Engineering and Technology Journal

Solar thermal energy is essential for industrial and home applications, such as solar drying, space heating, water heating, and water desalination. Solar collectors are essential elements in these systems, as they transform solar irradiance into thermal energy. Evacuated heat pipes (EHPs) have emerged as efficient thermal transfer devices among sophisticated solar thermal technologies, capable of handling heat with low losses. These pipes function by employing a vacuum-sealed environment that markedly diminishes thermal resistance and convective heat loss. The heat transfer process is facilitated by the phase change of a working fluid, which evaporates at the heat source and condenses at the cooler end, so permitting efficient thermal management. This research study provides a thorough examination of developments in heat pipe-evacuated tube solar collectors (ETSCs), emphasizing diverse techniques for improving their efficiency. The initial section underscores the significance of ETSCs in solar residential hot water systems, outlining the particular applications and benefits of various collector types. The second section addresses the application of nanofluids to enhance heat transfer efficiency and the incorporation of phase change materials (PCMs) to guarantee a continuous heat supply, even post-sunset. Moreover, the work proposes the ideal concentration of nanofluids for diverse applications, offering significant insights for the next research.

Composite sandwich panel structures have been widely used in engineering and aerospace applications. Predicting the flexural properties of theoretical composite constructions is crucial for efficiently designing sandwich composite panel products. This research investigates four different cell core forms—circular, hexagonal, rectangular, and triangular—utilized in the manufacture of sandwich composite structures using a numerical program. For each case, the sandwich composite panel structure maintained constant weight and constant thickness for all models. The skin was fabricated from one layer of carbon fiber and two layers of glass fiber, combined with 3% carbide silicon and 6% polysulfide rubber in an epoxy matrix. The volume fraction for both carbon fiber and glass fiber was 35%, embedded in the epoxy mixture containing polysulfide rubber and carbide silicon (SiC). Finite element analysis using ANSYS Workbench 17.2 under three-point bending tests of the models revealed the rectangular cell core form as the optimal choice, exhibiting the least distortion (0.42992 mm) compared to other forms. The circular, hexagonal, and triangular core forms demonstrated deformations of 0.47267 mm, 0.48254 mm, and 0.51483 mm, respectively, representing a 9.05%, 10.91%, and 16.5% increase in deformation compared to the rectangular core. The maximum elastic strain for the rectangular core was 0.0067369, while the circular, hexagonal, and triangular cores exhibited strains of 0.0098421, 0.0092298, and 0.0072145, respectively, showing a 31.55%, 27%, and 6.62% increase in strain compared to the rectangular core. From the results of the finite element analysis, the rectangular model was chosen for manufacturing experimental models. Three models were prepared according to the bending test requirements. The experimental results demonstrated strong agreement with the numerical findings of this study.

The interaction between structures and fluid flow in a direction perpendicular to
the body can induce vibrations in the structure, a phenomenon known as vortexinduced
vibration (VIV). This phenomenon may lead to structural failure due to
resonance, which occurs when the natural frequency of the structure matches the
vortex shedding frequency. Therefore, it is essential to employ vibration control
devices to address the resulting high-amplitude instabilities. In this study, a
subsonic wind tunnel with open-circuit specifications was constructed. This opentype
wind tunnel generates airflow at varying velocities through the test section.
To control vibrations around the cylindrical pipe, an Open-Loop Active Vibration
Control (OLAVC) system is proposed. This system utilizes dual control rods,
made of hollow stainless steel, driven by two DC motors positioned at the upper
and lower sides of the main cylindrical pipe, referred to as the CRBCP (Control
Rod-Based Cylinder Pipe). The effectiveness of a passive control strategy was
evaluated prior to energizing the DC motors at 12 V. The results indicated that
passive control alone was insufficient to adequately suppress the vibrations of the
cylinder pipe. Subsequently, the OLAVC procedure was implemented using
several voltage levels—12 V, 10 V, 8 V, and 6 V—corresponding to 100, 83, 75,
and 50% of motor power, respectively. The OLAVC system proved effective in
reducing vibrations across all actuator configurations. The maximum suppression,
reaching 79.05%, was achieved at a motor voltage of 12 V and a rotational speed
of 2349 rpm.

