Prediction of generated power from steam turbine waste heat recovery mechanism system on naturally aspirated spark ignition engine using artificial neural network

Herawan, Safarudin Gazali and Talib, Kamarulhelmy and Putra, Azma and Ismail, Ahmad Faris and Shamsudin, Shamsul Anuar and Musthafah, Mohd Tahir (2018) Prediction of generated power from steam turbine waste heat recovery mechanism system on naturally aspirated spark ignition engine using artificial neural network. Soft Computing, 22 (18). pp. 5955-5964. ISSN 1432-7643 E-ISSN 1433-7479

	PDF (In-press) - Accepted Version Restricted to Repository staff only Download (1MB) | Request a copy
Preview	PDF Download (386kB) | Preview
Preview	PDF (MYRA) - Supplemental Material Download (233kB) | Preview
Preview	PDF (SCOPUS) - Supplemental Material Download (198kB) | Preview

Abstract

The waste heat from exhaust gases represents a significant amount of thermal energy, which has conventionally been used for combined heating and power applications. This paper proposes a prediction model on the performance of a naturally aspirated spark ignition engine equipped with a waste heat recovery mechanism (WHRM) using steam turbine mechanism. The simulation method is created using an artificial neural network (ANN) to predict the power produced from this WHRM. The automated neural network was employed to run the simulation, where the ANN analysis used multilayer perceptrons as the network architecture, which is a feed-forward neural network architecture with uni-directional full connections between successive layers and applied Broyden–Fletcher–Goldfarb–Shanno algorithm iterative techniques to train the data. By using ANN, power generated from this WHRM could be predicted with good accuracy of 0.007, 0.011, and 0.016% error on training, test and validation data, respectively.

Item Type:	Article (Journal)
Additional Information:	1743/60709
Uncontrolled Keywords:	Waste heat recovery, Organic rankine cycle, Exhaust gas, Artificial neural network
Subjects:	T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering Kulliyyah of Engineering
Depositing User:	Prof Dr Ahmad Faris Ismail
Date Deposited:	02 Jan 2018 16:56
Last Modified:	30 Jan 2019 15:56
URI:	http://irep.iium.edu.my/id/eprint/60709

Actions (login required)

View Item