Search Results (117)

In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of Trachurus japonicus in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of T. japonicus density. A robust experimental design identified nine key factors significantly influencing this density: mean sea-level pressure (msl-0, msl-4), surface pressure (sp-0, sp-4), Summit ozone concentration (Ozone_sum), F10.7 solar flux index (F10.7_index), nitrate concentration at 20 m depth (N3M20), sonar-detected effective vertical range beneath the surface (Height), and survey month (Month). Crucially, stable causal relationships were identified among Ozone_sum, F10.7_index, Height, and N3M20. Variations in Ozone_sum likely impact surface UV radiation levels, influencing plankton dynamics (a primary food source) and potentially larval/juvenile fish survival. The F10.7_index, reflecting solar activity, may affect geomagnetic fields, potentially influencing the migration and orientation behavior of T. japonicus. N3M20 directly modulates primary productivity by limiting phytoplankton growth, thereby shaping the availability and distribution of prey organisms throughout the food web. Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. Surface pressures (msl-0/sp-0) and their lagged effects (msl-4/sp-4) significantly influence sea surface temperature profiles, ocean currents, and stratification, all critical determinants of suitable habitats and prey aggregation. The strong influence of Month predominantly reflects seasonal changes in water temperature, reproductive cycles, and associated shifts in nutrient supply and plankton blooms. Rigorous robustness checks (Data Subset and Random Common Cause Refutation) confirmed the reliability and consistency of these causal findings. This elucidation of the distinct biological and physical pathways linking these diverse factors leading to T. japonicus density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies. Full article

The characteristics and types of the sky can greatly influence photovoltaic (PV) power generation, potentially leading to a reduction in both the lifespan and efficiency of the entire system. Driven by the challenge of addressing fluctuations in solar PV energy utilization, the aim was to assess the solar energy potential by analyzing the clear sky index $\left(K_t^{*}\right)$ across elevation profiles. To achieve this, a theoretical model for determining $K_t^{*}$ was employed, which encapsulated the solar energy analysis. Initially, solar energy data collected from approximately 16 stations in various provinces of Mozambique, as part of the solar energy measurement initiatives by INAM, FUNAE, AERONET, and Meteonorm, was processed. Subsequently, the clear sky radiation was calculated, and $K_t^{*}$ was established. The statistical findings indicate a reduction in energy contribution from the predictors, accounting for 28% of the total incident energy; however, there are progressive increases averaging around ~0.02, with $K_t^{*}$ values ranging from 0.4 to 0.9, demonstrating a strong correlation between 0.7 and 0.9 across several stations and predictor parameters. No significant climate change effects were noted. The radiation flux is directed from areas with higher $K_t^{*}$ to those with lower values, as illustrated in the heat map. The region experiences an increase in atmospheric parameter deposition, with concentrations around ~0.20, yet there remains a substantial energy flow potential of 92% for PV applications. This interaction can also be applied in other locations to assess the potential for available solar energy, as the analyzed solar energy spectrum aligns closely with the theoretical statistical calibration of energy distribution relevant to the global solar energy population process. Full article

The earth’s surface has an uneven solar energy density that is sufficient to stimulate solar photovoltaic (PV) production. This causes variations in a solar plant’s output, which are impacted by geometrical elements and atmospheric conditions that prevent it from passing. Motivated by the focus on encouraging increased PV production efficiency, the goal was to use machine learning models (MLM) to map the distribution of solar energy in Mozambique in a regressive literal and geospatial–temporal manner on a short measurement scale. The clear-sky index $\left(K_t^{*}\right)$ theoretical approach was applied in conjunction with MLM that emphasized random forest (RF) and artificial neural networks (ANNs). Solar energy mapping was the result of the methodology, which involved statistically calculating $K_t^{*}$ for the analysis of solar energy in correlational and causal terms of the space-time distribution. Utilizing data from PVGIS, NOAA, NASA, and Meteonorm, a sample of solar energy was gathered at 11 measurement stations in Mozambique over a period of 1 to 10 min between 2012 and 2014 as part of the FUNAE and INAM measurement programs. The statistical findings show a high degree of solar energy incidence, with increments $\left(∆K_t^{*}\right)$ in the average order of −0.05 and $K_t^{*}$ mostly ranging between 0.4 and 0.9. In 2012 and 2014, $K_t^{*}$ was 0.8956 and 0.6986, respectively, because clear days had a higher incident flux and intermediate days have a higher frequency of ${∆K}_t^{*}$ on clear days and a higher occurrence density. There are more cloudy days now 0.5214 as opposed to 0.3569. Clear days are found to be influenced by atmospheric transmittance because of their high incident flux, whereas intermediate days exhibit significant variations in the region’s solar energy. Full article

