Frequency diversity measurements at 2.4 GHz for wireless sensor networks deployed in tunnels

Wireless Sensor Networks (WSNs) which utilise IEEE 802.15.4 technology operate primarily in the 2.4 GHz globally compatible ISM band. However, the wireless propagation channel in this crowded band is notoriously variable and unpredictable, and it has a significant impact on the coverage range and quality of the radio links between the wireless nodes. Therefore, the use of Frequency Diversity (FD) has potential to ameliorate this situation. In this paper, the possible benefits of using FD in a tunnel environment have been quantified by performing accurate propagation measurements using modified and calibrated off-the-shelf 802.15.4 based sensor motes in the disused Aldwych underground railway tunnel. The objective of this investigation is to characterise the performance of FD in this confined environment. Cross correlation coefficients are calculated from samples of the received power on a number of frequency channels gathered during the field measurements. The low measured values of the cross correlation coefficients indicate that applying FD at 2.4 GHz will improve link performance in a WSN deployed in a tunnel. This finding closely matches results obtained by running a computational simulation of the tunnel radio propagation using a 2D Finite-Difference Time-Domain (FDTD) method. ©2009 IEEE.

Measurement and simulation of surface roughness noise using phased microphone arrays

A turbulent boundary-layer flow over a rough wall generates a dipole sound field as the near-field hydrodynamic disturbances in the turbulent boundary-layer scatter into radiated sound at small surface irregularities. In this paper, phased microphone arrays are applied to the measurement and simulation of surface roughness noise. The radiated sound from two rough plates and one smooth plate in an open jet is measured at three streamwise locations, and the beamforming source maps demonstrate the dipole directivity. Higher source strengths can be observed on the rough plates which also enhance the trailing-edge noise. A prediction scheme in previous theoretical work is used to describe the strength of a distribution of incoherent dipoles and to simulate the sound detected by the microphone array. Source maps of measurement and simulation exhibit satisfactory similarities in both source pattern and source strength, which confirms the dipole nature and the predicted magnitude of roughness noise. However, the simulations underestimate the streamwise gradient of the source strengths and overestimate the source strengths at the highest frequency. © 2008 Elsevier Ltd. All rights reserved.

Theoretical simulation studies of pulsed field magnetisation of (RE)BCO bulk superconductors

The magnetisation of bulk high temperature superconductors (HTS), such as RE-Ba-Cu-O [(RE)BCO, where RE is a rare earth element or Y], by a practical technique is essential for their application in high field, permanent magnet-like devices. Research to-date into the pulsed field magnetisation (PFM) of these materials, however, has been limited generally to experimental techniques, with relatively little progress in the development of theoretical models. This is because not only is a multi-physics approach needed to take account of the heating of the samples but also the high electric fields generated are well above the regime in which there are reliable experimental results. This paper describes a framework of theoretical simulation using the finite element method (FEM) that is applicable to both single- and multi-pulse magnetisation processes of (RE)BCO bulk superconductors. The model incorporates the heat equation and provides a convenient way of determining the distribution of trapped field, current density and temperature change within a bulk superconductor at each stage of the magnetisation process. An example of the single-pulse magnetisation of a (RE)BCO bulk is described. Potentially, the model may serve as a cost-effective tool for the optimisation of the bulk geometry and the magnetisation profile in multi-pulse magnetisation processes. © 2010 IOP Publishing Ltd.

A detailed chemistry multi-cycle simulation of a gasoline fueled HCCI engine operated with NVO

A previously developed Stochastic Reactor Model (SRM) is used to simulate combustion in a four cylinder in-line four-stroke naturally aspirated direct injection Spark Ignition (SI) engine modified to run in Homogeneous Charge Compression Ignition (HCCI) mode with a Negative Valve Overlap (NVO). A portion of the fuel is injected during NVO to increase the cylinder temperature and enable HCCI combustion at a compression ratio of 12:1. The model is coupled with GT-Power, a one-dimensional engine simulation tool used for the open valve portion of the engine cycle. The SRM is used to model in-cylinder mixing, heat transfer and chemistry during the NVO and main combustion. Direct injection is simulated during NVO in order to predict heat release and internal Exhaust Gas Recycle (EGR) composition and mass. The NOx emissions and simulated pressure profiles match experimental data well, including the cyclic fluctuations. The model predicts combustion characteristics at different fuel split ratios and injection timings. The effect of fuel reforming on ignition timing is investigated along with the causes of cycle to cycle variations and unstable operation. A detailed flux analysis during NVO unearths interesting results regarding the effect of NOx on ignition timing compared with its effect during the main combustion. © 2009 SAE International.

Simulation-based optimal sensor scheduling with application to observer trajectory planning

The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. The aim is to minimise the variance of the estimation error of the hidden state w.r.t. the action sequence. We present a novel simulation-based method that uses a stochastic gradient algorithm to find optimal actions. © 2007 Elsevier Ltd. All rights reserved.