College of Engineering, University of Basrah
Review of Sophisticated for Thermal Management Systems in Battery Cooling
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 organized 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 summarizes the key recommendations for future research on battery thermal management.
Copyright (c) 2025 Basrah Journal for Engineering Sciences
Evaluation of Residual Stresses and Retained Austenite in AISI 4330 Low-Alloy Steel: A Critical Review of Experimental and Numerical Simulation Methods
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 influence 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.
Integrating Industrial Internet of Things and Cyber-Physical Systems: A Comprehensive Overview in Smart City Scenarios
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.
The Impact of Microstructure Tests on the Mechanical Behavior of Press Hardening Steel: A review
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.
Adding microalloying components to standard Mn-B steels.
Early Prediction of Tomato Diseases in Iraqi Agriculture using AI-Based Temperature and Humidity Data: A Random Forest Approach
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.
Impact of Contraction Scour in Tigris River on Al-Nuhairat Bridge in Basrah Governorate
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.
Optimization of Turbidity Removal from Domestic Wastewater by Electrocoagulation Using Aluminum Electrodes: A Design of Experiments Approach
A significant quantity 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.
Numerical Failure Pressure Predication of Corrosion Defect in Transmission Pipeline
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.
Experimental and Computational Analysis of Slug Flow Through a Horizontal Perforated Wellbore
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 $25.4~mm\times3$ m 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.
Bond Performance Evaluation for Members Cast with Reinforced Normal-Strength Concrete Strengthened by Slurry-Infiltrated Fiber Concrete Jacket
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.
Simulation Absorption Refrigeration System Powered by a Solar Pond
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.
Libr-H2O absorption refrigeration system
Experimental and Numerical Investigation of Deep Drawing Process for Carbon Fiber Reinforced High Density Polyethylene (CF-HDPE) Composites
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.
Improving the Enhanced Vold-Kalman Filter to Analyze Vibration in Rotating Machines
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.
Modelling and Solution of Trapezoidal Variable Orifice Flow Meter: 3D Fluid - Structure Interaction
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.
Determination of the Stress Intensity Factor in a Sandwich Structure with a Hexagonal Core under Various Loading Conditions
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 (kl) and the (a/tc) ratio was established.
A review: Assessment of the Theories of Fundamental Mechanisms, Designing, and Failure on Structural Adhesive Joints Bond
Adhesives have been around for millennia. Nevertheless, this technique for joining has only seen significant development within the past 70 years. Professional technical engineering applications primarily use adhesives derived from synthetic polymers, a development that dates back to the mid-1940s. Its characteristics facilitate their strong adhesion to most substrates, as well as their ability to transfer substantial loads. This paper presents an extensive assessment of the current knowledge in the field of adhesives and related technologies, with a focus on adhesion theories and their parameters, as well as designing, joint configuration, geometric aspects, and failure modes. The paper also explores the interplay between research and development efforts, industrial standards, and regulatory aspects, with the goal of fostering collaboration between academia and industry. Over the past years, the development of new materials, methods, and models has resolved many of the shortcomings. Nonetheless, it is still possible to evaluate and estimate the optimal combination of aspects that will give the greatest efficiency and performance for adhesive bond joints (ABJs).
Composite Materials Under Fatigue Loading: General Review
Advanced applications, such as aircraft manufacturing, require sophisticated materials. Composite materials are among these advanced materials and offer several advantages, including high strength and low weight. Given that these applications experience repeated loading, studying fatigue in composite materials is essential. This paper provides a comprehensive review of fatigue failure in composite materials, focusing on the types of fatigue loads, the characteristics of composite materials, and the damage mechanisms. Additionally, we discuss modelling and simulation techniques to understand fatigue behavior and the standards necessary for conducting fatigue failure testing in composite materials. The study of fatigue in composite materials is diverse, reflecting the materials' complexity, which varies across scales. Due to composite materials' heterogeneity, numerical modelling can be challenging. It often requires numerous constants that change with various factors, which can only be determined through experimental test. As a result, studying fatigue in composite materials can be costly.
