What is it about?

The first and second-laws efficiencies were applied to performance analysis of an irreversible Miller cycle and procedure named ANN was used for predicting the thermal efficiency values versus the compression ratio, and the minimum and maximum temperatures of the Miller cycle.

Featured Image

Why is it important?

The efficiency and performance analysis of an air-standard Miller cycle using thermodynamics and mathematics (Artificial neural network) is unique.

Perspectives

I hope this article help to other related researchers to analyze the same thermodynamic cycles and more complicated ones.

Alireza Hajipour
Islamic Azad University

Read the Original

This page is a summary of: Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction, Proceedings of the Institution of Civil Engineers - Energy, January 2016, Elsevier,
DOI: 10.1016/j.energy.2015.10.073.
You can read the full text:

Read

Resources

Contributors

The following have contributed to this page