Modelling the entrainment and motion of particles in a gap: Application to abrasive wear

The microscale abrasion or ball-cratering test is being increasingly applied to a wide range of bulk materials and coatings. The response of materials to this test depends critically on the nature of the motion of the abrasive particles in the contact zone: whether they roll and produce multiple indentations in the coating, or slide causing grooving abrasion. Similar phenomena also occur when hard contaminant particles enter a lubricated contact. This paper presents simple quantitative two-dimensional models which describe two aspects of the interaction between a hard abrasive particle and two sliding surfaces. The first model treats the conditions under which a spherical abrasive particle of size d can be entrained into the gap between a rotating sphere of radius R and a plane surface. These conditions are determined by the coefficients of friction between the particle and the sphere, and the particle and the plane, denoted by μs and μp respectively. This model predicts that the values of (μs + μp) and 2μs should both exceed √2d/R for the particles to be entrained into the contact. If either is less than this value, the particle will slide against the sphere and never enter the contact. The second model describes the mechanisms of abrasive wear in a contact when an idealized rhombus-sectioned prismatic particle is located between two parallel plane surfaces separated by a certain distance, which can represent either the thickness of a fluid film or the spacing due to the presence of other particles. It is shown that both the ratio of particle size to the separation of the surfaces and the ratio of the hardnesses of the two surfaces have important influences on the particle motion and hence on the mechanism of the resulting abrasive wear. Results from this model are compared with experimental observations, and the model is shown to lead to realistic predictions. © IMechE 2003.

Long range exhaustion-a mathematical model for the axisymmetric air flow of a local exhaust ventilation hood assisted by a turbulent radial jet

Abstract-Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art Banged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air Bow to be reduced and provide a means of identifying and assessing the various parameters that control the air Bow. The mathematical model is formulated in terms of the Stokes steam function, ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained Bow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions. | Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art flanged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air flow to be reduced and provide a means of identifying and assessing the various parameters that control the air flow. The mathematical model is formulated in terms of the Stokes steam function, Ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained flow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions.

Plane-strain discrete dislocation plasticity with climb-assisted glide motion of dislocations

A small-strain two-dimensional discrete dislocation plasticity (DDP) framework is developed wherein dislocation motion is caused by climb-assisted glide. The climb motion of the dislocations is assumed to be governed by a drag-type relation similar to the glide-only motion of dislocations: such a relation is valid when vacancy kinetics is either diffusion limited or sink limited. The DDP framework is employed to predict the effect of dislocation climb on the uniaxial tensile and pure bending response of single crystals. Under uniaxial tensile loading conditions, the ability of dislocations to bypass obstacles by climb results in a reduced dislocation density over a wide range of specimen sizes in the climb-assisted glide case compared to when dislocation motion is only by glide. A consequence is that, at least in a single slip situation, size effects due to dislocation starvation are reduced. By contrast, under pure bending loading conditions, the dislocation density is unaffected by dislocation climb as geometrically necessary dislocations (GNDs) dominate. However, climb enables the dislocations to arrange themselves into lower energy configurations which significantly reduces the predicted bending size effect as well as the amount of reverse plasticity observed during unloading. The results indicate that the intrinsic plasticity material length scale associated with GNDs is strongly affected by thermally activated processes and will be a function of temperature. © 2013 IOP Publishing Ltd.

Trajectory control based on discrete full-range dynamics

There has been an increasing interest in the use of mechanical dynamics, (e.g., assive, Elastic, And viscous dynamics) for energy efficient and agile control of robotic systems. Despite the impressive demonstrations of behavioural performance, The mechanical dynamics of this class of robotic systems is still very limited as compared to those of biological systems. For example, Passive dynamic walkers are not capable of generating joint torques to compensate for disturbances from complex environments. In order to tackle such a discrepancy between biological and artificial systems, We present the concept and design of an adaptive clutch mechanism that discretely covers the full-range of dynamics. As a result, The system is capable of a large variety of joint operations, including dynamic switching among passive, actuated and rigid modes. The main innovation of this paper is the framework and algorithm developed for controlling the trajectory of such joint. We present different control strategies that exploit passive dynamics. Simulation results demonstrate a significant improvement in motion control with respect to the speed of motion and energy efficiency. The actuator is implemented in a simple pendulum platform to quantitatively evaluate this novel approach.

Improved digital processing method used for image motion measurement based on hybrid opto-digital joint transform correlator

Hybrid opto-digital joint transform correlator (HODJTC) is effective for image motion measurement, but it is different from the traditional joint transform correlator because it only has one optical transform and the joint power spectrum is directly input into a digital processing unit to compute the image shift. The local cross-correlation image can be directly obtained by adopting a local Fourier transform operator. After the pixel-level location of cross-correlation peak is initially obtained, the up-sampling technique is introduced to relocate the peak in even higher accuracy. With signal-to-noise ratio >= 20 dB, up-sampling factor k >= 10 and the maximum image shift <= 60 pixels, the root-mean-square error of motion measurement accuracy can be controlled below 0.05 pixels.

