MHD natural convection flow from an isothermal horizontal circular cylinder under consideration of temperature dependent viscosity

Magnetohydrodynamic (MHD) natural convection laminar flow from an iso-thermal horizontal circular cylinder immersed in a fluid with viscosity proportional to a linear function of temperature will be discussed with numerical simulations. The governing boundary layer equations are transformed into a non-dimensional form and the resulting nonlinear system of partial differential equa-tions are reduced to convenient form, which are solved numerically by two very efficient methods, namely, (i) Implicit finite difference method together with Keller box scheme and (ii) Direct numerical scheme. Numerical results are presented by velocity and temperature distributions of the fluid as well as heat transfer characteristics, namely the shearing stress and the local heat transfer rate in terms of the local skin-friction coefficient and the local Nusselt number for a wide range of magnetohydrodynamic parameter, viscosity-variation parameter and viscous dissipation parameter. MHD flow in this geometry with temperature dependent viscosity is absent in the literature. The results obtained from the numerical simulations have been veri-fied by two methodologies.

Field study of air change and flow rate in six automobiles

For many people, a relatively large proportion of daily exposure to a multitude of pollutants may occur inside an automobile. A key determinant of exposure is the amount of outdoor air entering the cabin (i.e. air change or flow rate). We have quantified this parameter in six passenger vehicles ranging in age from 18 years to <1 year, at three vehicle speeds and under four different ventilation settings. Average infiltration into the cabin with all operable air entry pathways closed was between 1 and 33.1 air changes per hour (ACH) at a vehicle speed of 60 km/h, and between 2.6 and 47.3 ACH at 110 km/h, with these results representing the most (2005 Volkswagen Golf) and least air-tight (1989 Mazda 121) vehicles, respectively. Average infiltration into stationary vehicles parked outdoors varied between ~0 and 1.4 ACH and was moderately related to wind speed. Measurements were also performed under an air recirculation setting with low fan speed, while airflow rate measurements were conducted under two non-recirculate ventilation settings with low and high fan speeds. The windows were closed in all cases, and over 200 measurements were performed. The results can be applied to estimate pollutant exposure inside vehicles.

Arc voltage behavior in GMAW-P under different drop transfer modes

Purpose: Experimental measurements have been made to investigate meaning of the change in voltage for the pulse gas metal arc welding (GMAW-P) process operating under different drop transfer modes. Design/methodology/approach: Welding experiments with different values of pulsing parameter and simultaneous recording of high speed camera pictures and welding signals (such as current and voltage) were used to identify different drop transfer modes in GMAW-P. The investigation is based on the synchronization of welding signals and high speed camera to study the behaviour of voltage signal under different drop transfer modes. Findings: The results reveal that the welding arc is significantly affected by the molten droplet detachment. In fact, results indicate that sudden increase and drop in voltage just before and after the drop detachment can be used to characterize the voltage behaviour of different drop transfer mode in GMAW-P. Research limitations/implications: The results show that voltage signal carry rich information about different drop transfer occurring in GMAW-P. Hence it’s possible to detect different drop transfer modes. Future work should concentrate on development of filters for detection of different drop transfer modes. Originality/value: Determination of drop transfer mode with GMAW-P is crucial for the appropriate selection of pulse welding parameters. As change in drop transfer mode results in poor weld quality in GMAW-P, so in order to estimate the working parameters and ensure stable GMAW-P understanding the voltage behaviour of different drop transfer modes in GMAW-P will be useful. However, in case of GMAW-P hardly any attempt is made to analyse the behaviour of voltage signal for different drop transfer modes. This paper analyses the voltage signal behaviour of different drop transfer modes for GMAW-P.