Multi-Effect Desalination Powered by Concentrated Solar Power: A review
The desalination market is gradually growing as a result of the significant water scarcity in various regions throughout the world. Concentrated solar power (CSP) can be used to power distillation, which is an effective method for addressing water shortages in areas where there is both a severe lack of water and abundant direct normal irradiation. CSPs are ideal candidates for the advancement of desalination technologies due to their capacity to produce both thermal and electricity energy. This review article offers a comprehensive of the current status of cutting-edge CSP-desalination systems. The paper reviews previously published studies conducted by researchers in the field of multi-effect desalination using concentrated solar collectors, and they are classified into two main types. Exclusively freshwater generation and freshwater / electricity cogeneration. In addition, the paper reviews conventional desalination. This review illustrates that there are numerous prospective methods for integrating desalination systems into CSPs. Potential areas for future investigation in CSP-desalination systems. In particular, the most significant obstacles to be surmounted are lowering the costs and efficiency improvements of solar repayment and desalination equipment. A potential method to expedite the commercialization of these plants is to develop innovative strategies that optimize thermal efficiency and reduce costs. Environmental factors (solar radiation intensity, ambient temperature and wind speed) and design factors (solar field area, number of mirrors, number of stages, steam temperature, steam quantity and pressure) are the main effective parameters that affect the distilled water production process. In general, the CSP desalination systems are environmentally and technically appealing; however, there remains substantial progress to be made in order for these plants to be commercially viable.
Selection of Suitable Sites for Rainwater Harvesting Structures in the Northern of Iraq: A Review
Since the 1970s, rainwater harvesting has gained more attention, specifically in semi-arid and arid areas. It is essential to take into account how much water can be collected from a single catchment site. Rainfall that has been harvested provides an alternative source of water in the northern region of Iraq. Numerous scholars have developed and executed a range of strategies and guidelines to choose appropriate locations and methods for rainwater harvesting (RWH). However, choosing the optimal method or set of rules for the choice of site is challenging. This study's primary goal was to evaluate previous research regarding the selection of appropriate RWH locations in northern Iraq by assembling a list of the most important techniques and guidelines that evolved over the previous thirty years. The primary factors considered in the process of choosing acceptable locations for RWH were soil type, slope, land use/cover, rainfall, and runoff. A literature review for RWH indicated that these criteria were chosen more frequently and significantly, and the opinions of experts should be used to establish the weight of each criterion. The majority of studies select RHW sites using geographic information systems, hydrological models, and multi-criteria analysis.
Bearing Fault Diagnosis Based on Acoustic and Vibration Signals using Deep Learning Neural Network
Diagnosing faults in rotary machines is critical, as early fault detection is a precise and essential task in minimizing operational risks and economic losses. Bearings are vital components in rotary machines and are subject to gradual degradation due to continuous operation. Failure to detect early damage can lead to problem escalation, resulting in severe damage and increased costs. In this study, two types of signals from rotary machines are analyzed: acoustic emission (AE) signals and vibration signals. These signals are utilized as input features for a deep learning neural network based on images, where the features are extracted using the Kurtogram, a powerful fourth-order spectral analysis tool that generalizes spectral kurtosis (SK) for a given signal. The results demonstrate that the accuracy of diagnosing the machine’s operational condition whether healthy or faulty ranges from 99.2% to 100%, while the accuracy of fault classification reaches 96.6%. These findings highlight the high efficiency of this methodology in fault detection and classification, establishing it as one of the most important techniques for diagnosing faults in rotary machines.
