gyt9q5czx.pdf

Cubature Kalman Filtering for Continuous-Discrete Systems: Theory and Simulations

Aerodynamic modelling of insect-like flapping flight for micro air vehicles

https://www.math.kth.se/4ecm/program/tornberg.pdf

P. A. Raviart

Papers

An analysis of particle methods