Age-related loss of brain volume and T2 relaxation time in youth with type 1 diabetes

OBJECTIVE: Childhood-onset type 1 diabetes is associated with neurocognitive deficits, but there is limited evidence to date regarding associated neuroanatomical brain changes and their relationship to illness variables such as age at disease onset. This report examines age-related changes in volume and T2 relaxation time (a fundamental parameter of magnetic resonance imaging that reflects tissue health) across the whole brain. RESEARCH DESIGN AND METHODS: Type 1 diabetes, N = 79 (mean age 20.32 ± 4.24 years), and healthy control participants, N = 50 (mean age 20.53 ± 3.60 years). There were no substantial group differences on socioeconomic status, sex ratio, or intelligence quotient. RESULTS: Regression analyses revealed a negative correlation between age and brain changes, with decreasing gray matter volume and T2 relaxation time with age in multiple brain regions in the type 1 diabetes group. In comparison, the age-related decline in the control group was small. Examination of the interaction of group and age confirmed a group difference (type 1 diabetes vs. control) in the relationship between age and brain volume/T2 relaxation time. CONCLUSIONS: We demonstrated an interaction between age and group in predicting brain volumes and T2 relaxation time such that there was a decline in these outcomes in type 1 diabetic participants that was much less evident in control subjects. Findings suggest the neurodevelopmental pathways of youth with type 1 diabetes have diverged from those of their healthy peers by late adolescence and early adulthood but the explanation for this phenomenon remains to be clarified.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

Mathematical modelling of tumour-induced angiogenesis

The growth of solid tumours beyond a critical size is dependent upon angiogenesis, the formation of new blood vessels from an existing vasculature. Tumours may remain dormant at microscopic sizes for some years before switching to a mode in which growth of a supportive vasculature is initiated. The new blood vessels supply nutrients, oxygen, and access to routes by which tumour cells may travel to other sites within the host (metastasize). In recent decades an abundance of biological research has focused on tumour-induced angiogenesis in the hope that treatments targeted at the vasculature may result in a stabilisation or regression of the disease: a tantalizing prospect. The complex and fascinating process of angiogenesis has also attracted the interest of researchers in the field of mathematical biology, a discipline that is, for mathematics, relatively new. The challenge in mathematical biology is to produce a model that captures the essential elements and critical dependencies of a biological system. Such a model may ultimately be used as a predictive tool. In this thesis we examine a number of aspects of tumour-induced angiogenesis, focusing on growth of the neovasculature external to the tumour. Firstly we present a one-dimensional continuum model of tumour-induced angiogenesis in which elements of the immune system or other tumour-cytotoxins are delivered via the newly formed vessels. This model, based on observations from experiments by Judah Folkman et al., is able to show regression of the tumour for some parameter regimes. The modelling highlights a number of interesting aspects of the process that may be characterised further in the laboratory. The next model we present examines the initiation positions of blood vessel sprouts on an existing vessel, in a two-dimensional domain. This model hypothesises that a simple feedback inhibition mechanism may be used to describe the spacing of these sprouts with the inhibitor being produced by breakdown of the existing vessel's basement membrane. Finally, we have developed a stochastic model of blood vessel growth and anastomosis in three dimensions. The model has been implemented in C++, includes an openGL interface, and uses a novel algorithm for calculating proximity of the line segments representing a growing vessel. This choice of programming language and graphics interface allows for near-simultaneous calculation and visualisation of blood vessel networks using a contemporary personal computer. In addition the visualised results may be transformed interactively, and drop-down menus facilitate changes in the parameter values. Visualisation of results is of vital importance in the communication of mathematical information to a wide audience, and we aim to incorporate this philosophy in the thesis. As biological research further uncovers the intriguing processes involved in tumourinduced angiogenesis, we conclude with a comment from mathematical biologist Jim Murray, Mathematical biology is : : : the most exciting modern application of mathematics.

Advanced musculoskeletal simulation as an ergonomic design method

In recent years, the advent of new tools for musculoskeletal simulation has increased the potential for significantly improving the ergonomic design process and ergonomic assessment of design. In this paper we investigate the use of one such tool, ‘The AnyBody Modeling System’, applied to solve a one-parameter and yet, complex ergonomic design problem. The aim of this paper is to investigate the potential of computer-aided musculoskeletal modelling in the ergonomic design process, in the same way as CAE technology has been applied to engineering design.

An aspect query language model based on query decomposition and high-order contextual term associations

In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

Separation of acoustic emission signals from small size multi-cylinder diesel engine

This paper presents techniques which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outline, including time-frequency analysis and selection of optimum frequency band.The results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals and the effects of changing parameter values are also outlined. The results on separation of RMS signals show thsi technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events within the combustion process of multi-cylinder diesel engines.

