Linear multiscale analysis and finite element validation of stretching and bending dominated lattice materials

The paper presents a multiscale procedure for the linear analysis of components made of lattice materials. The method allows the analysis of both pin-jointed and rigid-jointed microtruss materials with arbitrary topology of the unit cell. At the macroscopic level, the procedure enables to determine the lattice stiffness, while at the microscopic level the internal forces in the lattice elements are expressed in terms of the macroscopic strain applied to the lattice component. A numeric validation of the method is described. The procedure is completely automated and can be easily used within an optimization framework to find the optimal geometric parameters of a given lattice material. © 2011 Elsevier Ltd. All rights reserved.

Magnetic shielding properties of high- Tc superconducting hollow cylinders: Model combining experimental data for axial and transverse magnetic field configurations

Magnetic shielding efficiency was measured on high- Tc superconducting hollow cylinders subjected to either an axial or a transverse magnetic field in a large range of field sweep rates, dBapp/dt. The behaviour of the superconductor was modelled in order to reproduce the main features of the field penetration curves by using a minimum number of free parameters suitable for both magnetic field orientations. The field penetration measurements were carried out on Pb-doped Bi-2223 tubes at 77K by applying linearly increasing magnetic fields with a constant sweep rate ranging between 10νTs-1 and 10mTs-1 for both directions of the applied magnetic field. The experimental curves of the internal field versus the applied field, Bin(Bapp), show that, at a given sweep rate, the magnetic field for which the penetration occurs, Blim, is lower for the transverse configuration than for the axial configuration. A power law dependence with large exponent, n′, is found between Blim and dBapp/dt. The values of n′ are nearly the same for both configurations. We show that the main features of the curves B in(Bapp) can be reproduced using a simple 2D model, based on the method of Brandt, involving a E(J) power law with an n-exponent and a field-dependent critical current density, Jc(B), (following the Kim model: Jc = Jc0(1+B/B1)-1). In particular, a linear relationship between the measured n′-exponents and the n-exponent of the E(J) power law is suggested by taking into account the field dependence of the critical current density. Differences between the axial and the transverse shielding properties can be simply attributed to demagnetizing fields. © 2009 IOP Publishing Ltd.

Detailed thermal modelling of a tubular linear machine for marine renewable generation

A detailed lumped-parameter thermal model is presented for a tubular linear machine that has been designed for use in a marine environment. The model has been developed for a static machine, the worst-case thermal scenario, and is used to establish a rating for the machine. The model has been validated against a large range of experimental tests and shows good correlation to both steady-state and transient experimental results. The model was constructed from a mostly theoretical basis with very little calibration, suggesting that the techniques used are applicable in a more general sense. © 2013 IEEE.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. The result can be interpreted as a generalization of classical consensus algorithms. Stronger conditions are shown to be sufficient-but to some extent, also necessary-to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2009 Elsevier Ltd. All rights reserved.

Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear time-invariant state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. Stronger conditions are shown to be sufficient - but to some extent, also necessary - to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2008 IEEE.

Improving the performance of low-gain designs for bounded control of linear systems

An online scheduling of the parameter ensuring in addition to closed loop stability was presented. Attention was given to saturated linear low-gain control laws. Null controllability of the considered linear systems was assumed. The family of low gain control laws achieved semiglobal stabilization.