As the planet most similar to Earth in the solar system, Mars holds an important role in exploring significant scientific problems, such as the evolution of the solar system and the origins of life. Research on Mars mainly rely on planetary remote sensing technology, among which thermal infrared remote sensing is of great studying significance. This technology enables the recording of Martian thermal radiation properties. However, the current spatial resolution of Mars thermal infrared remote sensing images remains relatively low, limiting the detection of fine-scale thermal anomalies and the generation of higher-precision surface compositional maps. While updating extraterrestrial exploration satellites can help enhancing the spatial resolution of thermal infrared images, this method entails high cost and long update cycles, making improvement difficult to conduct in the short term. To address this issue, this paper proposes a super-resolution reconstruction method for Mars thermal infrared remote sensing images integrating multi-source data. First, based on the principle of domain adaptation, we introduced a method using highly correlated visible light images as auxiliary to enhance the spatial resolution of thermal infrared images. Then, a multi-sources data integration method is designed to constrain the thermal radiation flux of resulting images, ensuring the radiation distribution remains consistent with the original low-resolution thermal infrared images. Through both subjective and objective evaluations, our method is demonstrated to significantly enhance the spatial resolution of existing Mars thermal infrared images. It optimizes the quality of existing data, increasing the resolution of the original thermal infrared images by four times. In doing so, it not only recovers finer texture details to produce better visual effects than typical super-resolution methods, but also maintains the consistency of thermal radiation flux, with the error after applying the consistency constraint reduced by nearly tenfold, ensuring the applicability of the results for scientific research. Full article

A grid-connected converter is the interface between renewable energy power generation systems, such as solar power generation, wind power, hydropower, etc., and the power grid, responsible for the stable and efficient transmission of electric energy generated by renewable energy power generation systems to the grid. In order to realize local access for distributed photovoltaic power generation devices and energy storage devices, a composite three-port converter has the advantages of small size, low cost and high power density compared with a combined three-port converter. In view of the current problems of the existing compound three-port (AC/DC/DC) converters, such as DC and AC circulating current in current composite three-port converters and the harmonic control problem, the proposed compound three-port topology consists of a full-bridge inverter with six switching tubes, a zigzag transformer, two sets of filter inductors and two filter capacitors. Among them, the power frequency transformer adopts the zigzag connection method, which can effectively restrain the AC circulation and eliminate the DC magnetic flux of the iron core while introducing the third port. Firstly, the principle of AC/DC and DC/DC power conversion in the composite three-port topology is analyzed, which has higher efficiency than other topologies. Secondly, the topology control strategy is analyzed, and a two-loop hybrid current control method with improved current loop is proposed. When the DC-side voltage fluctuates, the DC offset of the battery can effectively improve the stability of the network side. Through the MATLAB/Simulink simulation experiment platform, the high efficiency of energy conversion and stable grid-connected operation characteristics are verified. Finally, the experiment of integrating into the power grid was carried out. Experiments were used to verify the effectiveness and feasibility of the proposed topology and strategy. The experimental results show that Total Harmonic Distortion (THD) can be controlled below 3%. Full article

