Search Results (3,428)

Urban planning in arid climates must overcome numerous nonclimatic constraints that often result in outdoor thermal discomfort. This is particularly evident in Béchar, a city in southern Algeria known for its long, intense summers with temperatures frequently exceeding 45 °C. This study investigates the influence of urban morphology on thermal comfort and explores architectural and digital solutions to enhance energy performance in buildings. This research focuses on Béchar’s city center, where various urban configurations were analyzed using a multidisciplinary approach that combines typomorphological and climatic analysis with numerical simulations (ENVI-met 3.0 and TRNSYS 16). The results show that shaded zones near buildings have lower thermal loads (under +20 W/m²), while open areas may reach +100 W/m². The thermal comfort rate varies between 22% and 60%, depending on wall materials and occupancy patterns. High thermal inertia materials, such as stone and compressed stabilized earth blocks (CSEBs), reduce hot discomfort hours to under 1700 h/year but may increase cold discomfort. Combining these materials with targeted insulation improves thermal balance. Key recommendations include compact urban forms, vegetation, shading devices, and high-performance envelopes. Early integration of these strategies can significantly enhance thermal comfort and reduce energy demand in Saharan cities. Full article

Dental enamel discoloration, extrinsic staining, and periodontal biofilms remain persistent challenges in oral health. This study explores the in vitro, dual-functional potential of Magnolia figo flower extract (FMO), a sesquiterpene-rich botanical active phytochemical ingredient (API), for aesthetic and antimicrobial oral applications. FTIR identified characteristic terpenoid and long-chain fatty acid functional groups, including β-elemene, γ-elemene, and caryophyllene oxide. Whitening efficacy on coffee-stained bovine enamel was quantified using CIELAB colorimetry. The 0.5% FMO treatment achieved ΔE* = 8.49, which was within the clinical perceptibility threshold and the optimal biocompatibility balance. SEM confirmed no demineralization on the enamel surface after immersion in 3.0% FMO for 12 h. Antimicrobial assays demonstrated inhibition of Porphyromonas gingivalis, with MIC and MBC values of 0.25% and 0.5%, respectively. Biofilm formation was reduced by over 50% at a 0.148% concentration. Cytocompatibility assays using HGF-1 cells with various concentrations of FMO showed reduced cell viability at higher concentrations. When exposed for 5 min (simulating daily oral care) or 2 h, 0.5% FMO exhibited greater biocompatibility with L929 cells compared to toothpaste and peroxide-based agents. These findings suggest that FMO may serve as a natural candidate for dual-function oral care; however, further in vivo and clinical investigations are needed to validate its potential use within oral care treatments. Full article

The climatic conditions of a region are a constant object of study, especially now that climate change is clearly affecting quality of life and the way we live. The study of the climatic conditions of a region is conducted through meteorological data. Meteorological installations include a set of sensors to monitor the meteorological and climatic conditions of an area. Meteorological data parameters include measurements of temperature, humidity, precipitation, wind speed, and direction, as well as tools such as an oratometer and a pyranometer, etc. Specifically, the pyranometer is a high-cost instrument, which has the ability to measure the intensity of the sunshine on the surface of the earth, expressing the measurement in Watt/m². Pyranometers have many applications. They can be used to monitor solar energy in a given area, in automated systems such as photovoltaic system management, or in automatic building shading systems. In this research, both the implementation and the evaluation of an integrated low-cost pyranometer system is presented. The proposed pyranometer device consists of affordable modules, both microprocessor and sensor. In addition, a central server, as the information system, was created for data collection and visualization. The data from the measuring system is transmitted via a wireless network (Wi-Fi) over the Internet to an information system (central server), which includes a database for collecting and storing the measurements, and visualization software. The end user can retrieve the information through a web page. The results are encouraging, as they show a satisfactory degree of determination of the measurements of the proposed low-cost device in relation to the reference measurements. Finally, a correction function is presented, aiming at more reliable measurements. Full article

