AL-Rafidain Engineering Journal (AREJ)

Wireless Sensor Networks (WSNs) are crucial in applications such as environmental monitoring, healthcare, and smart cities. However, the constrained energy resource of sensor nodes and the application may face some critical issues when a large number of sensor nodes are deployed with efficient data transmission. Previously, wireless sensor networks relied on flat routing protocols and location-based protocols for data transmission. Still, the main problem with flat routing protocols is that they perform inefficiently on a large network size. The results from direct communications amongst all nodes result in high energy consumption and congestion. These problems led to the development of hierarchical routing protocols (HRPs) to address these issues by organizing nodes into clusters, thus reducing energy consumption and improving network scalability. This reduces the communication overhead and extends the network's lifetime. This review paper reviews the challenges that led to the development of HRPs and recent developments that have been made for HRPs, with a focus on Power-Efficient GAthering in Sensor Information Systems (PEGASIS). It estimates the solutions these protocols offer and examines the remaining challenges, such as dynamic cluster management and load balancing. As a result, PEGASIS greatly improves energy efficiency and scalability, but there are still gaps for potential optimizations. So research efforts will be required in these areas to maximize performance and applicability for hierarchical routing protocols in WSNs

Underwater Sensor Networks (UWSNs) have attracted the research community due to their critical applications, such as environmental monitoring, hurricane tracking, and disaster analysis, to mention a few. This kind of network struggles with many challenges, such as propagation delay and limited energy resources. Many efforts in the literature try to overcome these challenges. However, there is still a need to perform more investigations aiming to obtain more reliable approaches for UWSNs. Therefore, this article suggests an Efficient Energy-Depth Hybrid Routing Protocol (EEDH-RP) that addresses the aforementioned issues. The proposed method integrates energy-efficie and depth-based routing strategies, aiming at optimizing packet delivery and minimizing consumption of powe. The proposed routing involves a hybrid forwarding metric in a way that assumes residual energy and depth information, as well as adaptive transmission power control to improve reliability.The proposed routing is assessed against three well-known routing protocols, namely Vector-Based Forwarding VBF, Depth-Based Routing DBR, and HydroCast Routing HCR. The evaluation involves metrics such as packet delivery ratio, energy consumption, end-to-end delay, network lifetime, and throughput. According to the results, EEDH-RP performed better than the benchmark. It gains 92% for packet delivery ratio, energy consumption of 450 joules (with improvements of 25%, 18%, and 10% for VBF, DBR, and HCR, respectively), and 1.2s for end-to-end delay. Our proposal also extends network lifetime by 28% compared to VBF, and 12% compared to DBR

Given the widespread interest in the use of renewable and sustainable energy sources to address the issue of electricity supply, as well as their limitations, high costs and high prices of fossil fuels, in addition to the availability of suitable solar radiation, this paper presented a case study for the design and feasibility assessment of a 382 kWh grid-connected solar power system to supply electricity to four buildings on the University of Mosul campus, where these buildings were combined and considered as one area for the design. The simulation was performed by PVSyst software using a 700W Huasun DS700 solar panel and a 33kW Deye inverter. The simulation results showed an annual energy production of 670,459 kWh/year with a system efficiency of 85.06%. The cost of energy produced is $0.02/kWh, reducing emissions by 14,473.8 tons. Addressing the issues of fossil fuel depletion and greenhouse gas emissions, this strategy highlights the financial and environmental benefits of switching to renewable energy. This study can be applied to many government buildings and institutions that are transitioning to renewable energy, especially solar energy, in areas with suitable solar resources in terms of radiation, temperature and area to achieve clean and sustainable energy.

The primary objective is to enhance fault-tolerant reliability in Hypercube Networks by developing and evaluating novel adaptive routing methods. The proposed system resolves performance stability problems in failure environments by using adaptive routing techniques, which enhance network reliability. The primary aims include shortening response times while maximizing data rates, reducing energy consumption, and delivering quicker performance restoration, besides better reconnection capabilities than standard fault-tolerant techniques. The experimental research shows that adaptive routing achieves superior outcomes than conventional methods in performance measurements. The performance measures show improvements such as latency reduction from 54.5 ms traditional to 35.7 ms adaptive, while throughput increased from 17.5 bps to 20 bps and recovery time transformed from 4.7877 s to 0.7786 s, with a simultaneous reconnection rate increase from 95% to 98%. The decreased energy usage reached 33.386 J from its original level of 51.961 J. The research outcomes illustrate that adaptive routing approaches improve the fault-tolerant reliability of Hypercube Networks and yield superior performance, making them appropriate for parallel computing systems that require fault-tolerant operation.