The planetary boundary layer height (PBLH) in coastal Arctic regions is influenced by sea breeze circulation. However, the specific mechanisms through which sea breeze affects PBLH evolution remain insufficiently explored. This study uses meteorological data, micro-pulse lidar (MPL) data, and sounding profiles from 2014 to 2021 to investigate the annual and polar day PBLH evolution driven by sea breezes in the Barrow region of Alaska, as well as the specific mechanisms. The results show that sea breeze events significantly suppress PBLH, especially during the polar day, when prolonged solar radiation intensifies the thermal contrast between land and ocean. The cold, moist sea breeze stabilizes the atmospheric conditions, reducing net radiation and sensible heat flux. All these factors inhibit turbulent mixing and PBLH development. Lidar and sounding analyses further reveal that PBLH is lower during sea breeze events compared to non-sea-breeze conditions, with the peak of its probability density distribution occurring at a lower PBLH range. The variable importance in projection (VIP) analysis identifies relative humidity (VIP = 1.95) and temperature (VIP = 1.1) as the primary factors controlling PBLH, highlighting the influence of atmospheric stability in regulating PBLH. These findings emphasize the crucial role of sea breeze in modulating PBL dynamics in the Arctic, with significant implications for improving climate models and studies on pollutant dispersion in polar regions. Full article

This study presents a theoretical analysis of the solar flux distribution within the receiver of the high-flux solar furnace at IER-UNAM. The furnace comprises an array of 409 first-surface spherical facets, each hexagonal in shape with a side length of 20 cm, and all mounted on a spherical framework. Each facet is carefully adjusted to focus sunlight onto a single focal point. Initially, the distribution of solar radiation is evaluated based on measurements obtained in Temixco, Morelos, Mexico (18°50′21″ N, 99°14′7.5″ W). Using these data, an analytical model is proposed to describe the solar radiation distribution using a Gaussian approximation. An additional analytical model is then developed to estimate the concentration distribution and its geometric shape at the furnace’s focal point, considering the solar width’s root mean square (RMS) value along with the optical errors associated with the heliostat and the reflective facets. Ultimately, by applying the concept of the effective solar source, an analysis of the solar flux distribution within the furnace receiver is conducted. This results in an analytical equation that characterizes the two-dimensional and three-dimensional distribution of the concentrated solar flux. Calculations reveal that the system captures approximately 30 kW of power, with peak concentrations reaching around 10,000 suns. Full article

Predicting the solar flux density distribution formed by heliostats in a concentrated solar tower power (CSP) plant is important for the optimization and stable operation of a CSP plant. However, the high temperature and blackbody attribute of the receiver makes direct measurement of the concentrated solar irradiance distribution a difficult task. To address this issue, indirect methods have been proposed. Nevertheless, these methods are either costly or not accurate enough. This study proposes a ray tracing-assisted deep learning method for the prediction of the concentrated solar flux density distribution formed by a heliostat. Namely, a generative adversarial neural network (GAN) model using Monte Carlo ray tracing results as the input was built for the prediction of solar flux density distribution concentrated by a heliostat. Experiments showed that the predicted solar flux density distributions were highly consistent with the concentrated solar spots on the Lambertian target formed by the same heliostat. This ray tracing-assisted deep learning method can be extended to other heliostats in the CSP plant and pave the way for the prediction of the solar flux density distribution concentrated by the whole heliostat field in a CSP plant. Full article

Energy savings issues are important in the context of building operation. An interesting solution for the southern external walls of the building envelope is the thermal storage wall (TSW), also known as the Trombe wall. The article considers four variants of the wall structure, including three containing phase change material (PCM). The purpose of this study was to determine the influence of the amount and location of phase change material in the masonry layer on the storage and flow of heat through the barrier. Each wall is equipped with a double-glazed external collector system with identical physical parameters. The research was carried out in specially dedicated testing stations in the form of external solar energy chambers, subjected to real climatic loads. The distribution of the heat flux density values was determined using experimental tests and was subjected to comparative analysis for the various variants considered using statistical analytical methods. A comparative analysis was performed between the heat flux density values obtained for each barrier in the assumed time interval from the one-year research period. The Kruskal–Wallis test and the median test were used for analyses performed in the Statistica 13.3 programme. The purpose of these analyses was to determine the occurrence of significant differences between individual heat flux flows through the barriers tested. The results obtained indicate that the use of PCM in thermal storage walls extends the time required to transfer the accumulated heat in the barrier to the internal environment while reducing the amplitude of the internal air temperature. Full article

