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Engineering and Technology Journal, الجامعه التكنولوجيا, Baghdad (2026)

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الجامعه التكنولوجيا

22/09/2026

Optimization Algorithms and Modeling Techniques for Hybrid Renewable Energy Systems: A Mini Review
https://doi.org/10.30684/2412-0758.1018
Abstract
The growing world-wide demand of power from renewable sources has brought up considerable attention to HRES system as the strong supplementary or alternative systems for fossil-fuel based energy generation. The efficient deployment of HRESs has to tackle a number of difficult optimization problems that involve the trade-offs between cost, reliability and sustainability. Sophisticated optimization techniques are the key in system design and operation. This paper classifies and assesses the solar, wind, biomass and energy storage based HRES optimization methodologies. It defines significant modeling methodologies and measures, such as Loss of Power Supply Probability (LPSP) and Levelized Cost of Energy (LCOE). Evaluations are made between traditional programming approaches, meta- heuristic algorithms (GAs, PSO and DE) based ones along with the new AI paradigms in use for adaptive energy management. The primary issues consist in the varying resources to be allocated and varying size of components, storage limitations and computational costs. With proper design, hybrid systems can be cost effective and produce fewer greenhouse gases than single-source systems. Suggested areas for further investigation are AI-based predictive control, next-level storage integration and digital twins as basis for autonomous operation.
Highlights
1. A comprehensive review of Hybrid Renewable Energy Systems (HRES) from 2020 to 2025 was
conducted.
2. Optimization algorithms such as GA, PSO, DE, ACO, CSA, GWO, and other AI methods were
comparatively analyzed.
3. PVsystems, wind energy, storage units, and hybrid configurations were modeled with governing
equations.
4. Machine learning and IoT integration were explored for intelligent energy management in HRES.
5. Key challenges and future research trends in HRES design and operation were identified.
Keywords: Optimization algorithms, Metaheuristic methods, Artificial intelligence, Energy storage, Hybrid renewable energy systems
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss2/4/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1018&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

20/09/2026

Spiral ISM Band Antenna Design for Biomedical Applications
https://doi.org/10.30684/2412-0758.1017
Abstract
This paper introduces a dual-band spiral-shaped implantable antenna engineered for medical applications, addressing the growing demand for reliable subcutaneous implantable monitoring systems. The proposed antenna is designed to operate within the Industrial, Scientific, and Medical (ISM) band centered at 2400 MHz, leveraging a highly compact form factor with total dimensions of 6 mm × 5 mm × 0.254 mm, yielding a minimal volumetric footprint of 7.62 mm3. The structure is fabricated on the RO3010 substrate, characterized by a relative permittivity of ϵr = 10.2, a loss tangent of tanδ= 0.0022, and a substrate thickness of 0.254 mm. Notable features of the antenna include its dual-band functionality, absence of a shorting pin in the ground layer, and a highly miniaturized profile. Performance metrics demonstrate a maximum gain of -15 dBi and an impressive bandwidth of 888 MHz at the 2.45 GHz resonance, underscoring its suitability for high-data-rate biotelemetry applications. Specific absorption rate (SAR) evaluations were conducted to ensure compliance with international safety standards, yielding values of 936 W/kg for 1-gram tissue and 98.6 W/kg for 10-gram tissue, confirming adherence to regulatory limits. Owing to its optimized electrical performance, compact architecture, and conformity to safety guidelines, the antenna represents a promising solution for advanced implantable medical devices.
Highlights
1. Design of a compact dual-band spiral implantable antenna operating in the ISM band (2400
MHz).
2. Miniaturization to a volume of 7.62 mm3 was achieved through a spiral radiator and slotted
ground plane.
3. Achieving a peak gain of–15 dBi and co
Keywords: Biomedical, Bandwidth, Miniaturized, Implantable antenna, Specific absorption rate
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss2/3/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1017&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

