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Abstract This paper investigates the forced convection of alumina-water nanofluids within helical tubes, maintaining a constant wall temperature and assuming thermal equilibrium between the nanoparticles and the base fluid. The nanofluid model incorporates the effects of alumina (Al2O3) nanoparticle volume fraction, diameter, and temperature on thermophysical properties. The governing equations are solved using the Forward-Time Central-Space Finite Volume method in conjunction with the simple algorithm. Numerical results are validated against experimental data, demonstrating high accuracy. The study explores the effects of pitch size, curvature ratio, nanoparticle volume fraction, nanoparticle diameter, and Reynolds number on velocity contours, temperature profiles, secondary flow, thermophysical properties, friction coefficient, and heat transfer rate. Additionally, the figure of merit evaluates the impact of these parameters on the thermal performance of the system. The results indicate that an increase in Reynolds number and nanoparticle diameter negatively affects thermal performance, while higher nanoparticle volume fraction, curvature ratio, and pitch size enhance it. Furthermore, incorporating nanoparticles in straight tubes proves to be more advantageous compared to helical tubes. This study tested volumetric ratios of 1%, 2%, and 4%, which resulted in increases in heat transfer coefficients of 21%, 32%, and 43%, respectively, compared to pure water under similar conditions, such as Reynolds number and coil pitch.

The textile industry plays a major part in the economy of the Kingdom of Saudi Arabia (KSA). However, the environmental impact of textile dyeing and wastewater discharge has become a growing concern in the region. This study addressed this issue by identifying and characterizing azo dye degrading enzymes that can be used in bioremediation strategies. Six enzymes, namely Thiol reductase, Thiol peroxidase, Alkene reductase, NADH-oxidoreductase, Oxidoreductase, and Sulfite reductase, were identified through a literature review and used as queries in BLASTp to search for homologous enzymes from Bacillus cereus, Brevibacillus brevis, Bacillus acidicola, and Paenibacillus alvei. The physicochemical characteristics and subcellular distribution of these enzymes were determined using online tools. Phylogenetic analysis was performed to investigate the evolutionary connection of these enzymes across different bacterial species. Additionally, gene structure and motif analysis were conducted to gain insights into functional motifs and gene organization of these enzymes. Domain prediction and protein–protein interaction analysis were carried out to identify conserved domains and potential protein interactions. The outcomes of this study offer valuable understandings on prospect of azo dye degrading enzymes for bioremediation strategies in the KSA textile industry, which is in agreement with the future Vision 2030 strategy. The identified enzymes and their homologs from other microbial genomes represent promising candidates for further experimental validation and utilization in bioremediation processes. Moreover, they contribute to the development of effective bioremediation strategies for the textile industry in the KSA region. Overall, this study enhances our understanding on azo dye degrading enzymes and their potential uses in the textile industry, particularly in the context of KSA.

Enhancing the performance of traditional vapor compression cooling cycles is an important aspect in the quest to minimize global energy consumption, to own sustainable energy systems soon, and to preserve the environment. This study performed a comparative analysis of the performance of a water cooler with different working fluids to replace R143a and improve system performance. A mathematical model derived from energy and exergy analysis is developed for the evaluation of the effect of operating conditions on the system COP, exergetic losses, and exergetic efficiency. The evaluation has been conducted for evaporation and condensation temperatures ranging between -30°C to 15°C and 25°C to 55°C, respectively. Results showed that the cycle with R510A has the maximum COP. The average system COP with R510A, RE170, and R152a are 19.54%, 13.53%, and 9.36 % higher than that with R134a, respectively. The highest value of exergy loss takes place in the compressor. At different working fluids, exergy losses decrease as evaporation temperatures increase and condensation temperatures decrease. The system with R510A has the minimum exergy losses. The average exergy losses for systems with R510A, RE170, and R152a are 34.62%, 28.33%, and 18.64% lower than that of R134a, respectively. The system with R510A has higher exergy efficiency and R134a has the minimum values of exergy efficiency. Generally, the water cooler provided better performance with R510A and RE170 than with R152a and R134a. Therefore, R510A can be considered as the best replacement for R134a and R152a.

Gas turbine (GT) power plants operating in arid climates suffer a decrease in output power during the hot summer months because of insufficient cooling. Cooling the air intake to the compressor has been widely used to mitigate this shortcoming. An energy analysis of a GT Brayton cycle coupled to a refrigeration cycle shows a promise for increasing the output power with a little decrease in thermal efficiency. A thermo-economics algorithm is developed and applied to an open cycle, Hitachi MS700 GT plant at the industrial city of Yanbu by the Red Sea in the Kingdom of Saudi Arabia. Result shows that the enhancement in output power depends on the degree of chilling the air intake to the compressor (a 12 - 22 K decrease is achieved). For this case study, maximum power gain ratio (PGR) is 15.46%, at a decrease in thermal efficiency of 12.25%. The cost of adding the air cooling system is also investigated and a cost function is derived that incorporates time-dependent meteorological data, operation characteristics of the GT and the air intake cooling system and other relevant parameters such as interest rate, lifetime, and operation and maintenance costs. The profit of adding the air cooling system is calculated for different electricity tariff.

