Wasit Journal of Engineering Sciences

Bidirectional DC-DC converters allow power to be transferred in any direction between two electrical sources. These converters are increasingly employed in a variety of applications, including battery chargers and dischargers, energy storage devices, electrical vehicle motor drives, aircraft power systems, telecom power supplies, and others, due to their ability to reverse the direction of power flow. One of these basic types of bidirectional DC-DC converters is the SEPIC-ZETA converter. In this paper, the structure of this converter has been studied when MOSFET power switches are employed. Also, an electrical thermal analysis, which is based on the ambient temperature (between 25 °C and 40 °C), has been employed by using two MOSFET models (UJ3C065080K3S and SCT50N120). The study shows the effects of utilizing different MOSFET models on power losses and thermal analysis. According to the simulation results, the junction temperature of the MOSFET was 151.38 °C in the forwarding mode and for the first model (UJ3C065080K3S) at T = 40 °C, while the MOSFET junction temperature was 158.5 °C in the backward mode. In the second model (SCT50N120) and at the same T = 40°C, the MOSFET junction temperature exceeds 130.6°C in the forwarding mode. When the converter was operating in backward mode, its junction temperature was 128.7 °C. The bidirectional SEPIC-ZETA converter performs better in the second model of the MOSFET (SCT50N120).

The use of bio-signal is very crucial, providing enormous information concerning health and well-being of the individual. such signals can be measured and monitored by specialized devices to each bio-signal, for instance, the electrocardiogram (ECG), electromyography (EMG), electroencephalogram (EEG), and electrooculogram (EOG). Due to use of such devices, these signals could be utilized for several objectives. As it is observed in the devices of medical detection and Human to Machine Interactions (HCI). This paper presents a low-cost bio-signal collection device which is having the ability to record ECG, EMG, and EOG signals. Furthermore, STM32F103C8 system is used in Analog to Digital Conversion (ADC), with its particular application. An application has been developed in order to allow admins to observe and save the data signal simultaneously. This application has been developed by using C++ programming language and MATLAB’s code. The data signal is recorded in a format of mat file, which can be studied in details in the proposed system. This system is capitalized on Universal Serial Bus (USB) wired communication link, which is used to transmit the bio-signal through, that guarantees the safety ,avoid noise and interference. The system shows its compatiblity with various operating systems, such as, Windows, Linux, and Mac.

The development of machine learning strategies has made it possible to diagnose some disease automatically based on data obtained from medical imaging. Brain age is one of the factors that can be used as an indicator of cognitive well-being. Recent advancements in machine learning have made it possible for computers to anticipate classification and prediction outcomes more accurately than humans.

In this study, five widely used machine learning regression models (Linear support vector regression (L-SVR), radial basis function support vector regression (RBF-SVR), relevance vector regression (RVR), Elastic Net and Gaussian process regression (GPR)) were trained and evaluated to predict brain age using volumes of brain regions data. Moreover, a dimensionality reduction technique was utilized to reduce the dimensionality of the input feature space. The data were collected from one hundred and eleven participants.

The results showed no performance difference amongst models trained on the same type of data, suggesting that the type of input data had a stronger influence on prediction performance than the model choice. The experimental results indicated that the GPR was the best fit model (R2=0.57, R=0.75) among the other regression models while the G-SVR was the worst fit model (R2=0.0006, R=0.025) with such number of the input data.

Generally, open channel lateral intake structures are extensively used in the water and environmental projects. The passing flow at side intakes is mostly turbulence containing vertical and horizontal spiral currents causing sediment problems. The flow separation region in the intake channel is critical for sediment and water distribution during the diversion. It denotes a large reduction in the possible breadth of the lateral branch's incoming flow, as well as a place where sediment has collected, obstructing the deviated flow.

