The CO2-Assisted Gravity Drainage process (GAGD) has been introduced to become one of the mostinfluential process to enhance oil recovery (EOR) methods in both secondary and tertiary recovery through immiscibleand miscible mode. Its advantages came from the ability of this process to provide gravity-stable oil displacement forenhancing oil recovery. Vertical injectors for CO2 gas have been placed at the crest of the pay zone to form a gas capwhich drain the oil towards the horizontal producing oil wells located above the oil-water-contact. The advantage ofhorizontal well is to provide big drainage area and small pressure drawdown due to the long penetration. Manysimulation and physical models of CO2-AGD process have been implemented

This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas.

Global technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid “Al2O3-Cu/water” nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simu

In this research, a novel synthesis of CaONPs has been developed via an environmentally friendly, green method. Garlic extract (Allium sativum) was used as a green-reducing and stabilizing agent for CaONPs. The average particle size of CaONPs was approximately 24.42 nm. The synthesized CaONPs were identified by using Fourier transform infrared (FT-IR) spectroscopy, U.V.-vis spectrum, X-ray diffraction (XRD), Field Emission-Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy, transmission electron microscopy (TEM), Energy Dispersive X-ray spectroscopy (EDX), Atomic Force Microscopy (AFM), and zeta potential (Zp) analysis. The current study highlights the notable applications for CaONPs. First, an antimicrobial assay revea

This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

In this work an experimental study is performed to evaluate the thermal performance
of locally made closed loop solar hot water system using a shell and helical coiled tube
heat exchanger as a storage tank. Several measurements are taken include inlet and outlet
temperatures of both collectors and supply water and temperature distribution within the
storage tank. This is beside the water flow rate in both collectors and load cycle. The
main parameters of the system are obtained.

This study concerns a new type of heat exchangers, which is that of shell-and-double concentric tube heat exchangers. The case studies include both design calculations and performance calculations.

       The new heat exchanger design was conducted according to Kern method. The volumetric flow rates were 3.6 m³/h and 7.63 m³/h for the hot oil and water respectively. The experimental parameters studied were: temperature, flow rate of hot oil, flow rate of cold water and pressure drop.

A comparison was made for the theoretical and experimental results and it was found that the percentage error for the hot oil outlet temperature was (- 1.6%). The percentage

Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in