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This study investigates the spray combustion characteristics of waste cooking oil (WCO) in comparison between a swirl nozzle (SN) and a conventional nozzle (CN) of equal cross‐section. n‐Heptane, methyl decanoate, and methyl‐9‐decenoate were used as WCO substitutes in the simulation. The research primarily focuses on multiphase flow using the Lagrangian‐drop Eulerian‐fluid (LDEF) method, employing an equilibrium phase spray model (EP) for droplet behaviour analysis. The model's efficacy was validated through comparisons with experimental works by other engine researchers. At varying injection pressures, the study found that SN slightly reduced evaporative spray tip penetration but increased the cone angle compared to CN. This suggests early fuel jet disintegration and improved air entrainment due to SN. SN also showed a higher heat release rate and temperature, with soot reduction between 3.20 to 6.72% as injection pressure increased from 100 to 300 MPa. This indicates that SN achieves better air‐fuel mixture than CN. Further, the study discovered that the influence of SN becomes more significant as the rheological properties of WCO lessen under ultra‐high injection pressures. [ABSTRACT FROM AUTHOR]

Hardware‐based sensing frameworks such as cooperative fuel research engines are conventionally used to monitor research octane number (RON) in the petroleum refining industry. Machine learning techniques are employed to predict the RON of integrated naphtha reforming and isomerisation processes. A dynamic Aspen HYSYS model was used to generate data by introducing artificial uncertainties in the range of ±5% in process conditions, such as temperature, flow rates, etc. The generated data was used to train support vector machines (SVM), Gaussian process regression (GPR), artificial neural networks (ANN), regression trees (RT), and ensemble trees (ET). Hyperparameter tuning was performed to enhance the prediction capabilities of GPR, ANN, SVM, ET and RT models. Performance analysis of the models indicates that GPR, ANN, and SVM with R2 values of 0.99, 0.978, and 0.979 and RMSE values of 0.108, 0.262, and 0.258, respectively performed better than the remaining models and had the prediction capability to capture the RON dependence on predictor variables. ET and RT had an R2 value of 0.94 and 0.89, respectively. The GPR model was used as a surrogate model for fitness function evaluations in two optimisation frameworks based on genetic algorithm and particle swarm method. Optimal parameter values found by the optimisation methodology increased the RON value by 3.52%. The proposed methodology of surrogate‐based optimisation will provide a platform for plant‐level implementation to realise the concept of industry 4.0 in the refinery. [ABSTRACT FROM AUTHOR]

Solar power tower technology has strong potential among the other concentration solar power techniques for large power generation. Therefore, it is necessary to make a new and efficient power conversion system for utilizing the solar power tower system. In present research, a novel combined cycle is proposed to generate power for the application of the solar power tower. The pre‐compression configuration of the Brayton cycle is used as a topping cycle in which helium is taken as the working fluid. The transcritical CO2 cycle is used as bottoming cycle for using the waste heat. The proposed system is investigated based on exergy, energy, and exergoenvironmental point of view using computational technique engineering equation solver. Also, the parametric analysis is carried out to check the impact of the different variables on the system performance. It is concluded that the overall plant's optimized thermal and exergy efficiencies are obtained as 31.59% and 33.12%, respectively, at 800 °C optimum temperature of combined cycle and 850 W m−2 of direct normal irradiation and 2.278 of compressor pressure ratio. However, exergetic stability factor and exergoenvironmental impact index are observed as 0.5952 and 0.6801 respectively. The present proposed system performs better than the previous studies with fewer components. [ABSTRACT FROM AUTHOR]

In the present study, a novel combined power cycle for solar power tower (SPT) system consisting of helium Brayton cycle (HBC) and transcritical CO2 (TCO2) for waste heat recovery is being studied for carbon‐free generation. The performance of the proposed SPT based combined cycle (SPT‐HBC‐TCO2 cycle) is compared with SPT based basic cycle (SPT‐HBC) based on exergoeconomic and thermodynamic analyses. It is concluded that the SPT‐based combined cycle (SPT‐HBC‐TCO2 cycle) produces a thermal efficiency of 32.39% and exergy efficiency of 34.68% with an electricity cost of 1.613 UScent kWh−1. The exergy and thermal efficiency of the SPT‐based combined cycle are enhanced by 13.18% and 13.21% respectively, while electricity cost is reduced by around 2% as compared to the SPT‐based basic cycle (SPT‐HBC) configuration at base conditions. A notable finding is that, despite the additional expenditures related to the bottoming cycle, the cost of electricity is lesser for the proposed combined cycle. Additionally, a comparison with the related prior published research exhibits that the performance of the current novel system is superior to that of the systems based on steam rankine cycle and supercritical CO2 cycles. [ABSTRACT FROM AUTHOR]