Prediction of Steam Turbine Performance as a Waste Heat Recovery Mechanism on Naturally Aspirated Spark Ignition Engine Using Artificial Neural Network

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 explores the performance of a naturally aspirated spark ignition engine equipped with a waste heat recovery mechanism (WHRM). The amount of heat energy from exhaust is presented and the experimental test results suggest that the concept is thermodynamically feasible and could significantly enhance the system performance depending on the load applied to the engine. However, the power generated from the WHRM is slightly small. The simulation method is created using an artificial neural network (ANN) which can predict accurately the power produced from the WHRM.