Thermal resistance of ridge-waveguide laser diodes based on GaAs,GaSb or InP

The effects of different substrates (GaAs, GaSb and InP) on the thermal properties of laser diodes with a ridge-waveguide structure are presented. Laser diodes with the same basic geometry exhibit different thermal resistances. The reason is therefore the difference in thermal conductivity of the substrates and the active layer compounds. This leads to different temperature distributions in the structures. The theoretical results were supported by experimental data.

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Zusammenfassung Es wurde der Einfluß verschiedener Substrate (GaAs, GaSb und InP) auf die thermischen Eigenschaften von Laserdioden mit gefurchter Hohlleiterstruktur untersucht. Laserdioden mit dem gleichen geometrischen Grundaufbau zeigen verschiedene Wärmewiderstände. Die Ursache ist folglich der Unterschied in der Wärmeleitfähigkeit der Substrate und der Verbindungen der aktiven Schicht. Dies führt zu einer unterschiedlichen Temperaturverteilung in der Strukturen. Theoretische Ergebnisse werden durch experimentelle Daten bekräftigt.

     

Stabilized finite element method for flows with multiple reference frames

We present a space‐time finite element method capable of dealing with flows in multiple co‐rotating reference frames. Since equal order interpolation is used for all degrees of freedom, Galerkin/least‐squares stabilization is applied. We give a detailed derivation of the equations involved, introduce the variational form, present the stabilization parameters, and also discuss implementation issues. Numerical examples in 2D and 3D show generality and efficiency of the method, if steady‐state behavior of rotating components is sufficient for the CFD analysis. Copyright © 2015 John Wiley & Sons, Ltd.     

Anwendung von mathematischen statistischen methoden für einige probleme der quantitativen emissionsspektralanalyse

The standard deviation of the ΔY-values of an analytical line pair is discussed in function of the correlation and orthogonal regression coefficients as well as of the standard deviations of Y_x and Y_r.

It was stated that the orthogonal regression coefficient depends on the ratio s_x/s_r.

A criterium is set up for choosing the right analytical line pair. The optimal field for the values ^sδy is given in function of the ratio s_x/s_r as well as of the correlation coefficient.     

Velocity and acceleration level inverse kinematic calculation alternatives for redundant manipulators

For both non-redundant and redundant systems, the inverse kinematics (IK) calculation is a fundamental step in the control algorithm of fully actuated serial manipulators. The tool-center-point (TCP) position is given and the joint coordinates are determined by the IK. Depending on the task, robotic manipulators can be kinematically redundant. That is when the desired task possesses lower dimensions than the degrees-of-freedom of a redundant manipulator. The IK calculation can be implemented numerically in several alternative ways not only in case of the redundant but also in the non-redundant case. We study the stability properties and the feasibility of a tracking error feedback and a direct tracking error elimination approach of the numerical implementation of IK calculation both on velocity and acceleration levels. The feedback approach expresses the joint position increment stepwise based on the local velocity or acceleration of the desired TCP trajectory and linear feedback terms. In the direct error elimination concept, the increment of the joint position is directly given by the approximate error between the desired and the realized TCP position, by assuming constant TCP velocity or acceleration. We investigate the possibility of the implementation of the direct method on acceleration level. The investigated IK methods are unified in a framework that utilizes the idea of the auxiliary input. Our closed form results and numerical case study examples show the stability properties, benefits and disadvantages of the assessed IK implementations.

     

Random-order bin packing

The average-case analysis of algorithms usually assumes independent, identical distributions for the inputs. In [C. Kenyon, Best-fit bin-packing with random order, in: Proc. of the Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, 1996, pp. 359–364] Kenyon introduced the random-order ratio, a new average-case performance metric for bin packing heuristics, and gave upper and lower bounds for it for the Best Fit heuristics. We introduce an alternative definition of the random-order ratio and show that the two definitions give the same result for Next Fit. We also show that the random-order ratio of Next Fit equals to its asymptotic worst-case, i.e., it is 2.