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Thermodynamic analysis and performance of SRC and ORC power generation systems using waste heat source

In this work mathematical models of Steam Rankine Cycle (SRC) and Organic Rankine Cycle (ORC) power systems have been developed to explore the feasibility that combines the fluid-flow temperature, waste heat steam and low-boiling-point organic working fluids for power generation. The effects of the thermodynamic parameters on the SRC and ORC performance are examined. Among the commonly available working fluids, a selection based on environmental and technical criteria was carried out resulting in a list of 8 working fluids: R143a, R245fa, R600a, R124, R134a, RC318, R236fa, and Ammonia. Using the numerical models, we calculate and compare thermal efficiency, generating capacity, etc. of two power systems, namely SRC and ORC under the same heat source conditions. The results show that under the same condition of heat source, ORC has the highest thermal efficiency and power generation.

Published by: Surendra Kumar Vishwakarma, Sujeet Kumar Singh

Author: Surendra Kumar Vishwakarma

Paper ID: V5I2-1949

Paper Status: published

Published: April 17, 2019

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Research Paper

Implementation of automated wind power generation system on Indian highway

Wind energy has been the subject of research in the field of power generation. As the population increases and energy demand increases, renewable energy sources such as wind can be used to generate electricity with proper technology. To make the traditional method more efficient, i.e. Horizontal wind turbine axis, experimental research has shown that for low wind conditions vertical axis wind turbine can be used. The omnidirectional vertical axis wind turbine uses less space and higher power output. Since the rollers used in earlier models lead to a high loss of friction, we make use of magnetic levitation. We propose this design model with two steps, each with three blades in each stage. The blades are savonius type blades. Power generation is done using a pulley and belt system with the help of a DC motor.

Published by: Ajay Mishra, Ashutosh Mishra, Mohit Pandey

Author: Ajay Mishra

Paper ID: V5I2-1855

Paper Status: published

Published: April 17, 2019

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Review Paper

A review on thermodynamic analysis and performance of SRC and ORC power generation systems using waste heat source

The development of the world today has largely been achieved through the increasingly efficient and extensive use of various forms of energy. Over the past decades, the growth in energy consumption around the world has shown that fossil fuel energy source alone will not be capable of meeting future energy demands. With the increase in fossil fuel consumptions, more and more industrial activities produce an increasing amount of waste heat. Energy generated as a result of industrial activities that are not practically utilized is referred to as industrial waste heat. Several studies have shown that the specific amount of industrial waste heat is poorly measured, it is estimated that 25 to 55% of the input energy in industries are actually used while the remaining are discharged as waste heat.

Published by: Surendra Kumar Vishwakarma, Sujeet Kumar Singh

Author: Surendra Kumar Vishwakarma

Paper ID: V5I2-1948

Paper Status: published

Published: April 17, 2019

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Research Paper

Automated wet waste composting system for wet waste material

Composting is the acceleration of the natural process of breakdown of the organic material into a more stable organic substance. This paper focuses on the aerobic composting method. In the presence of oxygen, microorganisms consume organic matter and release heat and carbon dioxide; resulting in compost. This document addresses a composting plan and recommendations for AUI. After analyzing the background, the waste stream, the restrictions and the methods that will be used; a composting tumbler has been made in order to convert AUI’s organic waste into compost

Published by: Aditya Rao, Hrishikesh Manjerakar, Smit Soni, Priyanka Singh

Author: Aditya Rao

Paper ID: V5I2-1725

Paper Status: published

Published: April 17, 2019

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Research Paper

Casting defects reduction in a foundry shop using DMAIC Technique

This work presents a systematic procedure to identify as well as to analyze major casting defects. Defects are responsible for time waste, money and eventually they affect productivity adversely. The defects need to be diagnosed correctly for appropriate remedial measures; otherwise, a new defect may get introduced. The proper classification and identification of a particular defect is the basic need to correct and control the quality of the casting. Keeping rejection to a bare minimum is essential to improve the yield and increase the effective capacity of the foundry unit and also improve productivity. Casting defect can negatively impact the bottom line of a foundry. A defect in a casting deteriorates casting surface quality and mechanical properties. It is responsible for loss of profitability, quality level and productivity of component. So it is preferably necessary to reduce it as much as possible by appropriate analysis. The present work is carried out in the foundry to minimize casting rejection due to a major defect. Quality analysis is carried out which includes the Root cause analysis to find out actual reasons behind occurring the blowholes. Quality control tools such as Pareto analysis, Cause, and Effect (Ishikawa) diagram, and Why-why analysis are used for analysis. Accordingly corrective actions and preventive measures are suggested and implemented.

Published by: Wasim Ahmad, Anil verma, Priyanka jhavar

Author: Wasim Ahmad

Paper ID: V5I2-1953

Paper Status: published

Published: April 16, 2019

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Research Paper

Real time emotions recognition and analysis based music player

One of the most essential components of an individual’s body is the human face and it acts as the main indicator for the behavioral and the emotional state of the individual face and it's very important for the human to extracting the required input from the human face can be done by using camera directly. The mean of this examination is making facial expression Recognition (FER) conspire by Utilizing the CNN Algorithm and tensor flow to recognize the face by the camera. Facial expression analysis is used in a different way to detect human emotions. There are four types of emotions are recognized: happy, sad, angry, neutral depends on the mood. The playlist itself have the songs in the database, it plays the songs according to the mood detect by the Camera. This research paper is effective because we are using the different algorithm i.e. CNN model which is based on Machine Learning which gives accuracy and reduces the time to recognize the emotions

Published by: Mahek Gupta, Shreya Singhal, Mohit Pandey

Author: Mahek Gupta

Paper ID: V5I2-1899

Paper Status: published

Published: April 16, 2019

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