Basrah Journal for Engineering Sciences

Gas flow measurements are pivotal in several medical applications. For instance, mechanical ventilators and respiratory monitoring applications need flowmeters with strict requirements. This study is concerned with a three-dimensional computational fluid dynamics (CFD) analysis. The CFD methodology was confirmed by analyzing the flow characteristics of flexible membrane with trapezoidal orifice plates. Variable area orifice meters (VAOMs) are increasingly being embraced in respiratory monitoring applications, employed in the context of mechanical ventilation within medical settings. Each system integrates a flexible orifice plate within the conduit. The simulations are conducted considering realistic deformations in structure through two-way fluid–structure interactions (FSI) using the Arbitrary-Lagrangian–Eulerian (ALE) approach. This research paper analyzes using the finite volume method (FVM). A thorough numerical simulation was performed for the turbulence models. The orifice\'s thickness and shape significantly influence pressure drop and deflection.

This study investigates the deep drawing process of carbon fiber-reinforced high-density polyethylene (CF-HDPE) composites through experimental and numerical approaches. The experimental part involved fabricating CF-HDPE sheets and conducting deep drawing operations under controlled parameters (punch speed, temperature, and forming depth) to evaluate material behavior and mechanical properties. Numerically, finite element analysis (FEA) using ABAQUS simulated the forming process, analyzing stress distribution, strain development, and material deformation under varying conditions. Results revealed that increasing forming depth and decreasing forming temperature elevated the required forming force. Comparisons between experimental and numerical outcomes showed consistent trends, though some differences arose due to factors like friction and material nonlinearity. The findings contribute to optimizing deep drawing processes for composite materials, enhancing manufacturing precision, and minimizing material defects.

Vibration analysis is indispensable for different mechanical applications for early fault diagnosis, and many methods are used to analyze signals. Order tracking is one of these methods that is necessary for vibration analysis, especially for rotating machines. One critical and widely used method of order tracking is Vold-Kalman order tracking (VK-OT), which is used to diagnose faults in non-stationary machines. However, it has complicated and intensive calculations, requires special analysis tools, needs large memory, and takes a very long time to extract the results.
The proposed method aims to analyze signals by using Vold-Kalman filter order tracking with shorter time and less calculation memory with high accuracy by using partitioning method that separates the signal into many blocks with overlaps. The proposed method achieved less processing time and need much smaller memory than the original Vold-Kalman filter-based methods.

Due to the significance of structural sandwiches with hexagonal cores, utilized in various applications including aerospace, marine industries, and rail transport, and their design that imparts superior strength compared to conventional forms. In this paper, fracture behavior of these structural sandwiches was examined. Initially, the equivalent modulus of elasticity was empirically determined for many cell side lengths, utilizing the stress-strain relationship derived from tensile tests on hexagonal specimens. The fracture behavior was analyzed numerically using Abaqus software. The core and the complete sandwich structure were examined under various loads, including tensile and shear forces. The influence of the hexagonal cell dimensions on the fracture modules and the stress intensity factor (SIF), was assessed. It was observed that when the cell thickness remains constant while the side length varies, the SIF increases with the increasing in side length. This leads to the influence of stiffness, where it decreases with the increase in side length of the cell core. For instance, when the side length is 10, the stress intensity factor is 4.821, while when the side length is 20, the stress intensity factor becomes 22.35. A relationship was found between the stress intensity factor and thickness, similar to the tension case. However, here, a relationship between (kI) and the (a/tc) ratio was established.

The thermal performance of an absorption refrigeration system powered by solar pond heat was studied, simulated, and evaluated under the climatic conditions of Basra, Iraq. The simulation used MATLAB to solve the heat and mass transfer equations within the three layers of the solar pond (assuming NaCl as the salinity gradient medium) and linked them via a heat exchanger to the absorption refrigeration system to determine the temperatures supplied to the absorption cycle. The absorption cooling system operates on a lithium bromide-water pair and contains an internal heat exchanger between the generator and absorber with an assumed efficiency of 80%. The simulation was conducted over several months of the year, from March to October, and daily climatic variables such as solar radiation and ambient temperature specific to Basra were considered, allowing the system\\'s performance to be evaluated under realistic climatic conditions. The objective was to evaluate the coefficient of performance (COP) of absorption refrigeration systems and demonstrate the feasibility of using solar ponds as a sustainable heat source for cooling in hot regions. The study demonstrated the feasibility of operating an absorption refrigeration system using the thermal energy stored in the lower layer of the solar pond, while maintaining good thermal stability in that layer throughout the day, especially in areas with high solar radiation, such as Basra. The simulation model was developed entirely in MATLAB using fundamental physical equations that describe each component of the solar pond and absorption refrigeration system, without relying on pre-existing components or tables. This provides greater modeling flexibility and a deeper understanding of system behavior under hot climate conditions.