As people spend most of their time indoors, the quality of the indoor lighting environment plays a crucial role in occupant health, mood, and productivity. While modern glazed curtain walls improve daylighting potential, they also heighten the risks of glare and associated solar heat gains that may result in occupant discomfort and overheating. To continuously ensure visual comfort while providing shading, kinetic responsive facades controlled by sensors and actuators can change the angles of the elements. Conventional control methods for shading devices mainly involve the unified control of each element. However, as each element of the kinetic responsive facade can be controlled independently, the number of potential control actions increases exponentially with the number of facade elements and possible angles. Traditional rule-based methods are challenging for handling this multi-objective high-dimensional control problem. This paper introduces a novel self-learning, real-time reinforcement learning (RL) controller that can interact with the environment to find a globally optimal control solution for each element in kinetic responsive facades, thereby meeting visual quality and shading goals. The configuration and workflow of the proposed RL controller are introduced and tested vertically, diagonally, and radially folding responsive facades. The results demonstrate that the proposed RL controller effectively maintains horizontal and vertical illuminance, with 72.92% of test points in occupied spaces falling within the defined comfort range. Additionally, it keeps the daylight glare probability (DGP) below 0.35, a level generally considered imperceptible. Full article

Partial shading conditions cause current mismatches between series-connected panels in photovoltaic (PV) arrays, significantly reducing power efficiency. To mitigate this limitation, reconfiguration methods based on dynamically changing the electrical connections within the PV array have been proposed. In recent years, adaptive and dual-adaptive PV connection structures, which particularly balance the line currents and aim to restore current symmetry under irregular shading conditions, have gained prominence due to their notable efficiency improvements. The dual nature of these structures inherently supports this symmetry by enabling balanced reconfigurations on both sides of the array. However, the dual-adaptive structure expands the solution space due to the exponential growth of the connection combinations with the increasing number of lines, and this makes real-time optimization difficult. In fact, this structure has been optimized with genetic algorithm (GA) before; however, the convergence time of GA exceeds acceptable limits in large arrays. In this study, a Particle Swarm Optimization (PSO) algorithm is applied to solve the dual-adaptive PV array reconfiguration problem. Particle Swarm Optimization (PSO) is a metaheuristic algorithm that utilizes swarm intelligence to efficiently explore large solution spaces. PSO’s fast convergence capability and low computational cost enable real-time applications by enabling optimization in acceptable times even for larger PV arrays. Simulation results reveal that PSO successfully manages the exponential growth in the solution space and significantly increases the real-time applicability of the reconfiguration process by effectively increasing the efficiency. In this respect, PSO is considered a powerful and practical solution for reconfiguration problems in large-scale PV arrays. Full article

There is increasing interest in the role of parks as potential cool refuges in the age of climate change. Such potential refuges result from the Park Cool Island (PCI) effect, reflecting the temperature differential between the park and surrounding urban areas. However, this study of different park typologies in Perth, Australia, illustrates that while surface temperatures are 10–15 °C lower in parks during summer afternoons (much less than at other times), air temperatures are generally no different from the adjacent streetscape for the smaller parks. Only the largest park in the study had 1–2 °C lower morning and mid-afternoon air temperature differentials. The study illustrates that while the PCI is a real phenomenon, the magnitude in terms of air temperature is small, and it is of less relevance to the conditions felt by humans in average summer daytime conditions than the direct effects of solar radiation. Many studies have assessed the PCI effect, an indicator that has shown a wide range across different studies and measurement techniques. However, this novel paper utilises satellite remote-sensed land surface temperatures, on-ground measurements of surface temperatures, air temperatures, and humidity, as well as modelling using the microclimatic simulation software ENVI-met version 5.0. A reliance on land surface temperature, which in isolation has a marginal correlation with human experience of thermal comfort, has led some researchers to overstate the PCI effect and its influence on adjoining urban areas. The research reported in this paper illustrates that it is the shade provided by the canopy in parks, rather than parks themselves, that provides meaningful thermal comfort benefits. Accordingly, adaptation to increasing temperatures requires the creation of a continuous canopy, ideally over parks, streetscapes, and private lots in an interconnected network. Full article

