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.

Flexible pneumatic micro-actuators: Analysis and production

Compliant pneumatic micro-actuators are interesting for applications requiring large strokes and forces in delicate environments. These include for instance minimally invasive surgery and assembly of microcomponents. This paper presents a theoretical and experimental analysis of a balloon-type compliant micro-actuator. Finite element modeling is used to describe the complex behavior of these actuators, which is validated through prototype experiments. Prototypes with dimensions ranging from 11mm × 2mm × 0.24mm to 4mm × 1mm × 0.12mm are fabricated by a newly developed production process based on micromilling and micromolding. The larger actuators are capable of delivering out-of-plane strokes of up to 7mm. Further, they have been integrated in a platform with two rotational and one translational degree of freedom. © 2011 Published by Elsevier Ltd.

On the relation of slow feature analysis and Laplacian eigenmaps

The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement learning. Here, we show that LEMs are closely related to slow feature analysis (SFA), a biologically inspired, unsupervised learning algorithm originally designed for learning invariant visual representations. We show that SFA can be interpreted as a function approximation of LEMs, where the topological neighborhoods required for LEMs are implicitly defined by the temporal structure of the data. Based on this relation, we propose a generalization of SFA to arbitrary neighborhood relations and demonstrate its applicability for spectral clustering. Finally, we review previous work with the goal of providing a unifying view on SFA and LEMs. © 2011 Massachusetts Institute of Technology.

Electroluminescence analysis and simulation of the effects of injection and temperature on carrier distribution in InGaN-based light-emitting diodes with color-coded quantum wells

This paper reports on an extensive analysis of the electroluminescence characteristics of InGaN-based LEDs with color-coded structure, i.e., with a triple quantum well structure in which each quantum well has a different indium content. The analysis is based on combined electroluminescence measurements and two-dimensional simulations, carried out at different current and temperature levels. Results indicate that (i) the efficiency of each of the quantum wells strongly depends on device operating conditions (current and temperature); (ii) at low current and temperature levels, only the quantum well closer to the p-side has a significant emission; (iii) emission from the other quantum wells is favored at high current levels. The role of carrier injection, hole mobility, carrier density and non-radiative recombination in determining the relative intensity of the quantum wells is discussed in the text. © 2013 The Japan Society of Applied Physics.