Search Results (100)

Floating photovoltaic (FPV) systems are promising for coastal aquaculture where reliable electricity is essential for pumping, oxygenation, sensing, and control. A sustainable FPV–storage hybrid tailored to monsoon-prone sites is developed, with emphasis on energy efficiency and structural resilience. The prototype combines dual-axis solar tracking with a spray-cooling and cleaning subsystem and an active wind-protection strategy that automatically flattens the array when wind speed exceeds 8.0 m/s. Temperature, wind speed, and irradiance sensors are coordinated by an Arduino-based supervisor to optimize tracking, thermal management, and tilt control. A 10 W floating module and a fixed-tilt reference were fabricated and tested outdoors in Penghu, Taiwan. The FPV achieved a 25.17% energy gain on a sunny day and a 40.29% gain under overcast and windy conditions, while module temperature remained below 45 °C through on-demand spraying, reducing thermal losses. In addition, a hybrid energy storage system (HESS), integrating a 12 V/10 Ah lithium-ion battery and a 12 V/24 Ah lead-acid battery, was validated using a priority charging strategy. During testing, the lithium-ion unit was first charged to stabilize the control circuits, after which excess solar energy was redirected to the lead-acid battery for long-term storage. This hierarchical design ensured both immediate power stability and extended endurance under cloudy or low-irradiance conditions. The results demonstrate a practical, low-cost, and modular pathway to couple FPV with hybrid storage for coastal energy resilience, improving yield and maintaining safe operation during adverse weather, and enabling scalable deployment across cage-aquaculture facilities. Full article

In our previous study, the transition behavior of a flared cone–swept fin configuration was investigated under an angle of attack (AoA) of 0°. To further explore the role of AoA in complex three-dimensional geometries with strong fin–body interactions, wind tunnel experiments were conducted at Ma = 9.3, Re = 1.36 × 10⁷/m, with AoA ranging from −6° to 6°. Global surface temperature distributions were obtained using temperature-sensitive paint (TSP), while localized heat flux and pressure fluctuations were captured using thin-film thermocouples and high-frequency pressure sensors. The results show that varying AoA shifts the location of high heat flux between the upper and lower surfaces of the flared cone and induces a switch from streamwise to separation vortices. The windward side exhibits stronger disturbance responses than the leeward side. The junction region between the flared cone and the near-horizontal surface is highly sensitive to AoA variations, consistently exhibiting pronounced second-mode instabilities. These findings provide experimental support for understanding transition mechanisms under the combined effects of shock/boundary layer interaction (SBLI), crossflow, and adverse pressure gradients, with implications for transition prediction and thermal protection system design. Full article

The use of drones for monitoring mammal populations has increased in recent years due to their relatively low cost, accessibility, and ability to survey large areas quickly and efficiently. The type of drone sensor used during surveys can significantly influence species detection probability. For arboreal mammals, thermal infrared (TIR) sensors are commonly used because they can detect heat signatures of canopy-dwelling species. However, drones equipped with TIR cameras are more expensive and thus less accessible to conservation practitioners who often work with limited funding compared to drones equipped exclusively with standard visual spectrum cameras (Red, Green, Blue; RGB drones). Although RGB drones may represent a viable low-cost alternative for wildlife monitoring, their effectiveness for monitoring arboreal mammals remains poorly understood. Our objective was to evaluate the use of RGB drones for monitoring arboreal mammals, focusing on Geoffroy’s spider monkeys (Ateles geoffroyi) and southern muriquis (Brachyteles arachnoides). We used pre-programmed flights for spider monkeys and manual flights for muriquis, selecting the most suitable method according to the landscape characteristics of each study site; flat terrain with relatively homogeneous forest canopy height and mountainous forests with highly variable canopy height, respectively. We detected spider monkeys in only 0.4% of the 232 flights, whereas we detected muriquis in 6.2% of the 113 flights. Considering that both species are highly arboreal, use the upper canopy, and share similar locomotion patterns and group size, differences in detectability are more likely related to the type of drone flights used in each case study than to species differences. Preprogrammed flights allow for systematic and efficient area coverage but limit real-time adjustments to environmental conditions such as wind, canopy structure, and visibility. In contrast, manual flights offer greater flexibility, with pilots being able to adjust speed, height, and flight path as needed and spend more time over specific areas to conduct a more exhaustive search. This flexibility likely contributed to the higher detection rate observed in the muriqui study, but detectability was still low. The findings of the two studies suggest that RGB drones are better suited as a complementary tool rather than a primary method for monitoring arboreal mammals in dense forest habitats. Nonetheless, RGB drones offer valuable opportunities for other applications, and we highlight several examples of their potential utility in arboreal mammal research and conservation. Full article

