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Nanofluid-assisted enhanced sealing security for efficient geological hydrogen storage in Saudi Arabian basalt
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The modification of hydrophobic rock surfaces to the water-wet state via nanofluid treatment has shown promise in enhancing their geological storage capabilities and the efficiency of carbon dioxide (CO2) and hydrogen (H2) containment. Despite this, the specific influence of silica (SiO2) nanoparticles on the interactions between H2, brine, and rock within basaltic formations remains underexplored. The present study focuses on the effect of SiO2 nanoparticles on the wettability of Saudi Arabian basalt (SAB) under downhole conditions (323 K and pressures ranging from 1 to 20 MPa) by using the tilted plate technique to measure the contact angles between H2/brine and the rock surfaces. The findings reveal that the SAB's hydrophobicity intensifies in the presence of organic acids, with significant increases in both advancing (θa) and receding (θr) contact angles upon exposure to organic acid at 323 K and 20 MPa. Contrastingly, the application of SiO2 nanoparticles under these conditions results in a marked shift towards hydrophilicity, with θa and θr decreasing substantially, thus indicating an optimal nanoparticle concentration (0.1 wt% SiO2) for effecting the transition from H2-wet to water-wet states. This change in wettability aligns with the known pressure-dependent behavior of contact angles. Moreover, the treatment of organically-aged basalt with 0.1 wt% SiO2 nanofluids at 20 MPa and 323 K enhances the H2 column height significantly, from −424 m to 4340 m, suggesting a reduced risk of H2 migration across the caprock and thereby enhancing both the structural/residual trapping and containment security of H2 within the basaltic formations of Saudi Arabia. This article highlights the crucial role of SiO2 nanofluids in improving the efficacy of H2 storage in basalt, offering a new insight towards the optimization of geological storage solutions for hydrogen, a critical component in the transition to a sustainable energy future.

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Design of L1 -Adaptive Controller for Single Axis Positioning Table
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L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of  L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.

    The tracking and steady state performances of both controllers have been assessed fo

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Publication Date
Sat Oct 31 2020
Journal Name
Eastern-european Journal Of Enterprise Technologies
Design and development of high-accuracy machine for wire bending
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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem
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Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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Publication Date
Sat Jul 09 2022
Journal Name
Wireless Communications And Mobile Computing
An Optimized Approach for Industrial IoT Based on Edge Computing
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Wed May 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Simulation Physical and Chemical Blowing Agents for Polyurethane Foam Production
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Abstract<p>Use of computer simulation to quantify the effectiveness of blowing agents can be an effective tool for optimizing formulations and for the adopting of new blowing agents. This paper focuses on a mass balance on blowing agent during foaming including the quantification of the amount that stays in the resin, the amount that ends up in the foam cells, and the pressure of the blowing agent in the foam cells. Experimental data is presented both in the sense of developing the simulation capabilities and the validating of simulation results.</p>
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A Finite Element Analysis for the Damaged Rotating Composite Blade
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In this paper, the finite element method is used to study the dynamic behavior of the damaged rotating composite blade. Three dimensional, finite element programs were developed using a nine node laminated shell as a discretization element for the blade structure (the same element type is used for damaged and non-damaged structure). In this analysis the initial stress effect (geometric stiffness) and other rotational effects except the carioles acceleration effect are included.  The investigation covers the effect speed of rotation, aspect ratio, skew angle, pre-twist angle, radius to length, layer lamination and fiber orientation of composite blade. After modeling a non-damaged rotating composite blade, the work procedure was to ap

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Publication Date
Fri Apr 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An adaptive neural control methodology design for dynamics mobile robot
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