Identifying the mineral pigments used in the decoration of prehistoric pottery is a significant step for understanding the evolution of the technological practices over time. On the Balkan Peninsula during late prehistory, the techniques used for red and dark-colored decorations underwent a significant transformation. In the Early Neolithic period, pottery was often decorated with dark-toned paints, ranging from deep red to brown. However, this approach declined noticeably during the Chalcolithic period, when red pigment pseudo-incrustation became the predominant decorative method. This study aims to identify the mineral pigments used in red and dark decorations on Neolithic and Chalcolithic pottery from Bulgaria and to trace possible technological, regional, or chronological variations in their composition. A total of 34 ceramic sherds, decorated in shades from red to brown and black, were analyzed using two complementary spectroscopic techniques: laser-induced breakdown spectroscopy (LIBS) and Fourier-transform infrared spectroscopy (FTIR). LIBS data were further evaluated using principal component analysis (PCA) to classify materials based on elemental composition. The results indicate that red decorations are consistently composed of hematite and remain compositionally stable regardless of the region, time period, or application technique. In contrast, dark decorations contain various combinations of iron oxides (magnetite and hematite) and manganese oxides, often including barium-rich manganese compounds—potentially indicating pigment provenance. Additionally, the dark decorations display regional differences. Full article

This article examines the advantages and disadvantages of deploying photovoltaic power plants in residential areas, considering both their current development status and specific operational risks, such as the unpredictability associated with potential faults. It highlights that errors of existing PV technologies can pose risks, including the potential for fire and electrocution. To improve efficiency and address these identified issues, the paper emphasizes the benefits of using additional electronic equipment, called “optimizers”, which, in conjunction with the inverters, can provide arc-fault circuit interruption and rapid shutdown of the photovoltaic systems. These technologies are designed to reduce faults and enhance operational safety, thereby reducing the risk of electrocution for maintenance personnel. They are recommended especially for rooftop PV systems that are affected by shading conditions. Furthermore, experimental results indicate that the use of such optimizers can lead to a power gain of up to 50% in partial shading. Full article

This paper presents a literature review of low-power hybrid wind–photovoltaic (PV) systems and introduces a 3 m diameter prototype rotor featuring twelve PV-coated pivoting blades stiffened by a peripheral rim. Existing solutions—foldable umbrella concepts, Darrieus rotors with PV-integrated blades, and morphing blades—are surveyed, and current gaps in simultaneous wind + PV co-generation on a single moving structure are highlighted. Key performance indicators such as power coefficient (C_p), DC ripple, cell temperature difference (ΔT), and levelised cost of energy (LCOE) are defined, and an integrated assessment methodology is proposed based on blade element momentum (BEM) and computational fluid dynamics (CFD) modelling, dynamic current–voltage (I–V) testing, and failure modes and effects analysis (FMEA) to evaluate system performance and reliability. Preliminary results point to moderate aerodynamic penalties (ΔC_p ≈ 5–8%), PV output during rotation equal to 15–25% of the nominal PV power (P_PV), and an estimated 70–75% reduction in blade–root bending moment when the peripheral ring converts each blade from a cantilever to a simply supported member, resulting in increased blade stiffness. Major challenges include the collective pitch mechanism, dynamic shading, and wear of rotating components (slip rings); however, the suggested technical measures—maximum power point tracking (MPPT), string segmentation, and redundant braking—keep performance within acceptable limits. This study concludes that the concept shows promise for distributed microgeneration, provided extensive experimental validation and IEC 61400-2-compliant standardisation are pursued. This paper has a dual scope: (i) a concise literature review relevant to low-Re flat-blade aerodynamics and ring-stiffened rotor structures and (ii) a multi-fidelity aero-structural study that culminates in a 3 m prototype proposal. We present the first evaluation of a hybrid wind–PV rotor employing untwisted flat-plate blades stiffened by a peripheral ring. Using low-Re BEM for preliminary loading, steady-state RANS-CFD (k-ω SST) for validation, and elastic FEM for sizing, we assemble a coherent load/performance dataset. After upsizing the hub pins (Ø 30 mm), ring (50 × 50 mm), and spokes (Ø 40 mm), von Mises stresses remain < 25% of the 6061-T6 yield limit and tip deflection ≤ 0.5%·R acrosscut-in (3 m s⁻¹), nominal (5 m s⁻¹), and extreme (25 m s⁻¹) cases. CFD confirms a broad efficiency plateau at λ = 2.4–2.8 for β ≈ 10° and near-zero shaft torque at β = 90°, supporting a three-step pitch schedule (20° start-up → 10° nominal → 90° storm). Cross-model deviations for C_p, torque, and pressure/force distributions remain within ± 10%. This study addresses only the rotor; off-the-shelf generator, brake, screw-pitch, and azimuth/tilt drives are intended for later integration. The results provide a low-cost manufacturable architecture and a validated baseline for full-scale testing and future transient CFD/FEM iterations. Full article

