1,152 research outputs found

    Investigations on the Problem of Moisture Absorption13; by Kevlar Fibres

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    Kevlar fibres are know, to have affinity for moisture. We have investigated (i) the effect of relative humidity (RH) of ambient atmosphere and ( ii ) the effect of crystallinity of fibres on the process of moisture uptake.13; For RH values ranging fran 3 to 80% variation of moisture content of initially dry fibres with time has been measured. It is found that saturation moisture content varies with RH value. Specimens in which crystallinity has been reduced by apropriate treatmrent exhibit a marked increase in moisture content.Experiments on the effect of soaking the fibres in water at 26xB0;C and 98xB0;C have also been carried out. The site of ITOisture absorption has been studied using X-ray of dry Kevlar 49 fibres and those with clifferent levels13; of misture content. The results suggest that water molecules do not enter the unit cell

    Tackling India’s deepening gender inequality during COVID-19

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    As India slowly re-opens its economy following its emergency national measures to contain the spread of the novel coronavirus, Kalyani Raghunathan (International Food Policy Research Institute (IFPRI), New Delhi) and M Niaz Asadullah (University of Malaya, Malaysia) explain how India’s already high levels of gender inequality will deepen thanks to the pandemic

    Tribological Properties of Polymer Composites Using Non Traditional Optimization Technique: a review

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    Specific wear rate of composite materials plays a significant role in industry. The processes to measure it are both time and cost consuming. It is essential to suggest a modeling method to predict and analyze the effectiveness of parameters of specific wear rate. Nowadays, computational methods such as Grey Relational Analysis (GRA), Artificial Neural Network (ANN), Fuzzy Inference System (FIS) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as applicable tools from modeling point of view. The objective of using ANN, ANFIS is also to apply this tool for systematic parameter studies in the optimum design of composite materials for specific applications. In the present review, various principles of the neural network approach for predicting certain properties of polymer composite materials are discussed. The aim of this review is to promote more consideration of using GRA, ANN and ANFIS in the field of polymer composite property prediction and design
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