esa-sceva/satcom-chunk-collection huggingface dataset:
# CFD-DEM Simulation of the Transport of Manganese Nodules in a Vertical Pipe
## 5 Results and Discussion
### Retention Ratio  
The retention ratio, \(C_{v,l}/C_{v,0}\), is defined to describe the variation of local solid-phase concentration with the initial mixture velocity. In Figure 17, cases of different initial SVFs and particle diameters are presented. It is seen that with increasing initial mixture velocity, the retention ratio decreases continuously, which is common for all of the six cases. This can be attributed to the fact that the drag coefficient decreases with increasing mixture velocity, which implies that necessary slip velocity can be easily attained. At a certain particle diameter and the initial mixture velocity, the increase of the initial SVF contributes to the increase of \(C_{v,l}/C_{v,0}\). This could be due to the growing importance of particle-particle and particle-wall interaction in energy dissipation. In addition, the liquid and solid velocities decrease, which means that the mass flow rate of the outlet is smaller than that of the inlet. Despite the fact that particle slip velocity decreases as concentration increases, this is insufficient to compensate for the blocking effect caused by the decrease in mixture velocity and the increase in particle collision. It is seen that variations of the retention ratio with the particle diameter at \(V_{mix,0}\) = 3 m/s and \(V_{mix,0}\) = 4 m/s are not monotonic. At \(V_{mix,0}\) = 3 m/s and 4 m/s, the highest retention ratio is reached at \(d_{s}\) = 15.0 mm and \(C_{v,0}\) = 10%. For particles exposed to this condition, the ability of following the carrying liquid is explicitly low. The slip velocity becomes increasingly relevant as the initial mixture velocity decreases, resulting in the retention ratio of a large particle being greater than that of a small particle. At \(V_{mix,0}\) = 4.5 m/s, the retention ratio decreases with increasing particle diameter. At \(V_{mix,0}\) = 4.5 m/s, highly frequent collisions between particles with \(d_{s}\) = 5.0 mm reduce the liquid and solid velocities, leading to increases in local SVF and the retention ratio. As the influence of slip velocity diminishes with increasing initial mixture velocity, the relationship between particle size and retention ratio varies predictably. In the case of infinite initial mixture velocity, slip velocity can be ignored, resulting in a retention ratio close to 1.  
Figure 17: Relationship between initial mixture velocity and retention ratio.  
\begin{table}
\begin{tabular}{c c c c} \hline \(V_{mix,0}\) (m/s) & 3.0 & 4.0 & 4.5 \\ \(C_{v,l}\) (\%) & 8.6 & 6.8 & 6.4 \\ \(I_{v}\) (m/m) & 0.1756 & 0.2303 & 0.2736 \\ \hline \end{tabular}
\end{table}
Table 5: Relationship between total pressure drop and initial mixture velocity at \(C_{v,0}\) = 5% and \(d_{s}\) = 15.0 mm.
## 2 Methodology
### Integrated Methodology for the Elaboration of Geospatial Exposure Databases
#### 2.3.3 Building Height  
Building height, expressed either in meters or number of levels, is a relevant attribute in standardized urban cadaasters. However, many areas of the world lack this information. In certain urban areas, there is information in OpenStreetMap [52], stored in the key height = \" that describes the actual height of a feature (meters) and/or the tag \"building.levels\". The building.levels tag records the actual number of above-ground levels (=floors = storeys) of a building or building part, considering that the underground levels and the roof do not count as levels.  
If the building height is not available, its obtention implies an investment that should be periodic, as cities evolve over time. The most fitted geomatic technique to estimate height is the calculation from the Z (heights) of a 3D point cloud derived from satellite, plane, or UAV photogrammetry or LiDAR clouds [52].  
In the case study of San Jose, heights were not available, so the attribute was not included in the city-GED. In order to test its relevance in forecasting building typologies,  
Figure 3: Presentation of the Polsby–Popper index result: very regular buildings (green), regular buildings (yellow), and irregular buildings (red).  
two samples of height were processed, the heights obtained visually for the 7226 buildings of the sample-GED [48] and the heights obtained from a LiDAR-derived 3D point cloud covering a part of the study area (8010 buildings, 9.5%), provided freely by the CNE. The original flight was conducted in July-August 2012, covering a landslide-prone area over the Cerros de Esczau, with FOV: 45\({}^{\circ}\), laser pulse rate: 68,000 Hz, scan rate: 24.4 Hz, and an average point density of 2 points/m\({}^{2}\)[50].