This study aims to reduce and control sediment problems at the lateral intake by improving the flow pattern at this area using three-dimensional numerical models simulated in CFD, ANSYS Fluent software. The correctness of the three-dimensional numerical model was validated by a previous experimental study that showed good accuracy. Different discharge ratios and a range of shape designs were used to simulate the flow pattern at the intake channel junction. The findings demonstrated that the separation zone measurements minimize as the discharge ratio increases. Based on the changing the intake entrance shape results, cutting the outer boundary of the canal entrance widens the separation area, as well as an additional separation spot as the cutting size grows. In contrast with the internal chamfered angle models of the intake inlet, the separation area dimensions are reduced. The chamfered and rounded inner intake edge model with 30o angle to the main channel flow direction and the length of the chamfered side that normal to the flow direction (c value ) equal to three-quarters of the intake width was noticed to be the best design for lessening separation extent in this study. Thereby, the reduction ratio of the separation area width and length reaches in this case to 90% and 72%, respectively.

Excessive use of nitrogen fertilizers has increased nitrate concentrations in groundwater, which poses a health hazard from nitrate-contaminated drinking water and contributes to eutrophication. Nitrate removal from water systems has been carefully studied; However, new, low-cost solutions are urgently needed. Clay and terracotta minerals are commonly used in environmental applications due to their non-toxicity, global availability, low cost, and physical and chemical properties (ion-exchange capacity, high surface area, high adsorption, and catalytic properties). Although most are used to reduce cationic pollutants, depending on the method of modification or the materials with which they are mixed, they can be equally effective in removing anionic contamination. The goal of the study is to treat water containing excessive concentrations of nitrates to produce water of acceptable environmental specifications and to evaluate the performance of fired clay as a low-cost and environmentally friendly water treatment material.

Climate change could affect the world's water resources system, especially at the level of the basin. Climate change would impact streamflow and corresponding future water resources. The lower basin of the Diyala River is currently experiencing water shortage and contamination issues. This study aims to use Water Evaluation And Planning (WEAP) model to create an integrated modeling system for evaluating the effects of climate change on water supply and demand within the lower Diyala River basin. The WEAP model was calibrated and verified employing monthly streamflow data from the Diyala River outflow station. Following that, the calibrated model was loaded with various future scenarios ranging from 2020-2045. Future scenarios used included the reference scenario, the high population growth rate scenario, and the climate change scenario. The results indicated that the WEAP model accurately predicted the basin's water supply and demand, with RMSE, NSE, and R² values of 0.85, 0.91, and 0.867, respectively, throughout the validation period. Furthermore, Water demand and supply were found to be unmet in all projected future scenarios, showing that sustainable water management in the lower basin of the Diyala River is highly required.

From low-grade heat sources, the organic Rankine cycle may be exploited to create power. The thermal efficiency of the organic Rankine cycle is affected by the value of the lowest cycle temperature, which is the condensation temperature. This study looks at the effect of condensation temperature on the efficiency of energy systems that use organic Rankine cycles. At a condensing temperature of 10–20 °C, the ORC thermal efficiency is calculated. R134a working fluid was used in the study. The expander's power output was boosted to 0.09765 kW by decreasing the condensing temperature. Additionally, the thermal efficiency has been enhanced by 3.826 %. At a minimum temperature of 10 °C, the expander speed at 595 rpm. Exergy efficiency has an 18.26 %. is shown that lowering the condensing temperature increased the ORC system's thermal efficiency and energy output.

Researchers in heat transfer are paying close attention to nanofluids because of their potential as high-performance thermal transport media. In light of natural convection's enormous significance, the addition of nanoparticles significantly enhances the thermophysical properties of the nanofluids compared to the base fluid. In this study, numerical work was used to evaluate the influence of CuO nanoparticles on natural convection with the magnetohydrodynamic (MHD) flow in a square cavity. The hollow's left and right vertical walls were maintained at different temperatures, and the top and bottom walls of the cavity were each insulated. This numerical study applied a horizontal magnetic field with uniform strength. Results were obtained for a variety of Hartmann numbers ranging from 0–300, Rayleigh numbers going from 2.76E+8 to 6.89E+8, and solid volume fractions ranging from 0 to 1.5%. Results showed that the heat transfer coefficient and Nusselt number values decreased with the increase in the values of the Hartmann number, except for the heat transfer coefficients at Ha=100 and 150 were larger than the heat transfer coefficients at Ha= 0. The maximum heat transfer coefficient enhancement was 40.8% at 1.5% volume concentration of CuO nanoparticles, Ra= 6.7E+8 and Ha=100 compared to water at Ha=0. The maximum enhancement of the Nusselt number was found to be 28.5% at a 1.5% volume concentration of CuO nanoparticles Ra= 6.7E+8 and Ha=100 compared to water at Ha=0. At a 1.5% volume concentration of CuO nanoparticles, Ra= 6.7E+8 and Ha=100, the increase in the heat transfer coefficient was 56 %, and the rise in the Nusselt number was 43 % compared to water at Ha=100.