There have been efforts and studies that have been carried out with respect to the flow patterns, pressure drops (PD), and void fraction (VF) that can be found in horizontal wells. Notwithstanding, particular attention has not been paid to research of two-phase flow (TFF) in perforated horizontal boreholes. Recently, a number of attempts have been undertaken to investigate the features of gas-liquid systems, which exist in a TFF in a perforated horizontal wellbore, which is a little studied tree of the wellbore family. The stated investigations are devoted to the TFF of liquid and gas in a horizontal wellbore, which has a diameter and length of 25.4 mm * 3m respectively, with 18 uniform perforations. In the developed Fluent VOF model integrated in ANSYS 22 R1, the turbulence treatment and flow conditions within three-dimensional space, including water and air, with various flow rates were used to study the influence of high water and air velocities (SVW, SVA) on flow characteristics including PD, production (Q), VF, and liquid retention time in a horizontal well. The sequences of slug flow (SF) phenomena have been studied in detail for this pulsated flow. In particular, the first scenario is where SVW can reach velocities of 1.22 m/s and SVA of 1.68 m/s; in the second scenario, an increase in the SVW to 2.52 m/s is noted; and in the last scenario, the value of SVA is increased to 2.2 m/s. The empirical study was mainly targeted on the SF through a perforated horizontal wellbore. The productivity (Q), PD, and SF were found to benefit from an increase in axial flow rate (SVW), more than from increase in radial flow rate (SVA). In scenario two, productivity rises by even 84.108% as SVW changes, while in the last scenario Q increases by only 9.708% as SVA is increased. Further, the numerical and experimental results provide a reasonable match.

In recent decades, the need for strengthening and repairing reinforced concrete structures has increasingly arisen. One common method is the use of concrete jackets. Slurry Infiltrated Fiber Concrete (SIFCON), a newly developed material, offers superior mechanical properties, making it a preferred choice for strengthening and repairing concrete structures. However, there is limited understanding of its bonding performance when used as an overlay on a Normal Strength Concrete (NSC) substrate. This study conducted a direct Shear Test (DST) to evaluate the bond performance using reinforced NSC cubes externally bonded with SIFCON jackets subjected to direct shear. Eighteen reinforced cubes were strengthened with various bonding systems to investigate how different factors affect the bond performance between the NSC substrate and SIFCON overlay. The parameters studied included surface preparation methods, binder types, jacket configurations, bonding conditions (fresh overlay on hardened substrate and hardened overlay on hardened substrate), dowel placement, and bonding mechanisms. The results show that using bonding agents significantly improved bond strength, with epoxy proving more effective than latex. Specimens prepared by chipping showed better bonding performance compared to those prepared through diamond cutting. Chipping increased bond strength by 8.91% to 13.84% over diamond cutting in the case of fresh SIFCON overlay on hardened substrate. Using dowels in the bonding systems also improved bond performance by 10.89% to 16.97%. Applying jackets to three sides instead of two increased the ultimate failure load by 31.76% when dowels were used in both the two-sided and three-sided strengthened samples, and by 35.45% in the absence of dowels in both types of strengthened specimens. The cast-in-situ specimens demonstrated superiority over those strengthened with precast jacket layers.

This study addresses of contraction scour affect in Tigris River on Al-Nuhairat Bridge on the Basrah Governorate. It includes an analysis of key hydraulic variables and their interaction with the geological nature of the river and structural behavior of the concrete bridge, influencing the development of erosion. The data were entered and analyzed into the Federal Highway Administration (FHWA) hydraulic toolbox. The data were collected through a field survey of the bridge site and information obtained from the Directorate Irrigation of Basrah, some tests was also conducted at the Soil Laboratory of the University of Basrah. Two computational methods were used to determine the scour depth, erosion through clear-water and live -bed scour and cohesive soil erosion. The results of the study showed that the depth of scour in the live-bed and clear water flow method increases by 25% approximately with each increase in the depth of flow and the amount of discharge. However, in the cohesive soil method, it depends on the effect of the shear force resulting from the velocity and depth of flow, which is much less, as its effect is 1% approximately with each increase in these parameters. The results of each method were discussed in detail, and the necessary recommendations were made to mitigate the effects resulting from the occurrence of such a type of scour and its impact on the Al-Nuhairat bridge.

