Machine Learning of ignition delay times under dual-fuel engine conditions-Reference-Cited by-同舟云学术

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Machine Learning of ignition delay times under dual-fuel engine conditions

Published:2021-03 Issue: Volume:288 Page:119650
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Han Wang,Sun Zhen,Scholtissek Arne,Hasse Christian

Funder

German Research Foundation

Federal Ministry for Economic Affairs and Energy

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference41 articles.

1. Experimental and numerical study on the combustion characteristics of partially premixed charge compression ignition engine with dual fuel;Lee;Fuel,2003

2. Direct numerical simulations of premixed methane flame initiation by pilot n-heptane spray autoignition;Demosthenous;Combust Flame,2016

3. On the effect of injection timing on the ignition of lean PRF/air/EGR mixtures under direct dual fuel stratification conditions;Luong;Combust Flame,2017

4. Fundamental physics of flame development in an autoigniting dual fuel mixture;Wang;Proc Combust Inst,2015

5. Dynamics of triple-flames in ignition of turbulent dual fuel mixture: A direct numerical simulation study;Jin;Proc Combust Inst,2019

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2. An efficient data-driven approach for modeling and optimization of reactivity-controlled compression ignition engine fueled with polyoxymethylene dimethyl ethers and hydrogen;International Journal of Hydrogen Energy;2024-08

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4. Development of an Artificial Intelligence Model to Predict Combustion Properties, With a Focus on Auto-Ignition Delay;Journal of Engineering for Gas Turbines and Power;2024-01-04

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