13/09/2026

Methodological Design and Performance Simulation of a 25 MW Grid-Connected Solar PV Plant Using PVsyst
https://doi.org/10.30684/2412-0758.1016
Abstract
The weakness of the energy transmission system is one of the primary challenges facing Iraq, significantly contributing to the country’s economic crisis due to its reliance on non-renewable energy sources. The rise in oil prices increased electricity production costs. These issues, including weak transmission, can be addressed by integrating renewable energy with the grid. This research presented a methodology for designing and simulating a 25 MW grid-connected photovoltaic station. It used the PVsyst System program to predict energy production and AutoCAD to develop the layout. The steps included evaluating the site, selecting solar units, configuring inverters, and integrating them with the 132 kV substation. The system was divided into 4 units of 6.25 MW each, increasing flexibility and fault isolation. Simulation results indicated an annual production of approximately 44,630 MWh, with a performance ratio of 82.21% and a capacity factor of 19.28%, reflecting high efficiency under Iraqi solar radiation conditions. The research also employed technical strategies, including increasing the reflector size by 45%, improving cable paths, and utilizing specialized transformers to minimize losses. The economic evaluation indicated a production cost of about 0.025 per kWh, confirming feasibility, particularly with government support. This research offers a practical framework for deploying large solar stations in similar climates, providing recommendations for integrating advanced solar technologies and enhancing simulation tools to improve design accuracy and efficiency.
Keywords:SolarPV,PVsystsimulation, Grid-connected system, Substation integration, Performance
ratio, Utility-scale solar
Highlights
1. Designed a 25MW grid-connected PV plant using PVsyst and AutoCAD tools.
2. Divided the system into four 6.25MW modular blocks for flexibility and fault isolation.
3. Achieved an annual energy yield of 44,630MWh with a performance ratio of 82.21%.
4. Implemented inverter oversizing by 45% and optimized cable layout to reduce losses.
5. Estimated an LCOE of $0.035/kWh, showing strong economic feasibility under subsidies.
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss2/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1016&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

30/08/2026

Adaptive Wheelchair Control Using Fuzzy Logic and Eye Gaze Metrics
https://doi.org/10.30684/2412-0758.1015
Abstract
Intelligent wheelchair systems are crucial for enabling hands-free mobility in individuals with severe physical impairments. This paper presents a novel eye-movement-based wheelchair control system that integrates camera-based gaze detection with fuzzy logic decision-making. By analyzing the Eye Aspect Ratio (EAR), along with horizontal and vertical gaze ratios, the system interprets real-time eye movements into five navigational commands: “Move Forward,” “Move Backward,” “Move Left,” “Move Right,” and “Stop.” A time threshold mechanism (2–5 seconds) ensures intentionality by filtering out involuntary gaze fluctuations. The novelty of this work lies in its hybrid use of real-time video processing and fuzzy logic reasoning to improve directional decision accuracy while maintaining non-invasive interaction. The system achieves a high detection accuracy of 99.8% with excellent performance in terms of precision, recall, and geometric mean. Unlike previous works that depend on wearable electrodes or basic rule-based classifiers, this work emphasizes adaptability, comfort, and stability in dynamic environments. The proposed solution demonstrates strong potential for assistive mobility, promoting independence and user comfort without the need for intrusive hardware.
Highlights
1. Areal-time eye-controlled wheelchair was developed using gaze metrics and fuzzy logic
2. Fuzzy rules were applied to convert eye aspect ratio and gaze direction into commands
3. Atime threshold was introduced to filter short gaze shifts and reduce false triggers.
4. The system achieved 99.8% accuracy under different lighting conditions.
5. It enables safe, non-invasive control using only a camera and a Raspberry Pi module
Keywords: Assistive technology, Eye aspect ratio, Eye gaze, Fuzzy logic, Navigation behavior, Real
time, Wheelchair
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss2/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1015&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