Rotary friction welding (RFW) is one of the most effective and efficient methods of joining for welding similar and dissimilar materials in different industrial applications. In this study, the influence of friction pressure of Continuous Drive Rotary Friction Welding (CDRFW) was investigated for welding austenitic stainless-steel pipe (grade TP316L) at two different friction times, while other welding process parameters remained constant during the process. The results demonstrate a complex relationship between the friction welding parameters. For the first set of samples with a longer period of friction time of 45 seconds, increasing the friction pressure decreases the mechanical properties. In contrast, for a shorter period of friction time of 15 seconds, increasing the friction pressure increases the mechanical properties. The best result among the welded samples was achieved at the highest friction pressure and the shorter friction time, with the tensile strength reaching 457 MPa. However, for the longer period of friction time of 45 seconds, the tensile strength is dropped to a minimum of 171 MPa. The key parameter in this process is the heat input, which must be carefully controlled. Excessive or insufficient heat input can lead to improper bonding and poor weld quality. The findings of this study show that welded joints with the highest friction pressure combined with lower friction time give the best result of tensile strength and hardness profile. In contrast, the high friction pressure and friction time together need to be avoided to prevent degraded weld performance.

The protection and management of residential solar panel energy systems in smart cities that depend on the Internet of Things (IoT) are vital. Controlling residential energy consumption manually is hard. In addition, significant challenges should be addressed, including facilitating communication between devices, conducting real-time data analysis, and ensuring security. In other words, constraints associated with interoperability, real-time data analysis, usability, scalability, and cost-effectiveness should be overcome in any reliable management system design. In this paper, a smart energy management system based on IoT to improve the efficiency and safety of residential solar panels is presented. The suggested approach focuses on prioritizing load shedding, which plays a crucial role in promoting sustainable energy practices in smart cities. The system is designed using Particle Photon, which includes a microcontroller with Wi-Fi and current transformers (CTs) to dynamically manage energy usage, helping minimize wastage and extend the life of limited power sources such as solar panels or local generators. The energy consumption for the proposed system is calculated assuming a 3576 mAh battery capacity, and the battery lifetime is 1000 hours. OPNET 14.5 Network Simulator is used to simulate the system. The Blynk platform is suggested for publishing data to the cloud for further analysis. Furthermore, recommendations concerning data privacy and security issues are proposed. As a result, stakeholders can smoothly monitor and control their energy consumption through a user-friendly mobile interface. The research shows that integrating IoT technology enhances energy management and supports the development of greener, more sustainable urban environments.

The increasing reliance on wireless networks for data transmission has increased the demand for microwave filters that are characterized by high efficiency, small size, and low cost. This study presents an improved design of a Butterworth low-pass filter that can be used in 5G networks at a cutoff frequency of 3.6 GHz. The design was developed using Advanced Design System (ADS) simulation software using an FR4 dielectric substrate. Modern communications require accurate designs to be provided in less time and effort, and achieve better performance. Therefore, several machine learning (ML) algorithms, such as artificial neural networks (ANNs), decision trees (DTs), linear regression (LRs), and support vector machines (SVMs), were used to optimize LPF designs. A dataset was created that included parameters of the length and width of filter transmission lines at different frequencies. The ML algorithms were then trained by generating their code in Python. The results demonstrate significant improvements in the various algorithms' prediction accuracy and computational efficiency. The ANN (Model 1) achieved the lowest average error of 0.17%, but with the longest training time, while the SVM provided a balance between accuracy and training time with an error of 0.21%. In contrast, DT achieved the fastest training times, but with a higher average error of 2.63%. This approach significantly reduced the need for manual tuning and simulation iterations. These results highlight the potential of machine learning techniques to optimize microwave filter designs, providing engineers with flexible and high-precision tools for modern communications applications.