References

In concentrated solar energy applications, the Stirling engine is the optimum option for extracting mechanical work. The engine's most notable features are minimal noise, vibration, and pollution, as well as its capacity to function with any external heat source, including biomass, solar energy, and industrial waste. The gamma-type STE-1008 Stirling engine is the subject of our research. This engine can handle a maximum charging pressure of 10 bar. The engine is divided into two sections (expansion and compression) and three heat exchangers (regenerator, cooler, and heater). The cooler is a finned aluminium heat exchanger with 144 internal fins, each with a cross-sectional area of 1 mm by 10 mm. The regenerator is fitted with a diameter of 31 m and a volumetric porosity of 90%. This investigation employed a random fiber with three different metals: stainless steel, copper, and aluminium. Nitrogen and air served as the working fluids. From the results, stainless steel, copper, and aluminium regenerators produced 583 W, 562 W, and 553 W, respectively. When nitrogen is utilized at 500 °C, the engine generates 11 N.m of torque compared to 8.5 N.m when air is used, and the engine has a thermal efficiency of 19% compared to 15% when air is used. The results of other researchers were used to compare and validate our model. With errors of no more than 12%, the results were close enough to the experimental data to be useful.

Solar power, thermal storage facilities, reactor cooling and microelectronic devices are all examples of renewable energy use natural convection heat transfer from a heated supplier to a chilly environment or enclosure. The purpose of this research is to investigate the influence of porous media on the convective heat transfer coefficient and the modified Rayleigh number as a function of the cavity's aspect ratio. This study investigated the free convective 3D flow then heat transmission in a cavity that has a width of 20 cm in width, a depth of 2.7 cm in depth, and varying heights of 20, 25 and 30 cm. The cavity has an anisotropic fluid-filled porous wavy enclosure with steady-state incompressible flow. The bottom surface radiates heat with a steady heat flux. (300, 500, 700, 900, 1100 W/m²), while the top is exposed to the environment at 25 C˚ (h=25 W/m²) and other walls are adiabatic. Rayleigh’s number range (3.13* to 2.61* ) (1.9* ), aspect ratio (As=1,1.25,1.5), porosity (ɛ=0.36), permeability (k=7.593* m²), amplitude (a=1.5 cm). The findings indicate that increasing the heat flow alters the temperature profile. progressively increases the pressure and velocity. The highest value for the heat transfer coefficient and modified Rayleigh No. was obtained when the aspect ratio was 1.

The current numerical analysis was utilised to compare the hemodynamic effects caused by flow disruptions in coronary arteries with and without stenosis in order to evaluate the hemodynamic importance of patient-specific coronary stenosis using Computational Fluid Dynamics (CFD) to provide information to the public, particularly surgeons, and assist them in reducing the risk of stenosis. Assuming the flow is turbulent and non-Newtonian viscosity, the Carreau model is incorporated by utilizing STAR-CCM+ 2021.2.1. The test model is a patient-specific coronary stenosis with area stenosis (60%). The velocity, shear stress, and strain rate were evaluated and revealed that the stenosed artery experiences more hemodynamic impacts as the flow rate increases compared to the normal artery. The turbulent kinetic energy and turbulent viscosity ratio findings showed that the TKE and TVR are almost the same downstream of the stenoses, with the TKE and TVR being somewhat higher with the stenosed artery model than the unstenosed artery model, and it increases as the flow increases. Moreover, to determine the stenosis severity, the coefficient of pressure drop (CDP) and lesion flow coefficient (LFC) were used and showed that the CDP value be higher in stenosed artery (107pa) compared to a normal artery (5.2pa) but it was less when the flow increased (84.4pa), (2.5pa) respectively. whereas the LFC value in the stenoses artery is higher (0.61) and rises as flow increases (0.69).

