Nanofluids are proven to be efficient agents for wettability alteration in subsurface applications including enhanced oil recovery (EOR). Nanofluids can also be used for CO2-storage applications where the CO2-wet rocks can be rendered strongly water-wet, however no attention has been given to this aspect in the past. Thus in this work we presents contact angle (θ) measurements for CO2/brine/calcite system as function of pressure (0.1 MPa, 5 MPa, 10 MPa, 15 MPa, and 20 MPa), temperature (23 °C, 50 °C and 70 °C), and salinity (0, 5, 10, 15, and 20% NaCl) before and after nano-treatment to address the wettability alteration efficiency. Moreover, the effect of treatment pressure and temperature, treatment fluid concentration (SiO2 wt%) and the period of nano-treatment on the wettability of calcite is examined. We find that nano-treatment alters the wettability significantly i.e. intermediate-wet calcite turns strongly water-wet after treatment (e.g. at 20 MPa and 50 °C, θ = 64° for intermediate-wet calcite, and θ = 28° for nano-treated calcite). Consequently, pre-injection of nanofluids will significantly enhanced the storage potential. It was also found that the permanent shift in wettability after nano-treatment is a function of treatment conditions including temperature, pressure, and treatment duration time and that surfaces treated under high pressure and low temperature yield better wettability alteration efficiency. We point out that the change in wettability is attributed to the changes in surface properties of the nano-treated sample. The results of the study thus depict that nanoparticles can significantly enhance storage potential and de-risk storage projects.
This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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Two experiments were carried out, the first at the College of Agriculture - University of Baghdad during spring season 2017 Everest cv. class (Elite) was used to study the effect of foliar application of calcium and magnesium and addition of humic acid to the soil on potato growth and yield, The layout of the experiment was factorial within RCBD design using three replicates. Calcium and Magnesium sprayed with concentrations (0, 500, 1000 mg.L-1), while the humic acid was added to the soil with (0, 0.75 gm.m2), The second experiment included storage of tubers produced from the spring season, with to study the effect of field treatments on improving the storability of the tubers. The results showed that the treatment of calci
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A twisted-fin array as an innovative structure for intensifying the charging response of a phase-change material (PCM) within a shell-and-tube storage system is introduced in this work. A three-dimensional model describing the thermal management with charging phase change process in PCM was developed and numerically analyzed by the enthalpy-porosity method using commercial CFD software. Efficacy of the proposed structure of fins for performing better heat communication between the active heating surface and the adjacent layers of PCM was verified via comparing with conventional longitudinal fins within the same design limitations of fin material and volume usage. Optimization of the fin geometric parameters including the pitch, numb
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Vascular patterns were seen to be a probable identification characteristic of the biometric system. Since then, many studies have investigated and proposed different techniques which exploited this feature and used it for the identification and verification purposes. The conventional biometric features like the iris, fingerprints and face recognition have been thoroughly investigated, however, during the past few years, finger vein patterns have been recognized as a reliable biometric feature. This study discusses the application of the vein biometric system. Though the vein pattern can be a very appealing topic of research, there are many challenges in this field and some improvements need to be carried out. Here, the researchers reviewed
... Show MoreUsing the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreEnvironmental Control Systems form one of the integral tasks of the designer, resulting from his/her acquaintance with the nature of sites and the way they are deployed to achieve modern space entity which is witnessing significant development in the field of interior design.Good deployment of these systems offer us, as designers, high potential and several varied solutions to configure internal spaces characterised as a fertile field of study and knowledge.The research problem was identified in the marginalisation of the importance of Environmental Control Systems as an important designing factor to achieve integrated design. The research problem was demonstrated in Chapter One, along with defining the objectives and formulating
Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
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