ABSTRACT

This research included the preparation and characterization of new demulsifies from natural and synthetic polymers of chitosan and polyvinyl alcohol that are environmentally friendly and at the same time have high efficacy comparable to emulsifiers. imported foreign. The prepared compounds were examined using infrared spectroscopy and nuclear magnetic resonance spectroscopy, and all the spectral signals of the polymers were in good agreement with the chemical composition of the polymers. And the melting and decomposition that occur on polymers at high temperatures. The effect of the length and type of side chain in the compositions of polymers on the process of water separation of oil emulsions w

Steel corrosion in acidic environments is a critical industrial challenge, necessitating effective yet eco-friendly inhibitors. This study aims to address this problem by introducing a novel, green alternative: frankincense extract (FE). The distinctive contribution of this work lies in the comprehensive investigation of FE natural, sustainable, and economically viable resin as an effective corrosion inhibitor for carbon steel in 1 M HCl. The research employs an integrated methodology, including electrochemical techniques (potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS)), adsorption isotherm modeling, surface analysis (FT-IR and FESEM/EDX), and density functional theory (DFT) calculations. Key res

The principal forms of radiation dosage for humans from spontaneous radiation material are being recognized as radon and its progenitors in the interior environment. Radiation-related health risks are caused by radon in water supply, which can be inhaled or ingested. Materials and Methods: The solid-state CR-39 nuclear trace detectors method was using in this research for measuring accumulation of radioactivity in water supply in different locations of Iraq's southwest corner of Baghdad. In Baghdad district, 42 samples were selected from 14 regions (3 samples out of each region) and put in dosimeters for 50 days. Results: The mean radon concentration was 49.75 Bq/m3, that is lower than the internationally recognized limit of 1100 Bq /m3. Th

This paper presents the thermophysical properties of zinc oxide nanofluid that have been measured for experimental investigation. The main contribution of this study is to define the heat transfer characteristics of nanofluids. The measuring of these properties was carried out within a range of temperatures from 25 °C to 45 °C, volume fraction from 1 to 2 %, and the average nanoparticle diameter size is 25 nm, and the base fluid is water. The thermophysical properties, including viscosity and thermal conductivity, were measured by using Brookfield rotational Viscometer and Thermal Properties Analyzer, respectively. The result indicates that the thermophysical properties of zinc oxide nanofluid increasing with nanoparticle volume f

This work investigates the effect of the gas nitriding process on the surface layer microstructure and mechanical properties for steel 37, tool steel X155CrVMo12-1 and stainless steel 316L. Nitriding was conducted at a temperature of 550 °C for 2 hours during the first stage and at 750 °C for 4 hours during the second stage. SEM and X-ray diffraction tests were performed to evaluate the microstructural features and the major phases formed after surface treatment. SEM and X-ray diffraction tests were performed to assess the microstructural features and the primary phases formed after surface treatment. The new secondary precipitates were identified as γ′-Fe4N, ε (Fe2–3N), and α-Fe, exhibiting an uneven chain-like pattern wit

This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification