Catalytic reforming is an important intermediate in the processing of crude (naphtha in particular) to obtain gasoline. The catalyst used in the process (platinum) is quite expensive and may negatively impact the business if not used judiciously. The aforesaid not only refers to the reduction in loss of the catalyst per unit of gasoline produced but also to the manufacturing of an environmentally friendlier product alongside which is the need of the planet and also a necessity to meet the increasingly strict government norms. In order to meet the above requirements, various refineries around the world use various well-known conventional methods which depend on the quality and quantity of crude manufactured by them.
This paper focuses on highlighting recent advancements in methods of catalytic regeneration (CR) in the reforming unit of petroleum industries to produce high octane gasoline, without any major replacements in their existing setup. Research papers formulated by the application of methodologies involving non-linear models and real-time refinery data have only been considered to avoid any deviations/errors in practical applications. In-depth analysis of these papers has led to the origin of some ideas which have been included as suggestions and can be considered as subjects of further research. In all, the objective of the paper is to serve as a reference for researchers and engineers working on devising optimum methods to improve the regeneration of reforming catalysts.

Despite many years of development in the field of rotor dynamics, many issues still need to be resolved. This is due to the fact that turbomachines, even those with low output power, have a very complex design. The author of this article would like to signal these issues in the form of several questions, to which there are no precise answers. The questions are as follows: How can we build a coherent dynamic model of a turbomachine whose some subsystems have non-linear characteristics? How can we consider the so-called prehistory in our analysis, namely, the relation between future dynamic states and previous ones? Is heuristic modelling the future of rotor dynamics? What phenomena may occur when the stability limit of the system is exceeded? The attempt to find answers to these questions constitutes the subject of this article. There are obviously more similar questions, which encourage researchers from all over the world to further their research.

The study makes an attempt to model a complete vibrating guitar including its non-linear features, specifically the tension-compression of truss rod and tension of strings. The purpose of such a model is to examine the influence of design parameters on tone. Most experimental studies are flawed by uncertainties introduced by materials and assembly of an instrument. Since numerical modelling of instruments allows for deterministic control over design parameters, a detailed numerical model of folk guitar was analysed and an experimental study was performed in order to simulate the excitation and measurement of guitar vibration. The virtual guitar was set up like a real guitar in a series of geometrically non-linear analyses. Balancing of strings and truss rod tension resulted in a realistic initial state of deformation, which affected the subsequent spectral analyses carried out after dynamic simulations. Design parameters of the guitar were freely manipulated without introducing unwanted uncertainties typical for experimental studies. The study highlights the importance of acoustic medium in numerical models.

Today’s electricity management mainly focuses on smart grid implementation for better power utilization. Supply-demand balancing, and high operating costs are still considered the most challenging factors in the smart grid. To overcome this drawback, a Markov fuzzy real-time demand-side manager (MARKOV FRDSM) is proposed to reduce the operating cost of the smart grid system and maintain a supply-demand balance in an uncertain environment. In addition, a non-linear model predictive controller (NMPC) is designed to give a global solution to the non-linear optimization problem with real-time requirements based on the uncertainties over the forecasted load demands and current load status. The proposed MARKOV FRDSM provides a faster scale power allocation concerning fuzzy optimization and deals with uncertainties and imprecision. The implemented results show the proposed MARKOV FRDSM model reduces the cost of operation of the microgrid by 1.95%, 1.16%, and 1.09% than the existing method such as differential evolution and real coded genetic algorithm and maintains the supply-demand balance in the microgrid.