Performing quantitative MFM measurements on soft magnetic nanostructures.

We have extended our previous work (Rawlings et al 2010 Phys. Rev. B 82 085404) on simulating magnetic force microscopy (MFM) images for magnetically soft samples to include an accurate representation of coated MFM tips. We used an array of square 500 nm nanomagnets to evaluate our improved MFM model. A quantitative comparison between model and experiment was performed for lift heights ranging from 20 to 100 nm. No fitting parameters were used in our comparison. For all lift heights the qualitative agreement between model and experiment was significantly improved. At low lift heights, where the magnetic signal was strong, the difference between theory and experiment was less than 30%.

Dynamical structure function identifiability conditions enabling signal structure reconstruction

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. © 2012 IEEE.

2-Scale topography dry electrode for biopotential measurements.

The design and fabrication of a novel 2-scale topography dry electrode using macro and micro needles is presented. The macro needles enable biopotential measurements on hairy skin, the function of the micro needles is to decrease the electrode impedance even further by penetrating the outer skin layer. Also, a fast and reliable impedance characterization protocol is described. Based on this impedance measurement protocol, a comparison study is made between our dry electrode, 3 other commercial dry electrodes and a standard wet gel electrode. Promising results are already obtained with our electrodes which do not have skin piercing micro needles. For the proposed electrodes, three different conductive coatings (Ag/AgCl/Au) are compared. AgCl is found to be slightly better than Ag as coating material, while our Au coated electrodes have the highest impedance.

Localized tail state distribution in amorphous oxide transistors deduced from low temperature measurements

In this paper, we extract density of localized tail states from measurements of low temperature conductance in amorphous oxide transistors. At low temperatures, trap-limited conduction prevails, allowing extraction of the trapped carrier distribution with energy. Using a test device with a-InGaZnO channel layer, the extracted tail state energy and density at the conduction band minima are 20 meV and 2 × 10 19 cm -3 eV -1, respectively, which are consistent with values reported in the literature. Also, the field-effect mobility as a function of temperature from 77 K to 300 K is retrieved for different gate voltages, yielding the activation energy and the percolation threshold. © 2012 American Institute of Physics.

Turbulence length scale measurements in a motored internal combustion engine

A novel technique, using a 'flying' Hot Wire Anemometer is described; it is shown how the turbulent structure in a motored engine, using a high molecular weight gas as the working fluid, may be investigated with relative simplicity and very little engine modification. Initial results are presented for integral and micro length scales, which are within the range expected based on previous work. Copyright © 1987 Society of Automotive Engineers, Inc.

Investigation of the dilution process for measurement of particulate matter from spark-ignition engines

Measurements of particulate matter (PM) from spark ignition (SI) engine exhaust using dilution tunnels will become more prevalent as emission standards are tightened. Hence, a study of the dilution process was undertaken in order to understand how various dilution related parameters affect the accuracy with which PM sizes and concentrations can be determined. A SI and a compression ignition (CI) engine were separately used to examine parameters of the dilution process; the present work discusses the results in the context of SI exhaust dilution. A Scanning Mobility Particle Sizer (SMPS) was used to measure the size distribution, number density, and volume fraction of PM. Temperature measurements in the exhaust pipe and dilution tunnel reveal the degree of mixing between exhaust and dilution air, the effect of flowrate on heat transfer from undiluted and diluted exhaust to the environment, and the minimum permissible dilution ratio for a maximum sample temperature of 52°C. Measurements of PM concentrations as a function of dilution ratio show the competing effects of temperature and particle/vapor concentrations on particle growth dynamics, which result in a range of dilution ratios-from 13 to 18-where the effect of dilution ratio, independent of flowrate, is kept to a minimum. This range of dilution ratios is therefore optimal in order to achieve repeatable PM concentration measurements. Particle dynamics during transit through the tunnel operating at the optimal dilution ratio was found statistically insignificant compared to data scatter. Such small differences in number concentration may be qualitatively representative of particle losses for SI exhaust, but small increases in PM volume fraction during transit through the tunnel may significantly underestimate accretion of mass due to unburned hydrocarbons (HCs) emitted by SI engines. The fraction of SI-derived PM mass due to adsorbed/absorbed vapor, estimated from these data, is consistent with previous chemical analyses of PM. © 1998 Society of Automotive Engineers, Inc.

Effects of the biodiesel fuel physical properties on the swirl stabilised spray combustion characteristics

An increasin g interest in biofuel applications in modern engines requires a better understanding of biodiesel combustion behaviour. Many numerical studies have been carried out on unsteady combustion of biodiesel in situations similar to diesel engines, but very few studies have been done on the steady combustion of biodiesel in situations similar to a gas turbine combustor environment. The study of biodiesel spray combustion in gas turbine applications is of special interest due to the possible use of biodiesel in the power generation and aviation industries. In modelling spray combustion, an accurate representation of the physical properties of the fuel is a first important step, since spray formation is largely influenced by fuel properties such as viscosity, density, surface tension and vapour pressure. In the present work, a calculated biodiesel properties database based on the measured composition of Fatty Acid Methyl Esters (FAME) has been implemented in a multi-dimensional Computational Fluid Dynamics (CFD) spray simulation code. Simulations of non-reacting and reacting atmospheric-pressure sprays of both diesel and biodiesel have been carried out using a spray burner configuration for which experimental data is available. A pre-defined droplet size probability density function (pdf) has been implemented together with droplet dynamics based on phase Doppler anemometry (PDA) measurements in the near-nozzle region. The gas phase boundary condition for the reacting spray cases is similar to that of the experiment which employs a plain air-blast atomiser and a straight-vane axial swirler for flame stabilisation. A reaction mechanism for heptane has been used to represent the chemistry for both diesel and biodiesel. Simulated flame heights, spray characteristics and gas phase velocities have been found to compare well with the experimental results. In the reacting spray cases, biodiesel shows a smaller mean droplet size compared to that of diesel at a constant fuel mass flow rate. A lack of sensitivity towards different fuel properties has been observed based on the non-reacting spray simulations, which indicates a need for improved models of secondary breakup. By comparing the results of the non-reacting and reacting spray simulations, an improvement in the complexity of the physical modelling is achieved which is necessary in the understanding of the complex physical processes involved in spray combustion simulation. Copyright © 2012 SAE International.

Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.