In this study, a simulation for two story building associated with a vertical solar chimney was made by using ANSYS 2022/R1. The study conducted under the climatic conditions of Al-kut city/ Iraq on 5/8/2016. The study involved a comparison between the ventilation performance of SC before and after adding Energy Storage. Al-dura, RT-42, and block-shaped paraffin wax were the three types of PCM that were studied in order to find the optimum ES. The numerical results showed that the best Paraffin wax was Al-dura depending on the average Air Change per Hour (ACH), average indoor temperature, and the ventilation period after sunset. Comparing with the 1st model (without ES), After adding Al-dura wax, the ACH increased by 18.3 % and 9.95 % for 1st and 2nd floor, respectively. whereas, the indoor temperature was reduced by 1.17 k and 0.68 k on the 1st and 2nd floor, respectively. As for the ventilation period, it was lasted for 5 h after sunset.

In this paper, the improvement of heat exchange in a compact heat exchanger that is used in the automotive cooling system is numerically studied due to the importance that this part of the automotive represents in removing the heat generated in the automotive engine. The study adopted CFD simulation to introduce a new design of radiator that included changing the geometry and material of the tube while maintaining the same cross-section area In addition, the study also included replacing the shape of the fins from the louver to plain fin with the increase in the number of tubes. The study used a water-Ethylene glycol mixture (50:50) as a hot fluid with four flow rates (10, 12, 18, 24) l/h, (75, 85, 95) °C inlet temperature, and air as a cold fluid with 1.5, 2.5, 4.5, 5.5) m/s and (35) °C inlet temperature. Through the results obtained, the designed model appeared to have a higher thermal performance than the standard model due to the material and shape of the tube and fins. The designed model performed well, achieving an improvement ratio of (18.6%) for the heat transfer rate, (13.8%) for the overall heat transfer coefficient for the hot fluid, and (29.8%) for the air-side heat transfer coefficient

Most developing countries that bypass rivers are concerned about water pollutants. Water quality within the permissible limits for agricultural, industrial, and drinking reasons is a difficult problem to solve. On the basis of their importance, ten physical and chemical parameters were chosen for this investigation from Al Kut textile factory. For the last eight years, physical-chemical parameters measurements of water samples have been researched for ten parameters are total dissolved solids TDS, TSS, Tur., Electrical conductivity, sulfate SO4, Chloride, Phosphate, COD, DO and biological oxygen demand BOD5. The findings of the water quality examination were compared to the World Health Organization's maximum permitted limit concentration and Iraqi limitations spastically. Moreover, the water quality parameters were gradually decreased according to the findings. Results shows the annual variation of Al-Kut TSS concentration with decreasing rate of (71%), Turbidity concentration with decreasing rate of (11.44%), Chloride and Phosphate concentrations within its decreasing rate of 50 % and 70.23 % respectively during the study period of the last eight years. While the average BOD5 values decrease in concentration and the annual variation of Al-Kut DO concentration within its decreasing rate of (51%) during the study period of the last eight years.

This paper presents Membrane Bioreactor (MBR) and Nanofiltration (NF) systems as alternative and effective approaches for treatment and reusing domestic sewage. The goal is to investigate the general performance of a membrane bioreactor and nanofilteration membrane ability to satisfy water reuse requirements using water quality index such as total suspended solids (TSS), chemical oxygen demand (COD), and ammonia (NH3). The findings show that the MBR system produces high-quality permeating water. TSS, COD and NH3 rejection rates were 99%, 90.3%, and 82.5% (on average). In addition, MBR technology is quite successful as a pre-NF treatment. We also evaluated how pressure and temperature affect the effectiveness of the NF membrane removal of TDS, COD, ammonia, and permeating flux. The results showed that the applied pressure has a favorable impact on the total removal rate; however, the feeding temperature has a negative impact. The feeding temperature, in addition to pressure, has a good influence on the flux of the NF system.