This study aims to review the use of artificial intelligence applications in the
management of gas turbine stations and their impact on enhancing and raising the
efficiency of these stations, including managing the stations themselves, then
improving operational efficiency, predicting faults, and developing strategies for
road maintenance and precautionary maintenance while reducing the cost
through a methodology that is a combination. One of several methodologies
describes the factors that influence the enhancement of operational efficiency and
management of turbine plants using artificial intelligence applications. The
quantitative methodology in collecting data and studies that included the subject
and the analytical and comparative methods in comparing studies and analyzing
the most critical results reached, as the article relies on an analysis of scientific
literature and recent studies to clarify the potential benefits and challenges
associated with the application of artificial intelligence in this field. The review
discusses the artificial intelligence tools employed, including machine learning
and neural networks, and highlights future innovations that may enhance the
efficiency of turbine systems. The study concludes by discussing current
limitations and providing recommendations for research and development in this
promising field. Most studies have indicated that artificial intelligence
applications play a significant role in enhancing the management of gas turbine
plants, increasing operational efficiency by 3 to 5%, and reducing operating costs
by 8 to 15%.

Integrating AI-driven robotics and automation revolutionizes smart manufacturing
by enhancing operational efficiency, productivity, and system flexibility across
automotive, aerospace, and general equipment manufacturing industries. This
review synthesizes findings from 84 peer-reviewed publications to evaluate the
transformative potential of key AI technologies—including machine learning,
digital twins, edge AI, and human-machine collaboration—in optimizing
production lines and enabling predictive maintenance, real-time monitoring, and
adaptive decision-making. While these innovations offer significant benefits in
quality control, cost reduction, and sustainability, challenges remain in integrating
AI with legacy systems, addressing workforce skill gaps, and ensuring
cybersecurity and ethical compliance. Emerging trends such as 5G-enabled edge
computing and collaborative robots (cobots) pave the way for low-latency
communication and safer, more adaptable production environments aligned with
Industry 5.0 principles. Real-world case studies demonstrate measurable economic
impacts, including a 30% reduction in downtime at KONE’s elevator
manufacturing facility and scalable ROI for SMEs adopting AI-driven solutions.
Furthermore, regulatory frameworks and ethical AI guidelines are increasingly
essential for ensuring transparency, safety, and responsible deployment. Looking
ahead, the convergence of immersive technologies (AR/VR/MR), digital twins,
and ethical AI will further enhance virtual simulation, reduce material waste, and
support sustainable industrial ecosystems. As manufacturers adopt these cuttingedge
innovations, resilient, agile, and human-centric systems will become the new
standard, balancing dynamic market demands with environmental and social
responsibility. Ultimately, AI-driven automation promises to reshape global
manufacturing ecosystems, driving economic growth and sustainable industrial
transformation

This study presents a comprehensive performance and exergoeconomic assessment of a solar-driven triple combined cycle (TCC) power system integrated with a rock bed thermal storage unit and an Organic Rankine Cycle (ORC) for enhanced sustainable power generation in Iraq. The proposed system combines Brayton, Rankine, and Organic Rankine Cycle (ORC) cycles to maximize energy recovery from both high- and low-grade heat sources. The integration of the ORC unit significantly improves system efficiency by utilizing residual thermal energy that would otherwise be wasted. The analysis used Engineering Equation Solver (EES) software, incorporating monthly climatic data from Salahaddin, Iraq. Thermodynamic and exergoeconomic evaluations assessed energy efficiency, exergy destruction, component costs, and electricity production cost. Unlike previous studies, this research introduces an advanced exergoeconomic perspective, providing a more realistic assessment of technical and economic performance. Results indicate that the system achieves a power output of 12.4 MW in June, with energy and exergy efficiencies of 37.37% and 40.8%, respectively, and a unit electricity cost of $33.31 per hour. In January, the output increases to 14.17 MW with higher exergy efficiency (46.21%) but at a higher cost due to reduced solar availability. The addition of the ORC unit enhances both energy recovery and economic performance, especially during periods of low solar input, supporting the system’s viability for year-round renewable power generation

