Search Results (1,037)

For decades, GNSS code measurements were much noisier than phase ones, limiting their applicability to ionospheric total electron content (TEC) studies. Ultra-wideband AltBOC signals changed the situation. This study revisits the Galileo E5 and BeiDou B2 AltBOC signals and their potential applications in TEC estimation. We found that TEC noises are comparable for the single-frequency AltBOC phase-code combination and those of the dual-frequency legacy BPSK/QPSK phase combination, while single-frequency BPSK/QPSK TEC noises are much higher. A two-week high-rate measurement campaign at the ACRG receiver revealed a mean 100 sec TEC RMS (used as the noise proxy) of 0.26 TECU, 0.15 TECU, and 0.09 TECU for the BeiDou B2(a+b) AltBOC signal and satellite elevations 0–30°, 30–60°, and 60–90°, correspondingly, and 0.22 TECU, 0.14 TECU, and 0.09 TECU for the legacy B1/B3 dual-frequency phase combination. The Galileo E5(a+b) AltBOC signal corresponding values were 0.25 TECU, 0.14 TECU, and 0.09 TECU; for the legacy signals’ phase combination, the values were 0.19 TECU, 0.13 TECU, and 0.08 TECU. The AltBOC (for both BeiDou and Galileo) SNR exceeds those of BPSK/QPSK by 7.5 dB-Hz in undisturbed conditions. Radio frequency interference (the 28 August 2022 and 9 May 2024 Solar Radio Burst events in our study) decreased the AltBOC SNR 5 dB-Hz more against QPSK SNR, but, due to the higher initial SNR, the threshold for the loss of the lock was never broken. Today, we have enough BeiDou and Galileo satellites that transmit AltBOC signals for a reliable single-frequency vTEC estimation. This study provides new insights and evidence for using Galileo and BeiDou AltBOC signals in high-precision ionospheric monitoring. Full article

Predicting solar power generation is a complex challenge with multiple issues, such as data quality and choice of methods, which are crucial to effectively integrate solar power into power grids and manage photovoltaic plants. This study creates a hybrid methodology to improve the accuracy of short-term power prediction forecasts using a model called Transformer Bi-LSTM (Bidirectional Long Short-Term Memory). This model, which combines elements from the transformer architecture and bidirectional LSTM (Long–Short-Term Memory), is evaluated using two strategies: the first strategy makes a direct prediction using meteorological data, while the second employs a chain of deep learning models based on transfer learning, thus simulating the traditional physical chain model. The proposed approach improves performance and allows you to incorporate physical models to refine forecasts. The results outperform existing methods on metrics such as mean absolute error, specifically by around 24%, which could positively impact power grid operation and solar adoption. Full article

This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only characterized the highlands of Ecuador but also similar geographical locations. The model integrates three interconnected neural networks to predict global collector efficiency by considering atmospheric, geometric, and physical variables, including overall loss coefficient, efficiency factors, outlet fluid temperature, and useful heat gain. The PINNs model surpasses traditional simplified thermodynamic equations employed in engineering design by effectively integrating thermodynamic principles with data-driven insights, offering more accurate modeling of nonlinear phenomena. This approach enhances the precision of solar collector performance predictions, making it particularly valuable for optimizing designs in Ecuador’s highlands and similar regions with unique climatic conditions. The ANN predicted a collector overall loss coefficient of 5.199 W/(m²·K), closely matching the thermodynamic model’s 5.189 W/(m²·K), with similar accuracy in collector useful energy gain (722.85 W) and global collector efficiency (33.68%). Although the PINNs model showed minor discrepancies in certain parameters, it outperformed traditional methods in capturing the complex, nonlinear behavior of the data set, especially in predicting outlet fluid temperature (55.05 °C vs. 67.22 °C). Full article