Advective heat fluxes (chimney effect) in porous debris facilitate ground cooling on scree slopes, even at low altitudes, and promote the occurrence of sporadic permafrost. The spatial distribution of ground surface temperature on an overcooled, low-altitude scree slope in the Romanian Carpathians was analyzed using UAV-based infrared thermography in different seasons. The analysis revealed significant temperature gradients within the scree slope, with colder, forest-insulated lower sections contrasting with warmer, solar-exposed upper regions. Across all surveyed seasons, this pattern remained evident, with the strongest temperature contrasts in December and April. February exhibited the most stable temperatures, with thermal readings primarily corresponding to snow surfaces rather than exposed rock. Rock surfaces displayed greater temperature variation than vent holes. Vent holes were generally cooler than rock surfaces, particularly in warmer periods. The persistent presence of ice and low temperatures at the end of the warm season suggested the potential existence of isolated permafrost. The results confirm the chimney effect, where cold air infiltrates the lower talus, gradually warms as it ascends, and outflows at higher elevations. UAV-based thermal imagery proved effective in detecting microclimatic variability and elucidating thermal processes governing talus slopes. This study provides valuable insights into extrazonal permafrost behavior, particularly in the context of global climate change. Full article

The porous solar receiver (PSR) is a promising technology in advanced high-temperature applications. However, the non-uniform distribution of concentrated solar flux (CSF) and the dense pore structure lead to localized overheating and significant thermal losses for the PSR. This review focuses on the optimization strategies to enhance the thermal performance of the PSR, including porosity parameters, spectral selectivity, geometric configurations, and optical windows. Furthermore, mitigation strategies for addressing localized high temperatures in the PSR were thoroughly discussed, including methods for homogenizing CSF and improving the velocity of heat transfer fluid (HTF). Additionally, a numerical simulation and experimental measurements were introduced and evaluated. Additionally, the paper emphasizes the need to optimize the macroscopic geometry of OPSRs to improve their flow and heat transfer performance, thereby enhancing their practical value. It also suggests designing PPSRs that integrate adjustments for HTF mass velocity, CSF, optical window load, and reflection losses. Consequently, future studies should focus on developing efficient simulation and validation methods to advance the practical application of PSRs. Full article

A theoretical and experimental evaluation was conducted on a prototype radiative flux homogenizer (HOFRAC) specifically designed for the Solar Furnace at Instituto de Energías Renovables (HoSIER) of Universidad Nacional Autónoma de México. The development of HOFRAC included three versions (HOFRAC-PRO, HOFRAC-PRI, and HOFRAC-PRIK); each iteration incorporated improvements based on theoretical modeling and experimental results. Evaluations were performed using ray-tracing simulations and experimental tests capturing radiative flux distribution images. The last two versions were used to characterize a densely packed photovoltaic array operated in the solar furnace. Some results of this study show that misaligned mirrors in the furnace were identified as the main problem in achieving a high flux uniformity degree for photovoltaic concentration applications. Full article

