esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology and Modeling
### Passive Solution Tests
#### 2.6.1 Building Orientation  
Based on the floor plans in Section 2.2, initially aligned with true north (0\({}^{\circ}\)), the buildings were rotated clockwise in 45\({}^{\circ}\) increments, resulting in orientations of 0\({}^{\circ}\), 45\({}^{\circ}\), 90\({}^{\circ}\), 135\({}^{\circ}\), 180\({}^{\circ}\), 225\({}^{\circ}\), 270\({}^{\circ}\), and 315\({}^{\circ}\). The rotation angle is measured clockwise from true north to plan north [60], as seen in Figure 5.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Element** & **U, Brazil** & **U, Portugal** & **U, Turkey** & **References** \\ \hline Exterior wall & 1.69 & 1.38 & 0.87 & [42; 46; 51; 52; 53; 54; 55; 56; 57] \\ Roof & 1.27 & 1.27 & 0.71 & [42; 46; 51; 52; 56; 58] \\ Ground contact slabs & 0.19 & 0.19 & 0.59 & [42; 46; 51; 59] \\ Exterior windows & 5.89 & 5.89 & 5.89 & [51; 52] \\ \hline \hline \end{tabular}
\end{table}
Table 4: U-values, in W/(m\({}^{2}\)-K), for the constructive elements used in each location.  
Figure 5: True north rotation from plan north.
###### Abstract  
Methods for determining the characteristics of self-acting (aerodynamic) gas bearings have been developed for many years, but many researchers and engineers still question how sophisticated a model of such bearings should be to obtain reliable results. This is the subject of this article, which presents a numerical analysis of aerodynamic gas bearings using two alternative methods: a specialized program based on the finite difference method, and a universal CFD program using the finite volume method. Gas bearings with a nominal diameter of 49 mm, designed for a 10 kW turbogenerator operating at a rotational speed of 40,000 rpm, are analyzed. The vapor of the low-boiling medium, designated HFE-7100, is used as the bearing lubricant. The calculations focus on determining the position of the bearing journal where the bearing achieved the required load capacity and checking the bearing characteristics beyond the nominal operating point. The most important results obtained by the two independent methods are compared, and recommendations are made for those interested in the numerical analysis of self-acting gas bearings.  
gas bearings; journal bearings; oil-free bearings; aerodynamic lift; load capacity Article
# Rainfall Estimation from Tropospheric Attenuation Affecting Satellite Links
## 2 Experimental Setup  
A relevant part of the data used during this work is collected within the measurement campaign of the Alphasat Aldo Paraboni propagation experiment [12], whose main goal is to better investigate the propagation impairments that affect Ka/Q/V band satellite channels. In 2014, NASA Glenn Research Center (GRC) joined the experimental campaign by installing the equipment to receive the beacon signals transmitted by the Aldo Paraboni Payload (also known as Technology Development Payload 5--TDP 5) [13] aboard the Alphasat geosynchronous Earth orbit satellite at Politecnico di Milano. The payload is equipped with two beacons that transmit coherent, continuous-wave signals at 19.701 and 39.402 GHz, respectively.  
The NASA experimental equipment is installed on the rooftop of the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) at Politecnico di Milano, Italy. The instruments, as depicted in Figure 1, include:  
Figure 1: Experimental setup on DEIB rooftop in Milan, Italy.  
Two beacon receivers (Ka band and Q band), each of which consists in a Cassegrain antenna (diameter of 0.6 m and 1.2 m for the Ka and Q band, respectively), and a down-conversion stage enclosed in a box positioned just behind the antenna. The received power level is sampled with a rate of 8 Hz.  
* A Thies Clima Laser Precipitation Monitor, an optical disdrometer counting and classifying hydrometeors according to their size and falling velocity, from which the rain rate \(R\) can be calculated with 1-min integration time.
* A weather station, monitoring wind speed and direction, pressure, temperature, and relative humidity, with a sampling interval of 1-min.
* A tipping bucket rain gauge, providing an additional measurement of \(R\) (1-min integration time), though with a more limited accuracy if compared to the disdrometer.
