Sami Al-Alimi

PV panels has been proven to be a good renewable energy source. However, excessive heat of the panel can lead to degradation of the longevity of the panel. Crucial determinants impacting the effectiveness of PV panels encompass the type of materials, temperature, and the level of solar radiation received. Thus, cooling is required to overcome this issue which leads to improved electrical efficiency and lifespan of the panel. This study provides an overview of different techniques that can be employed to mitigate the adverse effects of elevated temperatures while simultaneously improving the performance of photovoltaic solar panels operating above the recommended temperature of the Standard Test Conditions (STC). The objective of this review is to enhance comprehension of the mentioned technologies in order to decrease the surface temperature of the PV module. Cooling methods that are reviewed are heat exchanger, nanofluids and phase change material (PCM). The review and classification of many research publications is conducted based on their specific focus, contribution, and the sort of technology employed to facilitate the cooling of photovoltaic panels. Each of these systems is exemplified with precise schematics and extensively examined and compared. Moreover, this work presents a novel categorization system for the cooling techniques employed in photovoltaic panels, providing useful direction for future investigations and enhancing efficiency. The findings of this review shows that heat exchanger with higher flowrate has better higher temperature improvement. Moreover, different heat exchanger pipes shapes resulted in different cooling efficiency outcome. Hybrid nanofluids shows higher temperature drops compared to nanofluid with water. Addition of porous material to PCM resulted in a lower melting point thus cooling occurs faster compared to regular PCM.

This study presents a detailed computational fluid dynamics (CFD) investigation into the aerodynamic performance of the NREL Phase VI wind turbine, focusing on torque and power generation under different turbulence models. The primary objective was to analyse the effect of various turbulence models and their responses in wind turbine torque generation. Furthermore, it also investigates the distance effect on wind velocity deficit. The research utilizes 2D and 3D simulations of the S809 airfoil and the full rotor, examining the predictive capabilities of the k-epsilon, k-omega, and k-omega SST turbulence models. The study incorporates both experimental validation and wake analysis using the Gaussian wake model to assess wind velocity deficits. Simulations were conducted for a wind speed range of (6–10 m/s), with results indicating that the k-epsilon model provided the closest match to experimental data, particularly at higher wind speeds within the targeted range. Even though k-epsilon results had better agreement when validated with experimental data, theoretically k-omega (SST) should perform better as it combines k-epsilon and k-omega advantages in predicting the flow regardless of its farness from the wall. However, in simulations using the k-omega (SST), the separation of flow and the shear stress transients were only visible at wind speeds of 10 m/s or higher. Wake effects, on the other hand, were found to cause significant velocity deficits behind the turbine, following an exponential decay pattern. The findings offer valuable insights into improving wind turbine performance through turbulence model selection and wake impact analysis, providing practical guidelines for future wind energy optimizations.

This study delves into computational fluid dynamics (CFDs) predictions for SiO₂–water nanofluids, meticulously examining both single-phase and two-phase models. Employing the finite volume approach, we tackled the three-dimensional partial differential equations governing the turbulent mixed convection flow in a horizontally corrugated channel with uniform heat flux. The study encompasses two nanoparticle volume concentrations and five Reynolds numbers (10,000, 15,000, 20,000, 25,000, and 30,000) to unravel these intricate dynamics. Despite previous research on the mixed convection of nanofluids using both single-phase and two-phase models, our work stands out as the inaugural systematic comparison of their predictions for turbulent mixed convection flow through this corrugated channel, considering the influences of temperature-dependent properties and hydrodynamic characteristics. The results reveal distinct variations in thermal fields between the two-phase and single-phase models, with negligible differences in hydrodynamic fields. Notably, the forecasts generated by three two-phase models—Volume of Fluid (VOF), Eulerian Mixture Model (EMM), and Eulerian Eulerian Model (EEM)—demonstrate remarkable similarity in the average Nusselt number, which are 24% higher than the single-phase model (SPM). For low nanoparticle volume fractions, the average Nusselt number predicted by the two-phase models closely aligns with that of the single-phase model. However, as the volume fraction increases, differences emerge, especially at higher Reynolds numbers. In other words, as the volume fraction of the nanoparticles increases, the nanofluid flow becomes a multi-phase problem, as depicted by the findings of this study.