The effect of lumbar support on the trunk muscle activity and pelvic tilt in a passenger vehicle car seat

In order to gain a competitive edge in the market, automotive manufacturers and automotive seat suppliers have identified seat ergonomics for further development to improve overall vehicle comfort. Adjustable lumbar support devices have been offered since long as comfort systems in either a 2-way or 4-way adjustable configuration, although their effect on lumbar strain is not well documented. The effect of a lumbar support on posture and muscular strain, and therefore the relationship between discomfort and comfort device parameter settings, requires clarification. The aim of this paper is to study the effect of a 4-way lumbar support on lower trunk and pelvis muscle activity, pelvic tilt and spine curvature during a car seating activity. 10 healthy subjects (5 m/f; age 19-39) performed a seating activity in a passenger vehicle with seven different static lumbar support positions. The lumbar support was tested in 3 different height positions in relation to the seatback surface centreline (high, centre, low), each having 2 depths positions (lumbar prominence). An extra depth position was added for the centre position. Posture data were collected using a VICON MX motion capture system and NORAXON DTS goniometers and inclinometer. A rigid-body model of an adjustable car seat with four-way adjustable lumbar support was constructed in UGS Siemens NX and connected to a musculoskeletal model of a seated-human, modelled in AnyBody. Wireless electromyography (EMG) was used to calibrate the musculoskeletal model and assess the relationship between (a) muscular strain and lumbar prominence (normal to seatback surface) respective to the lumbar height (alongside seatback surface), (b) hip joint moment and lumbar prominence (normal to seatback surface) respective to lumbar height (alongside seatback surface) and (c) pelvic tilt and lumbar prominence (normal to seatback surface) respective to the lumbar height (alongside seatback surface). This study was based on the assumption that the musculoskeletal human model was seated at the correct R-Point (SgRP), determined via the occupant packaging toolkit in the JACK digital human model. The effect of the interaction between the driver/car-seat has been investigated for factors resulting from the presence and adjustment of a 4-way lumbar support. The results obtained show that various seat adjustments, and driver’s lumbar supports can have complex influence on the muscle activation, joint forces and moments, all of which can affect the comfort perception of the driver. This study enables the automotive industry to optimise passenger vehicle seat development and design. It further more supports the evaluation of static postural and dynamic seat comfort in normal everyday driving tasks and can be applied for future car design to reduce investment and improve comfort.

A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.

Improved design rules for hollow flange sections subject to lateral distortional buckling

The LiteSteel Beam (LSB) is a new hollow flange section with a unique geometry consisting of torsionally rigid rectangular hollow flanges and a relatively slender web. It is subjected to lateral distortional buckling when used as flexural members, which reduces its member moment capacity. An investigation into the flexural behaviour of LSBs using experiments and numerical analyses led to the development of new design rules for LSBs subject to lateral distortional buckling. However, the comparison of moment capacity results with the new design rules showed that they were conservative for some LSB sections while slightly unconservative for others due to the effects of section geometry. It is also unknown whether these design rules are applicable to other hollow flange sections such as hollow flange beams (HFB). This paper presents the details of a study into the lateral distortional buckling behaviour of hollow flange sections such as LSBs, HFBs and their variations. A geometrical parameter defined as the ratio of flange torsional rigidity to the major axis flexural rigidity of the web (GJf/EIxweb) was found to be a critical parameter in evaluating the lateral distortional buckling behaviour and moment capacities of hollow flange sections. New design rules were therefore developed by using a member slenderness parameter modified by K, where K is a function of GJf/EIxweb. The new design rules based on the modified slenderness parameter were found to be accurate in calculating the moment capacities of not only LSBs and HFBs, but also other types of hollow flange sections.

