KUFA JOURNAL OF ENGINEERING

Diwaniya is one of the middle Euphrates cities through which the Euphrates River passes through. The Euphrates section that passes through Diwaniya city is called (Shatt al-Diwaniya). This study deals with the river water quality for the period between 2015 and 2023 at that section. The aim of study is to assess the influence of pollution on the sustainability quality of Shatt al-Diwaniyah area using the Nemerow pollution index (NPI) based on artificial neural network (ANN) and regression analysis model (RA). To determine critical water performance parameters for the river section, investigation is required precisely to find out which characteristics and stations contribute to river pollution. Physicochemical water parameters such as Biochemical Oxygen Demand (BOD5), Total Dissolved Solid (TDS), pH, Dissolved Oxygen (DO), Nitrate (NO3), and phosphates (PO4) along the length of the river were measured by fifteen sites from Diwaniya\'s river during (2015-2023). NPI was calculated for the water samples in each station of examination. The growing NPI value indicated that the river water quality in this section is deteriorating. Where the river\'s NPI values vary between 2.14 and 3.48, indicating that its water quality is slightly polluted. Mathematical models of artificial neural networks and regression concluded that the most polluted parameter is phosphate PO4 which is concentrated in station 15 which recapitulates that river water is not suitable for use as a source of drinking water, besides, it can still be consumed to irrigate agricultural property and plants

In this study, a comparison between thermal conductivity and dynamic viscosity of a pure propylene glycol liquid as a solar thermal fluid and its nanofluid has been carried out using different concentrations of nanoparticles. Aluminum oxide nanoparticles (α phase - size 50-90 nm) were added to the pure propylene glycol liquid at three different concentrations (0.2%, 0.4%, and 0.6%). The different thermal fluids (pure and nano-propylene glycol) were tested at different temperatures (20, 60, 100, 140, 180°C) on five different days. Regarding pure liquid, as temperature increases the thermal conductivity and viscosity drop for all experiment days. The minimum value for thermal conductivity and viscosity were recorded on the first day test at 180°C temperature with (k=0.13 W/m.K and µ=13.2 centipoise). However, adding the nanoparticles has reversed the temperature effect on the resulting nanofluids thermal conductivity. Where k reached its maximum value (0.307 W/m.K) at 180 °C for 0.6% concentration nanofluid on day (60) recording an improvement of (136.14%). Viscosity in contrast kept decreasing with temperature rise for each nanoparticles concentration. Yet the nanoparticles concentration proportional directly with dynamic viscosity at constant temperature. In this contest, on day (60) test, the viscosity at 20°C for both pure PG and 0.6% nano-PG were 58 and 64 centipoises, respectively. While at 180°C, µ= 14.9 and 21 centipoises respectively. The behaviour of PG nanofluid dynamic viscosity in different concentrations and different temperatures has almost the same response to concentration and temperature for ethylene glycol based nanofluid. Finally, SEM images showed homogeneity and distribution of the nanofluid at a concentration of 0.4%, and some aggregates were detected at a concentration of 0.6%.

Functionally Graded Materials (FGMs) represent a notable advancement in materials research as they enable the smooth incorporation of distinct characteristics from various materials. This study examines the vibrational characteristics of functionally graded ceramic-metal composite beams via the use of Finite Element Analysis (FEA) in MATLAB. To capture and study the dynamic response of the replicas. The focus of this investigation is on ceramic and metallic materials that are represented by power-law distribution along their length. In order to include material variation in the global mass and stiffness matrices, the beam segments have been divided into many sections. In this regard, the objective was to calculate natural frequencies and mode shapes of these beams using eigenvalue problems. Results obtained reveal that MATLAB is a reliable tool for investigating dynamic properties of Functionally Graded Materials (FGMs) because it has proven to be user-friendly as well. The present work shows how to use functionally graded indices and porosity on vibration characteristics of composite beams.