Strength and Bearing Capacity of Rectangular Footing Rested on a Soil Layer Reinforced with Waste Materials
A series of unconfined compression and direct shear tests were carried out to investigate the compressive strength and shear strength parameters of clay soil reinforced with different contents and lengths of wheat straw and palm frond fibers and by adding different percentages of furnace slag. The bearing capacity and settlement characteristics of the rectangular footing based on a clay soil layer reinforced with wheat straw fibers, palm fronds and furnace slag at different thicknesses were also studied by conducting model footing tests. The results indicated that the compressive strength and shear strength parameters improved significantly when adding 0.5% of natural fibers and 20% of furnace slag. The maximum compressive strength of soil samples reinforced with wheat straw fiber MT1 and palm frond fiber MT2 was 365 and 407 kPa, respectively. Compared to the unreinforced sample, samples reinforced with natural fibers and furnace slag significantly improve the shear strength parameters c and ϕ . The cohesion of soil sample reinforced with wheat straw and palm frond fibers increased by 8% and 43% respectively, while the internal friction angles improved by 19% and 40% respectively. The sample treated with furnace slag MT3 showed improved significantly in cohesion by 76% and less effect in internal friction angle. Compared to unreinforced soil samples, the cohesion of soil samples reinforced with wheat straw and palm fibers and treated with furnace slag MT4 and MT5 increased by 77% and 92% respectively, and less effect in internal friction angle. Moreover, the bearing capacity and settlement characteristics of the rectangular footing improved significantly with the increase in the thickness of the top layer reinforced with natural fibers and treated with furnace slag. The ultimate bearing capacity of layer reinforced with wheat straw fibers MT1 increases to 193.2, 220.15 and 247.5 kPa at thicknesses of 0.5 B, 1.0 B, and 1.5 B respectively, while the settlement decreased by 10.4%, 15% and 20.48% respectively at same thicknesses.
Absorption Refrigeration Systems Powered by Waste Heat Engine and Renewable Energy: A Review
Conventional Refrigeration Systems (VCRS) are the most commonly used in industrial buildings and facilities. Conventional refrigeration systems are among the most energy-consuming sources in addition to causing more environmental problems and gas emissions, such as hydrocarbons (HCs) and hydrochlorofluorocarbons (HCFCs), are known to contribute to global warming and ozone depletion. Absorption Refrigeration Systems (VARS) are a good alternative to conventional refrigeration systems because they use low-grade heat sources and operate with environmentally friendly liquids. The most important of these heat sources is the heat wasted from engines, industrial processes and many other sources. The global objective of the study is a literature review on the different ways to operate the absorption refrigeration system using waste heat in engines that include exhaust gases and engine cooling water as well as renewable energy that includes solar energy. Reviews of the literature have demonstrated how the absorption refrigeration system can be used and operated using a variety of thermal sources. This study also supports the usage of ecologically friendly chillers to provide air conditioning and refrigeration, as it shows these systems have a lower performance coefficient when compared to conventional refrigeration systems.
The Impact of Iraqi Crude Oil Sulphur Content on the Mechanical Characteristics and Corrosion Resistance of Various Carbon Steel Grades Pipeline Welded Joints
The enormous volume of crude oil that needs to be transported results from the growing demand for petroleum. One of the most practical ways to move crude oil is via pipelines. This paper's primary objective is to examine the effects of sulphur, one of the components of crude oil, on welded pipes (API 5L X60, X46, and X42 pipes as well as ASTM A106 pipes). It also aims to show how sulphur content influences different kinds of pipes separately from the other important components of crude oil. The sulphur content of crude oil is determined using the TR-TCXRF equipment. The corrosion rates of welded pipes in four immersion solutions (Different percentages of sulphur content) were computed using weight loss. The samples' corrosion characteristics were assessed morphologically using an optical microscope (OM), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). Petroleum welded pipelines' mechanical qualities and resistance to corrosion are significantly impacted by sulphur; an increase in sulphur concentration resulted in a higher rate of corrosion and a decrease in mechanical properties. Among all the welded pipes utilized in the paper, the API 5L X60 welded pipe had the highest corrosion rate, whereas X46 welded pipe was more corrosion-resistant than X46 and X42 in API 5L-type pipes and ASTM A106 pipe.
Improvement Thermal Efficiency of Al-Rumaila Gas Turbine Power Plant in Basrah by Upstream Inlet Air Cooling System
The efficiency of gas turbine units is highly affected by the variation of ambient temperature. Increasing the ambient temperature decreasing the efficiency of gas turbine. Cooling the inlet air to the compressor of the gas turbine units is an essential and economical technique for improving its efficiency. Al-Rumaila gas turbine power plant was located in Basrah city, Iraq, which is characterized by its hot climates for more than six months during the year. A novel upstream inlet air cooling system was applied and tested for Rumaila gas turbine power plant. This article represents a thermo-economic evaluation of applying upstream inlet air cooling system. The analysis is based on the test results for operating single unit of Rumaila gas turbine power plant using upstream inlet air system for cooling. The test was performed during July of 2019 for 90 minutes of operation period with ambient temperature of 45 °C. The evaluation analysis shows that, the power output increased from 217.71 MW to 250.11 MW during the period test with percentage increase in power by 15%. This increase in power output led to net economic gains is approximately 1000 $/h.