electricity. In this research, the potential of ZigZag PVNBs has been investigated. The ZigZag Solar product, developed by Wallvision, has proven to offer multiple advantages in energy yield and aesthetics for building fa & ccedil;ade applications. For noise barrier applications, the ZigZag structure could offer interesting features in safety and noise cancellation (obtained by filling the ZigZag construction with Rockwool material) on top of the advantages in aesthetics and energy yield. A ZigZag PVNB has been designed and constructed at the Brightlands Chemelot Campus in Geleen, after which the electrical performance has been automatically monitored under Dutch climate conditions. The measurements have been compared to simulated data, which allowed optimiza

The conventional approach for controlling the supply temperature in collective space heating networks relies on a predefined heating curve determined by outdoor temperature and heat emitter type. This prioritises thermal comfort but lacks energetic and financial optimisation. This research proposes an adaptive supply temperature control in well-insulated dwellings, responsive to diverse environmental parameters. The approach considers variable electricity prices and accommodates different indoor temperature set points in dwellings. The study evaluates the effectiveness of two Deep Reinforcement Learning (DRL) algorithms, i.e., Proximal Policy Optimisation (PPO) and Deep Q-Network (DQN), across various scenarios. Results reveal that DQN excels in collective space heating systems with underfloor heating in each dwelling, while PPO proves superior for radiator-based systems. Both outperform the traditional heating curve, achieving up to 13.77% (DQN) and 16.15% (PPO) cost reduction while guaranteeing thermal comfort. Additionally, the research highlights the capability of DRL-based methods to dynamically set the supply temperature based on a cloud of set points, showcasing adaptability to diverse environmental factors and addressing the growing significance of indoor heat gains in well-insulated dwellings. This innovative approach holds promise for more efficient and environmentally conscious heating strategies within collective space heating networks.

The world is currently grappling with the detrimental effects of escalating pollution stemming from exhaust gases emitted by vehicles, exacerbating environmental degradation and posing severe health risks. To mitigate this crisis, leveraging appropriate technologies capable of curbing emissions is imperative. A recent study undertook a comprehensive assessment, comparing the carbon footprint of various vehicles, considering parameters such as emissions in battery manufacturing and fuel consumption. Employing entropy and TOPSIS methodology, the analysis assigned weights and rankings to these criteria and vehicle alternatives. Results indicated that battery manufacturing emissions carried the most significant weight (81.91%), followed by emissions from fuel consumption (15.99%). Hybrid vehicles emerged as the most favorable alternative, closely followed by biodiesel, exhibiting the lowest carbon emissions including CO, CO2, and UBHC. This study offers invaluable insights for future decision-makers in the transportation sector, facilitating informed choices towards adopting environmentally sustainable vehicles, thereby contributing to a greener and healthier future.

The natural fiber composites have attracted much interest among the researchers, due to their low cost, easy availability and enhancement in their properties. Many plants based natural fibers, including banana, sisal, hemp, jute, oil palm, Coirand kenaf, among others, have been studied extensively. Sansevieria cylindrica fiber (SCF) is one of the plant-based leaf fibers, which has not been explored to a greater extent. The main purpose of this study focused on utilizing SCF as a potential reinforcement to produce polyester matrix composites. Unsaturated polyester resin was used as matrix, because of its low cost and ease of use. In this work, free vibration studies were performed for pure SCF reinforced polyester composites. The SCF composites were fabricated with various fiber percentage weight (wt%) and different curing temperatures. The effects of both fiber wt% and curing temperatures on natural frequency and damping of SCF composites were studied. It was observed that both natural frequency and damping showed significant variations on different process conditions of polymer composites. Based on vibrations studies, the optimum fiber wt% was obtained at 40 and optimum curing temperature was observed as 60 °C. Furthermore, the effects of various chemical treatments on vibration behaviors of SCF composites was also investigated for the optimum fiber loading and curing temperature of 40 wt% and 60 °C, respectively. Ca(OH)2 treated composite exhibited highest natural frequencies for all the three modes of vibration and silane treated counterpart showed highest damping values for the last two modes of vibration. Therefore, it was evident that chemical treatment significantly influenced the dynamic properties, including natural frequency and damping of SCF reinforced polyester composites. This study can guide the composites/manufacturing companies to design and manufacture composites for engineering system applications, especially where vibration response is inevitable.

With the advent of employing bio-fuels along with the diesel in compression ignition engines the study of performance and emission characteristics have occupied the prominence, owing to diversified multi responses. As the limited information is available about the application of Taguchi based GTMA process to maximize the overall performance and emission characteristics of diesel engine, in the present work the investigation was carried out to maximize the overall utility by employing the Taguchi based GTMA process. By following the user preference rating, weights for the response characteristics namely brake thermal efficiency, brake specific fuel consumption, carbon monoxide and oxides of nitrogen were calculated using graph theory and matrix approach (GTMA). The parameter hydrogen induction played a major role to an extent of 78.62% while Injection opening pressure playing a minor role with a contribution of 7.06%. The optimal parameters condition was at mid-level of the governing parameters namely IOP, CR and volume of hydrogen inducted. The predicted results were within 95% of confidence interval of the optimal values. Therefore, the hydrogen inductance into the cylinder not only improving the performance but also minimizing the emission characteristics.