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Gaseous-liquid fuel combinations of biogas as primary fuel and diesel as pilot fuel were employed to power a compression ignition (CI) engine in this study. The effects of variable input factors such as engine load, compression ratio, and pilot fuel injection advance on the dual-fuel engine's combustion, thermal, and emission performance were investigated. The data acquired during this lab-based testing was used to develop a prognostic model using a Bayesian optimization strategy for hyperparameter optimization and a contemporary ensemble Gaussian process regression (GPR) technique. During model testing, the error analysis revealed that the developed model could predict the experimental data rather correctly, with R2 values ranging from 0.9995 to 0.9999 and MSE values ranging from 0.00018 to 0.1334. The mean absolute error was discovered to be between 0.0091 and 0.3065. Consequently, the developed GPR model can effectively simulate the on-board performance, emission, and combustion characteristics of a diesel-biogas dual-fuel setting. As a consequence, the current work established the GPR model in the existing CI engine meta-modeling framework as a consistent, trustworthy, and robust system analytical approach for diesel-biogas dual fuel mode of operation. • Waste-derived biogas was used to power the diesel engine in dual-fuel mode. • Gaussian process regression was employed to develop a prognostic model. • Bayesian approach was used for hyper parameter optimization for best results. • Used model could predict emission and performance of the engine with 99.9% accuracy. • A precise metamodel framework to simulate the input–output paradigm was developed. [ABSTRACT FROM AUTHOR]

• Diesel engine was powered with ternary blends of biodiesel-diesel-oxyhydrogen. • Third-generation biodiesel was synthesized from biomass of Azolla Pinnata. • A low-cost device-31 plates generator generated oxyhydrogen gas. • Oxyhydrogen addition improved engine performance and lowered emissions. • Box-Behnken design coupled with desirability approach used for optimization. The current study explores and improves the effects of engine load, injection time, and oxyhydrogen fuel flow rate on the combustion and emissions characteristics of a diesel engine. Experiment with the combustion and exhaust characteristics of a medium-sized diesel engine working in tri-fuel mode using microalgae oil methyl ester-diesel blends as injected fuel and an oxyhydrogen gas combination as inducted fuel. The Box-Behnken design (BBD) was used to reduce the number of testing. The parameters and proposed attributes were calculated utilizing response surface techniques and BBD-generated quadratic models. The response surface analysis displayed the patterns of input interactions on the output using surface diagrams. The desirability-based optimization revealed the optimal engine operating parameters as 22.92° crank angles advance, 76% engine load, and 0.92 L per minute oxyhydrogen flow rate. At these optimized operating ranges, the performance and combustion output of the study was 30.8 % brake thermal efficiency (BTE), 0.3 kg/kWh brake specific fuel consumption (BSFC), and 65.6 bar peak cylinder pressure (PCP). On the emission front, the CO emission was 0.0107%, UHC was 26 ppm, and NO x was 853 ppm. The optimized values were validated through experimental testing, and all the results were within 7% of the model-predicted output. The addition of oxyhydrogen significantly improved the combustion of an algal biodiesel-diesel-oxyhydrogen-powered diesel engine in terms of fuel efficiency and fuel consumption and lower carbon-based emission levels except for nitrogen oxide emissions. [ABSTRACT FROM AUTHOR]