This study demonstrates a rich complexity of the time–frequency ionospheric signal spectrum, dependent on the measurement type and platform. Different phenomena contributing to satellite-derived and ground-derived geophysical data that only selected signal bands can be potentially sensitive to seismicity over time, and they are applicable in lithosphere–atmosphere–ionosphere coupling (LAIC) studies. In this study, satellite-derived and ground-derived ionospheric observations are filtered by a Fourier-based band-pass filter, and an experimental selection of potentially sensitive frequency bands has been carried out. This work focuses on band-pass filtered ionospheric observations and seismic activity in the region of the Aegean Sea over a two-year time period (2020–2021), with particular focus on the entire system of tectonic plate junctions, which are suspected to be a potential source of ionospheric disturbances distributed over hundreds of kilometers. The temporal evolution of seismicity power in the Aegean region is represented by the record of earthquakes characterized by M ≥ 4.5, used for the estimation of cumulative seismic energy. The ionospheric response to LAIC is explored in three data types: short inspections of in situ electron density (Ne) over a tectonic plate boundary by Swarm satellites, stationary determination of three Ne density profile parameters by the Athens Digisonde station AT138 (maximum frequency of the F2 layer: foF2; maximum frequency of the sporadic E layer: foEs; and frequency spread: ff), and stationary measure of vertical total electron content (VTEC) interpolated from a UPC-IonSAT Quarter-of-an-hour time resolution Rapid Global ionospheric map (UQRG) near Athens. The spectrograms are made with the use of short-term Fourier transform (STFT). These frequency bands in the spectrograms, which show a notable coincidence with seismicity, are filtered out and compared to cumulative seismic energy in the Aegean Sea, to the geomagnetic Dst index, to sunspot number (SN), and to the solar radio flux (F10.7). In the case of Swarm, STFT allows for precise removal of long-wavelength Ne signals related to specific latitudes. The application of STFT to time series of ionospheric parameters from the Digisonde station and GIM VTEC is crucial in the removal of seasonal signals and strong diurnal and semi-diurnal signal components. The time series formed from experimentally selected wavebands of different ionospheric observations reveal a moderate but notable correlation with the seismic activity, higher than with any solar radiation parameter in 8 out of 12 cases. The correlation coefficient must be treated relatively and with caution here, as we have not determined the shift between seismic and ionospheric events, as this process requires more data. However, it can be observed from the spectrograms that some weak signals from selected frequencies are candidates to be related to seismic processes. Full article

This paper aims to compare the thermal performances of the conical solar collector (CSC) system and the spot Fresnel lens system (SFL) using water and CuO nanofluid as the working fluids. The studied CFD models for both systems were validated using experimental data. At an optimal flow rate of 6 L/min, the SFL system showed higher optical and thermal performance in comparison with that of the CSC system. In the case of the SFL system, the availability of a greater amount of solar energy per unit collector area caused an increase in thermal energy. Moreover, in the case of the CSC system, the non-uniform distribution of solar flux on the absorber’s outer surface leads to an increase in temperature gradient and heat losses. As a heating medium, the CuO nanofluid outperformed the water in terms of higher thermal conductivity and heat capacity. The average thermal efficiencies of 64.7% and 61.2% were achieved using SFL with and without CuO nanofluid, respectively, which were 2.4% and 0.5% higher than those of the CSC with and without nanofluid. CFD simulations show a 2.80% deviation for SFL and 2.92% for CSC, indicating acceptable accuracy compared to experimental data. Full article

This study develops the heliostat curve tracing parametric model (HCTPM) to predict solar energy distribution in concentrated solar power (CSP) systems with sun-tracking capabilities. HCTPM uses curve tracing techniques to visualize flux distribution on mirrors and receivers, producing results that align closely with established models like HFLCAL, which use Gaussian and Tonatiuh ray-tracing methods. Simulations revealed that deviations in energy distribution increase as Sun shape error decreases, with greater impact on flux density and sensitivity. Variations in Sun disk radius caused notable deviations, especially in elliptical projections. The model’s flexibility in adjusting mirror shapes and sizes allows for the evaluation of spill losses, optimizing mirror designs for different positions. Spill loss analysis showed that larger mirrors reduce spill loss on mirrors but increase it on receivers, particularly when mirrors deviate from the north. Although total spill loss decreases with larger mirrors, this effect weakens as receiver spill loss grows. These findings emphasize the importance of optimizing mirror and receiver design to maximize energy efficiency and minimize resource waste, contributing to more sustainable solar energy systems. The HCTPM model plays a crucial role in improving the sustainability of CSP systems by optimizing configurations based on Sun disk characteristics, reducing energy losses, and promoting efficient resource use. Full article