Accreting stellar-mass black holes represent unique laboratories for studying matter and radiation under the influence of extreme gravity. They are highly variable sources going through different accretion states, showing various components in their X-ray spectra from the thermal emission of the accretion disc dominating in the soft state to the up-scattered Comptonisation component from an X-ray corona in the hard state. X-ray polarisation measurements are particularly sensitive to the geometry of the X-ray scatterings and can thus constrain the orientation and relative positions of the innermost components of these systems. The IXPE mission has observed about a dozen stellar-mass black holes with masses up to 20 solar masses in X-ray binaries with different orientations and in various accretion states. The low-inclination sources in soft states have shown a low fraction of polarisation. On the other hand, several sources in soft and hard states have revealed X-ray polarisation higher than expected, which poses significant challenges for theoretical interpretation, with 4U 1630–47 being one of the most puzzling sources. IXPE has measured the spin of three black holes via the measurement of their polarisation properties in the soft emission state. In each of the three cases, the new results agree with the constraints from the spectral observations. The polarisation observations of the black hole X-ray transient Swift J1727.8–1613 across its entire outburst has revealed that the soft-state polarisation is much weaker than the hard-state polarisation. Remarkably, the observations furthermore show that the polarisation of the bright hard state and that of the 100 times less luminous dim hard state are identical within the accuracy of the measurement. For sources with a radio jet, the electric field polarisation tends to align with the radio jet, indicating the equatorial geometry of the X-ray corona, e.g., in the case of Cyg X–1. In the unique case of Cyg X–3, where the polarisation is perpendicular to the radio jet, the IXPE observations reveal the presence and geometry of obscuring material hiding this object from our direct view. The polarisation measurements acquired by the IXPE mission during its first 2.5 years have provided unprecedented insights into the geometry and physical processes of accreting stellar-mass black holes, challenging existing theoretical models and offering new avenues for understanding these extreme systems. Full article

Polar mesospheric clouds (PMCs) are ice crystal clouds formed in the mesosphere of high-latitude regions in both the northern (NH) and southern hemispheres (SH). Peak height is an important physical characteristic of PMCs. Satellite observation data from solar occultation for ice experiments (SOFIE) during seven PMC seasons from 2007 to 2014 show that the difference between the height of the mesopause and the peak height of the PMCs (Z_mes-Z_max) were inversely correlated with the atmospheric mesopause temperature. The Z_mes-Z_max averages for all seasons for the NH and SH were 3.54 km and 2.66 km, respectively. They were smaller at the starting and ending stages of each PMC season and larger in the middle stages. Analysis of the individual cases and statistical results simulated by the PMCs 0-D model also revealed the inverse correlations between the Z_mes-Z_max and mesopause temperature, with correlation coefficients of −0.71 and −0.62 for the NH and SH, respectively. The corresponding rates of change of Z_mes-Z_max with respect to mesopause temperature were found to be −0.21 km/K and −0.14 km/K, respectively. The formation mechanism of PMCs suggests that a lower temperature around the mesopause can lead to a greater distance and longer time for ice crystals to condense and grow in clouds. Thus, ice crystals sediment to a lower height, making the peak height of the PMCs further away from the mesopause. In addition, disturbances in small-scale dynamic processes tend to weaken the impact of temperature on the peak height of PMCs. Full article

Long-term storage of seasonally available solar energy and its provision to balance heating energy demand can contribute significantly to the sustainable use of energy resources. Thermochemical energy storage is a suitable process for this purpose, offering the possibility of loss-free long-term energy storing and heat supply. In order to develop suitable technical solutions for the use of this technology, novel reactor concepts and scientific questions regarding material and technology development are being investigated. In this publication, the energy storage process of a long-term energy storage system based on a ploughshare reactor is experimentally investigated under various technically relevant operating conditions. One specific aspect of this technology is related to the release of water vapour during the charging process. Therefore, this work focusses, in particular, on the possibility of technically utilizing the latent heat of the released water vapour in the range of 45 °C to 80 °C, which covers the operating requirements of common heating systems in households. The experiments have shown that the dehydration process enables the separation of two heat fluxes: the chemically bound energy for long-term storage and the physically (sensible and latent) stored energy for short-term applications. However, the limitation of gas transport was also identified as the most important influencing parameter for optimising the performance of the process. Full article

