Owing to the ever-growing impetus towards the development of eco-friendly and low carbon footprint energy solutions, biodiesel production and usage have been the subject of tremendous research efforts. The biodiesel production process is driven by several process parameters, which must be maintained at optimum levels to ensure high productivity. Since biodiesel productivity and quality are also dependent on the various raw materials involved in transesterification, physical experiments are necessary to make any estimation regarding them. However, a brute force approach of carrying out physical experiments until the optimal process parameters have been achieved will not succeed, due to a large number of process parameters and the underlying non-linear relation between the process parameters and responses. In this regard, a machine learning-based prediction approach is used in this paper to quantify the response features of the biodiesel production process as a function of the process parameters. Three powerful machine learning algorithms—linear regression, random forest regression and AdaBoost regression are comprehensively studied in this work. Furthermore, two separate examples—one involving biodiesel yield, the other regarding biodiesel free fatty acid conversion percentage—are illustrated. It is seen that both random forest regression and AdaBoost regression can achieve high accuracy in predictive modelling of biodiesel yield and free fatty acid conversion percentage. However, AdaBoost may be a more suitable approach for biodiesel production modelling, as it achieves the best accuracy amongst the tested algorithms. Moreover, AdaBoost can be more quickly deployed, as it was seen to be insensitive to number of regressors used.

Many commodities such as food, medicines & vaccines are required to be kept in commercial cold storages within a specified temperature range. problems arise in these systems within times of failure, power cuts, or transportation. The absence of refrigeration leads to an increase in temperature within the system which may lead to spoilage of products stored inside. Phase change materials may pose as a promising solution as they absorb the latent heat of the system at the expense of the phase change absorbing, latent heat. Ethylene glycol is selected as the phase change material due to its high latent heat content and negligible hazards. The system incorporated with phase change material was found to retain the cooling effect after cut off. In this paper, for investigation we conducted four experiments namely 0/0%, 75/25%, 50/50%, 100/0% Ethylene glycol and water respectively as phase change material for studying the retention of cooling within the system during power failures. The result shows that the retention of cooling in cold storage unit with 100% Ethylene glycol phase change material is very low 50% Ethylene glycol and 50% water has more retention of cooling. This indicates that addition of water in the phase change material increases the retention of cooling in cold storage unit.

Nanofluids are emerging as more suitable heat transfer fluid compare to conventionally used fluids for transferring heat in various engineering applications. Nanofluid is a fusion of very small quantity of nanoparticles and host fluid with considerable stability. The presence of nanoparticles in host fluid significantly enhance its thermal conductivity, which leads to the improvement in thermal performance. Introduction of submicron particles influence the viscus behaviour of the host fluid. In general viscosity enhancement is not desirable as it imposes a penalty in terms of increased pumping power in many engineering applications. Presence of more than one type of nanoparticles in host fluids provide opportunities to enhance thermal conductivity with control over other properties of resultant nanofluid. The nanofluid having more than one type of nanoparticles termed as hybrid nanofluid are in focus of researchers for investigation. A large variety of hybrid nanofluids are prepared and their properties investigated by various researchers. This review paper is an attempt to compile the research work related to preparation techniques, stability analysis and thermophysical properties of hybrid nanofluids. The potential applications of hybrid nanofluids and challenges associated with it are also discussed.

This In this paper combustion of hydrogen under unsteady and supersonic conditions has been presented. The combustor having an injector for injecting fuel parallel to the base. The main flow is also parallel to the base. Modeling of this supersonic combustion has been done using K-ε model with Finite rate chemistry combustion model. In supersonic combustion time available is very short for proper mixing. Intensity of heat release, duct geometry, injection techniques, and mixture (fuel + oxidizer) quality and flow regime are the predominating parameter which decides the flame stabilization. This numerical result demonstrates that flamelet approach is suitable in supersonic flows. Combustion characteristics for injected fuel and supersonic air flow in combustor are presented in this paper. The result shows that the mixing quality increases flame speed almost linearly. The stagnation temperature reaches up to 2420 k in the combustor.

The emissions from the vehicles causes for severe air pollution which resulted the development of stringent regulatory norms. Therefore there is a need of improvement in combustion phenomenon to decrease the NOx and PM, as they are directly dependent on combustion. To improve environmental conditions which are directly affecting human health, all automobile companies are endeavouring to satisfy strict emission standards. In this context stratified charge compression ignition (SCCI) engines seems promising and developing its application by incorporating the different types of combustion mode with the help of direct fuel injection and by ranging its capacity to full load condition. Alongside SCCI, a new concept of multi stage induction and Exhaust Gas Recirculation (EGR) can be incorporated in engine to reduce emissions, increase power output and efficiency. Various parameters have been considered to understand the combustion process for developing an engine to meet the requirements. The effect of different variables influencing the combustion process is highlighted.