Directional performance in motion transparency

Motion transparency provides a challenging test case for our understanding of how visual motion, and other attributes, are computed and represented in the brain. However, previous studies of visual transparency have used subjective criteria which do not confirm the existence of independent representations of the superimposed motions. We have developed measures of performance in motion transparency that require observers to extract information about two motions jointly, and therefore test the information that is simultaneously represented for each motion. Observers judged whether two motions were at 90 to one another; the base direction was randomized so that neither motion taken alone was informative. The precision of performance was determined by the standard deviations (S.D.s) of probit functions fitted to the data. Observers also made judgments of orthogonal directions between a single motion stream and a line, for one of two transparent motions against a line and for two spatially segregated motions. The data show that direction judgments with transparency can be made with comparable accuracy to segregated (non-transparent) conditions, supporting the idea that transparency involves the equivalent representation of two global motions in the same region. The precision of this joint direction judgment is, however, 2–3 times poorer than that for a single motion stream. The precision in directional judgment for a single stream is reduced only by a factor of about 1.5 by superimposing a second stream. The major effect in performance, therefore, appears to be associated with the need to compute and compare two global representations of motion, rather than with interference between the dot streams per se. Experiment 2tested the transparency of motions separated by a range of angles from 5 to 180 by requiring subjects to set a line matching the perceived direction of each motion. The S.D.s of these settings demonstrated that directions of transparent motions were represented independently for separations over 20. Increasing dot speeds from 1 to 10 deg/s improved directional performance but had no effect on transparency perception. Transparency was also unaffected by variations of density between 0.1 and 19 dots/deg2

The human synovial fluid proteome: A key factor in the pathology of joint disease

This review aims to summarise our knowledge to date on the protein complement of the synovial fluid (S F). The tissues, structure and pathophysiology of the synovial joint are briefly described. The salient features of the S F proteome, how it is composed and the influence of arthritic disease are highlighted and discussed. The concentrations of proteins that have been detected and quantified in SF are drawn together from the literature on osteoarthritis, rheumatoid arthritis and juvenile idiopathic arthritis. The measurements are plotted to give a perspective on the dynamic range of protein levels within the SF. Approaches to proteomic analysis of SF to date are discussed along with their findings. From the recent literature reviewed within, it is becoming increasingly clear that analysis of the SF proteome as a whole, could deliver the most valuable differential diagnostic fingerprints of a number of arthritic disorders. Further development of proteomic platforms could characterise prognostic profiles to improve the cliniciads ability to resolve unremitting disease by existing and novel therapeutics.

Nonlinear theory of solitary waves associated with longitudinal particle motion in lattices - Application to longitudinal grain oscillations in a dust crystal

The nonlinear aspects of longitudinal motion of interacting point masses in a lattice are revisited, with emphasis on the paradigm of charged dust grains in a dusty plasma (DP) crystal. Different types of localized excitations, predicted by nonlinear wave theories, are reviewed and conditions for their occurrence (and characteristics) in DP crystals are discussed. Making use of a general formulation, allowing for an arbitrary (e.g. the Debye electrostatic or else) analytic potential form phi(r) and arbitrarily long site-to-site range of interactions, it is shown that dust-crystals support nonlinear kink-shaped localized excitations propagating at velocities above the characteristic DP lattice sound speed v(0). Both compressive and rarefactive kink-type excitations are predicted, depending on the physical parameter values, which represent pulse- (shock-)like coherent structures for the dust grain relative displacement. Furthermore, the existence of breather-type localized oscillations, envelope-modulated wavepackets and shocks is established. The relation to previous results on atomic chains as well as to experimental results on strongly-coupled dust layers in gas discharge plasmas is discussed.

A probabilistic modelling scheme for analysis of long-term failure of cemented femoral joint replacements