This study focuses on evaluating the structural integrity of SA-312 Grade TP316 pipeline with various forms of corrosion defects. The corrosion defects were characterized by three distinct geometries: internal rectangular, external rectangular, and internal elliptical. The effect of defect length, width and depth on pipeline failure pressure is investigated using the finite element method ANSYS software version 21. Regression analysis is conducted to develop equations relating maximum pressure to defect dimensions. The results show good agreement between the finite element results, experimental data, theoretical predictions, and design codes, with an error rate ranging from 3.98% to 17.79%. Failure pressure was found to be highly sensitive to corrosion dimensions, but the depth of corrosion has a greater impact on the failure pressure. Furthermore, it was observed that internal corrosion poses a greater threat to pipeline integrity than external corrosion.

A significant amount of pollutants are contained within domestic wastewater which creates a substantial environmental issue with a large quantity of effluent that contains high amounts of contaminants. Turbidity is a major indicator of water quality and a measure of suspended solids. The purpose of this investigation was to study the use of electrocoagulation (EC) as a method of removing turbidity from municipal wastewater using aluminum electrodes. Using a Design of Experiments (DOE) approach, specifically Response Surface Methodology (RSM), the effect of three important operating variables was studied. These were: the initial pH of the wastewater in the range from 3 to 9; the current (or amperage, ranged from 0.1 A to 1.1 A); and the time for which the wastewater was treated by the EC process (ranged from 10 minutes to 20 minutes). The initial turbidity of each of the municipal wastewaters used in the testing remained constant at 336 NTU (nephelometric turbidity units) throughout the entire investigation. The effect of a number of different experiments was made in order to evaluate the effectiveness of the EC process for removing turbidity from the municipal wastewaters, and in addition take a measure of a predictive model of turbidity removal efficiency. The main conclusion drawn from the investigation was that the EC process will be very effective for removing turbidity from municipal wastewaters, which can vary from 5% removal to total removal (as high as 97%). There appeared to be a statistical correlation between the removal efficiency and the three experimental variables: pH (r = 0.4316); amperage (r = 0.3714); and time of treatment (r = 0.3965). The removal efficiency was highest using the variables of Run 8 whereby the pH was equal to 9, the current was held constant at 0.6 A and the treatment time was 10 minutes, resulting in a turbidity removal efficiency of 97%. The various data showed that both slightly acid (pH = 6) and alkaline (pH = 9) gave a markedly superior removal than acid (pH = 3) for obtaining constant, high removal efficiencies (average of 90.00% and 90.33%, respectively). Also, it was determined that a current of 0.6 A provided the most optimum amperage, giving an average removal efficiency of 95.33%. In addition, it was shown that long treatment times resulted in high removal efficiency, with the most averages of removal efficiencies recorded when the time of treatment was set at a high of 20 minutes.

Exceptionally strong press-hardened steels (PHS) are significantly demanded in the automobile industry for satisfying the carbon neutrality criterion. Recent research attempts to produce advanced-ultrahigh-strength medium steels have resulted in a variety of alloying approaches, thermomechanical processing techniques, and microstructural modifications for these steel grades. It has been shown that adding microalloying components to standard Mn-B steels can refine the microstructure of PHS which leads to better mechanical properties such as hydrogen embrittlement resistance and other performance indicators for service. In this paper a general review about the effect of microstructure test on the mechanical behavior of Press Hardening Steel (PHS) where microstructure approaches have also demonstrated good potential for the mechanical characteristics of PHS steel, in line with need for new evaluation and discovery meantime, statistical data of the microstructural phases heavily influence the mechanical properties, microstructural image analysis is essential. The purpose of this paper is to know how the microstructure phases will effect on the strength and hardness of press hardening steel also the alloying elements adding impact on the microstructure formulation and mechanical features of PHS.