Despite advances in precision irrigation, no systematic review has yet integrated the roles of remote sensing, agro-meteorological data, and wireless sensor networks in high-value, water-sensitive crops such as mango, avocado, and vineyards. Existing research often isolates technologies or crop types, overlooking their convergence and joint performance in the field. This review fills that gap by examining how these tools estimate crop water demand and support sustainable, site-specific irrigation under variable climate conditions. A structured search across major databases yielded 365 articles, of which 92 met the inclusion criteria. Studies were grouped into four categories: remote sensing, agro-meteorology, wireless sensor networks, and integrated approaches. Remote sensing techniques, including multispectral and thermal imaging, enable the spatial monitoring of vegetation indices and stress indicators, such as the Crop Water Stress Index. Agro-meteorological data feed evapotranspiration models using temperature, humidity, wind, and radiation inputs. Wireless sensor networks provide continuous, localized data on soil moisture and canopy temperature. Integrated approaches combine these sources to improve irrigation recommendations. Findings suggest that combining remote sensing, wireless sensor networks, and agro-meteorological inputs can reduce water use by up to 30% without yield loss. Challenges include sensor calibration, data integration complexity, and limited scalability. This review also compares methodologies and highlights future directions, including artificial intelligence systems, digital twins, and affordable Internet of Things platforms for irrigation optimization. Full article

Energy harvesting (EH) is a rapidly evolving domain that is primarily focused on capturing and converting ambient energy sources into more convenient and usable forms. These sources, which range from traditional renewable sources such as solar or wind power to thermal gradients and vibrations, present an alternative to typical power generation. The temptation to use energy harvesting systems is in their potential to power low-power devices, such as environment monitoring devices, without relying on conventional power grids or standard battery implementations. This improves the sustainability and self-sufficiency of IoT devices and reduces the environmental impact of conventional power systems. Applications of EH include wearable health monitors, wireless sensor networks, and remote structural sensors, where frequent battery replacement is impractical. However, these systems also face challenges such as intermittent energy availability, limited storage capacity, and low power density, which require innovative design approaches and efficient energy management. The paper provides a general overview of the subsystems present in the energy harvesting systems and a comprehensive overview of the energy transducer technologies used in energy harvesting systems. Full article

This study presents an innovative pipeline for processing, compressing, and remotely visualizing large-scale numerical simulations of fluid dynamics in a virtual wind tunnel (VWT), leveraging virtual and augmented reality (VR/AR) for enhanced analysis and high-end visualization. The workflow addresses the challenges of handling massive databases generated using Direct Numerical Simulation (DNS) while maintaining visual fidelity and ensuring efficient rendering for user interaction. Fully immersive visualization of supersonic (Mach number 2.86) spatially developing turbulent boundary layers (SDTBLs) over strong concave and convex curvatures was achieved. The comprehensive DNS data provides insights on the transport phenomena inside turbulent boundary layers under strong deceleration or an Adverse Pressure Gradient (APG) caused by concave walls as well as strong acceleration or a Favorable Pressure Gradient (FPG) caused by convex walls under different wall thermal conditions (i.e., Cold, Adiabatic, and Hot walls). The process begins with a .vts file input from a DNS, which is visualized using ParaView software. These visualizations, representing different fluid behaviors based on a DNS with a high spatial/temporal resolution and employing millions of “numerical sensors”, are treated as individual time frames and exported in GL Transmission Format (GLTF), which is a widely used open-source file format designed for efficient transmission and loading of 3D scenes. To support the workflow, optimized Extract–Transform–Load (ETL) techniques were implemented for high-throughput data handling. Conversion of exported Graphics Library Transmission Format (GLTF) files into Graphics Library Transmission Format Binary files (typically referred to as GLB) reduced the storage by 25% and improved the load latency by 60%. This research uses Unity’s Profile Analyzer and Memory Profiler to identify performance limitations during contour rendering, focusing on the GPU and CPU efficiency. Further, immersive VR/AR analytics are achieved by connecting the processed outputs to Unity engine software and Microsoft HoloLens Gen 2 via Azure Remote Rendering cloud services, enabling real-time exploration of fluid behavior in mixed-reality environments. This pipeline constitutes a significant advancement in the scientific visualization of fluid dynamics, particularly when applied to datasets comprising hundreds of high-resolution frames. Moreover, the methodologies and insights gleaned from this approach are highly transferable, offering potential applications across various other scientific and engineering disciplines. Full article