# Western Mediterranean Precipitation Extremes, the Result of Quasi-Resonant Sea-Atmosphere Feedbacks
## 3 Results
### The Western Mediterranean SST Anomaly Is Strong, in Phase with EREs  
A quasi-resonance phenomenon occurs when the positive SST anomalies of the western Mediterranean and the Adriatic Sea, as well as most of the enclosed or semi-enclosed European seas, have a high amplitude and are in phase with EREs. EREs 3 and 10 (Figures 3 and S1) exhibit these characteristics.  
According to Figure 3, the Baltic Sea is strongly involved in the co-evolution of oceanic and atmospheric phenomena. SST anomalies in phase with ERE 3 exceed 0.5 \({}^{\circ}\)C along the arc following the coasts of Spain, France, and Italy, as well as in the Adriatic and Baltic seas (Figure 3e,f). Clustering of lows occurs on a large scale; the precipitation anomaly in the period range of 11.4 to 42.7 days, in phase with EREs, largely covers the Gulf of Lion as well as the French territory located north of the Gulf of Lion (Figure 3c,d). The rainfall depth averaging over 0.2\({}^{\circ}\)\(\times\) 0.2\({}^{\circ}\) meshes greater than 60 mm/day is located in the Nimes region (the main anomaly is centered at 44\({}^{\circ}\)N, 4\({}^{\circ}\)E) both in the daily and bi-daily period ranges (Figure 3a,b); precipitation height reaches 431 mm/day locally.  
The SST anomaly of the western Mediterranean in phase with ERE 10 follows the French coast, then the coast at the north of Italy, exceeding 0.5 \({}^{\circ}\)C (Figure S1e,f). The SST anomaly in the Adriatic Sea in phase with EREs exceeds 0.7 \({}^{\circ}\)C, extending to the South in the Central Mediterranean. The eastern Black Sea, the Baltic Sea, and the North Sea off the Scandinavian peninsula are also involved in the quasi-resonance since they exhibit strong SST anomalies in phase with EREs. The rainfall anomaly in the period range of 11.4 to 42.7 days, in phase with EREs, is a wide south-west-north-east strip that follows the Spain and French coasts (Figure S1c,d). The rainfall depth greater than 60 mm/day is located off the Toulon region (the main anomaly is centered at 42\({}^{\circ}\)N, 6\({}^{\circ}\)E) in the daily period range (Figure S1a,b); precipitation height reaches 326 mm/day locally.
## 3 Results and Discussion
### Discussion on Applicability in Other Regions  
Using MODIS and Landsat 8 imagery, captured on 30 August 2024, as experimental data; we analyzed the study area, located in Beijing, China (Figure 11a). A color composite image of the study area (Figure 11b) revealed a densely built-up central region surrounded by natural surfaces and water bodies, indicative of diverse landcover types. Figure 11c highlights a pronounced urban heat island effect, with the central urban region exhibiting surface temperatures significantly higher than the surrounding areas, with a temperature difference exceeding 10 K. By employing the OBD-based LST downscaling method, we enhanced the spatial resolution of the MODIS temperature data to match that of the Landsat multispectral data (Figure 11d). The downscaling process increased the maximum temperature values by nearly 4 K, unveiling finer details in surface temperature and enabling a clearer depiction of spatial temperature variations within urban areas. These improvements provide valuable insights for urban managers to better guide activities in zones affected by extreme temperatures.  
Figure 10: Process and results of OBD method considering adjacency effect: (**a**) true LST of subpixels, (**b**) true LST of pixels before decomposing, (**c**) firstly decomposed LST of subpixels, (**d**) weights of subpixels, (**e**) double decomposed LST of subpixels, (**f**) OBD decomposed LST of subpixels.
