3 research outputs found
Effect of Equivalence Ratio on Composition and performance of Biogas and Gasoline Exhaust from Spark Ignition Engine by Mathematical Modeling
No full textThis paper presents the numerical computationnal of pressure, temperature and exhaust characteristics of spark ignition engine with biogas as fuel. The solution of non-linear combustion equation systems have been computed, that based on a quasi-one-dimensional engine model, high order iteration method with the equilibrium constants method. Computer program was used to calculate the mole fractions of 10 combustion products when biogas and gasoline fuel are burnt along with variable equivalence ratios. In cylinder chamber model is based on the classical two-zone approach, wherein parameters like heat transfer from the cylinder, blow by energy loss and heat release rate are also considered and calculated. Biogas is defined as fuel produced from using anaerobic digestion of biodegradable or waste materials and the constituents are C5H7O2N, CH4, CO2 N2 H2O of biogas and C7H17 of gosoline. Which general fuel model is specified by way of its CaHbOcNd values. The curve-fitted coefficients of energy were then employed to simulate air and fuels data along with frozen composition and practical chemical equilibrium routines from Gill data. The calculated data were used to plot the various pressure and temperature with the crank angle of each step of four stroke engine cycle and combustion products versus equivalence ratio. All results were compared with gasoline as reference fuel in the spark ignition engine according to the same numerical method
Comparison of combustion products by the iteration method and application of gasoline and biogas
No full textIntegration of image processing with 6-degrees-of-freedom robotic arm for advanced automation
Full text linkThis paper presents the design, construction, and development of a 6-degrees-of-freedom robotic arm, specifically tailored to the conditions at our university. The arm is powered by stepper motors and controlled via a programmable logic controller, while utilizing image processing data from a Raspberry Pi board. The objective of this research is to study automated pick-and-place operations, specifically targeting the handling of fruits such as oranges and apples. The system integrates advanced motion control techniques with vision-based object recognition to enable precise and reliable manipulation of the fruits. The robotic arm is equipped with an end-effector capable of handling objects with varying shapes and sizes, ensuring safe and efficient grasping and placement. Image processing algorithms are employed to identify and localize the fruits in real time, allowing the robotic arm to perform tasks in dynamic environments with minimal human intervention. Calibration, motion planning, and feedback control strategies are optimized to ensure high accuracy and prevent collisions or damage to the fruits. The system’s performance is evaluated through a series of experiments that demonstrate its capability to effectively pick and place oranges and apples, making it a promising solution for applications in agricultural automation and food processing