Interaction of myxomatosis and Rabbit Haemorrhagic Disease in wild rabbit

Increasing resistance of rabbits to myxomatosis in Australia has led to the exploration of Rabbit Haemorrhagic Disease, also called Rabbit Calicivirus Disease (RCD) as a possible control agent. While the initial spread of RCD in Australia resulted in widespread rabbit mortality in affected areas, the possible population dynamic effects of RCD and myxomatosis operating within the same system have not been properly explored. Here we present early mathematical modelling examining the interaction between the two diseases. In this study we use a deterministic compartment model, based on the classical SIR model in infectious disease modelling. We consider, here, only a single strain of myxomatosis and RCD and neglect latent periods. We also include logistic population growth, with the inclusion of seasonal birth rates. We assume there is no cross-immunity due to either disease. The mathematical model allows for the possibility of both diseases to be simultaneously present in an individual, although results are also presented for the case where co infection is not possible, since co-infection is thought to be rare and questions exist as to whether it can occur. The simulation results of this investigation show that it is a crucial issue and should be part of future field studies. A single simultaneous outbreak of RCD and myxomatosis was simulated, while ignoring natural births and deaths, appropriate for a short timescale of 20 days. Simultaneous outbreaks may be more common in Queensland. For the case where co-infection is not possible we find that the simultaneous presence of myxomatosis in the population suppresses the prevalence of RCD, compared to an outbreak of RCD with no outbreak of myxomatosis, and thus leads to a less effective control of the population. The reason for this is that infection with myxomatosis removes potentially susceptible rabbits from the possibility of infection with RCD (like a vaccination effect). We found that the reduction in the maximum prevalence of RCD was approximately 30% for an initial prevalence of 20% of myxomatosis, for the case where there was no simultaneous outbreak of myxomatosis, but the peak prevalence was only 15% when there was a simultaneous outbreak of myxomatosis. However, this maximum reduction will depend on other parameter values chosen. When co-infection is allowed then this suppression effect does occur but to a lesser degree. This is because the rabbits infected with both diseases reduces the prevalence of myxomatosis. We also simulated multiple outbreaks over a longer timescale of 10 years, including natural population growth rates, with seasonal birth rates and density dependent(logistic) death rates. This shows how both diseases interact with each other and with population growth. Here we obtain sustained outbreaks occurring approximately every two years for the case of a simultaneous outbreak of both diseases but without simultaneous co-infection, with the prevalence varying from 0.1 to 0.5. Without myxomatosis present then the simulation predicts RCD dies out quickly without further introduction from elsewhere. With the possibility of simultaneous co-infection of rabbits, sustained outbreaks are possible but then the outbreaks are less severe and more frequent (approximately yearly). While further model development is needed, our work to date suggests that: 1) the diseases are likely to interact via their impacts on rabbit abundance levels, and 2) introduction of RCD can suppress myxomatosis prevalence. We recommend that further modelling in conjunction with field studies be carried out to further investigate how these two diseases interact in the population.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Statistical modelling of wind effects on signal propagation for wireless sensor networks

A wireless sensor network system must have the ability to tolerate harsh environmental conditions and reduce communication failures. In a typical outdoor situation, the presence of wind can introduce movement in the foliage. This motion of vegetation structures causes large and rapid signal fading in the communication link and must be accounted for when deploying a wireless sensor network system in such conditions. This thesis examines the fading characteristics experienced by wireless sensor nodes due to the effect of varying wind speed in a foliage obstructed transmission path. It presents extensive measurement campaigns at two locations with the approach of a typical wireless sensor networks configuration. The significance of this research lies in the varied approaches of its different experiments, involving a variety of vegetation types, scenarios and the use of different polarisations (vertical and horizontal). Non–line of sight (NLoS) scenario conditions investigate the wind effect based on different vegetation densities including that of the Acacia tree, Dogbane tree and tall grass. Whereas the line of sight (LoS) scenario investigates the effect of wind when the grass is swaying and affecting the ground-reflected component of the signal. Vegetation type and scenarios are envisaged to simulate real life working conditions of wireless sensor network systems in outdoor foliated environments. The results from the measurements are presented in statistical models involving first and second order statistics. We found that in most of the cases, the fading amplitude could be approximated by both Lognormal and Nakagami distribution, whose m parameter was found to depend on received power fluctuations. Lognormal distribution is known as the result of slow fading characteristics due to shadowing. This study concludes that fading caused by variations in received power due to wind in wireless sensor networks systems are found to be insignificant. There is no notable difference in Nakagami m values for low, calm, and windy wind speed categories. It is also shown in the second order analysis, the duration of the deep fades are very short, 0.1 second for 10 dB attenuation below RMS level for vertical polarization and 0.01 second for 10 dB attenuation below RMS level for horizontal polarization. Another key finding is that the received signal strength for horizontal polarisation demonstrates more than 3 dB better performances than the vertical polarisation for LoS and near LoS (thin vegetation) conditions and up to 10 dB better for denser vegetation conditions.