# Landsat Surface Product Validation Instrumentation:
## 3 ASD and UAS Technology Assessment
### Precision
#### 3.1.3 NIR Band  
Tables 5-7 show the repeatability results for the NIR band. In the case of this spectral band, the bright targets were the same, except the RIT Red target replaced the asphalt target for a range of reflectance from 0.38 to 0.53. Only three really dark targets existed for this band--Permaflect 5%, RIT 2%, and Mystery Black. For the individual ASD system, bright (0.4 to 0.6 reflectance) target repeatability is 0.014-0.020 \(\pm\) 0.01 and darker (0.02 to 0.06 reflectance) target repeatability is 0.001-0.002 \(\pm\) 0.001. From Table 6, results across all ASD systems indicate repeatability for bright targets from \(\pm\)0.01 to 0.02 and for darker targets \(\pm\)0.001. The results for the UAS indicate that brighter target average reflectance values were quite consistent with the ASD values. However, bright target repeatability ranged from 0.01 to 0.04. In comparison to all ASD teams, bright target uncertainty (standard deviation) is almost double for the UAS but is very similar if the Mystery Gray target is removed. Dark target average reflectance measurements were quite different than ASD values, and dark target repeatability was also larger as follows: 0.005 versus 0.001. Interestingly, repeatability was the highest for the Permaflect target.
## 4 Case Study: Conceptual UAM Flight Routes and Establishment of Holding Areas
### Selecting Locations for Holding Area in Seoul-GyungIn Area  
An analysis has been performed to determine where each holding area designed with the three concepts can be established. Each holding area concept should be applied to appropriate spaces according to its clear pros and cons. A concept 1 holding area can be established at three locations along the Han River Corridor [6]. There is a prohibited area to the north of the Han River, and there are many high-rise buildings to the south of the Han River. So, there are many restrictions to consider. Therefore, holding areas can be established in three places where straight flight routes for cruising are located so that the holding procedure could be performed within range of the Han River.  
Compared to the other holding area concepts, concept 2 has fewer space constraints, so it can be established in relatively many places. In the case of the GyungIn area, compared to Seoul, the height of obstacles is not great, and establishing the holding area is relatively easy because there are open spaces and coasts. Therefore, concept 2 can be established between  
Figure 12: UAM flight routes in Seoul and GyungIn area [1].  
Yeongjongdo and Incheon, Songdo, Siheung, and Bucheon [6]. These holding areas can be utilized for detours due to bad weather conditions or for UAM vehicle flow management.  
Concept 3 can be established in sections where the surrounding spaces are narrow and the speed of the UAM vehicle needs to be reduced for urban air traffic flow management. Anyang and Gwacheon, where spaces are narrow due to the mountainous terrain on both sides, and there is a need to reduce noise, and the west of Gangseo-gu, where Gimpo Airport is located, are suitable for concept 3 holding areas [6]. Figure 13 shows an example in which holding areas based on the three concepts can be established. The purple holding areas are concept 1, the light-blue holding areas are concept 2, and the green holding areas are concept 3. In particular, the holding areas around Gimpo Airport can be utilized when the UAM corridor passing through the airport is closed while the existing aircraft have to perform abnormal procedures, such as to go around.
# Spectrum Allocation Based on an Improved Gravitational Search Algorithm
## 5 Simulation Experiment
### Experimental Environment and Parameter  
Simulations are operated in Matlab R2014a platform. We use the topology structure of cognitive radio system as suggested in [25], it is assumed that there is a wireless network covering \(20\times 20\) square area. The number of PU is fixed to 10, with protection radius \(d_{p}=4\). The number of SUs is \(N\), with interference radius \(d_{s}=2\). The number of available spectrum is M, which are completely orthogonal. The matrix \(B\), \(L\) and \(C\) are generated according to the reference.  
The parameters of the algorithms are set as shown in Table 1. Especially, the parameter setting of IGSA references the configuration of the original GSA to guarantee the comparability with GSA. The default parameter configuration cannot be the optimal setting for various problems. Thus we cannot assure they are optimal for IGSA in solving spectrum assignment. Parameter configuration could be a limitation of our current work, and we will try to find an effective parameter setting method in our further work. Additionally, the maximum iteration times of GSA and PSA in IGSA should be properly chosen so as to ensure the satisfactory performance of the algorithm with minimum computational efforts. A series of experiments were conducted to properly choose the run times in IGSA. The convergence experiments show that the original GSA usually reaches the convergence state after 100 iterations. To enhance the exploitation ability of the proposed algorithm while assuring the exploration capability, the iteration of GSA and PSA are set at 50 and 150, respectively. The population size is the same for all the algorithms in each experiment. Each individual performs one fitness evaluation after an iteration, then the best fitness value of each algorithm is selected to validate the performance of the algorithm.  
