It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl

Markov chains are an application of stochastic models in operation research, helping the analysis and optimization of processes with random events and transitions. The method that will be deployed to obtain the transient solution to a Markov chain problem is an important part of this process. The present paper introduces a novel Ordinary Differential Equation (ODE) approach to solve the Markov chain problem. The probability distribution of a continuous-time Markov chain with an infinitesimal generator at a given time is considered, which is a resulting solution of the Chapman-Kolmogorov differential equation. This study presents a one-step second-derivative method with better accuracy in solving the first-order Initial Value Problem

Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 ^oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

The ability to inhibit corrosion of low carbon steel in a salt solution (3.5%NaCl) has been checked with three real expired drugs (Cloxacillin, Amoxicillin, Ceflaxin) with variable concentrations (0, 250, 500, 750) mg/L were examined in the weight loss. The inhibition efficiency of the Cloxacillin 750 mg/L showed the highest value (82.8125 %) and the best inhibitor of the rest of the antibiotics. The different concentrations of Cloxacillin drug (0, 250, 500, 750) mg/L and temperature (25, 35, 45, 55) ^oC were studied as variables with potentiodynamic polarization, Scanning Electron Microscopy (SEM) for surface morphology and electrochemical impedance spectroscopy (EIS) depending on current values and the resistance of charge to

This study provides an empirical and strategic contribution to the revenue management literature by investigating the transition from static cost-plus pricing to a dynamic, elasticity-based framework within state-owned extractive industries (SOEs). While dynamic pricing is extensively studied in flexible, data-rich private markets, its application in structurally rigid SOEs within transitional economies remains a critical research gap. Drawing on primary fiscal and production data from the 2024 fiscal year of the General Company for Mining Industries (SCMI), we developed a mathematical model to determine optimal pricing ( ) based on marginal cost principles and demand elasticity. The findings demonstrate that replacing rigid accounting rout