Rotary Friction Welding Versus Fusion Butt Welding of Plastic Pipes – Feasibility and Energy Perspective

According to the Plastics Pipe Institute, butt fusion is the most widely used method for joining lengths of PE pipe and pipe to PE fittings “by heat fusion” (https://plasticpipe.org/pdf/chapter09.pdf). However, butt-welding is not energy-cognizant from the point of view of a phase-change fabrication method. This is because the source of heating is external (heater plate). The initial heating and subsequent maintenance at relatively high temperature (above 200 C for welding of high-density polyethylene pipe) is energy intensive. Rotary friction welding, on the other hand focuses the energy where and when as needed because it uses electric motor to generate mechanical (spinning) motion that is converted to heat. This work will make the case for friction heating as energy efficient. An initial feasibility study will also be introduced to demonstrate that the resulting welded pipe joints may be of comparable quality to those produced by butt fusion and to virgin PE material

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Analyzing CAD competence with univariate and multivariate learning curve models

Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested. (C) 2008 Elsevier Ltd. All rights reserved

Correlating trainee attributes to performance in 3D CAD training

Purpose - The purpose of this exploratory study is to identify trainee attributes relevant for development of skills in 3D computer-aided design (CAD). Design/methodology/approach - Participants were trained to perform cognitive tasks of comparable complexity over time. Performance data were collected on the time needed to construct test models, and the number of features used to construct them. A written questionnaire survey profiled the trainees' technical capabilities, motivation, and dedication. Findings - Correlation analysis between the trainees' attributes/capabilities and performance showed that a mix of the trainees' psychological and technical attributes contributed to CAD competence development. Prior technical knowledge influenced initial performance whereas dedication had a strong influence on the rate of improvement. Practical implications - The methodology serves as basis for developing specific guidelines for constructing questionnaires for trainee profiling and for customizing the training of mechanical 3D CAD. Originality/value - This original research proposes a framework for classifying CAD-training candidates based on their technical and personality profiles, which may lead to more effective training

APPLICATION OF HOMOGENIZATION THEORY TO STUDY THE MECHANICS OF CORTICAL BONE

ABSTRACT Homogenization theory is utilized to study the effect on the axial stiffness of secondary osteons in cortical bone due to the presence of micro porous features (e.g., lacunae, canaliculi clusters, and Haversian canals). Specifically, 2 geometric characteristics were used to describe these features within the secondary osteons: volume fraction (% porosity) and shape (circular-or elliptical-shaped). Such information was determined for each individual porous feature from an image segmentation methodology developed earlier by Hage and Hamade. For each feature, aspect ratio vectors (or arrays of ratios for each individual porous feature) were used to classify each pore inhomogeneity as cylindrical, elliptical or irregular shape. Two prominent homogenization theories were used: the Mori-Tanaka (MT) and the generalized self-consistent method (GSCM). Using the results of image segmentation, it was possible to calculate the respective Eshelby tensors of each porous feature. To calculate the isotropic stiffness tensors for matrix (C m ) and pores (C p ) the Young's modulus and Poisson's ratio for the matrix (E m , ν m ) were assigned as obtained from literature and as those of blood (E p =10MPa, ν p = 0.3), respectively. The effective elastic stiffness tensors (C*) for the secondary osteons were obtained from which axial Young's modulus was obtained as function of volume fraction (% porosity) of each pore type and their individual shapes. The normalized axial Young's modulus was found to 1) significantly decrease with increasing volume fraction (%) of porosity and 2) for the same % porosity, to slightly decrease (increase) with increasing ratio of circular-shaped to elliptical-shaped (elliptical-shaped to circular-shaped) porous features. These findings were validated using experimental micro-indentation study performed on secondary osteons