30/08/2026

Numerical Study Using NARX to Improve Pipe Vibration in Dosing Pump Systems
https://doi.org/10.30684/2412-0758.1014
Abstract
Pressure pulsation is a serious problem in the piping system. It is generated at the beginning and end of the water-pumping process, or when valves suddenly close. The high turbulence of fluid particles in the presence of pressure waves causes multiple stresses on the pipe walls, requiring maintenance and eventual replacement over time. In this research, an experimental setup for a piping system vibration model induced by pulsating pressure is designed, developed, and fabricated. The objective of the present work is to create a MATLAB program using the NARX method at the beginning of the Neural Network time series. Nonlinear Auto-Regressive External Input was described as a method of system identification to predict pressure pulsation and acceleration as a performance measure for the system. NARX can be used to model and predict flow rates based on the input (flow rate) and output (acceleration, pressure) in four cases. For the fourth case (3/4 closed valve), the pressure pulsation initially reaches 0.8 bar and is reduced to 0.3 bar after applying the NARX model in Simulink, corresponding to a 75% reduction. Similarly, the fourth case (3/4 closed valve) yields the best acceleration response. The pressure is 0.1 m/S2 and is reduced to 0.007 m/S2 after using NARX in Simulink. The percentage improvement in acceleration after using NARX in Simulink is 93%.
Highlights:
1. An intelligent MATLAB NARX neural network was developed to reduce pipe pressure and
acceleration without dampers.
2. Pressure was reduced from 0.6 to 0.4 bar (fully open) and from 0.8 to 0.3 bar (3/4 closed).
3. Acceleration was reduced from 0.065 to 0.004 m/s2 (fully open) and from 0.10 to 0.007 m/s2
(3/4 closed).
4. Overall improvement reached 75% in pressure reduction and 93% in acceleration reduction
Keywords: NARX, Pipe vibration, Simulation, ANN, Pressure fluctuations
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/15/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1014&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

29/06/2026

Deep Learning for Manufacturing: Surface Roughness Prediction in CNC Turning via 1D CNN
https://doi.org/10.30684/2412-0758.1013
Abstract
Optimisation of machining parameters is crucial to achieve an excellent surface finish, with surface roughness serving as the primary indicator of product quality. This study investigates the application of a one-dimensional Convolutional Neural Network (1D CNN) to predict surface roughness in Computer Numerical Control (CNC) turning processes. In contrast to conventional machine learning methods, the proposed CNN captures local dependencies within the tabulated input features, which include cutting speed, feed rate, depth of cut, and force components (Fx, Fy, Fz, and resultant force). A laboratory data set was used for model training, with the mean square error serving as the loss function. The performance was evaluated using the mean absolute percentage error (MAPE), the mean absolute error (MAE), and the coefficient of determination (R2). The experimental results show that the CNN achieves high prediction accuracy (e.g., R2 = 98.95%, MAE = 0.0515, and MAPE = 3.4087), outperforming traditional baseline models. The results highlight the potential of CNNs as a robust approach for tabular regression tasks in manufacturing and emphasis their value for data-driven optimization of machining parameters for defect-free production.
Highlights
1. Surface roughness in CNC turning was predicted using a 1D CNN trained on machining and force
data.
2. The CNN achieved competitive MAE and MAPE while providing precise quantitative Ra predic
tions.
3. The CNN’s predictive ability supported improved quality control in machining processes.
The model enabled process optimization and automation, leading to improved manufacturing
outcomes.
Keywords: CNC machining, Convolutional neural network, Surface roughness, Artificial intelligence
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/14/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1013&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