Traditional motor temperature rise testing generally uses temperature sensors. To solve problems such as sensor detachment, aging, and space occupation, this study takes a three-phase asynchronous motor as an example to propose a method for building a temperature rise monitoring model driven by a multi-physics field model based on the digital twin framework of power equipment. A twin monitoring model with defined input–output parameters is constructed to solve the problems of measurement inconvenience in traditional methods. Firstly, the losses of the iron core and the winding copper in the motor were obtained through electromagnetic field simulation. Secondly, the temperature distribution of the motor stator was obtained based on the bidirectional coupling characteristics of the magnetic and thermal fields. Subsequently, a temperature field reduced-order model based on the proper orthogonal decomposition method was built in Twin Builder, achieving fast calculation of the motor stator temperature. Finally, using the YE3-80M1-4 motor as the experimental subject, the model’s output results were compared with and validated against the experimental results. The results indicate that the simulation time of the reduced-order model is 2.1 s, and the relative error compared with the test values is within 5%, which confirms the practical applicability of the proposed method. Full article

This paper presents the design, fabrication, simulation, and partial validation of a low-cost, fixed-wing unmanned glider equipped for temperature and image monitoring. Aerodynamic optimization was performed using XFLR5 and ANSYS Fluent 2023 R1, with spanwise variation between NACA 63(3)-618 and NACA 4415 to enhance performance. Wind tunnel tests of the selected airfoil showed good agreement with CFD predictions, with deviations within 5–10%. The airframe, fabricated using 3D-printed PLA with a cross-lattice structure, was integrated with an ESP32-CAM and temperature sensor. A reflective thermal coating was applied to mitigate the heat sensitivity of PLA. Propeller-induced flow was analyzed separately using the lattice Boltzmann method. Real-time flight behavior was simulated in a virtual environment via Simulink and FlightGear. While full in-flight testing is pending, the results demonstrate a scalable, open-source UAV platform for environmental monitoring and academic research. Full article

This article examines the modeling of sustainable development in transport logistics, focusing on the impact of climate factors, changing weather conditions, and digitalization processes. The study analyzes the complex influence of adverse weather phenomena, such as fog, rain, snow, extreme temperatures, and strong winds, whose frequency and intensity are increasing due to climate change, on the efficiency, safety, and reliability of transport systems across all modes except pipelines. Special attention is paid to the integration of weather-resilient sensor technologies, including LiDAR, thermal imaging, and advanced monitoring systems, to strengthen infrastructure resilience and ensure uninterrupted transport operations under environmental stress. The methodological framework combines comparative analytical methods with economic–mathematical modeling, particularly Leontief’s input–output model, to evaluate the mutual influence between the transport sector and sustainable economic growth within an interconnected ecosystem of economic and technological factors. The findings confirm that data-driven management strategies, the digital transformation of logistics, and the strengthening of centralized hubs contribute significantly to increasing the resilience and flexibility of transport systems, mitigating the negative economic impacts of climate risks, and promoting long-term sustainable development. Practical recommendations are proposed to optimize freight flows, adapt infrastructure to changing weather risks, and support the integration of innovative digital technologies as part of an evolving ecosystem. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

This work presents the development of an adaptive thermal protection system for synchronous machines (SMs), taking into consideration the final cooling temperature and the operation point of the machine. This system aims to improve current thermal protections, which consist of a fixed alarm and trip thresholds regardless of the generator’s operating point or ambient temperature. A recurrent neural network (RNN)-based approach has been employed to predict SM temperatures during operation. Multiple tests have been conducted on a specially designed test bench. Inside the windings and iron core of the 5.5 kVA generator, multiple Pt100 sensors have been installed to train the neural network with real temperature values, enabling accurate predictions. The selected RNN model is Long Short-Term Memory (LSTM). Its inputs include electrical variables and the inlet and outlet air temperatures of the SM’s cooling system. The results show that the model accurately defines warning and trip thresholds, significantly improving thermal protection, as these thresholds are no longer fixed values. Additionally, the study suggests validating the model under cooling system failures and exploring its application in water-cooled systems. This research is supported by a patent on real-time thermal diagnostics for synchronous machines, highlighting its potential contribution to predictive maintenance and the monitoring of power generation systems. Full article