The study demonstrates the efficiency of using recycled materials to create solar water heaters, in particular in enhancing heat transfer. The innovative heater surpasses traditional commercial models in performance, offering a sustainable solution for residential water heating. The research, conducted in Baghdad, Iraq, entailed reusing heat exchangers from an outdated air conditioner to serve as a solar water heater collector. Equipped with a thermal insulator ,and an electronic control system, the heater achieved impressive results, raising the water temperature to 55 o C in just 30 minutes with a thermal efficiency of 83.122%. While the commercial heater took an hour and a half to heat the water to 57 o C. By integrating features such as serpentine fins, black coating and foam insulation, the system increases heat absorption and reduces losses. The electronic control system enhances the efficiency of heat transfer, which makes the homemade solar heater a viable and affordable option whose manufacture costs no more than 30,000 IQD while the commercial one costs 179,000 IQD. Both are environmentally friendly for residential use. In general, the research emphasizes the possibility of using recycled materials to develop efficient and sustainable solar water heating systems.

The bond is considered one of the factors that plays an important role in the behavior of the reinforced concrete structural elements. In recent years, using the glass fiber reinforced polymer (GFRP) as an alternative to steel bars is needed to verify its performance in the structures. In this study, the bond between the concrete and GFRP bars is investigated through using two different surface enhancement techniques (sand and steel fibers). Fourteen beam specimens were cast and tested considering three different parameters, concrete compressive strength (55 and 78 MPa), bar diameter size (6mm and 10 mm) and the surface scheme (non-coated, sand-coated and steel fiber-coated). The experimental work included the recording of the bond stress and corresponding slip. For a certain value of concrete grade and 6 mm bar diameter, the bond behavior improved by 206% and 198% for the sand-coated surface and steel fiber-coated bars as compared to non-coated bars, respectively. For the same bar size (6mm), the best enhancement in bond strength was found by (61%) for the non-coated surface when the concrete compressive strength increased from 55 to 78 MPa. The use of larger bar diameter for the same concrete compressive strength, the higher bond strength improvement was 55% for the non-coated surface bar. From the bond stress-slip curves, the tests indicate that when the surface of the GFRP bars is coated by sand, it will give the best enhancement in the bond strength.

Android malware has grown steadily into a major internet threat. Despite efforts to identify and categorize malware in seemingly safe Android apps, addressing this issue is still lacking. Therefore, understanding the unique behaviors of common Android malware categories is essential. This study utilizes machine learning techniques namely, K-Nearest Neighbor, Random Forest and Decision Tree to classify Android malware based on dynamic analysis. As feature selection and reduction techniques, Mutual Information and Principle Component Analysis are used. The research analyzes a large dataset, containing fourteen primary malware categories using the CCCS-CIC-AndMal2020 dataset. Unlike previous research, the proposed method makes a balance between the number of features and classifiers’ performance, resulting in an overall detection accuracy of 98% in the fourteen analyzed categories and excluding 78.87% of the original dataset’s features. The research, thus, introduces an efficient Android malware detection method that reduces the computational cost and improves the classification accuracy.

Evaluation of residual sludge and water quality of a treatment plant is an integrated activity through the analysis of physical and chemical properties related to health, environment, and specific water used. This study aimed to address the characteristics and properties of the raw water, treated water, and the residual sludge from Al-Wihda water treatment plant (WTP) based on two stage. The first is the historical data from 2018 to 2023 and the results showed that the maximum amount of sludge produced was 259.2 kg/1000 m3 exceeded the reported limit, while turbidity and TSS have a significant contribution to the amount of sludge produced by Al-Wihda WTP. The second, experimental tests were carried out for the residual sludge in the sedimentation tank for the duration (15 July-15 December, 2023) and the results showed that the maximum TSS in residual sludge was about 1585 m3/d, while the maximum COD was about 200 mg/L which exceeded the Iraqi standard limit (100 mg/L). The study concluded that residual sludge is dependent on the amount of TSS contained in the raw water and contains high amount of COD that could be used for the treatment of saline wastewater.