Kinship verification is a crucial research area due to its diverse applications, including paternity tests, family reunions, and criminal investigations. While DNA analysis has been the predominant method, artificial intelligence techniques are still being explored and tested. Facial kinship verification, which involves comparing features between two facial images, has garnered significant research interest. This paper introduces a new approach to kinship verification using hand-palm images. The EfficientNetB0 model was utilized for deep feature extraction through transfer learning. A Siamese neural network architecture was employed to assess similarity. Various experimental scenarios were conducted concerning network architecture, training parameters, and fine-tuning. The Mosul Kinship Hand (MKH) dataset was used to create the palm dermal image dataset, consisting of 7,332 pairs equally divided into related and unrelated categories. The results were promising, achieving approximately 99% validation accuracy, and 77.02 ms average inference time per image pair using a post-training Principal Component Analysis (PCA) technique.

Segmentation of medical images is a crucial step in the diagnosis and treatment of various diseases, particularly when analyzing magnetic resonance imaging (MRI) scans. Despite significant progress, accurate segmentation remains challenging due to the complexity of anatomical structures, ambiguous boundaries, and variations in image quality. This paper proposes an enhanced Nested U-Net structure that incorporates an attention mechanism and fuzzy pooling to improve retail performance. Nested U-Net benefits from extensive skip connections to capture multi-level contextual information, while the attention mechanism enhances the model's ability to focus on relevant features and noise suppression. In addition, we replace the traditional extreme pooling layers with fuzzy pooling, which enables the network to handle spatial ambiguity more effectively and produce more accurate and refined retail maps. Experimental results on publicly available MRI datasets show that the proposed model achieves remarkable improvements, with a 4.97% increase in the dice coefficient, a 2.76% improvement in accuracy, and a 4.25% increase in recall compared to enhanced U-Net structures. Furthermore, significant improvements have been observed in Hausdorff's distance measures.

The development of simple gas power plants is attracting significant interest. In this regard, the possibility of developing a simple gas power plant with a capacity of (125MW) is being discussed. The first stage represents the utilizing of the thermal energy carried by the exhaust gases coming out of the simple gas turbine unit, by combining the gas turbine unit with a steam turbine unit through a dual-heat recovery steam generator, to form the combined cycle gas turbine unit. As for the second stage, it is represented by capitalizing on the solar energy through integrating the latter with the solar energy field, to form the integrated solar combined cycle unit. The results show that the advantages obtained from the first stage are high power output, thermal efficiency and, best specific fuel consumption, which can be obtained at (185.423MW), (49.77%) and (0.147kg/kW.hr) respectively. Regarding the second phase, the results show that adding a solar collector contributed to increasing the amount of steam entering the steam unit. As a result, the power output and thermal efficiency of the combined cycle unit increased to (207.964MW) and (55.3%), respectively. As for the specific fuel consumption, it reached (0.1315kg/kW.hr).

Operating pressure is one of the most important factors in breaking up and dispersion of the water jet into
droplets. In addition, the sprinkler riser helps calm, stabilize, and regulate the flow entering from the lateral pipe. The
research aims to determine the effect of the sprinkler riser height and the variation of cyclic pressure head on the water
distribution pattern for a single sprinkler and their interaction with the spacing and for rectangular and triangular
arrangements of sprinklers. The results showed that the water distribution patterns for a single sprinkler operating under
constant pressure head and under a cyclically varying pressure head are similar, and the largest differences didn’t show
a noticeable change in Christiansen's uniformity coefficient (UC). In addition, increasing riser height resulted in water
distribution patterns of lower depths with increase in the wetted radius. Moreover, the largest increase in UC appeared in
the triangular arrangement and in the lowest pressure head, and the average increase in UC was 8.65%. It was also noted
that increasing the pressure head led to distribution pattern of greater depths near the sprinkler, while the pattern tends to
stabilize after that. The overall increase in UC under all variables considered is 1.98%, and 70% of the UC values in the
rectangular arrangement are greater than or equal to those in the triangular arrangement.

