Multi-objective design and optimisation of bypass outlet-guide vanes

This paper describes the development of an automated design optimization system that makes use of a high fidelity Reynolds-Averaged CFD analysis procedure to minimize the fan forcing and fan BOGV (bypass outlet guide vane) losses simultaneously taking into the account the down-stream pylon and RDF (radial drive fairing) distortions. The design space consists of the OGV's stagger angle, trailing-edge recambering, axial and circumferential positions leading to a variable pitch optimum design. An advanced optimization system called SOFT (Smart Optimisation for Turbomachinery) was used to integrate a number of pre-processor, simulation and in-house grid generation codes and postprocessor programs. A number of multi-objective, multi-point optimiztion were carried out by SOFT on a cluster of workstations and are reported herein.

Thin film shape memory alloys for optical sensing applications

Based on shape memory effect of the sputtered thin film shape memory alloys, different types of micromirror structures were designed and fabricated for optical sensing application. Using surface micromachining, TiNi membrane mirror structure has been fabricated, which can be actuated based on intrinsic two-way shape memory effect of the free-standing TiNi film. Using bulk micromachining, TiNi/Si and TiNi/Si 3N 4microcantilever mirror structures were fabricated. © 2007 IOP Publishing Ltd.

Optimisation of the chirp performance of electroabsorption modulators using a numerical system model

A model to simulate an electroabsorption modulator in a dispersive communications system is described and confirmed experimentally for a 5Gbit/s 100km system. Optimisation of the device shows that transmission of 10Gbit/s over 100km is possible.

Thin film shape memory alloys and microactuators

For Micro-electro-mechanical System (MEMS) applications, TiNi-based thin film Shape Memory Alloys (SMAs) possess many desirable properties, such as high power density, large transformation stress and strain upon heating and cooling, superelasticity and biocompatibility. In this paper, recent development in TiNi-based thin film SMA and microactuator applications is discussed. The topics related to film deposition and characterisation is mainly focused on crystal nucleation and growth during annealing, film thickness effect, film texture, stress induced surface relief, wrinkling and trenches as well as Temperature Memory Effect (TME). The microactuator applications are mainly focused on microvalve and microcage for biological applications, micromirror for optical applications and data storage using nanoindentation method. Copyright © 2009, Inderscience Publishers.

Optimisation of a piezoelectric system for energy harvesting from traffic vibrations

Piezoelectric systems are viewed as a promising approach to energy harvesting from environmental vibrations. The energy harvested from real vibration sources is usually difficult to estimate analytically. Therefore, it is hard to optimise the associated energy harvesting system. This work investigates the optimisation of a piezoelectric cantilever system using a genetic algorithm based approach with numerical simulations. The genetic algorithm globally considers the effects of each parameter to produce an optimal frequency response to scavenge more energy from the real vibrations while the conventional sinusoidal based method can only optimise the resistive load for a given resonant frequency. Experimental acceleration data from the vibrations of a vehicle-excited manhole cover demonstrates that the optimised harvester automatically selects the right frequency and also synchronously optimises the damper and the resistive load. This method shows great potential for optimizing the energy harvesting systems with real vibration data. ©2009 IEEE.

Learning shape priors for single view reconstruction

In this paper, we aim to reconstruct free-from 3D models from a single view by learning the prior knowledge of a specific class of objects. Instead of heuristically proposing specific regularities and defining parametric models as previous research, our shape prior is learned directly from existing 3D models under a framework based on the Gaussian Process Latent Variable Model (GPLVM). The major contributions of the paper include: 1) a probabilistic framework for prior-based reconstruction we propose, which requires no heuristic of the object, and can be easily generalized to handle various categories of 3D objects, and 2) an attempt at automatic reconstruction of more complex 3D shapes, like human bodies, from 2D silhouettes only. Qualitative and quantitative experimental results on both synthetic and real data demonstrate the efficacy of our new approach. ©2009 IEEE.