29/06/2026

Thermal Performance Investigation of a Double Pipe Heat Exchanger Using Experimental and Simulation Techniques
https://doi.org/10.30684/2412-0758.1012
Abstract
A heat exchanger is a device that transfers heat between two media. It is widely applied in various Industrial processes and power plants. Most previous studies relied either on CFD without experimental validation or on limited diameters, while this work integrates both experiments and CFD and compares three diameters. An experimental study on a counter-flow double-pipe heat exchanger with a 12 mm inner pipe was conducted to validate the CFD model. The validated model was then used to assess the effects of inner pipe diameter (12, 15, and 18 mm), flow rate, and temperature on thermal performance. For validation purposes, the experimental data were compared with simulation results for the overall heat transfer coefficient and effectiveness. The results show that the percentage error ranges between (0–12.95) % and (0–11.63) % for both the overall heat transfer coefficient and effectiveness, respectively. This, in turn, indicated an acceptable and accurate simulation model that can be reliably used for further numerical studies. In general, the findings show that the coefficients of overall heat transfer (Ui) and effectiveness (ϵ) can be controlled by selecting an appropriate inner pipe diameter and carefully managing the flow rate and temperatures. The results indicated that a 188% increase in the overall heat transfer coefficient and a 177% increase in the effectiveness can be achieved at the same flow rate and temperatures by reducing the inner pipe diameter from 18 mm to 12 mm. Finally, the study underscores the critical roles of the inner pipe dimensions as a passive technique in optimizing heat exchanger efficiency.
Highlights
1. The CFD simulation of a double-pipe heat exchanger was validated experimentally with high
accuracy.
2. Deviation between experimental and simulation results ranged were 0–12.95% for the OHTC and
0–11.63% for effectiveness.
3. Pipe inner diameter, flowrate and fluid temperatures were identified as key parameters influenc
ing thermal performance.
4. Reducing the ID pipe to 12 mm enhanced the overall heat transfer coefficient and effectiveness
by 188% and 177%
Keywords: Double pipe heat exchanger, Counter flow, CFD analysis, Heat transfer enhancement,
Difference diameters, Effectiveness, Overall heat transfer coefficient
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/13/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1012&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

23/06/2026

Metaheuristic Evaluation of Paraffin Wax-Related Flow Assurance Challenges for Optimal Productivity in Onshore Facilities
https://doi.org/10.30684/2412-0758.1011
Abstract
In this research, paraffin wax deposition models were evaluated using a multi-objective genetic algorithm (MOGA). This is a metaheuristic approach to multi-parametric solution of complex mathematical problems. The study aims to apply a suitable metaheuristic technique to analyse the parameters of paraffin wax-related flow assurance issues in onshore oil and gas facilities in Nigeria, thereby ensuring optimal productivity and operational efficiency. Thus, a paraffin wax sample collected from a typical onshore production facility was analysed in a laboratory to determine its thermophysical and transport properties and composition. These properties are the WAT, melting point, flash point, liquid density, and dynamic viscosities, respectively, given as 32 °C, 52 °C, 191 °C, 906 kg/m3 and 6.812 × 10-5kg/ms. This showed the range of safe thermal exposure for optimal flow assurance. Also, the compositional analysis revealed the molecular mass, molecular formula, structural formula, and spectral orientations of the different components of the sample. The molar volume of the heaviest component was estimated to evaluate the time required for a wax particle to diffuse a length equal to its diameter under different deposition mechanisms. The average minimum times taken by a wax particle to diffuse a length equal to its diameter by molecular diffusion, Brownian diffusion, shear dispersion, gravity settling, and thermal diffusion are respectively 1.0265 × 1016 seconds, 4.6650 × 1026 seconds, 2.0004 × 103 seconds, 9.9010 × 103 seconds and 4.7453 × 109 seconds. Therefore, maintaining the safe thermal exposure of the waxy fluid in the piping system and ensuring the residency time does not exceed the minimum of these values guarantees optimal flow assurance and operational efficiency.
Highlights
1. Laboratoryanalyses were conductedonparaffinwaxcollectedfromanonshorefacilityinNigeria.
2. Thermophysical and transport properties of paraffin wax were determined through laboratory
analysis.
3. Thesafetemperature range for the paraffin wax sample was found to be between52°Cand191°C.
4. Minimum diffusion times for paraffin wax particles were evaluated using MOGA with different
methods.
Keywords: Piping systems, Flow assurance, Paraffin wax deposition, Multi-objective, Genetic algo
rithms
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/12/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1011&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

