Artificial Neural Network Modeling and Numerical Simulation of Syngas Fuel and Injection Timing Effects on the Performance and Emissions of a Heavy-Duty Compression Ignition Engine-Reference-Cited by-同舟云学术

Artificial Neural Network Modeling and Numerical Simulation of Syngas Fuel and Injection Timing Effects on the Performance and Emissions of a Heavy-Duty Compression Ignition Engine

Published:2021-11-26 Issue:48 Volume:6 Page:32379-32394
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Foroutani Saeed¹,Salehi Gholamreza²^ORCID,Fallahsohi Hossein¹,Lary Kamran³,Arasteh Afshin Mohseni³

Affiliation:

1. Department of Energy System Engineering, North Tehran Branch, Islamic Azad University, Tehran 5550, Iran

2. Department of Mechanical Engineering, Central Tehran Branch, Islamic Azad University, Tehran 5550, Iran

3. Department of Physical Oceanography, North Tehran Branch, Islamic Azad University, Tehran 5550, Iran

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c02829

Reference51 articles.

1. BP Energy Outlook 2019 Edition; London, United Kingdom, 2019.

2. Walker, N. R.; Chuahy, F. D. F.; Reitz, R. D. Comparison of diesel pilot ignition (DPI) and reactivity controlled compression ignition (RCCI) in a heavy-duty engine. In ASME 2015 Internal Combustion Engine Division Fall Technical Conference; American Society of Mechanical Engineers Digital Collection, 2015.

3. Direct Dual Fuel Stratification, a Path to Combine the Benefits of RCCI and PPC

4. Fuel Reactivity Controlled Compression Ignition (RCCI) Combustion in Light- and Heavy-Duty Engines

5. Boosted HCCI - Controlling Pressure-Rise Rates for Performance Improvements using Partial Fuel Stratification with Conventional Gasoline

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