Solar power plants that incorporate parabolic trough collectors (PTC) to generate solar energy can be regarded as a viable alternative to conventional power plants. To enhance the performance and productivity of these systems, it is imperative to improve the direct steam generation process. This study proposes the implementation of a passive enhancement technique to improve steam production in the PTC absorber, with the aim of optimising the overall size and cost of solar power plants. For this purpose, longitudinal fins have been attached to the inner bottom part of the tube. A numerical investigation was conducted to examine the two-phase flow with vaporisation using the ANSYS Fluent code. The analysis of two-phase flow was carried out via the volume of fluid technique. Additionally, a phase-change model was integrated to elucidate the vaporisation process. The Monte-Carlo ray-tracing approach was employed to identify the irregular distribution of heat flux across the tube. The integration of fins within the absorber tube has been demonstrated to enhance heat transfer and vapor fraction, thereby optimising the thermal performance of the system. Furthermore, the configuration that optimised steam generation was achieved through the utilisation of an absorber tube equipped with two rectangular longitudinal fins, displaying an aspect ratio of 0.5. The optimum thermal performance factor was found to be 1.58, which is reached in the laminar regime. The study's findings indicate a reduction in the overall dimensions of the PTC absorber, leading to a decrease in the size of solar power plants and their associated costs.

This study addresses the critical challenge of reducing operating temperature in photovoltaic (PV) systems, as excessive heat generation impairs their electrical efficiency and power output. A novel mini-channel heat sink with a folded U-shaped fin design is introduced to enhance heat dissipation, offering a scalable solution for optimizing PV performance. The design increases the heat transfer area while reducing airflow velocity by narrowing the channels, and optimizing thermal management. Experiments were conducted indoors under controlled conditions, with inlet air velocity of 0.3, 0.6, 0.8, and 1 m/s and solar irradiances of 500 and 1000 W/m². The outcomes showed that the mini-channel heat sink effectively reduced the average cell temperature by 57.44 %. This significant thermal regulation increased electrical efficiency by 26.6 %, resulting in a 37.55 % increment in power output. The experimental findings were further compared to numerical simulations achieving an acceptable range of variation and ensuring the reliability of the results with an average heat transfer coefficient error percentage below 5 %. The originality of this work lies then in its unique U-shaped mini-channel design, which mitigates thermal stress and optimizes energy output. It provides a promising approach to advancing PV cooling technologies and a scalable solution for improving solar energy efficiency.

This research conducts a comprehensive numerical evaluation into an advanced heat dissipation system for low-concentrated photovoltaic systems, addressing the limitations of conventional minichannel heat sink designs. To overcome their inherent inefficiencies, a novel minichannel configuration with wavy surfaces and a trapezoidal inlet section (TWMC) is proposed, aiming to enhance convective heat transfer through increased surface area and induced flow turbulence. Three configurations wavy minichannel (TWMC), trapezoidal minichannel (TMC), and rectangular minichannel (RMC) are systematically compared in terms of key performance metrics, including thermal resistance, Nusselt number, pressure loss, and friction index. Water serves as the coolant, operating in a laminar flow regime (Re = 200–900) and absorbing a uniform heat flux of 100 kW/m² applied to the channel base. Results demonstrate that the TWMC configuration outperforms conventional designs, achieving a 30.82 % decline in heat resistance and a 9.2 % surge in Nusselt number at peak Reynolds numbers. The TWMC design improves the performance evaluation criterion (PEC) to 1.06, with exceptional overall thermohydraulic performance PEC(R) ranging from 1.078 to 1.271, despite higher pressure drop. These findings offer insights into optimizing CPV system performance, emphasizing the potential of innovative wavy-channel geometries to revolutionize thermal management and energy efficiency in advanced photovoltaic applications.

A numerical investigation is undertaken, employing a 3D conjugated heat transfer model to examine the impact of geometric configurations and hydrodynamical parameters on the overall thermal resistance and pumping power in mini-channels heat sinks. The aim lies in its holistic approach, integrating the non-uniform section of the mini-channel, the impact of the inlet velocity, the energy and exergy analysis, multi-objective optimization and performance evaluation criteria (PEC) evaluations, and the consideration of metal Galinstan and Cu-water nanofluid working fluids. The parametric analysis highlighted metal Galinstan as the best coolant for the five configurations involved in the present study. Furthermore, The PEC results indicate that the best performance is achieved by the Converged-Diverged Mini-channel (CDMC)heat sink. CDMC configuration with metal Galinstan performs well in terms of exergy evaluations and shows a better average temperature distribution with a maximum temperature of about 328K. The optimal inlet velocity (Uin = 0.21 m/s) is determined on the basis of the pumping power and thermal resistance profiles. The optimization process is based on the impact of the mini-channel's maximum width on the PEC. It is shown that the PEC increases with the maximum width of the CDMC and the highest (PEC = 1.31) is obtained at a maximum width of 0.95 mm.

L'écriture est une compétence fondamentale au cours de la scolarité primaire, permettant non seulement de communiquer des idées, mais aussi de développer la créativité des élèves. Cet article examine l’importance de l’enseignement de l’écriture aux élèves du primaire dans un contexte plurilingue. Nous proposerons des outils et des méthodes qui favorisent une écriture authentique et confiante.

Global sustainability initiatives increasingly rely on innovative technologies to safeguard biodiversity and mitigate environmental impacts. In this paper, we present EcoWatch, a novel framework that leverages Wireless Multimedia Sensor Networks (WMSNs) using LoRaWAN technology for efficient data transmission to enable real-time bird species detection and counting in their natural habitat. EcoWatch combines YOLOv8 You Only Look Once for object detection and Learning to Count Everything (LTCE) for precise object counting at the base station. To address the inherent limitations of WSNs in terms of energy and bandwidth, EcoWatch incorporates a multi-level ROI-based video compression technique. Extensive evaluation demonstrates that EcoWatch significantly reduces energy consumption (up to 58.7%) and data transmission load (by 69.8%) compared to other methods while maintaining acceptable image quality, detection and counting accuracy. Notably, EcoWatch exhibits robust performance across seasons and adapts well to varying environmental conditions, making it a promising solution for real-world ecological monitoring applications.

This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.