Our water quality continues to be negatively impacted by human activities, this is a global problem of critical importance (particularly concerning fresh water and human consumption). Since the 1960s, the critical water quality index (WQI) technique has been used to assess the worldwide water quality state of surface water and groundwater systems. Plans for water resource management must consider extensive data and knowledge about the quality of available water. Water quality indicators are a straightforward technical method for evaluating the state of a river's water quality. In this approach, many water quality characteristics are examined and interpreted in research on river water quality. It can be considered the most important parts of monitoring plans for river quality. In this study, a monitoring plan is achieved for three different stations located on Tigris and branch rivers Al-Dujaili and Al-Gharraf in Wasit/ Kut during the study period for eight weeks from 1/3/2022 to 1/5/2022. Water quality assessment has been conducted using arithmetic quality indices of general water used for drinking and agricultural consumption. It is where the qualitative indices are turned into a single number with no units. Classifying water quality is done by comparing the values ​​of the indices to a scale of ratings that have already been set up. In this study, It has been utilized the Water Quality Index. The following physical and chemical factors are used to determine the water quality index: pH, total dissolved solids (TDS), turbidity, biological oxygen demand (BOD5), nitrate (NO3), sulphate (SO4), chloride (Cl), and phosphate (PO4). The results showed that each station had a low rating for the water quality index The average readings for the Tigris River were 187.44, Al-Dujaili 211.49 and Al-Gharaf 255.85, showing that Tigris River and its branches' water is seriously polluted for aquatic life due to the discharge of insufficiently treated wastewater from Kut's residential neighbourhoods.

Drought modelling is essential to managing water resources in arid regions to limit its impacts. Additionally, climate change has a significant effect on the frequency and intensity of drought. This research provides a novel approach to forecasting the standardised precipitation index (SPI 3), considering several climatic variables by employing hybrid methods including (i.e., data pre-processing represented by normalisation, cleaning (i.e., outliers and Singular Spectrum Analysis), and best model input (i.e., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. The result revealed that data pre-processing techniques enhance the data quality by increasing the correlation coefficient between independent and dependent variables; and choosing the optimal input model scenario. Also, it was found that the PSO algorithm precisely predicts the parameters of the proposed model. Moreover, the finding confirmed that the supposed methodology precisely simulated the SPI 3 depending on several statistical criteria (i.e., R², RMSE, MAE).

An electrocoagulation with membrane bioreactor technique (EC-MBR) was developed to treat domestic wastewater and prevent membrane fouling. To support the new design, experiments were conducted on a few levels. The structure and distribution of organic matter removal utilizing the membrane are investigated using a laboratory-scale (EC-MBR) treatment of domestic wastewater. The study's goals were to assess the removal efficiency of organic matter (biological oxygen demand (BOD) and chemical oxygen demand (COD) in Al-Hawraa's wastewater, as well as its links to statistical indicators. It was chosen to sample and evaluate effluent from domestic wastewater using EC-MBR with operating temperature (25 0C), pH (7-8), DO (4-6) mg/L, beginning and final concentrations of BOD (184-6 mg/L), and COD (489-20 mg/L) using biological and electrochemical treatment procedures. According to the results, the organic matter removal efficiency may be calculated using the multilinear regression (MLR) and neural network (NN) models in the SPSS modeler. In addition, the results showed that the entire reactor had good BOD and COD maximum removal efficiencies of 96.7% and 95.9%, respectively. Finally, the highest accuracy of the MLR algorithm for COD and BOD is 99.6 for both, whereas the maximum accuracy of the NN algorithm for COD and BOD is 99.2 % and 99.1%, respectively. To choose the best algorithm for analysis and modeling the outcomes, a comparative study has been achieved to compare the results of two algorithms that used in this study. Therefore, for this study MLR algorithm was chosen.