Meteorological satellite remote sensing is important for numerical weather forecasts, but its accuracy is affected by many things during observation and retrieval, showing that it can be improved. As a standard way to measure wind from space, atmospheric motion vectors (AMVs) are used. They are separate pieces of information spread out in the troposphere, which gives them more depth than regular surface or sea surface wind measurements. This makes rectifying problems more difficult. For error correction, this research builds a deep-learning model that is specific to AMVs. The outcomes show that AMV observational errors are greatly reduced after correction. The root mean square error (RMSE) drops by almost 40% compared to ERA5 true values. Among these, the optimization of solar observation errors exceeds 40%; the discrepancies at varying atmospheric pressure altitudes are notably improved; the degree of optimization for data with low QI coefficients is substantial; and there remains potential for enhancement in data with high QI coefficients. Furthermore, there has been a significant enhancement in the consistency coefficient of the wind’s physical properties. In the assimilation forecasting experiments, the corrected AMV data demonstrated superior forecasting performance. With more training, the model can fix things better, and the changes it makes last for a long time. The results show that it is possible and useful to use deep learning to fix errors in meteorological remote-sensing data. Full article

One method of preparing sludge for management and use is solar drying. To intensify the drying process, natural lignocellulosic additives can be used to alter the structure of the sludge and accelerate water evaporation. Light, hard materials with low absorption capacity are best suited for this purpose, e.g., walnut shells, which are unused waste. The aim of the study was to determine the impact of the evaluation of walnut shells on the sludge drying process and to assess the impact of the drying process on the chemical, physical, and fuel properties of the additive. The moisture content, crushing strength, chemical composition, and physical and fuel properties of mixtures were determined. A small addition of walnut shells (25%) was found to accelerate the drying process even in winter and spring (up to 30 days) compared to sludge without additives. Walnut shells retain their chemical composition and strength despite unfavourable conditions and a chemically aggressive environment, indicating they may be reused. The mixture containing sewage sludge and walnut shells has a calorific value of 15.6 MJ/kg, which is similar to wood; it is also fully biodegradable and suitable as a fertiliser to improve soil structure, as it contains approx. 80–90% DM (including approx. 40% carbon, 3% nitrogen, and other elements, such as phosphorus and potassium.) Full article

Solar flares are significant occurrences in solar physics, impacting space weather and terrestrial technologies. Accurate classification of solar flares is essential for predicting space weather and minimizing potential disruptions to communication, navigation, and power systems. This study addresses the challenge of selecting the most relevant features from multivariate time-series data, specifically focusing on solar flares. We employ methods such as Mutual Information (MI), Minimum Redundancy Maximum Relevance (mRMR), and Euclidean Distance to identify key features for classification. Recognizing the performance variability of different feature selection techniques, we introduce an ensemble approach to compute feature weights. By combining outputs from multiple methods, our ensemble method provides a more comprehensive understanding of the importance of features. Our results show that the ensemble approach significantly improves classification performance, achieving values 0.15 higher in True Skill Statistic (TSS) values compared to individual feature selection methods. Additionally, our method offers valuable insights into the underlying physical processes of solar flares, leading to more effective space weather forecasting and enhanced mitigation strategies for communication, navigation, and power system disruptions. Full article