In addition, we use the CSGC which is commonly used to solve the spectrum allocation problem as the benchmark algorithm to compare with others, for more information on CSGC, please refer to [24]. All algorithms use the same topology, and the number of repetitions in convergence experiments is 500, others are 50, and the average is finally taken.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Algorithm** & **Specific Parameter** & **Genetic Parameter** \\ \hline \hline \multirow{2}{*}{GSA} & & the initial gravitational \\  & the mesh size \(\Delta_{1}=1\), & constant \(G_{0}=100\), \\  & the shrink factor \(\beta_{s}=0.5\), & the coefficient \(\alpha=20\) \\  & the enlarge factor \(\beta_{e}=2\). & iteration \(E_{itr}=200\). \\ \hline \multirow{2}{*}{PSO} & the acceleration coefficients \(c_{1}=c_{2}=2\), & \\  & inertia weight \(\omega=0.5\), the maximum speed \(v_{x}=4\). & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter setting for algorithms.
## 4 Results
### Validation of Hygro-Chemo-Thermo Transport Model
#### 4.1.2 Comparison of Experimental and Numerical Results  
According to the experimental results of [PERSON] et al., the concrete specimens exposed to a 5% chloride solution reached a steady-state temperature after 14 days at 35 \({}^{\circ}\)C when using a heater, while those exposed to 50 \({}^{\circ}\)C required approximately 23 days to reach a steady state [35]. Additionally, at a depth of 42 mm from the surface, the temperature was measured to be the same as that of the distilled water on the top surface of the concrete specimens. Since temperature effects were considered negligible beyond this period, the experimental results up to 24 days were used for comparison with the numerical analysis. The total chloride content profile was measured at 6 mm intervals from the surface, and the numerical analysis was conducted under the same boundary conditions as the experiment.  
Figures 3 and 4 compare the total chloride profiles obtained from the experiments and numerical analysis based on the water-cement (W/C) ratio and measurement time. These results highlight the influence of the W/C ratio and temperature gradient on chloride penetration in the unsaturated concrete.  
In terms of the W/C ratio, the numerical analysis results for a 0.55 W/C ratio showed better agreement with the experimental data. This trend remained consistent over time. However, at 24 days, the numerical results for a 0.65 W/C ratio also exhibited a similar tendency to the experimental data. Furthermore, for the same measurement duration, both the experimental and numerical results indicated that the total chloride content was higher for the 0.65 W/C ratio than for the 0.55 W/C ratio.  
Regarding the effect of the temperature gradient, the numerical results closely matched the experimental data under both 35 \({}^{\circ}\)C and 50 \({}^{\circ}\)C conditions. Over time, the influence of the temperature gradient was more significant in specimens with a 0.55 W/C ratio, whereas the effect was relatively smaller in specimens with a 0.65 W/C ratio.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**w/c**} & \multirow{2}{*}{**Temp.**} & \multirow{2}{*}{**Time (Day)**} & \multicolumn{6}{c}{**Measuring Depth (mm)**} \\ \cline{3-10}  & & & **0–6** & **6–12** & **12–18** & **18–24** & **24–30** & **30–36** & **36–42** \\ \hline \multirow{8}{*}{0.55} & \multirow{3}{*}{35 \({}^{\circ}\)C} & 3 & 0.416 & 0.169  
Figure 4: Chloride profile in concrete sample (0.65 w/c): (**a**) duration = 3 days, (**b**) 6 days, (**c**) 12 days, (**d**) 24 days.  
Figure 3: Chloride profile in concrete sample (0.55 w/c): (**a**) duration = 3 days, (**b**) 6 days, (**c**) 12 days, (**d**) 24 days.  
These findings confirm that the proposed transport model, which accounts for diffusion mechanisms, ion interactions, and combined temperature effects, can effectively predict chloride penetration in concrete structures under both isothermal and non-isothermal conditions.