Heat stress is one of the main welfare and productivity problems faced by dairy cattle in Mediterranean climates. The main objective of this work is to predict heat stress in livestock from shade-seeking behavior captured by computer vision, combined with some climatic features, in a completely non-invasive way. To this end, we evaluate two soft computing algorithms—Random Forests and Neural Networks—clarifying the trade-off between accuracy and interpretability for real-world farm deployment. Data were gathered at a commercial dairy farm in Titaguas (Valencia, Spain) using overhead cameras that counted cows in the shade every 5–10 min during summer 2023. Each record contains the shaded-cow count, ambient temperature, relative humidity, and an exact timestamp. From here, three thermal indices were derived: the current THI, the previous-night mean THI, and the day-time accumulated THI. The resulting dataset covers 75 days and 6907 day-time observations. To evaluate the models’ performance a 5-fold cross-validation is also used. The results show that both soft computing models outperform a single Decision Tree baseline. The best Neural Network (3 hidden layers, 16 neurons each, learning rate $={10}^{-3}$) reaches an average RMSE of $14.78$, while a Random Forest (10 trees, depth $=5$) achieves $14.97$ and offers the best interpretability. Daily error distributions reveal a median RMSE of $13.84$ and confirm that predictions deviate less than one hour from observed shade-seeking peaks. Although the dataset came from a single farm, the results generalized well within the observed range. However, the models could not accurately predict the exact number of cows in the shade. This suggests the influence of other variables not included in the analysis (such as solar radiation or wind data), which opens the door for future research. Full article

Semitransparent plastic films containing red-fluorescent pigments can increase the growth of some greenhouse crops despite a lower transmitted photosynthetic photon flux density (PPFD), but the underlying mechanism by which this occurs is not fully understood. We postulated it can be attributed to a lower blue-light environment that increases leaf expansion and thus photon capture. We examined the growth response and photosynthetic capacity of vegetable and ornamental greenhouse crops under a red-fluorescent plastic, plastics with varying transmission percentages of blue light (from 6% to 20%), and an uncovered greenhouse control with a 40% greater PPFD. When the transmitted PPFD was similar, decreasing the percentage of blue light increased the extension growth for some but not all species tested. Transmitted PPFD had a more pronounced effect on extension growth than the percentage of blue light. Lettuce shoot dry mass was greater under the red-fluorescent film than the other covered treatments and similar to the uncovered control with 40% more light. Regardless of the transmission spectrum, decreasing the transmitted PPFD reduced tomato fruit fresh mass and generally decreased the number of flowers ornamental on the species. Maximum photosynthetic rate (A_max), stomatal conductance (g_sw), and quantum yield of photosystem II (PhiPSII) consistently decreased as the percentage of blue light transmission decreased, but this did not correlate to biomass accumulation. An experimental red-fluorescent film had cultivar and species-specific effects on growth, highlighting both its potential for leafy greens and potential challenges for greenhouse crops with a greater quantum requirement. Full article

Bypass diode faults are among the most hard-to-detect but impactful anomalies in photovoltaic (PV) systems, especially under partial shading conditions, where their electrical signatures often resemble those caused by non-critical irradiance variations. This study presents a systematic simulation-based investigation into how different bypass diode fault types—short-circuited, open-circuited, and healthy—affect the electrical behavior of PV strings under diverse irradiance profiles. A high-resolution MATLAB/Simulink model is developed to simulate 27 unique diode fault configurations across multiple shading scenarios, enabling the extraction of key features from resulting I–V curves. These features include global and local maximum power point parameters, open-circuit voltage, and short-circuit current. To address the challenge of feature redundancy and classification ambiguity, a preprocessing step is applied to remove near-duplicate instances and improve model generalization. An artificial neural network (ANN) model is then trained to classify the number of faulty bypass diodes based on these features. Comparative evaluations are conducted with support vector machines and random forests. The results indicate that the ANN achieves the highest test accuracy (93.57%) and average AUC (0.9925), outperforming other classifiers in both robustness and discriminative power. These findings highlight the importance of feature-informed, data-driven approaches for fault detection in PV systems and demonstrate the feasibility of diode fault classification without precise fault localization. Full article