Reliable prediction of long-term medical device performance using computer simulation requires consideration of variability in surgical procedure, as well as patient-specific factors. However, even deterministic simulation of long-term failure processes for such devices is time and resource consuming so that including variability can lead to excessive time to achieve useful predictions. This study investigates the use of an accelerated probabilistic framework for predicting the likely performance envelope of a device and applies it to femoral prosthesis loosening in cemented hip arthroplasty.
A creep and fatigue damage failure model for bone cement, in conjunction with an interfacial fatigue model for the implant–cement interface, was used to simulate loosening of a prosthesis within a cement mantle. A deterministic set of trial simulations was used to account for variability of a set of surgical and patient factors, and a response surface method was used to perform and accelerate a Monte Carlo simulation to achieve an estimate of the likely range of prosthesis loosening. The proposed framework was used to conceptually investigate the influence of prosthesis selection and surgical placement on prosthesis migration.
Results demonstrate that the response surface method is capable of dramatically reducing the time to achieve convergence in mean and variance of predicted response variables. A critical requirement for realistic predictions is the size and quality of the initial training dataset used to generate the response surface and further work is required to determine the recommendations for a minimum number of initial trials. Results of this conceptual application predicted that loosening was sensitive to the implant size and femoral width. Furthermore, different rankings of implant performance were predicted when only individual simulations (e.g. an average condition) were used to rank implants, compared with when stochastic simulations were used. In conclusion, the proposed framework provides a viable approach to predicting realistic ranges of loosening behaviour for orthopaedic implants in reduced timeframes compared with conventional Monte Carlo simulations.

Advances in joint modelling: A review of recent developments with application to the survival of end stage renal disease patients

The use of joint modelling approaches is becoming increasingly popular when an association exists between survival and longitudinal processes. Widely recognized for their gain in efficiency, joint models also offer a reduction in bias compared with naïve methods. With the increasing popularity comes a constantly expanding literature on joint modelling approaches. The aim of this paper is to give an overview of recent literature relating to joint models, in particular those that focus on the time-to-event survival process. A discussion is provided on the range of survival submodels that have been implemented in a joint modelling framework. A particular focus is given to the recent advancements in software used to build these models. Illustrated through the use of two different real-life data examples that focus on the survival of end-stage renal disease patients, the use of the JM and joineR packages within R are demonstrated. The possible future direction for this field of research is also discussed. © 2013 International Statistical Institute.

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms:a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

The influence of water motion on the growth rate of the kelp Laminaria digitata

The shallow water kelp Laminaria digitata, abundant in coastal zones of the North Atlantic, is exposed to a range of hydrodynamic environments that makes it ideal for assessing the role of water motion on their growth rate. Here we quantify the growth of L. digitata, as a factor of blade and stipe elongation, at sites adjacent to Strangford Lough, Northern Ireland under different hydrodynamic conditions over a one year period. A modelling approach was used to numerically determine both the temporal and spatial variability of the hydrodynamic environment. Ambient seawater nutrient concentrations, temperature and irradiance were measured as well as the internal nutrient status of the L. digitata populations. Kelp populations growing in the greatest and lowest water motion showed the lowest growth rates. Differences observed in growth rate could not be attributed to seawater nutrient availability, temperature or light. The internal nutrient status also suggested no influence on the observed differences in growth rate. Therefore if there are minimal differences in light, temperature and nutrients between sites, then populations of L. digitata exposed to different water motions are likely to exhibit different growth rates. It is suggested that the growth rate differences observed were a function of water motion with the possibility that, in response to the hydrodynamic forces experienced by the algal cells, L. digitata kelps in the high energy environments were putting more energy into strengthening cell walls rather than blade elongation

The psychophysics of decision making in a two-direction random dot motion target selection task

La tâche de kinématogramme de points aléatoires est utilisée avec le paradigme de choix forcé entre deux alternatives pour étudier les prises de décisions perceptuelles. Les modèles décisionnels supposent que les indices de mouvement pour les deux alternatives sont encodés dans le cerveau. Ainsi, la différence entre ces deux signaux est accumulée jusqu’à un seuil décisionnel. Cependant, aucune étude à ce jour n’a testé cette hypothèse avec des stimuli contenant des mouvements opposés. Ce mémoire présente les résultats de deux expériences utilisant deux nouveaux stimuli avec des indices de mouvement concurrentiels. Parmi une variété de combinaisons d’indices concurrentiels, la performance des sujets dépend de la différence nette entre les deux signaux opposés. De plus, les sujets obtiennent une performance similaire avec les deux types de stimuli. Ces résultats supportent un modèle décisionnel basé sur l’accumulation des indices de mouvement net et suggèrent que le processus décisionnel peut intégrer les signaux de mouvement à partir d’une grande gamme de directions pour obtenir un percept global de mouvement.

An efficient scheme for the evaluation of coding performance of high speed links incorporating joint error behaviour based on Monte Carlo Method

While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting

Slow and Smooth: A Bayesian Theory for the Combination of Local Motion Signals in Human Vision

In order to estimate the motion of an object, the visual system needs to combine multiple local measurements, each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements from different image regions are combined according to a Bayesian estimator --- the estimated motion maximizes the posterior probability assuming a prior favoring slow and smooth velocities. In reviewing a large number of previously published phenomena we find that the Bayesian estimator predicts a wide range of psychophysical results. This suggests that the seemingly complex set of illusions arise from a single computational strategy that is optimal under reasonable assumptions.