A computational approach for cam size optimization of disc cam-follower mechanisms with translating roller followers

The main objective of this work is to present a computational approach for design optimization of disc cam mechanisms with eccentric translating roller followers. For this purpose, the objective function defined here takes into account the three major parameters that influence the final cam size, namely the base circle radius of the cam, the radius of the roller and the offset of the follower. Furthermore, geometric constraints related to the maximum pressure angle and minimum radius of curvature are included to ensure good working conditions of the system. Finally, an application example is presented and used to discuss the main assumptions and procedure adopted throughout this work.Fundação para a Ciência e a Tecnologia (FCT

High resolution in-vivo MR-STAT using a matrix-free and parallelized reconstruction algorithm

MR-STAT is a recently proposed framework that allows the reconstruction of multiple quantitative parameter maps from a single short scan by performing spatial localisation and parameter estimation on the time domain data simultaneously, without relying on the FFT. To do this at high-resolution, specialized algorithms are required to solve the underlying large-scale non-linear optimisation problem. We propose a matrix-free and parallelized inexact Gauss-Newton based reconstruction algorithm for this purpose. The proposed algorithm is implemented on a high performance computing cluster and is demonstrated to be able to generate high-resolution ($1mm \times 1mm$ in-plane resolution) quantitative parameter maps in simulation, phantom and in-vivo brain experiments. Reconstructed $T_1$ and $T_2$ values for the gel phantoms are in agreement with results from gold standard measurements and for the in-vivo experiments the quantitative values show good agreement with literature values. In all experiments short pulse sequences with robust Cartesian sampling are used for which conventional MR Fingerprinting reconstructions are shown to fail.Comment: Accepted by NMR in Biomedicine on 2019-12-0

Computer numerical control vertical machining centre feed drive modelling using the transmission line technique

This study presents a novel application of the Transmission Line Matrix Method (TLM) for the modelling of the dynamic behaviour of non-linear hybrid systems for CNC machine tool drives. The application of the TLM technique implies the dividing of the ball-screw shaft into a number of identical elements in order to achieve the synchronisation of events in the simulation, and to provide an acceptable resolution according to the maximum frequency of interest. This entails the use of a high performance computing system with due consideration to the small time steps being applied in the simulation. Generally, the analysis of torsion and axial dynamic effects on a shaft implies the development of independent simulated models. This study presents a new procedure for the modelling of a ball-screw shaft by the synchronisation of the axial and torsion dynamics into the same model. The model parameters were obtained with equipments such as laser interferometer, ball bar, electronic levels, signal acquisition systems etc. The MTLM models for single and two-axis configurations have been simulated and matches well with the measured responses of machines. The new modelling approach designated the Modified Transmission Line Method (MTLM) extends the TLM approach retaining all its inherent qualities but gives improved convergence and processing speeds. Further work since, not the subject of this paper, have identified its potential for real time application

Numerical modeling of oscillating Taylor bubbles

In this study, computational fluid dynamics (CFD) modeling is used to simulate Taylor bubbles rising in vertical pipes. Experiments indicate that in large diameter (0.29 m) pipes for an air–water system, the bubbles can rise in a oscillatory manner, depending on the method of air injection. The CFD models are able to capture this oscillatory behavior because the air phase is modeled as a compressible ideal gas. Insights into the flow field ahead and behind the bubble during contraction and expansion are shown. For a bubble with an initial pressure equal to the hydrostatic pressure at its nose, no oscillations are seen in the bubble as it rises. If the initial pressure in the bubble is set less than or greater than the hydrostatic pressure then the length of the bubble oscillates with an amplitude that depends on the magnitude of the initial bubble pressure relative to the hydrostatic pressure. The frequency of the oscillations is inversely proportional to the square root of the head of water above the bubble and so the frequency increases as the bubble approaches the water surface. The predicted frequency also depends inversely on the square root of the average bubble length, in agreement with experimental observations and an analytical model that is also presented. In this model, a viscous damping term due to the presence of a Stokes boundary layer for the oscillating cases is introduced for the first time and used to assess the effect on the oscillations of increasing the liquid viscosity by several orders of magnitude

Cross-Recurrence Quantification Analysis of Categorical and Continuous Time Series: an R package

This paper describes the R package crqa to perform cross-recurrence quantification analysis of two time series of either a categorical or continuous nature. Streams of behavioral information, from eye movements to linguistic elements, unfold over time. When two people interact, such as in conversation, they often adapt to each other, leading these behavioral levels to exhibit recurrent states. In dialogue, for example, interlocutors adapt to each other by exchanging interactive cues: smiles, nods, gestures, choice of words, and so on. In order for us to capture closely the goings-on of dynamic interaction, and uncover the extent of coupling between two individuals, we need to quantify how much recurrence is taking place at these levels. Methods available in crqa would allow researchers in cognitive science to pose such questions as how much are two people recurrent at some level of analysis, what is the characteristic lag time for one person to maximally match another, or whether one person is leading another. First, we set the theoretical ground to understand the difference between 'correlation' and 'co-visitation' when comparing two time series, using an aggregative or cross-recurrence approach. Then, we describe more formally the principles of cross-recurrence, and show with the current package how to carry out analyses applying them. We end the paper by comparing computational efficiency, and results' consistency, of crqa R package, with the benchmark MATLAB toolbox crptoolbox. We show perfect comparability between the two libraries on both levels

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods

Incorporating Inductances in Tissue-Scale Models of Cardiac Electrophysiology

In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and [...].Comment: 20 pages, 12 figure

Distance transform: a tool for the study of animal colour patterns

Summary The information in animal colour patterns plays a key role in many ecological interactions; quantification would help us to study them, but this is problematic. Comparing patterns using human judgement is subjective and inconsistent. Traditional shape analysis is unsuitable as patterns do not usually contain conserved landmarks. Alternative statistical approaches also have weaknesses, particularly as they are generally based on summary measures that discard most or all of the spatial information in a pattern. We present a method for quantifying the similarity of a pair of patterns based on the distance transform of a binary image. The method compares the whole pattern, pixel by pixel, while being robust to small spatial variations among images. We demonstrate the utility of the distance transform method using three ecological examples. We generate a measure of mimetic accuracy between hoverflies (Diptera: Syrphidae) and wasps (Hymenoptera) based on abdominal pattern and show that this correlates strongly with the perception of a model predator (humans). We calculate similarity values within a group of mimetic butterflies and compare this with proposed pairings of Müllerian comimics. Finally, we characterise variation in clypeal badges of a paper wasp (Polistes dominula) and compare this with previous measures of variation. While our results generally support the findings of existing studies that have used simpler ad hoc methods for measuring differences between patterns, our method is able to detect more subtle variation and hence reveal previously overlooked trends

Determination of Mealiness in Apples using Ultrasonic Measurements

A system based on ultrasonic energy absorbance was developed, for non-destructive measurements of three levels of texture degradation towards mealiness in Jonagold and Cox apples. The ultrasonic system comprises a high-power generator and a pair of 80 kHz ultrasonic transducers. One transducer, acting as a transmitter, sends a pulse through the apple tissue, which absorbs part of its energy, depending on internal textural attributes, and the transmitted pulse is received as an emerging signal by the other transducer. The detected ultrasound waves were analysed in parallel with the determination of the mealiness level of the fruit in accordance with destructive measurements in confined compression. The results obtained in Cox apples showed a good correlation between the ultrasound measurements and the confined-compression destructive tests for each mealiness level