Dr. Alok Satapathy | NIT ROURKELA (original) (raw)
Papers by Dr. Alok Satapathy
The finite element method (FEM) is a powerful computational technique for approximate solutions t... more The finite element method (FEM) is a powerful computational technique for approximate solutions to a
variety of ‘‘real-world” engineering problems having complex domains subjected to general boundary
conditions. In this paper FEM is implemented to determine the effective thermal conductivity of particulate
filled polymer composites and is validated by experimentation. A commercially available finite-element
package ANSYS is used to for this numerical analysis. Three-dimensional spheres-in-cube lattice
array models are constructed to simulate the microstructure of composite materials for various filler concentrations
ranging from about 6 to 36 vol.%. Composites with similar filler contents are fabricated by
hand layup technique by reinforcing micro-sized pine wood dust in epoxy resin. Guarded heat flow meter
test method is used to measure the thermal conductivity of these composites using the instrument Unitherm
™ Model 2022 as per ASTM-E1530. This study shows that the incorporation of pine wood dust
results in reduction of conductivity of epoxy resin and thereby improves its thermal insulation capability.
With addition of 6.5 vol.% of filler, the thermal conductivity of epoxy is found to decrease by about 19.8%
and with about 36 vol.% of filler addition, a 57.3% reduction in thermal conductivity of neat epoxy is
achieved. The experimentally measured conductivity values are compared with the numerically calculated
ones and also with the existing theoretical and empirical models. The values obtained using
finite-element analysis (FEA) are found to be in reasonable agreement with the experimental values.
This paper describes the processing and characterization of epoxy matrix composites reinforced wi... more This paper describes the processing and characterization of epoxy matrix composites reinforced with short flakes obtained from the scales of a typical fresh water fish (Lobea rohita) and also reports on their erosion wear characteristics. Composites are developed by reinforcement of randomly oriented short flakes obtained from fish scales into epoxy resin. Erosion characteristics are studied with the help of an air jet type erosion test rig employing the design of experiments approach based on Taguchi's orthogonal arrays. The findings of the experiments indicate that the rate of erosion by impact of solid erodent is greatly influenced by various control factors. The experimental results are in good agreement with the values from the theoretical model. An artificial neural network (ANN) approach is also applied to predict the wear rate of the composites and compared with the theoretical results. An optimal parameter combination is determined, which leads to minimization of erosion rate. Analysis of variance (ANOVA) is performed on the measured data and S/N (signal to noise) ratios. A mathematical correlation, consistent with the experimental observations is proposed as a predictive equation for estimation of erosion rate of these composites. Finally, popular evolutionary approach known genetic algorithm (GA) is used to generalize the method of finding out optimal factor settings for minimum wear rate.
The finite element method (FEM) is a powerful computational technique for approximate solutions t... more The finite element method (FEM) is a powerful computational technique for approximate solutions to a variety of ''real-world" engineering problems having complex domains subjected to general boundary conditions. In this paper FEM is implemented to determine the effective thermal conductivity of particulate filled polymer composites and is validated by experimentation. A commercially available finite-element package ANSYS is used to for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructure of composite materials for various filler concentrations ranging from about 6 to 36 vol.%. Composites with similar filler contents are fabricated by hand layup technique by reinforcing micro-sized pine wood dust in epoxy resin. Guarded heat flow meter test method is used to measure the thermal conductivity of these composites using the instrument Uni-therm™ Model 2022 as per ASTM-E1530. This study shows that the incorporation of pine wood dust results in reduction of conductivity of epoxy resin and thereby improves its thermal insulation capability. With addition of 6.5 vol.% of filler, the thermal conductivity of epoxy is found to decrease by about 19.8% and with about 36 vol.% of filler addition, a 57.3% reduction in thermal conductivity of neat epoxy is achieved. The experimentally measured conductivity values are compared with the numerically calculated ones and also with the existing theoretical and empirical models. The values obtained using finite-element analysis (FEA) are found to be in reasonable agreement with the experimental values.
This paper describes the development of multiphase hybrid composites consisting of polyester rein... more This paper describes the development of multiphase hybrid composites consisting of polyester reinforced with E-glass fiber and ceramic particulates. It further investigates the erosion wear response of these composites and presents a comparison of the influence of three different particulate fillers-fly ash, alumina ͑Al 2 O 3 ͒, and silicon carbide (SiC)-on the wear characteristics of glass-polyester composites. For this purpose, the erosion test schedule in an air jet type test rig is made, following design of experiments approach using Taguchi's orthogonal arrays. The Taguchi approach enables us to determine optimal parameter settings that lead to minimization of the erosion rate. The results indicate that erodent size, filler content, impingement angle, and impact velocity influence the wear rate significantly. The experimental results are in good agreement with the values from the theoretical model. An artificial neural network approach is also applied to predict the wear rate of the composites and compared with the theoretical results. This study reveals that addition of hard particulate fillers such as fly ash, Al 2 O 3 , and SiC improves the erosion resistance of glass-polyester composites significantly. An industrial waste such as fly ash exhibits better filler characteristics compared with those of alumina and SiC. Finally, a popular evolutionary approach known as genetic algorithm is used to generalize the method of finding out optimal factor settings for minimum wear rate.
