New nanotechnology-based approaches are increasingly being investigated for enhanced oil recovery (EOR), with a particular focus on heavy oil reservoirs. Typically, the addition of a polymer to an injection fluid advances the sweep efficiency and mobility ratio of the fluid and leads to a higher crude oil recovery rate. However, harsh reservoir conditions, including high formation salinity and temperature, can limit the performance of such polymer fluids. Recently, nanofluids, that is, dispersions of nanoparticles (NPs) in a base fluid, have been recommended as EOR fluids; however, such nanofluids are unstable, even under ambient conditions. In this work, a combination of ZrO2 NPs and the polyacrylamide (PAM) polymer (ZrO2 NPs–PAM) was us

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

The adsorption of copper ions onto produced activated carbon from banana peels (with particle size 250 µm) in a single component system with applying magnetic field has been studied using fixed bed adsorber. The fixed bed breakthrough curves for the copper ions were investigated. The adsorption capacity for Cu (II) was investigated. It was found that 1) the exposure distance (E.D) and strength of magnetic field (B), affected the degree of adsorption; and 2) experiments showed that removal of Cu ions and accumulative adsorption capacity of adsorbent increase as the exposure distance and strength of magnetic field increase.
 

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

The technology of subsurface soil water retention (SWRT) uses a polyethylene ‎trough that is fixed under the root zone of the plant. It is a modern technology to increase the values of water ‎use efficiency, plant productivity and saving irrigation water by applying as little irrigation water ‎as possible. This study work aims at improving the crop yield and water use efficiency of a cucumber plant with less applied irrigation water by installing membrane trough below the soil surface. The field experiment was conducted in the Hawr Rajab District of ‎Baghdad Governorate in Winter 2018 for testing various trickle irrigation ‎systems. Two agricultural ‎treatment plots were utilized in a greenhouse for the compa

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

Biodiesel production process was attracted more attention recently due to the surplus quantity of glycerol (G) as a byproduct from the process. Glycerol Utilization must take in to consideration to fix this issue also, to ensure biodiesel industry sustainability. Highly amount of Glycerol converted to more benefit material Glycerol carbonate (GC) was one of the most allurement compound derived from glycerol by transesterification of glycerol with dimethyl carbonate (DMC). Various parameters have highly impact on transesterification was investigated like catalyst loading (1-5) %wt., molar ratio of DMC: glycerol (5:1 – 1:1), reaction time (30 - 150) min and temperature (40 – 80) ᴼC. The Optimum glycerol carbonate yie

This research is devoted to investigating the thermal buckling analysis behaviour of laminated composite plates subjected to uniform and non-uniform temperature fields by applying an analytical model based on a refined plate theory (RPT) with five unknown independent variables. The theory accounts for the parabolic distribution of the transverse shear strains through the plate thickness and satisfies the zero-traction boundary condition on the surface without using shear correction factors; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by using the virtual work principle and solved via Navier-type analytical procedure to obtain critica