The research results show that urban form has a significant impact on urban building energy consumption. Therefore, it is of great significance to study the relationship between urban form and urban building energy consumption. This study selects 26 cities in China across four climate zones and studies the relationship on a macro scale. In terms of urban building energy consumption, this study summarizes a set of data collation methods for calculating the total energy consumption of residential buildings and public buildings. In terms of urban form, this study constructed three types of urban form indicators (basic indicators, two-dimensional indicators, and three-dimensional indicators) and proposes a set of methods for calculating the urban built-up area, the total urban building area, the urban residential building area, and the urban public building area. This research finds that in the four climate zones, total urban building energy consumption is extremely strongly correlated with indicators such as resident population, GDP, total building area, building base area, and built-up area, and urban building energy consumption per unit area is extremely strongly correlated with indicators such as clustering, building intensity, urban building orientation, shading factor, and shape coefficient of building, but the relevant indicators are not exactly the same in each climate zone. Full article

Surface solar irradiance (SSI) is a critical factor influencing the power generation capacity of photovoltaic (PV) power plants. Dynamic changes in cloud cover pose significant challenges to the accurate nowcasting of SSI, which in turn directly affects the reliability and stability of renewable energy systems. However, existing research often simplifies or overlooks changes in the optical and morphological characteristics of clouds, leading to considerable errors in SSI nowcasting. To address this limitation and improve the accuracy of ultra-short-term SSI forecasting, this study first forecasts changes in cloud optical thickness (COT) within the next 3 h based on a spatiotemporal long short-term memory model, since COT is the primary factor determining cloud shading effects, and then integrates the zenith and regional averages of COT, along with factors influencing direct solar radiation and scattered radiation, to achieve precise SSI nowcasting. To validate the proposed method, we apply it to the Albuquerque, New Mexico, United States (ABQ) site, where it yielded promising performance, with correlations between predicted and actual surface solar irradiance for the next 1 h, 2 h, and 3 h reaching 0.94, 0.92, and 0.92, respectively. The proposed method effectively captures the temporal trends and spatial patterns of cloud changes, avoiding simplifications of cloud movement trends or interference from non-cloud factors, thus providing a basis for power adjustments in solar power plants. Full article

In the context of green building development, the lighting design of campus living rooms in hot summer and cold winter areas faces the dual challenges of glare control in summer and insufficient daylight in winter. Based on BIM technology, this study uses Revit 2016 modeling and the HYBPA 2024 performance analysis platform to simulate and optimize the daylighting performance of the campus activity center of Hunan City College in multiple rounds of iterations. It is found that the traditional single large-area external window design leads to uneven lighting in 70% of the area, and the average value of the lighting coefficient is only 2.1%, which is lower than the national standard requirement of 3.3%. Through the introduction of the hybrid system of “side lighting + top light guide”, combined with adjustable inner louver shading, the optimized average value of the lighting coefficient is increased to 4.8%, the uniformity of indoor illuminance is increased from 0.35 to 0.68, the proportion of annual standard sunshine hours (≥300 lx) reaches 68.7%, and the energy consumption of the artificial lighting is reduced by 27.3%. Dynamic simulation shows that the uncomfortable glare index at noon on the summer solstice is reduced from 30.2 to 22.7, which meets the visual comfort requirements. The study confirms that the BIM-driven “static-dynamic” simulation coupling method can effectively address climate adaptability issues. However, it has limitations such as insufficient integration with international healthy building standards, insufficient accuracy of meteorological data, and simplification of indoor dynamic shading factors. Future research can focus on improving meteorological data accuracy, incorporating indoor dynamic factors, and exploring intelligent daylighting systems to deepen and expand the method, promote the integration of cross-standard evaluation systems, and provide a technical pathway for healthy lighting environment design in summer-hot and winter-cold regions. Full article