Journal of Solid …, Jan 1, 2007
The finite element method (FEM) is a powerful computational technique for approximate solutions t... more The finite element method (FEM) is a powerful computational technique for approximate solutions to a
variety of ‘‘real-world” engineering problems having complex domains subjected to general boundary
conditions. In this paper FEM is implemented to determine the effective thermal conductivity of particulate
filled polymer composites and is validated by experimentation. A commercially available finite-element
package ANSYS is used to for this numerical analysis. Three-dimensional spheres-in-cube lattice
array models are constructed to simulate the microstructure of composite materials for various filler concentrations
ranging from about 6 to 36 vol.%. Composites with similar filler contents are fabricated by
hand layup technique by reinforcing micro-sized pine wood dust in epoxy resin. Guarded heat flow meter
test method is used to measure the thermal conductivity of these composites using the instrument Unitherm
™ Model 2022 as per ASTM-E1530. This study shows that the incorporation of pine wood dust
results in reduction of conductivity of epoxy resin and thereby improves its thermal insulation capability.
With addition of 6.5 vol.% of filler, the thermal conductivity of epoxy is found to decrease by about 19.8%
and with about 36 vol.% of filler addition, a 57.3% reduction in thermal conductivity of neat epoxy is
achieved. The experimentally measured conductivity values are compared with the numerically calculated
ones and also with the existing theoretical and empirical models. The values obtained using
finite-element analysis (FEA) are found to be in reasonable agreement with the experimental values.
This paper describes the processing and characterization of epoxy matrix composites reinforced wi... more This paper describes the processing and characterization of epoxy matrix composites reinforced with short flakes obtained from the scales of a typical fresh water fish (Lobea rohita) and also reports on their erosion wear characteristics. Composites are developed by reinforcement of randomly oriented short flakes obtained from fish scales into epoxy resin. Erosion characteristics are studied with the help of an air jet type erosion test rig employing the design of experiments approach based on Taguchi's orthogonal arrays. The findings of the experiments indicate that the rate of erosion by impact of solid erodent is greatly influenced by various control factors. The experimental results are in good agreement with the values from the theoretical model. An artificial neural network (ANN) approach is also applied to predict the wear rate of the composites and compared with the theoretical results. An optimal parameter combination is determined, which leads to minimization of erosion rate. Analysis of variance (ANOVA) is performed on the measured data and S/N (signal to noise) ratios. A mathematical correlation, consistent with the experimental observations is proposed as a predictive equation for estimation of erosion rate of these composites. Finally, popular evolutionary approach known genetic algorithm (GA) is used to generalize the method of finding out optimal factor settings for minimum wear rate.
The finite element method (FEM) is a powerful computational technique for approximate solutions t... more The finite element method (FEM) is a powerful computational technique for approximate solutions to a variety of ''real-world" engineering problems having complex domains subjected to general boundary conditions. In this paper FEM is implemented to determine the effective thermal conductivity of particulate filled polymer composites and is validated by experimentation. A commercially available finite-element package ANSYS is used to for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructure of composite materials for various filler concentrations ranging from about 6 to 36 vol.%. Composites with similar filler contents are fabricated by hand layup technique by reinforcing micro-sized pine wood dust in epoxy resin. Guarded heat flow meter test method is used to measure the thermal conductivity of these composites using the instrument Uni-therm™ Model 2022 as per ASTM-E1530. This study shows that the incorporation of pine wood dust results in reduction of conductivity of epoxy resin and thereby improves its thermal insulation capability. With addition of 6.5 vol.% of filler, the thermal conductivity of epoxy is found to decrease by about 19.8% and with about 36 vol.% of filler addition, a 57.3% reduction in thermal conductivity of neat epoxy is achieved. The experimentally measured conductivity values are compared with the numerically calculated ones and also with the existing theoretical and empirical models. The values obtained using finite-element analysis (FEA) are found to be in reasonable agreement with the experimental values.
This paper describes the development of multiphase hybrid composites consisting of polyester rein... more This paper describes the development of multiphase hybrid composites consisting of polyester reinforced with E-glass fiber and ceramic particulates. It further investigates the erosion wear response of these composites and presents a comparison of the influence of three different particulate fillers-fly ash, alumina ͑Al 2 O 3 ͒, and silicon carbide (SiC)-on the wear characteristics of glass-polyester composites. For this purpose, the erosion test schedule in an air jet type test rig is made, following design of experiments approach using Taguchi's orthogonal arrays. The Taguchi approach enables us to determine optimal parameter settings that lead to minimization of the erosion rate. The results indicate that erodent size, filler content, impingement angle, and impact velocity influence the wear rate significantly. The experimental results are in good agreement with the values from the theoretical model. An artificial neural network approach is also applied to predict the wear rate of the composites and compared with the theoretical results. This study reveals that addition of hard particulate fillers such as fly ash, Al 2 O 3 , and SiC improves the erosion resistance of glass-polyester composites significantly. An industrial waste such as fly ash exhibits better filler characteristics compared with those of alumina and SiC. Finally, a popular evolutionary approach known as genetic algorithm is used to generalize the method of finding out optimal factor settings for minimum wear rate.
Journal of Solid …, Jan 1, 2007