Currently, the demand for sustainable materials has led to an interest in polymer composites filled with mineral fillers and recycled materials. High-density polyethylene (HDPE) is a potential matrix for green composite production due to its widespread application, excellent mechanical properties, ease of recycling, and high density. This study investigates the mechanical properties of HDPE composites containing different mix proportions of calcium carbonate (CaCO₃) and recycled plastic. The mechanical performance of composites was evaluated by testing their tensile strength, elongation at break, Young's modulus, hardness, flexural strength, flexural modulus, and impact strength. Inclusion of CaCO₃ in the matrix resulted in improved stiffness and rigidity of HDPE, with the Young's modulus increasing significantly to 1517.2 MPa for sample A3. However, with an increase in stiffness, there was a decrease in tensile strength and elongation at break, indicating a transition to a more brittle behavior. Samples containing a higher content of recycled plastic showed an increase in ductility and impact resistance, with sample A8 surpassing all others. The blends A9 to A12, which are the most balanced mixtures of HDPE, CaCO₃, and recycled plastic, offered the best compromise in terms of mechanical strength and flexibility. Sample A12 demonstrated good performance in terms of tensile strength (18.71 MPa), elongation at break (90%), Young's modulus (210 MPa), and impact strength (69.9 kJ/m²). The results of the current study support the idea that plastic waste can be recycled and used as components in functional materials, aligning with the sustainable development goals. Recycling plastic reduces landfill waste, conserves resources, and enables the creation of new products, thereby contributing to a more circular economy.

This research investigates the influence of cooling systems on the performance of photovoltaic (PV) solar panels, specifically using pulsing tubes filled with alumina and titanium dioxide nanofluids under conditions characteristic of solar power plants. Cooling photovoltaic (PV) solar panels is essential for improving their efficiency in solar generating facilities. This work examines the use of pulsing tubes containing Al₂O₃ and TiO₂ nanofluids, together with flow-guiding barriers, to enhance cooling efficiency. Through ANSYS Fluent simulations, we determined that two barriers decrease panel temperature by around 20% (from 60 °C to 48 °C), enhance heat transmission by around 30%, and augment efficiency by about 7% relative to the absence of obstacles. Al₂O₃ nanofluid surpasses TiO₂, achieving a temperature reduction of 22% compared to 18%. Pressure drop decreases by ~15% with two obstacles, improving fluid dynamics. These results indicate that efficient cooling solutions may substantially improve photovoltaic panel performance by up to 10%. The project aims to enhance thermal efficiency and minimize fluid strain loss by directing obstacles inside the cooling chamber. Simulations were conducted using ANSYS Fluent, and the results have been validated using empirical data. The study showed that incorporating steering obstacles produced optimal results, significantly reducing panel surface temperature, increasing heat transfer, and improving the cooling fluid's temperature homogeneity. This layout decreased pressure loss and minimized fluid vortices inside the chamber, resulting in enhanced heat transfer and performance, in contrast to configurations without impediments or featuring a single impediment. The results demonstrated optimal machine performance by implementing guiding constraints, whereas low efficiency was seen without such bounds. Furthermore, efficiency decreased around noon when solar radiation reached its zenith due to increased panel temperatures, but subsequently improved when the panels cooled in the following hours. The findings suggest adjusting flow-guiding barriers to improve the efficiency of solar panels under actual operating circumstances