Developing an Efficient Technique for Predicting Ball Bearing Defects Based on RDE Method Using CNN
The accurate prediction of machinery faults is considered an effective strategy to increase the operation life of machines, ensure smooth operation, and provide a safe environment. Accordingly, the demands on predictive tools such as machine learning to detect machinery faults before catastrophic failure occurs has increased rapidly. In this research, a diagnosis algorithm based on using a 2D color-coded map as the input to a deep artificial neural network is proposed. These maps are called RDEgram after the processing of vibrational signals based on reverse dispersion entropy (RDE) method. The effectiveness of the proposed algorithm is investigated by testing its capability to detect different faults located at different locations on ball bearings under constant speed conditions. First, the squared envelope signal is extracted by applying the short time Fourier transform to vibration signal. Then, the RDE is used to process the squared envelope to detect the range of frequencies at which the transients occur. The RDEgram color-coded map is used to represent the RDE values as a function of frequency and frequency resolution. The maps from different fault features are collected to form the diagnostic patterns. Finally, a pretrained convolutional neural network (CNN) is applied to learn the feature pattern and diagnose the bearing faults. The CNN is trained using fixed- speed data and then it is applied to diagnose faults in the test data recorded at the same speed. The prediction method adopted in the current research shows a 100% level of accuracy for predicting two types of faults (pit and slot) located at various positions a ball bearing (KOYO 1205 C3 type) running at two constant speeds (25 and 30 Hz).
Performance Evaluation of Single Leg Thermoelectric Module for Different Materials Under Various Operating Conditions
The thermoelectric behavior of different materials under various conditions has been investigated numerically by using the heat transfer module of the COMSOL Multiphysics software platform. A simulation study of the thermoelectric materials (TEM) performance was created by altering the current applied from 0.1 to 1.0 A and setting the hot side temperature (T H ) as 273 K. The impact of different performance metrics, such as cold side temperature and output voltage, has been proven and investigated. It has been shown that the material of the thermoelectric legs', length of leg, and thickness of electrodes significantly impact the thermal and electrical performance of the thermoelectric (TE) module. Appropriate ranges have been studied in the simulation, such as the amperage values applied to the unit as mentioned above, the length of the leg within a range of 1 to 8 mm, and the thickness of the electrode with different values of 0.1 to 0.5 mm, which will achieve excellent performance for the Thermoelectric unit. Modeling and simulation results demonstrated and revealed the optimal and potential use of bismuth telluride (Bi 2 Te 3 ) as well as lead telluride (PbTe) as suitable for Peltier cooling applications. As for the use of cobalt triantimonide (CoSb 3 ), it is in contrast to the two previous metals, as it is effective and appropriate if applied to power generation. The results are validated with another study from the literature, and there is an excellent agreement with an error rate that does not exceed 0.164%.
Comfort Ability of a Transtibial Amputee According to a Biomechanical Comparison Between SACH, Single-Axis and Multi-Axis Feet Using GRF and Interface Pressure Tests
Individuals with special needs who use lower limb prostheses (artificial devices designed to replace missing body parts) have specific sociocultural requirements that have driven the development of prosthetic feet. This study conducted a biomechanical analysis of three types of prosthetic feet (SACH, single-axis, and multi-axis) by comparing their biomechanical properties using ground reaction forces and an F-socket. The goal is to enhance prosthetic technology and improve the user experience for below-knee amputees by examining how different foot types affect stresses in below-knee prosthetic limbs during daily activities. The patient case study involves a 28-year-old man weighing 71 kg, who underwent a below-knee amputation of his left limb due to injuries sustained during battles with ISIS. Ground reaction force (GRF) testing is crucial for determining the forces exerted on a patient's feet while walking. Additionally, the Interface Pressure test was performed to measure the pressure between the remaining lower limb and the below-knee prosthetic socket using a pressure sensor. The healthy foot (right leg) served as the reference for comparison. The results of this study on GRF and knee force for various prosthetic feet provide valuable insights into their performance during gait analysis. The multi-axis foot demonstrated superior capabilities, potentially enhancing user mobility and quality of life. Furthermore, the F-socket test indicated that the multi-axis foot offers the best balance of pressure distribution, dynamic performance, and comfort, making it well-suited for adapting to different surfaces necessary for an active lifestyle.
