Industrial machining workshops generate substantial quantities of aluminum wire offcuts and filings that cannot be re-entered into bulk metal recycling circuits, posing both a resource management challenge and a potential environmental burden. This study demonstrates a closed-loop valorization route in which this low-grade aluminum waste is converted into nanostructured aluminum oxide (Al2O3) nanoparticles (NPs) by two scalable synthesis pathways (i) chemo-thermal calcination of precipitated Al(OH)₃ at 1000 °C and 1200 °C for 1 and 4 h, and (ii) direct chemical precipitation via AlCl3/Na2CO3 reaction, and then deployed as a functional additive in water-based drilling fluids (WBDFs) used by the oil and gas industry. Comprehensive chara

The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

The present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials.  Good agreement between the average theoretical and measured cooli

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l

γ-Al2O3–NPs were synthesized by a green synthesis process based on Boswellia carterii resin extract and aluminum sulphate in an alkaline medium. Boswellia carterii resin extract is a significant reducing and stabilizing agent for synthesizing γ-Al2O3–NPs.Several techniques, including Fourier–transform infrared (FT-IR), UV–visible spectroscopy, x-ray diffraction, electron microscopy (XRD), energy dispersive x-ray (EDX), scanning electron microscopy (SEM), Transmission electron microscopy (TEM), and atomic force microscopy (AFM), were utilized to investigate the final product. XRD and SEM confirmed a plate-like crystalline structure with an average size of 17.5 nm. FT-IR analysis identified aluminum oxide stretching vibrations (655,

The evaluation of residual stresses (RS) induced by the friction stir welding (FSW) process is crucial in anticipating the performance of the welded structure. The existence of such residual stresses within a friction stir welded structure may lead to excessive distortion and weakness to afford the applied external loads. To assess quantitatively the effect of these residual stresses generated by FSW process, the current paper implements a Coupled Eulerian–Lagrangian (CEL) finite element simulation to analyze both thermal and subsequent resulted remaining stress environments in dissimilar friction stir welding of AA6061-T6 and AA2024-T3 alloys. The thermal analysis step was conducted first and followed by a mechanical analysis step in whi

Organic soil is problematic soils in geotechnical engineering due to its properties, as it is characterized by high compressibility and low bearing capacity. Therefore, several geotechnical techniques tried to stabilize and improve this soil type. In this study, sodium silicate was used to stabilize sand dune columns. The best sodium silicate concentration (9%) was used, and the stabilized sand dune columns were cured for seven days. The results for this soil were extracted using a numerical analysis program (Plaxis 3D, 2020).In the case of studying the effect of (L/D) (where ‘’L” and ‘’D’’ length and diameter of sand dune columns) of a single column of sand dunes stabilized with sodium silicate with a diff