The Internet of Things (IoT) connects everyday objects to the Internet by integrating a vast network of interconnected smart devices into residential and commercial settings. When the Industrial Internet of Things (IIoT) changed how industries work by connecting and communicating devices and systems in industrial environments, these devices linked to the Internet gathered information from their surroundings, processed it, and sent it safely. Industry 4.0 transforms transportation and manufacturing industries by producing smart devices for total automation. This system has a substantial application in predictive maintenance. Predicting disasters in dangerous areas aids in managing safety and decreasing damage. In this paper, presented review for the integration of Cyber-Physical Systems (CPS) and IIoT in smart cities is fundamentally transforming urban services and infrastructure. Smart cities leverage technology to enhance inhabitants\\' quality of life, foster sustainability, and streamline municipal governance. Artificial intelligence is applied with IIoT\\'s production and analysis data to generate speedier outcomes. The article discusses IIoT uses, supporting technologies, growth issues and how to fix them, and suggestions for growth and better performance by limitless potential, including better manufacturing, greener electricity production, self-regulating structures, and smart cities that can modify traffic patterns to reduce congestion.

Plants and agriculture are important in Iraq and the world because they are among the essential basics of life; their importance lies in several fields, such as industry and food. Plant diseases are the first direct influence on plant production and the Iraqi economy. The primary contribution of this work is developing an efficient early warning system for tomato plant diseases based on readily available environmental data, demonstrating the usefulness of machine learning methods in real agricultural environments. This research investigates the use of artificial intelligence (AI) for the early prediction of tomato diseases in Iraqi agriculture, based on temperature and humidity data collected from Salah al-Din Governorate. Two major diseases were studied: Tomato Yellow Leaf Curl Virus (TYLCV) and late blight. The data were pre-processed and used to train predictive models, including linear regression and Random Forest Regressor (RFR). Results show that RFR outperformed linear regression, achieving a lower Root Mean Square Error (RMSE) of 0.053852 and a Mean Absolute Error (MAE) of 0.45000, indicating its superior accuracy in predicting disease occurrences.

The transition to electric vehicles (EVs) is a crucial step towards mitigating climate change and addressing the global energy crisis. The increasing use of lithium-ion batteries in EVs is attributed to their superior power density and efficiency. However, ensuring optimal battery performance and safety necessitates effective thermal management due to the significant heat generated during operation. Current cooling systems face challenges in maintaining the desired temperature range and uniformity. This paper reviews the state-of-the-art techniques in battery thermal management, focusing on phase change material (PCM) cooling and different cooling methods. This study, in accordance with its developments, compares the advantages and limitations of various cooling methods as potential solutions for next-generation EVs. It highlights the potential of method cooling, which, while promising, needs further research to establish its commercial viability and aims to guide future advancements in battery thermal management for next-generation EVs.

Under both typical and extreme usage scenarios, direct cooling may enhance the necessary battery performance and serve as an innovative method for managing the temperature of electric vehicle batteries. The primary challenge of this technique lies in its suitability for commercial application. This article is organised to cover the thermal properties of lithium-ion batteries, the main issues associated with lithium-ion battery heat, a discussion of reversible and irreversible heat generation and their effects on battery performance, as well as strategies for preventing and mitigating thermal runaway in battery systems. Finally, it summarises the key recommendations for future research on battery thermal management.

AISI 4330 Low-alloy steel is good material for advanced application because of its properties including strength and longevity. However, performance may be modified with heat treatment procedures, include quenching and tempering. These processes can create residual stresses and retained austenite (RA), which have an effect on the metal’s application. these factors influences fatigue life, dimensional stability, and fracture toughness of engineered components. uncontrolled residual stresses can reduce fatigue strength by up to 30%, while optimal retained austenite content (e.g., 5-10%) can enhance damage tolerance.
This study focuses on residual stresses and retained austenite measurement in AISI 4330 low-alloy steel after heat treatment. including experimental and simulation methods. The review summarizes many scientific studies published between 2019 and 2024 and shows some main challenges. One challenge is the difference between experimental results (for example, from X-ray diffraction (XRD) and neutron (diffraction) and simulation results (especially using ANSYS software). Another challenge is that different methods for measuring retained austenite can give different results, which can change how we understand the steel’s properties.
The review also explains new progress in modeling heat treatment. This includes adding phase transformation models to finite element simulations. Future efforts should combine multiscale simulation, characterization, and machine learning to achieve predictive control over these properties in manufacturing.