| 1 |
An insight into the estimation of fatty acid methyl ester based biodiesel properties using a LSSVM model
Razavi R, Bemani A, Baghban A, Mohammadi AH, Habibzadeh S
Fuel, 243, 133, 2019 |
| 2 |
Viscosities of some fatty acid esters and biodiesel fuels from a rough hard-sphere-chain model and artificial neural network
Hosseini SM, Pierantozzi M, Moghadasi J
Fuel, 235, 1083, 2019 |
| 3 |
A comprehensive study on measurement and prediction of viscosity of biodiesel-diesel-alcohol ternary blends
Gulum M, Bilgin A
Energy, 148, 341, 2018 |
| 4 |
Comparison of viscosity prediction capabilities of regression models and artificial neural networks
Gulum M, Onay FK, Bilgin A
Energy, 161, 361, 2018 |
| 5 |
Accurate predicting the viscosity of biodiesels and blends using soft computing models
Aminian A, ZareNezhad B
Renewable Energy, 120, 488, 2018 |
| 6 |
In-nozzle flow and spray characteristics for mineral diesel, Karanja, and Jatropha biodiesels
Agarwal AK, Som S, Shukla PC, Goyal H, Longman D
Applied Energy, 156, 138, 2015 |
| 7 |
Hybrid biofuels from non-edible oils: A comparative standpoint with corresponding biodiesel
Bora P, Konwar LJ, Boro J, Phukan MM, Deka D, Konwar BK
Applied Energy, 135, 450, 2014 |
| 8 |
Measurement and prediction of high-pressure viscosities of biodiesel fuels
Freitas SVD, Segovia JJ, Martin MC, Zambrano J, Oliveira MB, Lima AS, Coutinho JAP
Fuel, 122, 223, 2014 |
| 9 |
LHV predication models and LHV effect on the performance of CI engine running with biodiesel blends
Tesfa B, Gu F, Mishra R, Ball AD
Energy Conversion and Management, 71, 217, 2013 |
| 10 |
Development of a new model for biodiesel viscosity prediction based on the principle of corresponding state
do Carmo FR, Sousa PM, Santiago-Aguiar RS, de Sant'Ana HB
Fuel, 92(1), 250, 2012 |
