41 research outputs found
Experimental Investigation of Multiple Quality Characteristics of Laser Beam Machined Surface using Integrated Taguchi and Fuzzy Logic Method
Evaluation of milling characteristics of resin hybrid GFRP laminates using Taguchi approach
Process parameters optimization on machining force and delamination factor in milling of GFRP composites using grey relational analysis
313-320<span style="font-size:11.0pt;mso-bidi-font-size:
10.0pt;font-family:" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";="" mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:ar-sa"="" lang="EN-GB">In
this study, the optimization of process parameters for milling of glass fiber
reinforced polymer (GFRP) composites using grey relational analysis has been
investigated. Experiments are conducted using helix angle, spindle speed, feed
rate, depth of cut and fiber orientation angle as typical process parameters.
The grey relational analysis (GRA) is adopted to obtain grey relational grade
for milling process with multiple characteristics namely machining force and
delamination factor. Analysis of variance (ANOVA) is performed to get the
contribution of each parameter on the performance characteristics and it is
observed that fiber orientation angle and feed rate are the most significant
process parameters that affect the milling of GFRP composites. The experimental
results reveal that, the helix angle of 25o, spindle speed of
3000 rpm, feed rate of 500 mm/min, depth of cut of 1 mm and fiber orientation
angle of 15o is the optimum combination for lower machining force
and lower delamination factor. The experimental results for the optimal setting
show that there is considerable improvement in the process.</span
Machinability study of carbon fibre reinforced polymer (CFRP) composites using design of experiment technique
Free vibration analysis of a composite reinforced with natural fibers employing finite element and experimental techniques
Composites have been extensively used in the modern era in wide range of applications. This article deals with the study of vibration characteristics of natural fiber reinforced composite beam in which Aloe vera fiber is reinforced in epoxy matrix and is used in combination with glass-epoxy. Finite element method of analysis is adopted using Ansys software. Effects of several parameters like laminate stacking sequence, support conditions, material hybridization, and number of layers, etc. on the natural frequency of natural fiber reinforced composite beam are analyzed. Experimental study on Aloe vera fiber reinforced composite beam is also conducted for validation
Analysis and optimisation of machinability behaviour of CFRP composites using fuzzy logic
Preparation and characterisation of glass and cotton fibers reinforced epoxy hybrid composites
ACTSEA : annotated corpus for Tamil & Sinhala emotion analysis
The purpose of text emotion analysis is to detect and
recognize the classification of feeling expressed in text. In recent
years, there has been an increase in text emotion analysis studies
for English language since data were abundant. Due to the growth
of social media large amount data are now available for regional
languages such as Tamil and Sinhala as well. However, these
languages lack necessary annotated corpus for many NLP tasks
including emotion analysis. In this paper, we present our scalable
semi-automatic approach to create an annotated corpus named
ACTSEA for Tamil and Sinhala to support emotion analysis.
Alongside, our analysis on a sample of the produced data and the
useful findings are presented for the low resourced NLP
community to benefit. For ACTSEA, data were gathered from
twitter platform and annotated manually after cleaning. We
collected 600280 (Tamil) and 318308 (Sinhala) tweets in total
which makes our corpus largest data collection which is currently
available for these languages