This study employs both simulation and experimental methodologies to evaluate the effectiveness of bi-sectional horizontal kinetic shading systems (KSS) with horizontal fins in enhancing daylight comfort across various climates. It emphasizes the importance of optimizing daylight levels while minimizing solar heat gain, particularly in the context of increasing energy demands and shifting climatic patterns. The study introduces a custom-designed bi-sectional KSS, simulated in three distinct climates—Wroclaw, Tehran, and Bangkok—using climate-based daylight modeling methods with the Ladybug and Honeybee tools in Rhino v.7 software. Standard daylight metrics, such as Useful Daylight Illuminance (UDI) and Daylight Glare Probability (DGP), were employed alongside custom metrics tailored to capture the unique dynamics of the bi-sectional KSS. The results were statistically analyzed using box plots and histograms, revealing UDI_300–3000 medians of 78.51%, 88.96%, and 86.22% for Wroclaw, Tehran, and Bangkok, respectively. These findings demonstrate the KSS’s effectiveness in providing optimal daylight conditions across diverse climatic regions. Annual simulations based on standardized weather data showed that the KSS improved visual comfort by 61.04%, 148.60%, and 88.55%, respectively, compared to a scenario without any shading, and by 31.96%, 54.69%, and 37.05%, respectively, compared to a scenario with open static horizontal fins. The inclusion of KSS switching schedules, often overlooked in similar research, enhances the reproducibility and clarity of the findings. A physical reduced-scale mock-up of the bi-sectional KSS was then tested under real-weather conditions in Wroclaw (latitude 51° N) during June–July 2024. The mock-up consisted of two Chambers ‘1’ and ‘2’ equipped with the bi-sectional KSS prototype, and the other one without shading. Stepper motors managed the fins’ operation via a Python script on a Raspberry Pi 3 minicomputer. The control Chamber ‘1’ provided a baseline for comparing the KSS’s efficiency. Experimental results supported the simulations, demonstrating the KSS’s robustness in reducing high illuminance levels, with illuminance below 3000 lx maintained for 68% of the time during the experiment (conducted from 1 to 4 PM on three analysis days). While UDI and DA calculations were not feasible due to the limited number of sensors, the E_h1 values enabled the evaluation of the time illuminance to remain below the threshold. However, during the June–July 2024 heat waves, illuminance levels briefly exceeded the comfort threshold, reaching 4674 lx. Quantitative and qualitative analyses advocate for the broader application and further development of KSS as a climate-responsive shading system in various architectural contexts. Full article

The solar atmosphere is a complex, coupled, highly dynamic plasma environment, which shows rich structuring due to the presence of gravitational and magnetic fields. Several features of the Sun’s atmosphere can serve as guiding media for magnetohydrodynamic (MHD) waves. At the same time, these waveguides may contain flows of various magnitudes, which can then destabilise the waveguides themselves. MHD waves were found to be ubiquitously present in the solar atmosphere, thanks to the continuous improvement in the spatial, temporal, and spectral resolution of both space-born and ground-based observatories. These detections, coupled with recent theoretical advancements, have been used to obtain diagnostic information about the solar plasma and the magnetic fields that permeate it, by applying the powerful concept of solar magneto-seismology (SMS). The inclusion of asymmetric shear flows in the MHD waveguide models used may considerably affect the seismological results obtained. Further, they also influence the threshold for the onset of the Kelvin–Helmholtz instability, which, at high enough relative flow speeds, can lead to energy dissipation and contribute to the heating of the solar atmosphere—one of the long-standing and most intensely studied questions in solar physics. Full article

As a by-product of wastewater treatment, sewage sludge can be used for natural, agricultural, or energy purposes. One method of preparing sludge for management and use is solar drying. To intensify the drying process, natural additives can be used to alter the structure of the sludge and accelerate the evaporation of water. This research aimed to evaluate the influences of different organic additives in sewage sludge mixtures on the physicochemical and energy parameters of briquettes. This research was carried out without thermal boosting in a 4 × 2.5 × 2 m plastic tunnel. The tunnel was equipped with three drying stations and control and measuring equipment. In two test series, sludge additives in the form of straw and lignocellulosic materials, sawdust, bark, woodchips, and walnut shells, were used. Briquettes were made from the resulting mixtures and then subjected to physical and chemical analyses. This research showed high variability in the contents of trace elements, nitrogen, and sulphur in relation to an increase in the amount of sludge in the briquettes, which, for the briquettes made from sewage sludge, was nearly twice as high as for the briquettes made from the mixtures. The results of the flue gas analysis for the briquettes with sawdust and wood chip additives were very similar. The briquettes made from sewage sludge with lignocellulosic materials (bark and wood chips) had fuel properties similar to woody biomass, with a calorific value and heat of combustion of 15–16 MJ/kg. Fibrous additives (straw) significantly increased the strength parameters of the briquettes, by more than 50% of the value. The compositions and properties of the mixtures affected the following briquetting parameters: temperature and compressive force. The briquettes made from sewage sludge and additives can be classified according to ISO 21640 as SRFs (solid recovered fuels). In most of the results, the net calorific value (NCV) was 3 to 4; the chlorine content (CL) was 2 to 1; and the mercury content (Hg) was 1. The sewage sludge mixtures facilitated the agricultural and energy use of the briquettes. Full article