Adaptive Neuro-Fuzzy Inference System Model for Predicting the Tensile and Bending Properties of Carbon Fiber-Epoxy Composite
The aim of this work is to experimentally study the influence of fiber prestress and curing temperature on the tensile and flexural properties of carbon fiber-epoxy composite. Adaptive Neuro-Fuzzy Inference System model was used to predict the effect of fiber prestress and curing temperature on the tensile strength, tensile modulus, flexural strength and flexural modulus of carbon fiber-epoxy composite. It was found that, the best membership functions for predicting the tensile strength, tensile modulus and flexural modulus are Gaussian membership functions with 4 number of membership function, and for predicting the flexural strength are generalized bell membership functions with 4 number of membership functions. From the comparison between the experimental and predicted results of carbon fiber-epoxy composite properties, it is found that the prediction results of this model show a good agreement with experimental results.
Hourly Cooling Load Assessment Utilizing Three Different Methods for a Full Day
Human beings are facing an unprecedented rise in temperature rates not recorded for years. HVAC (heating, ventilation, and air conditioning) systems have been created and enhanced to solve this issue. Cooling load must be estimated with accepted methodologies before designing an efficient and effective air conditioning system. Companies, researchers, institutions, and others advise and develop many cooling load calculation methods. Each one of these methods has its advantages and disadvantages and may give a slightly different result for the same case. For each building, whether it was residential or commercial buildings, gyms, or shopping malls, before making the decision on (HVAC) systems to be used, both heating and cooling loads should be obtained as correctly as possible to minimize expenses as possible. Since the HVAC system consumes the most energy in an air-conditioned building, an accurate method of cooling load estimation is necessary. Consequently, an energy-efficient air conditioning system reduces greenhouse gas emissions into the atmosphere while also saving money on electricity. Two cases have been compared and studied, one in Dubai UAE, and the other in Baghdad Iraq. Three different methods, HAP, hand calculation method (CLTD/SCL/CLF), and MS-EXCEL E20 form sheet were used to compare the accuracy of the results for cooling load. Results of E20 and HAP are very close to each other with high accuracy for peak load, the big difference can be found between the CLTD method and the other two methods. The value of the maximum difference percentage was found between CLTD and E20 equals 3.28% and 7.96%, on the other hand, the lowest difference was equals to 0.3% and 1.51% between HAP and E20 results for Baghdad and Dubai respectively. Traditional and local materials came from local factories, used in buildings played a big effect on the results, which may not match those materials stated in the ASHRAE or CARRIER tables, which need to be considered in the results and calculation procedure. However, all methods have a percentage of difference but all results are within the accepted range and are applicable for practical cases. Of course, this percentage is minimal with some methods and maximum with others.
Using PSO Algorithm to Find Optimal Number and Location by Connecting Distribution Generators to Improve the Iraqi 400 kV Super Grid
Nowadays, it is crucial to assess power system contingencies resulting from line outages or generator failures, as they might cause breaches of system constraints. This is a vital part of ensuring the security of modern power supplies. Another hindrance to providing electricity to consumers is the increased system losses and voltage fluctuations resulting from increased demand and diminished power generation capacity. The DG connection is a crucial subject regarding these harmful consequences. This study is focused on clarifying the effect of distribution generators (DG) on mitigating congestion in electrical power transmission lines, minimizing power losses, and enhancing the voltage profile of the Iraqi national grid system. An optimization method is used to identify the optimal size and position based on fitness indicators such as voltage, power losses, and line congestion. The PSO algorithm is executed as proposed. The outcomes illustrate the effectiveness of the proposed technique for estimating the optimal size and placement of distributed generators (DG). At the same time, it reduces congestion and improves the voltage level of the bus. The proposed technique was implemented using the MATLAB/R2018a programming language.
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