Finite element analysis of stress distribution and the effects of geometry in a laser-generated single-stage ceramic tile grout seal using ANSYS

Optimisation of the geometry (curvature of the vitrified enamel layer) of a laser-generated single-stage ceramic tile grout seal has carried out with a finite element (FE) model. The overall load bearing capacities and load-displacement plots of three selected geometries were determined experimentally by the indentation technique. Simultaneously, a FE model was developed utilising the commercial ANSYS package to simulate the indentation. Although the load-displacement plots generated by the FE model consistently displayed stiffer identities than the experimentally obtained results, there was reasonably close agreement between the two sets of results. Stress distribution profiles of the three FE models at failure loads were analysed and correlated so as to draw an implication on the prediction of a catastrophic failure through an analysis of FE-generated stress distribution profiles. It was observed that although increased curvatures of the vitrified enamel layer do enhance the overall load-bearing capacity of the single-stage ceramic tile grout seal and bring about a lower nominal stress, there is a higher build up in stress concentration at the apex that would inevitably reduce the load-bearing capacity of the enamel glaze. Consequently, the optimum geometry of the vitrified enamel layer was determined to be flat

Bearing restoration by grinding

A joint program was undertaken by the NASA Lewis Research Center and the Army Aviation Systems Command to restore by grinding those rolling-element bearings which are currently being discarded at aircraft engine and transmission overhaul. Three bearing types were selected from the UH-1 helicopter engine (T-53) and transmission for the pilot program. No bearing failures occurred related to the restoration by grinding process. The risk and cost of a bearing restoration by grinding programs was analyzed. A microeconomic impact analysis was performed

Bioimpedance of soft tissue under compression

In this paper compression-dependent bioimpedance measurements of porcine spleen tissue are presented. Using a Cole–Cole model, nonlinear compositional changes in extracellular and intracellular makeup; related to a loss of fluid from the tissue, are identified during compression. Bioimpedance measurements were made using a custom tetrapolar probe and bioimpedance circuitry. As the tissue is increasingly compressed up to 50%, both intracellular and extracellular resistances increase while bulk membrane capacitance decreases. Increasing compression to 80% results in an increase in intracellular resistance and bulk membrane capacitance while extracellular resistance decreases. Tissues compressed incrementally to 80% show a decreased extracellular resistance of 32%, an increased intracellular resistance of 107%, and an increased bulk membrane capacitance of 64% compared to their uncompressed values. Intracellular resistance exhibits double asymptotic curves when plotted against the peak tissue pressure during compression, possibly indicating two distinct phases of mechanical change in the tissue during compression. Based on these findings, differing theories as to what is happening at a cellular level during high tissue compression are discussed, including the possibility of cell rupture and mass exudation of cellular material.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98622/1/0967-3334_33_6_1095.pd

Acúmulo de macronutrientes por cultivares de cebola, em um vertissolo no médio São Francisco.

O objetivo desse trabalho foi o de avaliar o acúmulo de macronutrientes pela cultura da cebola, cultivares Alfa São Francisco e Franciscana IPA 10, em um Vertissolo no médio São Francisco

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

Exploring the views of students on the use of Facebook in university teaching and learning

Facebook use among students is almost ubiquitous; however, its use for formal academic purposes remains contested. Through an online survey monitoring student use of module Facebook pages and focus groups, this study explores students’ current academic uses of Facebook and their views on using Facebook within university modules. Students reported using Facebook for academic purposes, notably peer–peer communication around group work and assessment – a use not always conceptualised by students as learning. Focus groups revealed that students are not ready or equipped for the collaborative style of learning envisaged by the tutor and see Facebook as their personal domain, within which they will discuss academic topics where they see a strong relevance and purpose, notably in connection with assessment. Students use Facebook for their own mutually defined purposes and a change in student mind- and skill-sets is required to appropriate the collaborative learning benefits of Facebook in formal educational contexts

Adubação foliar em tomateiro estaqueado. (Lycopersicum esculentum, mill). Santa Cruz - Kada.

Experimento realizado em solo latossol vermelho escuro-fase arenosa intergra de Terra roxa estruturada.Resumo

Outlier ensembles: A robust method for damage detection and unsupervised feature extraction from high-dimensional data

Outlier ensembles are shown to provide a robust method for damage detection and dimension reduction via a wholly unsupervised framework. Most interestingly, when utilised for feature extraction, the proposed heuristic defines features that enable near-equivalent classification performance (95.85%) when compared to the features found (in previous work) through supervised techniques (97.39%) — specifically, a genetic algorithm. This is significant for practical applications of structural health monitoring, where labelled data are rarely available during data mining. Ensemble analysis is applied to practical examples of problematic engineering data; two case studies are presented in this work. Case study I illustrates how outlier ensembles can be used to expose outliers hidden within a dataset. Case study II demonstrates how ensembles can be utilised as a tool for robust outlier analysis and feature extraction in a noisy, high-dimensional feature-space