The primary objective of this research is to investigate the process of direct recycling of AA7075 aluminium alloy, which is extensively utilised in the aerospace and flight sectors due to its exceptional strength and lightweight characteristics. Alumina (Al₂O₃) is used as a reinforcing agent and the effect of hot press forging (HPF) parameters on the mechanical characteristics and surface integrity of the metal matrix composite (MMC) constructed of AA7075 alloy with 1% Al₂O₃ has been studied. Furthermore, the utilisation of an integrated life cycle assessment (LCA) approach is implemented to assess the environmental impacts and economic expenses associated with the recycling of aluminium via high-pressure forming for both the metal matrix composite and AA7075 alloy. Response surface methodology (RSM) is applied to ascertain the optimal parameters for high-performance filtration. The findings suggest that employing a forging temperature of 532.34 °C and a holding time of 60 min produces favourable results. When comparing the characteristics of the MMC and recycled aluminium, it can be observed that they both demonstrate similar essential process attributes. The utilisation of HPF in conjunction with the Multi-Material Composite has the potential to yield a reduction of up to 24.97% in Global Warming Potential (GWP). This research demonstrates the efficacy of HPF as a viable approach for environmentally conscious and economically efficient recycling of AA7075 aluminium scrap, thereby improving product performance and promoting sustainability.

In the context of Industry 4.0, manufacturing metrology is crucial for inspecting and measuring machines. The Internet of Things (IoT) technology enables seamless communication between advanced industrial devices through local and cloud computing servers. This study investigates the use of the MQTT protocol to enhance the performance of circularity measurement data transmission between cloud servers and round-hole data sources through Open CV. Accurate inspection of circular characteristics, particularly roundness errors, is vital for lubricant distribution, assemblies, and rotational force innovation. Circularity measurement techniques employ algorithms like the minimal zone circle tolerance algorithm. Vision inspection systems, utilizing image processing techniques, can promptly and accurately detect quality concerns by analyzing the model’s surface through circular dimension analysis. This involves sending the model’s image to a computer, which employs techniques such as Hough Transform, Edge Detection, and Contour Analysis to identify circular features and extract relevant parameters. This method is utilized in the camera industry and component assembly. To assess the performance, a comparative experiment was conducted between the non-contact-based 3SMVI system and the contact-based CMM system widely used in various industries for roundness evaluation. The CMM technique is known for its high precision but is time-consuming. Experimental results indicated a variation of 5 to 9.6 micrometers between the two methods. It is suggested that using a high-resolution camera and appropriate lighting conditions can further enhance result precision.

Hydropower is considered one of the most reliable, inexpensive and environmentally friendly sources of renewable energies and it is predicted to play a significant role in future sustainable energy systems. The straight-blade Darrieus turbine is receiving more attention as it is simple to build at an inexpensive cost. However, Darrieus turbines still have a lower efficiency as opposed to axial turbines. Therefore, in this study, the Darrieus turbine is equipped with a duct geometry in the center in order to enhance its conversion efficiency using the computational fluid dynamics (CFD) simulation technique. A 2D simulation model with NACA 663-018 airfoil profile is developed to perform the simulation in Ansys Fluent software while using the K-ω shear stress transport (SST) as the turbulence model. The computational simulations cover a parametric study based on the variation of the rotational speeds while keeping the upstream velocity constant. The performances are evaluated in terms of power, power coefficient, torque and torque coefficient. The simulation results showed that the power coefficient and torque coefficient were found to increase with the rotational speeds with the highest efficiency at the TSR of 2 and then decrease. A similar conclusion was drawn in terms of power and torque output. However, the maximum power coefficient and torque coefficient were about 54% and 27%, respectively.

Wind resource assessment is a key stage in planning for a wind energy project to predict the output power. Therefore, a full understanding of the wind characteristics at the potential site is required. This study examines the potential wind power of twelve meteorological stations in the Chittagong division over a tenure of ten-year ranges from 2010 to 2019. The statistical analyzer as the Weibull two-parameter distribution method has been utilized to determine the characteristics of wind speed and wind energy potential at the selected locations. The "WRPLOT" software has also been used to display the wind direction and the corresponding wind speed direction. Among these stations, Ambagan has a high wind factor, ranging from 2.1 to 3.2 m/s. The highest wind speed for Ambagan station was recorded in April (3.26 m/s) and the lowest was in November (1.06 m/s) compared to other selected stations. The Weibull form parameter (k) and scale parameter (c) at Ambagan station had the highest values of 1.5 and 3.5 m/s, respectively. With additional analysis and observation of these parameters, it became possible to predict the location in Chittagong with the greatest wind energy potential. In terms of wind direction, the prevailing wind direction of all stations is generally in the south. Furthermore, the results concluded that all of the analyzed parameters considered for wind behavior were numerically higher for Ambagan in contrast to other stations of the Chittagong division. This study clearly indicates that the Ambagan station should be used to maximize the potential of wind energy to attain the future goals of sustainable development for Bangladesh.