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The present paper investigates the thermal mixing and cooling processes in a passive micromixer, which is applicable for the cooling of electronic devices. Employing a porous block and testing different configurations for the mixing channel is considered to enhance the mixing process and cooling performance. A 2D lattice Boltzmann thermal model is utilized to investigate the thermal performance of a T-micromixer with a porous block. Two different types of mixing channel configurations, including a step-shaped and a zigzag-shaped channel, are considered, and the obtained results are compared with those of the simple mixing channel. The thermal mixing and cooling of two miscible fluids, at 50 and 25°C entering the micromixer, are investigated. The results show that changing the mixing channel configuration may create a chaotic laminar flow, which enhances the heat transfer rate between the mixed flow and the channel wall. Whatever the Reynolds number, the step-shaped mixing channel exhibits better mixing performance than the zigzag-shaped one. For the T-micromixer with a zigzag-shaped and step-shaped mixing channel, the cases with h/H = 0.5 and h/H = 0, respectively, exhibit better thermal mixing and cooling performance. [ABSTRACT FROM AUTHOR]

A growing number of scholars are drawn to using numerical approaches powered by computer simulations as a potential solution to industrial problems. Replicating the compaction process in powder metallurgy with accuracy is one such issue. The Drucker-Prager-Cap model requires parameter calibration as the most used method for simulating powder compaction. This paper addresses this issue and presents a new technique for doing so. Utilizing Abaqus software 2020, the compaction process was simulated for the benchmark powder, which is the alloy Ag57.6-Cu22.4-Sn10-In10. The difference between simulation results and experimental data was reduced by applying the Particle Swarm Optimization technique in Python. The suggested approach may accurately forecast the Drucker-Prager-Cap model parameters, as demonstrated by comparing the optimized parameters utilizing the research's method with their experimental values. The findings revealed how well the suggested approach in this study calibrated the DPC model, yielding three parameters—Young's modulus, material cohesion, and hydrostatic pressure yield stress—with respective RMSEs of 1.95, 0.12, and 324.64 concerning their experimental values. [ABSTRACT FROM AUTHOR]

One of the key issues confronting modern greenhouses is the need to supply the necessary energy in an environmentally friendly manner to facilitate heating and cooling processes within greenhouses. Solar radiation entering the greenhouse during the day can sometimes be more than the energy demand of the greenhouse. In contrast, there are cases where the greenhouse must dissipate a significant amount of heat, absorbed over a long period, either naturally or forcibly, during the cooling process. Moreover, the system's efficiency could be enhanced if there is a mechanism capable of capturing heat expelled during greenhouse cooling and redistributing it on demand. Employing thermal energy storage is critical for maintaining stable temperatures, assuring energy efficiency, encouraging sustainability, and enabling year-round production. This technique ensures a safe environment for crops and eliminates temperature fluctuations inside the greenhouse. Nocturnal thermal energy storage, storing thermal energy during the daytime for later use at night, is essential to managing a contemporary greenhouse because it promotes consistent crop growth, sustainability, and profitability, particularly in areas with severe winters and significant day-to-night temperature variations. This work reviews various types of thermal energy storage systems employed in previous works focusing on greenhouse applications by researchers and categorizes them based on efficient factors. [ABSTRACT FROM AUTHOR]

This work uses artificial neural networks to evaluate heat transfer in a mini-channel heatsink using an alumina/water nanofluid. The multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are employed for the modeling. To apply the artificial neural network analysis, 60 data of experimental works are utilized. The outcomes depicted that the simulated annealing (SA) technique significantly increased the performance of the RBF network, although the optimal MLP structure was discovered by trial and error. The optimized RBF network carried over more data with less than 2% errors as compared to the MLP. While the results of the MLP network showed that the average relative error for the test data set was 2.0496%, this value was 1.417% for the RBF network. The modeling time is a significant determining element when choosing the optimal technique. The RBF network optimization took longer than 60 minutes, even though all MLP structures were run 100 times in less than 15 minutes. In summary, artificial neural networks are effective instruments for simulating these kinds of processes, and their application can save a lot of time-consuming experimentation. Additionally, the RBF network outperforms the MLP in terms of precision while requiring less processing time. [ABSTRACT FROM AUTHOR]

In this paper, a thermal performance assessment of traditional building constructions and configurations in various Moroccan climates is carried out. This research focuses on enhancing conventional energy efficiency of buildings by investigating the thermal behavior of single clay walls, double clay walls, simple brick walls, and double brick walls based on long-term meteorological data using TRNSYS software. The roof pitch, thermal comfort and discomfort index, and building energy consumption are considered while selecting buildings for each temperature zone. It is noticed that the double brick construction is more efficient in all climatic zones of Morocco. Thus, this material reduces the yearly energy requirement of building by 22% to 25% compared to the usual brick building. On the coldest winter days, a 30° south-facing roof raises the internal temperature by 2.5 °C compared to a horizontal roof. Temperature increases could reduce the air conditioning energy usage by 7% to 32% and overcooling hours by 12% to 21% in cities above 30° N. In addition, the findings are interesting enough to inspire individuals to implement the recommended construction design and study energy efficiency and thermal comfort in Moroccan buildings. Consequently, reducing energy consumption, mitigating climate change, and lowering greenhouse gas emissions. [ABSTRACT FROM AUTHOR]