22/06/2026

Numerical Study of Thermal Stress and Deformation in Piston and Cylinder Head Assemblies
https://doi.org/10.30684/2412-0758.1010
Abstract
This study examines the behavior of thermal stress and deformation in piston and cylinder head assemblies of internal combustion engines using numerical simulation techniques. Computational Fluid Dynamics (CFD) is employed to investigate the influence of varying thermal loads on the structural response and durability of these critical engine components. In our numerical investigation, we aimed to understand the role of temperature differences in thermal stresses and deformations within piston-cylinder head setups. These rates are indicative of the severe thermal stresses experienced by the material, which are significantly higher than typical rates observed in standard operating conditions. Results show that peak crown temperatures reach 320–400 °C, producing von Mises stresses of 150–220 MPa, which are concentrated at the ring-land region, leading to localized plastic strains of 0.1–0.3%. Radial skirt expansion of 50–150 μm and a 10–30 % reduction in contact pressure at the liner were also predicted. Parametric studies demonstrated that increasing crown thickness and enhancing cooling can lower peak stresses by 10–20%, while stronger alloys increase the allowable stress margin by 30%. A combination of these temperature variations, the materials’ characteristics, and the gaps in assembly all contribute to hotspots of stress and bending, especially in zones subjected to sharp thermal shifts, such as the top of the piston and the walls surrounding the combustion area. Beyond that, this work lays a solid groundwork for refining future engine layouts and offers practical guidance for extending the lifespan and improving the efficiency of internal combustion engines.
Highlights
1. FEA and CFD were used to study temperature distribution and thermal stresses in pistons and
cylinder heads.
2. Materials including ceramic coatings, were investigated to reduce thermal stresses and enhance
engine performance.
3. Evaluating the integrity of pistons and cylinder heads under combined thermal and mechanical
loads.
4. Design optimization studies showed that modifying piston rib structures can effectively reduce
thermal stresses and improve performance.
Keywords: Thermal, Deformation, Piston, Cylinder head, Computational fluid dynamics, Internal
combustion engine
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/11/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1010&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

21/06/2026

Enhancing Solar Desalination Performance Through PCMs, Nanomaterials, and Intelligent Control: A Review of Integrated Approaches
https://doi.org/10.30684/2412-0758.1009
Abstract
Solar desalination utilizing Phase Change Materials (PCMs) and nanomaterials offers promising avenues for water purification. Still, challenges must be addressed: PCM limitations include low thermal conductivity, supercooling, corrosion, and leakage, while nanomaterial challenges include stability, aggregation, toxicity, and scalability. System integration and performance include complexity, hybrid optimization, fouling, scaling, and durability. Intelligence can enhance the thermal work of systems with still water by enabling smarter design and control. This system relies on robust monitoring to provide data for analysis, optimization, and efficient operation. Monitoring is indispensable for reviewing and improving such systems. Freshwater scarcity is a global issue, especially in remote and off-grid areas. Solar stills offer a sustainable solution for potable water because they are simple and rely on solar energy. However, traditional stills suffer from low efficiency and limited output. Recent advancements aim to enhance performance by integrating PCMs, wick structures, and smart monitoring. PCMs such as paraffin wax and salt hydrates store latent heat, enabling extended operation during low-solar-radiation periods and minimizing temperature fluctuations. Nano-enhanced PCMs improve thermal conductivity and heat transfer. Wick materials facilitate water transport through capillary action. Their porous, dark surfaces enhance solar absorption, maintain a thin water layer, and expand the evaporation surface. Monitoring systems powered by Arduino, ESP32, or IoT devices track temperature, humidity, and water levels, enabling automation and remote control. Integration of efficient PCMs, wick materials, and digital monitoring offers a cost-effective, scalable approach to address water scarcity.
Highlights
1. Solar still systems with PCM were analyzed to enhance heat storage and distillation performance.
2. Wick materials were assessed for improving capillary action and thermal conductivity.
3. Monitoring and control systems were highlighted as essential for real-time optimization.
4. Various PCMs were compared by type, melting point, and basin placement for better heat
retention.
5. Integrating wick, PCM, and smart monitoring significantly improved productivity and efficiency.
Keywords: Solar still, Phase change material, Nanomaterials, Wick materials, Smart monitoring
(IoT)
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/journal/vol44/iss1/10/
Article: https://etj.uotechnology.edu.iq/cgi/viewcontent.cgi?article=1009&context=journal
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Engineering and Technology Journal

22/09/2026

20/09/2026

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