Fruit skin color and physical quality are important for customer acceptability and market value. Therefore, this study aimed to evaluate the effect of pneumatic defoliation on the fruit quality, coloration, and anthocyanin content of ‘Fuji’ apples. Apple trees were subjected to no defoliation (control) and defoliation at low (0.6 bar) and high (0.9 bar) air pressure 20 days before harvest at 1 km/h of tractor speed. High-defoliation treatment increased the leaf damage rate but did not significantly affect the defoliation rate compared to low-defoliation treatment. Additionally, photosynthetically active radiation and solar irradiance inside the tree canopies were highest in the high-defoliation group, followed by the low-defoliation and control groups. With the exception of higher firmness in the high-defoliation treatment, pneumatic defoliation treatments had little effect on fruit size and weight, titratable acidity, soluble solids content, the starch pattern index, and the sunburn incidence of fruit. Compared with that of the control group, both defoliation treatments significantly increased the a* and C values and decreased the h^o values of the fruit color. Moreover, both defoliation treatments significantly increased anthocyanin content and upregulated the anthocyanin biosynthesis genes (MdPAL, MdCHS, MdCHI, MdF3H, MdANS, MdANS, MdUFGT) and the transcription factor (MdMYB10). A Pearson′s correlation analysis also showed that anthocyanin production was strongly correlated with each of the anthocyanin biosynthesis genes, especially in the pneumatic defoliation treatments. Conclusively, the results show that pneumatic defoliation at low pressure bars could be an effective strategy for improving the red coloration of ‘Fuji’ apples. Full article

The objective of this paper is to reproduce and predict the series of solar cycle amplitudes using a simple time-series model that takes into account the variable time scale of the Gleissberg oscillation and the absence of clear evidence for odd–even alternation prior to Solar Cycle 9 (SC9). It is demonstrated that the Gleissberg oscillation can be quite satisfactorily modelled as a sinusoidal variation of constant amplitude with a period increasing linearly with time. Subtracting this model from the actual cycle amplitudes, a clear even–odd alternating pattern is discerned in the time series of the residuals since SC9. For this period of time, the mean value of the residuals for odd-numbered cycles is shown to exceed the value for even-numbered cycles by more than $4\sigma$, providing the clearest evidence yet for a persistent odd–even–odd alternation in cycle amplitudes. Random deviations from these means are less than half the standard deviation of the raw cycle amplitude time series for the same period, which allows the use of these regularities for solar cycle prediction with substantially better confidence than the simple climatological average. Predicted cycle amplitudes are found to be robust against the addition or omission of some data points from the input set, and the method correctly hindcasts SC23 and SC24. The potential physical background of the regularities is also discussed. Our predictions for the amplitudes of SC25, SC26, and SC27 are $155.8\pm 20.7$, $96.9\pm 25.1$ and $140.8\pm 20.7$, respectively. This suggests that the amplitude of SC26 will be even lower than that of SC24, making it the weakest cycle since the Dalton Minimum. Full article

Three-dimensional plasma nanostructures with high light–thermal conversion efficiency show the prospect of industrialization in various fields and have become a research hotspot in areas of light–heat utilization, solar energy capture, and so on. In this paper, a simple chemical synthesis method is proposed to prepare gold nanoparticles, and the electrophoretic deposition method is used to assemble large-area three-dimensional gold nanostructures (3D-GNSs). The light–thermal water evaporation monitoring and surface-enhanced Raman scattering (SERS) measurements of 3D-GNSs were performed via theoretical simulation and experiments. We reveal the physical processes of local electric field optical enhancement and the light–thermal conversion of 3D-GNSs. The results show that with the help of the efficient optical trapping and super-hydrophilic surface properties of 3D-GNSs, they have a significant effect in accelerating water evaporation, which was increased by nearly eight times. At the same time, the three-dimensional SERS substrates based on gold nanosphere particles (GNSPs) and gold nanostar particles (GNSTs) had limited sensitivities of 10⁻¹⁰ M and 10⁻¹² M to R6G molecules, respectively. Therefore, 3D-GNSs show strong competitiveness in the fields of solar-energy-induced water purification and the Raman trace detection of organic molecules. Full article