Akshansh Mishra – författare

The self-learning ability of machine learning algorithms makes the investigations more accurate and accommodates all the complex requirements. Development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The techniques also review the sustainability, life-span, the energy consumption in production polymer, etc. This book addresses the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms.

The self-learning ability of machine learning algorithms makes the investigations more accurate and accommodates all the complex requirements. Development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The techniques also review the sustainability, life-span, the energy consumption in production polymer, etc. This book addresses the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms.

Project Report from the year 2017 in the subject Engineering - Mechanical Engineering, grade: 8.9, SRM University, language: English, abstract: This paper deals with the mechanical, microstructural and fatigue analysis of welded joints. In the study, 6061-T6 aluminium alloy plates in 4mm thickness, that are particularly used for aerospace and in automotive industries, were welded using Tungsten Inert Gas (TIG) welding and Friction Stir Welding (FSW) methods as similar joints with one side pass and parameters of varying tool rotation, weld speed and 2.3 degree tool tilt angle. The weld zones cross sections were analysed with light optical microscopy (LOM). During recent years several investigations have been made of fatigue properties of friction stir welded joints. The great majority of available data from the fatigue analysis of friction stir welded joints are concerned with uniaxial loading conditions for a simple geometry. In uniaxial loading nominal stress is normally used as reference stress and it is easy to determine. However, fatigue failure is a highly localized phenomenon in engineering components and determining the nominal stress is not always possible due to the complexity of structures and presence of stress concentrators such as notches and cracks in which many approaches based on local parameters.

Scientific Study from the year 2017 in the subject Engineering - Mechanical Engineering, grade: 9.1, SRM University, language: English, abstract: This report presents an overview on the effects of different reinforcements in the magnesium and its alloy, so as to improve their mechanical and metallurgical properties. The morphology of microstructure and its effect on the physical properties of the magnesium is also discussed here. Magnesium matrix composites are potential materials for various applications of aerospace and defense organizations due to their low density, good mechanical and physical properties. The improvement of specific strength, stiffness, damping behavior, wear behavior, creep and fatigue properties are significantly influenced by the addition of reinforcing elements into the metallic matrix compared to the conventional engineering materials.