Aim: To simulate the workspace of a 2R robotic arm using MATLAB Robotic arm: It is a programmable mechanical arm which is a part of robot to do the desired function. Forward Kinematics: It is used to find the position of end effector (manipulator) for the given joint angles by using kinematic equations. Reverse Kinematics:…

Aim To plot P-V diagram for Otto cycle by studying engine kinematics and obtain the efficiency of the cycle using MATLAB Otto Cycle Engines, which are considered to be the heart of an automobile, ignite the fuel supplied in two ways. One is, by creating the spark (Spark Ignition – SI Engine) and other is by using…

SIMPLE PENDULUM Aim To simulate the transient behaviour of a simple pendulum with damping and to create an animation of its behaviour. Simple pendulum A simple pendulum consists of a mass m that is fixed to a pivot point P through a massless string of length L. Ideally, it is free to swing back and forth when it is displaced…

CURVE FITTING Aim             To perform regression analysis for the specific heat of Oxygen at constant temperature. Regression analysis             Regression analysis is a statistical tool used to estimate the…

Aim To optimise the stalagmite function using Genetic Algorithm (GA). Genetic Algorithm GA is one of the optimisation algorithms that is widely used in all engineering fields. It is a search heuristic inspired by Charles Darwin’s theory of natural evolution. In this algorithm, from initial population, the fittest…

Please find the report in below link https://skill-lync.com/projects/optimisation-of-stalagmite-function-using-genetic-algorithm-5  

FILE PARSING AIM To extract the co-efficient of all species from file and calculate specific heat, enthalpy and entropy of all species. SPECIFIC HEAT It is the amount of heat required to raise the temperature of 1Kg of substance by 1K. ENTHALPY It is a state variable that represents the total heat content of the system.…

Please find the report in below link https://skill-lync.com/projects/file-parsing-90

Mean and Expected value Mean(µ) indicates the average value of the outcome when probability of all outcomes in that sample space is equal. Expected value(E(X)) is the weighted average calculated by multiplying the number of occurrences of outcome and probability of outcome. Let x1, x2, x3…,xn in sample space…