Measuring the airtightness of high-rise buildings presents significant challenges due to the effects of wind and thermal lift (stack effect). Small indoor/outdoor temperature differences, combined with the building’s height, can create substantial natural pressure differences on the building envelope, while winds induce pressure fluctuations. The international standard ISO 9972 provides insufficient guidelines for dealing with these high and fluctuating natural pressure differences. In addition, it is crucial to achieve a uniform internal pressure distribution during the test. This paper discusses the airtightness testing of high-rise buildings up to 125 m tall using portable blower door devices, following the “airtightness measurement of high-rise buildings” Passive House guideline. Differential pressure sensors were placed on the ground and top floors to record the effects of wind and thermal lift, and additional sensors helped to achieve a uniform pressure distribution within the building. The readings from the ground and top floors ensured full depressurization and pressurization during testing. The setup of the measuring fans, mainly on the ground floor, was supplemented with additional fans on higher floors to maintain pressure uniformity within a 10% tolerance. To be able to conduct a multi-point regression test, it is recommended to limit the product of the indoor/outdoor temperature difference and building height to ≤1250 mK and to achieve a coefficient of determination of 0.98 or higher, a wind speed ≤ 3 Beaufort. The study concludes that an airtight building envelope and larger internal flow paths, such as stairwells and elevator shafts, simplify the measurement. Full article

The rapid urbanization of developing cities has intensified the challenge of maintaining thermal comfort in buildings, particularly in hot–humid climates. This study investigates the impact of floor level on airflow patterns and indoor temperatures in multi-purpose mid-rise buildings in Onitsha, Nigeria, where increasing urban density and frequent power outages necessitate effective passive cooling strategies. Through a mixed-method approach combining empirical measurements, computational fluid dynamics (CFD) simulations, and thermal performance analysis, the research examined variations in ventilation rates and temperature distributions across different floor levels of a six-story educational building over an annual cycle, focusing on the hottest (27 February), coldest (28 December), most windy (3 April), and least windy (17 September) days. Results revealed distinct floor-level ventilation patterns: upper floors (fourth–fifth) achieved 39–40 air changes per hour (ACH) during hot periods while maintaining temperatures of 30–35 degrees Celsius (°C); middle floors (second–third) showed moderate ventilation (15–22 ACH) but experienced heat accumulation (35–42 °C); and lower floors reached 20 ACH during windy conditions. Temperature stratification varied from 15 °C between floors across the entire building during peak conditions to 7 °C during windy periods. Stack-driven ventilation in upper floors contributed to temperature reductions of up to 3 °C, while wind-driven ventilation promoted uniform temperature distribution across all levels. These findings informed floor-specific design recommendations: hybrid ventilation systems with automated controls, strategic architectural features including a minimum floor level area of 15% for the central atrium, and comprehensive monitoring systems with six temperature sensors per floor. This study provides evidence-based strategies for optimizing thermal comfort in tropical urban environments, particularly valuable for designing energy-efficient buildings in rapidly developing cities with hot-humid climates. Full article

The key equipment for performing aerodynamic testing of objects, such as road and railway vehicles, aircraft, and wind turbines, as well as stationary objects such as bridges and buildings, are multichannel pressure measurement instruments (pressure scanners). These instruments are typically based on arrays of separate pressure sensors built in an enclosure that also contains temperature sensors used for temperature compensation. However, there are significant limitations to such a construction, especially when increasing requirements in terms of miniaturization, the number of pressure channels, and high measurement performance must be met at the same time. In this paper, we present the development and realization of an innovative MEMS multisensor chip, which is designed with the intention of overcoming these limitations. The chip has four MEMS piezoresistive pressure-sensing elements and two resistive temperature-sensing elements, which are all monolithically integrated, enabling better sensor matching and thermal coupling while providing a high number of pressure channels per unit area. The main steps of chip development are preliminary chip design, numerical simulations of the chip’s mechanical behavior when exposed to the measured pressure, final chip design, fabrication processes (photolithography, thermal oxidation, diffusion, layer deposition, micromachining, anodic bonding, and wafer dicing), and electrical testing. Full article

This paper presents the results of experimental tests and computer simulations on the stiffness of composite aluminium mullions used in unitised façades. The elements analysed were subjected to bending in order to simulate the actual operating conditions of aluminium façades subjected to significant wind pressure or suction loads. The basic mechanical and physical properties of the materials from which the analysed type of aluminium façade is made (Aluminium EN AW-6060 in the T66 temper and polyamide PA66 25GF), the test method, and the results obtained are described. As a result of the tests, equivalent moments of inertia of the composite profile (aluminium profile with the thermal break) were determined, which are strongly dependent on the strength of the connection between the individual elements, the asymmetry of the cross-section, and the properties of the thermal break. Strain measurements carried out using FBG (Fiber Bragg Grating) strain sensors installed in the profiles under tests allowed for determining the actual stress values of the aluminium profiles under consideration. The results obtained were compared to theoretical (numerical) values, indicating discrepancies at higher load values. The methodology presented in this article is to be used to monitor the deformation of the aluminium façade mullions of HRB (High-Rise Buildings). Full article