Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III DOI Creative Commons
Mingzhang Pan, Cao Xinxin,

Changcheng Fu

et al.

Energy and AI, Journal Year: 2024, Volume and Issue: unknown, P. 100466 - 100466

Published: Dec. 1, 2024

Language: Английский

ANN-ANFIS model for optimising methylic composite biodiesel from neem and castor oil and predicting emissions of the biodiesel blend DOI Creative Commons

Chao-zhe Zhu,

Olusegun David Samuel, Amin Taheri‐Garavand

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 15, 2025

Abstract Researchers and stakeholders have shown interest in heterogeneous composite biodiesel (HCB) due to its enhanced fuel properties environmental friendliness (EF). The lack of high viscosity datasets for parent hybrid oils has hindered their commercialisation. Reliable models are lacking optimise the transesterification parameters developing HCB, scarcity predictive affected climate researchers experts. In this study, basic were analysed, developed yield HCB kinematic (KV) biodiesel/neem castor seed oil methyl ester (NCSOME) using Artificial Neural Network (ANN) Adaptive Neuro Fuzzy Inference System (ANFIS). Statistical indices such as computed coefficient determination (R 2 ), root-mean-square-error (RMSE), standard error prediction (SEP), mean average (MAE), absolute deviation (AAD) used evaluate effectiveness techniques. Emission NCSOME-diesel blends also established. study investigated impact optimised types/NCSOME-diesel (10–30 vol%), ZnO nanoparticle dosage (400–800 ppm), engine speed (1100–1700 rpm), load (10–30%) on emission characteristics (EFI) carbon monoxide (CO), Oxides Nitrogen (NOx), Unburnt Hydrocarbon (UHC) Response Surface Methodology (RSM). ANFIS model demonstrated superior performance terms R , RMSE, SEP, MAE, AAD compared ANN predicting KV HCB. optimal levels CO (49.26 NO x (0.5171 UHC (2.783) achieved with a type 23.4%, 685.432 ppm, 1329.2 rpm, 10% ensure cleaner EFI. can effectively predict fuel-related improve process, while RSM be valuable tool accurate forecasting promoting environment. provide reliable information strategic planning automotive industries.

Language: Английский

Citations

3
Production and engine performance analysis of biodiesel from Pongamia pinnata using PTSA and CaO nanocatalysts DOI
Ansar A. Mulla, Ajay M. Shah

Biomass and Bioenergy, Journal Year: 2025, Volume and Issue: 195, P. 107714 - 107714

Published: Feb. 18, 2025

Language: Английский

Citations

1
Valorization of waste seed oil from Cupressus macrocarpa L. for biodiesel production via green-synthesized iron oxide nanoparticles: A sustainable approach toward decarbonization DOI

Rozina Rozina,

Okezie Emmanuel, Mushtaq Ahmad

et al.

Next Energy, Journal Year: 2024, Volume and Issue: 7, P. 100218 - 100218

Published: Dec. 9, 2024

Language: Английский

Citations

4
Exploring possible pathways for green hydrogen-based transportation in Brazil: Fuel cells, hydrogen engines and dual-fuel combustion DOI

Vítor Brumano Andrade Cardinali,

Túlio Augusto Zucareli de Souza, Roberto Berlini Rodrigues da Costa

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 120, P. 238 - 253

Published: March 27, 2025

Language: Английский

Citations

0
Comparative Assessment of the Thermal Load of a Marine Engine Operating on Alternative Fuels DOI Creative Commons
Sergėjus Lebedevas,

Edmonas Milašius

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(4), P. 748 - 748

Published: April 8, 2025

The decarbonization of the operational fleet through implementation renewable and low-carbon fuels (LCFs) is considered a key factor in achieving regulatory greenhouse gas (GHG) reduction targets set by IMO EU. In parallel with optimizing engine energy efficiency emission characteristics during retrofitting for LCF operations, it equally important to assess ensure reliability components under permissible thermal mechanical loads. This study investigated factors influencing stresses on cylinder–piston assembly as engine’s operation shifts from diesel biodiesel, natural gas, methanol, or ammonia. methodological foundation this research was an original comparative analysis method that evaluates impacts stress combustion cycle factors. parameters were modeled using single-zone mathematical model. load determined based ALPHA (αgas) coefficient heat transfer intensity average temperature (Tavg). optimization simulated without changes structure (or “major” modernization, according terminology), modifications limited adjustment parameters. A characteristic transition LCFs significant increase maximum pressure (Pmax), stresses: ammonia, +43%; LNG, +28%; +54–70%; no changes. confirms adopted strategy maintain equal Dmax conditions. It emphasized that, after ensuring Pmax-idem conditions, aligns closely level minimal deviation. associated excess air (λ) controlled compression ratio within allowable variation ±1 unit. Based statistical correlations, rational λ identified, reaching up 2.5 units. Considering real-world marine engines, further will focus analyzing ISO 81/78, well E2 E3 cycles.

Language: Английский

Citations

0
Pathways to green/blue methanol: exploring 16 different approaches incorporating electrolyzer, Allam cycle, and steam methane reforming DOI
Taehyun Kim, Yungeon Kim, Jinwoo Park

et al.

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 162995 - 162995

Published: April 1, 2025

Language: Английский

Citations

0
Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III DOI Creative Commons
Mingzhang Pan, Cao Xinxin,

Changcheng Fu

et al.

Energy and AI, Journal Year: 2024, Volume and Issue: unknown, P. 100466 - 100466

Published: Dec. 1, 2024

Language: Английский

Citations

0