# A Review of the Evolution Characteristics and Argillization of Clay Interbeds in Rockslides
## 4 Observation Technique and Analysis Method of Clay Interbed
### Analysis Method of Clay Interbed
#### 4.2.3 Numerical Modeling Analysis Methods  
Numerical modeling analysis methods are useful in attempts to unify the meso-scale and macro-scale in terms of argillization. The Finite Element Method (FEM) and Discrete Element Method (DEM) can be used to connect the meso- and macro-scale in order to obtain a more accurate numerical model. Through FEM, a mesoscopic numerical model of a clay interbed could be established on a scale of 100 microns. Peak strength can be analyzed through numerical shear tests [70]. However, because the model is usually simplified from the actual clay interbeds, it is often considered a special case in terms of analysis. The universality of it needed to be improved.  
At present, DEM is mainly used to simulate the movement and deposition process [71; 72] because its simulation range occurs during the early stage of argillization evolution. The early stage does not show an obvious control effect. It is rarely used in the entire process of clay interbed evolution.
## 2 Materials and Methods
### Methodology Workflow  
Once the pre-processing stage finishes, the algorithm proceeds to raster calculations to determine the AOI's elevation for target years 2050 and 2100 under the three RCP scenarios of interest. Through an automated raster calculation process, the algorithm adds GLO-30 DEM values and EGMS vertical land movement values and, finally, subtracts NASA's SLR Projection Values (Figure 7). This step will provide six new raster layers depicting elevation value under RCP scenarios 2.6, 4.5, and 8.5 for the target years.  
The next algorithmic step involves using raster calculations and Boolean algebra to select and extract the sub-areas in the area of interest that are affected by the different RCP scenarios for target years 2050 and 2100, i.e., the areas that at present have an elevation value greater than zero but in the future--according to the available data and calculations performed at previous algorithmic steps--have a negative or equal to zero elevation value (Figure 8). The output of this stage is six raster files delineating affected areas by the  
Figure 6: Data pre-processing methodology.  
Figure 7: Flowchart for calculating probable elevation values in 2050 and 2100 under RCP 2.6, 4.5, 8.5.  
RCP scenarios under consideration for the target years 2050 and 2100. These files can be converted into vector features for further processing, i.e., area calculation, statistics calculation per country, proximity analysis to known heritage sites, etc. The final step involves performing spatial queries to identify the coastal heritage sites expected to be affected by Sea Level Rise under the studied scenarios and organize this information per type of monument (i.e., UNESCO World Heritage Site or Cultural Heritage Site) and per country to assess the level of vulnerability that each Mediterranean EU-27 country's heritage faces.
# BEVCorner: Enhancing Bird's-Eye View Object Detection with Monocular Features via Depth Fusion
## 2 Related Work  
### Monocular 3D Object Detection  
Monocular 3D object detection methods estimate 3D bounding boxes from a single camera. These methods are crucial for cost-effective applications where only a single camera is available. Despite having only a 2D image, these methods infer 3D positions, mimicking human depth perception by learning from vast image datasets. Anchor-based methods [4; 5; 6] have been a cornerstone of early monocular 3D object detection, drawing from 2D object detection paradigms like Faster R-CNN [7; 8]. These methods rely on predefined 3D bounding boxes (anchors) of various sizes and orientations, predicting whether or not each anchor contains an object and refining it to fit the object's dimensions. The rise of anchor-free methods [1; 9; 10] eliminates the need for predefined anchors, predicting objects based on keypoints, centers, or direct regression. They are preferred due to their effectiveness and simplicity [11]. CenterNet [12] pioneered this approach, and many works extend from this framework. Ref. [13; 14] focuses on depth estimation. FCOS3D [15] redefines centerness using a 2D Gaussian distribution based on the 3D center and is three times faster in learning compared to CenterNet. MonoPSR [16] uses proposals and shape reconstruction for accurate 3D localization. MonoPair [17] improves detection for occluded samples by encoding spatial constraints from adjacent objects, optimizing predictions with nonlinear least squares. MoVi-3D [18] leverages virtual views to normalize object appearances. MonoCD [19] introduces complementary depth predictions to mitigate errors in depth estimation. Ref. [20; 21] predicts depth maps from the image, creating a pseudo-3D representation. These methods demonstrate the potential of monocular approaches, particularly in handling size variability and depth estimation from a single view, with applications in scenarios with limited camera availability. However, they may struggle with accurate position and orientation due to the lack of multi-view constraints, which the proposed method seeks to enhance by integrating with multi-view data.