This study presents a comprehensive analysis of combustion mechanisms and emission formation in marine diesel engines using biodiesel blends through experimental validation and computational fluid dynamics simulation using Matlab 2024a. Two marine engines were tested—YANMAR 6HAL2-DTN (200 kW, 1200 rpm) and Niigatta Engineering 6L34HX (2471 kW, 600 rpm)—with biodiesel ratios B0, B20, B50, and B100 at loads from 10% to 100%. The methodology combines detailed experimental measurements of exhaust emissions, fuel consumption, and engine performance with three-dimensional CFD simulations employing k-ε RNG turbulence model, Kelvin–Helmholtz–Rayleigh–Taylor droplet breakup model, and extended Zeldovich mechanism for NOx formation modeling. Key findings demonstrate that biodiesel’s oxygen content (10–12% by mass) increases maximum combustion temperature by 25 °C at 50% load, resulting in NOx emissions increase of 5–13% across all loads. Conversely, CO emissions decrease by 7–10% due to enhanced oxidation reactions. CFD analysis reveals that B100 exhibits 12% greater spray penetration depth, 20% larger Sauter Mean Diameter, and 20–25% slower evaporation rate compared to B0. The thermal Zeldovich mechanism dominates NOx formation (>90%), with prompt-NO and fuel-NO contributions increasing from 6.5% and 0.3% for B0 to 7.2% and 1.3% for B100, respectively, at 25% load. Optimal injection timing varies with biodiesel ratio: 13–15° BTDC for B0 reducing to 10–12° BTDC for B100. These quantitative insights enable evidence-based optimization of marine diesel engines for improved environmental performance while maintaining operational efficiency.

Marine transportation contributes approximately 2.5% of global greenhouse gas emissions. While previous studies have examined biodiesel effects on automotive engines, research on marine applications reveals critical gaps: (1) existing studies focus on single-parameter analysis without considering the complex interactions between biodiesel ratio, engine load, and operating conditions; (2) most research lacks comprehensive lifecycle assessment integration with real-time operational data; (3) previous optimization models demonstrate insufficient accuracy (R² < 0.80) for practical marine applications; and (4) no adaptive algorithms exist for dynamic biodiesel ratio adjustment based on operational conditions. These limitations prevent effective biodiesel implementation in maritime operations, necessitating an integrated multi-parameter optimization approach. This study addresses this research gap by proposing an integrated optimization model for fuel efficiency and emissions of marine diesel engines using biodiesel mixtures under diverse operating conditions. Based on extensive experimental data from two representative marine engines (YANMAR 6HAL2-DTN 200 kW and Niigatta Engineering 6L34HX 2471 kW), this research analyzes correlations between biodiesel blend ratios (pure diesel, 20%, 50%, and 100% biodiesel), engine load conditions (10–100%), and operating temperature with nitrogen oxides, carbon dioxide, and carbon monoxide emissions. Multivariate regression models were developed, allowing prediction of emission levels with high accuracy (R² = 0.89–0.94). The models incorporated multiple parameters, including engine characteristics, fuel properties, and ambient conditions, to provide a comprehensive analytical framework. Life cycle assessment (LCA) results show that the B50 biodiesel ratio achieves optimal environmental efficiency, reducing greenhouse gases by 15% compared to B0 while maintaining stable engine performance across operational profiles. An adaptive optimization algorithm for operating conditions is proposed, providing detailed reference charts for ship operators on ideal biodiesel ratios based on load conditions, ambient temperature, and operational priorities in different maritime zones. The findings demonstrate significant potential for emissions reduction in the maritime sector through strategic biodiesel implementation.

This comprehensive study presents an integrated analysis of NO_x reduction strategies and operational optimization for the HYUNDAI-HiMSEN 7H35DFP dual-fuel marine engine. The optimization scope focuses on selective catalytic reduction control strategies and operational decision-making (fuel mode selection, load management) rather than engine hardware modifications, ensuring practical applicability within certified marine engine operational envelopes. The research employs a multifaceted approach combining experimental investigation, computational fluid dynamics (CFD) modeling, and advanced control algorithms to address the stringent IMO Tier III emission standards. The 3500 kW, 7-cylinder engine achieves IMO Tier III compliance through dual pathways: (1) gas mode operation meeting the 2.4 g/kWh limit inherently with measured emissions of 1.41–2.29 g/kWh across 25–100% load without aftertreatment, and (2) diesel mode achieving compliance via SCR aftertreatment, reducing Tier II baseline emissions (7.68–10.71 g/kWh) by 75–82% to final values of 1.60–1.96 g/kWh. The research quantifies NO_x reduction mechanisms separately for each operating mode and establishes optimal operational strategies for mode selection. A MATLAB v2025a-based SCR optimization model successfully predicts optimal urea injection rates, achieving >75% NO_x reduction efficiency across all operating conditions. Multivariate analysis using principal component analysis identifies the following three primary factors explaining 89.3% of dataset variability: combustion intensity (45.2%), fuel mixing characteristics (28.7%), and thermal management (15.4%). CFD analysis reveals that gas mode combustion produces more uniform temperature distributions (peak ~2000 K) compared to diesel operation (>2200 K), directly explaining NO_x generation differences. The developed digital twin framework with machine learning algorithms achieves 94.2% accuracy in SCR catalyst degradation prediction and 91.8% in fuel injection system performance prediction. Waste heat recovery analysis indicates 25–30% of fuel energy resides in exhaust gases, with theoretical energy recovery potential of 8.5–15.3%. This integrated approach validates dual-fuel technology’s capability to meet current and future maritime environmental regulations while maintaining operational flexibility.