Metal surface temperature induced by moving laser beams \ud

Whenever a metal is irradiated with a laser beam, electromagnetic energy is transformed into heat in a thin surface layer. The maximum surface temperature is the most important quantity which determines the processing result. Expressions for this maximum temperature are provided by the literature for stationary cases. In practice, however, moving beams are of more importance.\ud Based on a fast numerical algorithm which allows calculation of the induced temperature profile, the maximum surface temperature for stationary and moving laser beams is calculated. Next, two types of approximating functions are presented relating the scanning speed to the maximum surface temperature. Using dimensionless numbers, the results can be applied to different material

Force-Guiding Particle Chains for Shape-Shifting Displays

We present design and implementation of a chain of particles that can be programmed to fold the chain into a given curve. The particles guide an external force to fold, therefore the particles are simple and amenable for miniaturization. A chain can consist of a large number of such particles. Using multiple of these chains, a shape-shifting display can be constructed that folds its initially flat surface to approximate a given 3D shape that can be touched and modified by users, for example, enabling architects to interactively view, touch, and modify a 3D model of a building.Comment: 6 pages, 5 figure, submitted to IROS 201

Combined simple cautious and robust control for parameter and disturbance bounded distributions

The qualities and drawbacks of two control methods to cope with process uncertainty are considered: cautious control which only uses statistics, and robust control which only uses the bounds of the process uncertainty. On the basis of results obtained for new simple methods for both, two new performance measures are introduced which use statistics as well as bounds of process parameters and disturbances, and therefore combine the qualities of cautious and robust control. These controllers are shown to outperform cautious and robust contro

Conformally Mapped Polynomial Chaos Expansions for Maxwell's Source Problem with Random Input Data

Generalized Polynomial Chaos (gPC) expansions are well established for forward uncertainty propagation in many application areas. Although the associated computational effort may be reduced in comparison to Monte Carlo techniques, for instance, further convergence acceleration may be important to tackle problems with high parametric sensitivities. In this work, we propose the use of conformal maps to construct a transformed gPC basis, in order to enhance the convergence order. The proposed basis still features orthogonality properties and hence, facilitates the computation of many statistical properties such as sensitivities and moments. The corresponding surrogate models are computed by pseudo-spectral projection using mapped quadrature rules, which leads to an improved cost accuracy ratio. We apply the methodology to Maxwell's source problem with random input data. In particular, numerical results for a parametric finite element model of an optical grating coupler are given