Warm-mix asphalt (WMA) is produced at lower temperatures than hot-mix asphalt (HMA), suggesting reduced compaction efforts. This study aims to evaluate rutting, cracking, and fatigue resistance of WMA under three compaction efforts (CE: 35, 50, and 75 blows/face) using Kim and Semi-Circular Bending tests to measure deformation strength, fracture energy, flexibility index, and J-integral (fatigue parameter). A 40/50 penetration grade base binder was modified with 5% natural zeolite (NZ) and 5% synthetic zeolite (SZ) by mass to produce natural zeolite-warm mix asphalt (NZWMA) and synthetic zeolite-warm mix asphalt (SZWMA). Seventy-two Marshall-compacted samples underwent statistical analysis to determine optimal CE. Key finding can be listed as follows: NZWMA required 50 blows/face and SZWMA 75 blows/face to meet the minimum 3.2 MPa deformation strength (Kim test) and J-integral ≥ 0.5 (critical strain energy rate); NZWMA at 50 blows saved more time and fuel than SZWMA while satisfying performance criteria; Rutting, cracking, and fatigue resistance exhibited consistent trends with increasing CE for both mixes. The results demonstrate NZWMA’s efficiency under moderate compaction, offering practical advantages in asphalt production by balancing performance and energy savings. This study provides insights into optimizing CE for WMA technologies, emphasizing NZWMA’s potential for sustainable pavement applications.

Efficient electrical power management is crucial for both suppliers and consumers, significantly affecting consumer budgets and national economies. In Iraq, residential electricity consumption constitutes 56% of the national demand, leaving households with unpredictable monthly bills due to the absence of real-time usage monitoring. This financial uncertainty worsens grid instability and hinders efficient energy management. This paper proposes a methodology for energy management by estimating monthly electricity bills. We propose a predictive billing system that estimates monthly costs by analyzing kWh meter readings at 6-hour intervals, aligned with Iraq’s tiered pricing structure (10–120 IQD/kWh). The readings were collected over 30 days from a household in Mosul (House-1). To simulate high-consumption households (House-2 and House-3), the dataset was subsequently expanded by generating statistically and mathematically modeled synthetic data based on House-1 readings. Five management strategies were tested, including dynamic reductions (2–10 kWh) triggered by tiered thresholds. This methodology not only provides an estimate but also offers suggestions to help reduce the total bill, ensuring it stays within a reasonable range. The implementation of the proposed methodology led to a decrease in electricity consumption between 6% and 23%, resulting in cost savings of 14% to 49% across three different household profiles. The tiered feedback approach (Scenario 4) achieved the highest monthly cost savings, with a 49% reduction for households consuming more than 4000 kWh per month. This approach empowers consumers to align usage with budgetary goals while alleviating grid stress. Future work will integrate IoT-based outage detection and mobile app deployment.

Numerous factors, including soil type, moisture content, foundation type, and excitation intensity, have impacted how soil responds to excitation forces. An accumulation of underlining soil deformation caused by the machine\'s vibration may exceed the limit. An experimental investigation was conducted to evaluate the effect of machine-induced vibrations on four prototype footings positioned at the soil\'s surface. Among the four footing models, three were designed with stepped areas, while one had a uniform rectangular section. The stepped footings were constructed with varying bottom-to-top area ratios (A₂/A₁) of 1.0, 1.2, 1.5, and 2. Three operating frequencies (10, 40, and 70 Hz) were applied to each of the four footings. The soil used was sand with a medium relative density of 50%. Dynamic response data include vertical amplitudes (displacement, velocity, and acceleration), settlement, and pressures at various depths. Despite different in magnitudes, it was found that the stepped footings significantly reduced the machine-foundation system\'s pressure, settlement, and amplitude movements. For instance, the stepped footing with area ratio of (A2/A1=2.0) displayed the lowest dynamic response. The pressure decreased by an average of 14.5% when the area ration changes from (A2/A1=1.0) (A2/A1=2.0), while the total settlement, amplitude displacement and acceleration were reduced by about 30%, 42% and 54%, respectively. Further, compared to a uniform footing, stepped footing is more cost-effective with high-performance.

This paper presents the new dual-mode half-wavelength folded microstrip resonator. The capacitance effect achieves the external coupling by changing the gap distance, while stub loading achieves the internal coupling. The second-order Chebyshev bandpass (BPF) filter was simulated by HFSS software on a thin Rogers substrate. The BPF is operated at a center frequency of 1.980 GHz, which results in a return loss of 16.97 dB, while the insertion loss is equal to 1.2185 dB. The BPF measures its bandwidth at 3 dB, which is equivalent to 50 MHz. The spurious frequency occurs at 4.27 GHz. The resonator offers a size of about (0.726λg× 0.278λg) which is smaller than a single mode. Moving the feeding line close to the center of the resonator has significantly enhanced the spurious window by about 2.75, and two Tzs appear on both band sides. The results show a satisfactory agreement with the requirement for 5G applications.