# Modular Combined DC-DC Autotransformer for Offshore Wind Power Integration with DC Collection
## 1 Introduction
Obviously, resonant topologies are not suitable for scenario where large power transmission is required, such as OWFs. A step-up unidirectional DC-DC autotransformer is briefly introduced in [14], but the footprint of this topology is still very large due to the application of converter transformers. An input-independent-output-series structure is proposed in [15] with inter-module power balancing units. A non-isolated modular DC-DC auto-transformer (MDCAT) is proposed in [16], the developed two-port submodules are connected in the input-series-output-series structure. However, the topology and control strategies of this MDCAT are complex. Converter transformers cause extra power loss and increased cost. Aiming at improving operation efficiency and reducing the cost, this paper proposes a modular-combined DC-DC autotransformer (MCAT). In the MCAT, converter transformers are replaced by a DC-isolated capacitor and a compensation inductor in series, which are much smaller in size and cost than transformers, and do not incur additional power losses in series resonance. The reminder of this paper is organized as follows. Section 2 describes the circuit configuration of the proposed MCAT. The selection methods of main circuit parameters for the MCAT are introduced in Section 3. Section 4 analyzes the corresponding control strategy under steady-state operation and the AC side short circuit fault recovery strategy. Figure 1: DC collection grids of OWF: (**a**) DC series-connection OWF; (**b**) DC parallel-connection OWF. In addition, the recovery strategy of the internal three-phase short-circuit fault is proposed. To validate the feasibility and effectiveness of the proposed MCAT and control strategies, the simulation studies in PSCAD/EMTDC are presented in Section 5. Finally, Section 6 concludes this paper.
## 1 Introduction  
First conceived in the early 1970s, digital image correlation (DIC) is a technique that captures images of an object of interest and delivers full-field measurements on the object of interest using image analysis. Formerly, DIC was used for measuring deformations and strains on a planar object subjected mainly to in-plane loadings. This was referred to as two-dimensional (2D) DIC, which to date remains an important technique for 2D deformations and strain measurements in material testing [1; 2; 3; 4; 5; 6; 7; 8; 9; 10]. However, nonplanar objects subjected to out-of-plane loading and deformations are mostly unavoidable in practice. In the 1990s, 2D DIC was extended to three-dimensional (3D) measurements through stereovision systems [11; 12; 13]. Referred to as 3D DIC, the system consists of two or more cameras to capture digital images of the object of interest from two or more perspectives.  
Using a stereoscopic sensor setup, the position of each point in the area of interest is focused on a specific pixel in the camera plane. If the orientation of the sensors with respect to each other (extrinsic parameters) and the magnifications of the lenses and all imaging parameters (intrinsic parameters) are known, the 3D position of any point in the area of interest can be calculated by applying image correlation algorithms. This process determines the shift and/or rotation and distortion of little facet elements in the reference image [14].  
DIC offers full-field and noncontact measurements and has seen significant growth in recent years in different fields including aerospace, microscale measurements, bio materials, etc. The focus of this article is on the application of DIC in manufacturing and inspection of composite materials and structures. First, a few case studies where 3D DIC was used in testing composite structures at Concordia Center for Composites (CONCOM) labs are presented in the \"Conventional DIC Applications\" section. Subsequently, the development of two new DIC applications in manufacturing and inspecting of composites made by an automated fiber placement (AFP) process is discussed in the \"Development of New Applications for DIC\" section. One of the challenges for in situ manufacturing of thermoplastic composites using AFP is the formation of residual strain and distortion during manufacturing. However, because of the high temperature and pressure involved in in situ manufacturing of thermoplastic composites, strain gages cannot be used to monitor and measure strain and deformation during manufacturing. In Section 3.1, it is discussed how DIC can be employed to overcome this challenge. Another main challenge in automated manufacturing of composites using AFP is the inspection of theply during manufacturing. Conventional manual inspection techniques are tedious, time consuming, and operator-dependent. In Section 3.2, methodology and preliminary results are presented for the first time that show how DIC can be used for inspection purposes during AFP.
## 6 TTL Estimation
### Results under S-Type Offset
#### 6.1.3 Impact of Laser Frequency Noise  
The laser frequency noise generated by 1 and 10 times the ASD model (cf. Equation (1)) was tested for TTL estimation with \(\Delta x=\Delta y=\Delta z=0.5\,\mathrm{mm}\) for each satellite and \(0.1\,\mathrm{\SIUnitSymbolMicro rad}/\mathrm{Hz}^{1/2}\) white angle noise. As shown in Figure 10 and Table 5, the laser frequency noise in case (b) is 10 times that in case (a), and as a result, the estimation error (black) in case (b) increases compared to case (a), but is still not above the TTL error of GRACE-FO (green). Assuming that the laser frequency stability in future gravity missions will be at the same level as GRACE-FO, the laser frequency noise as well as other ranging noise lower than it may not be a serious problem for TTL estimation.
## 5 Conclusions  
To improve the quality of the acquired virtual view image, a virtual view acquisition technique for complex scenes of monocular images based on layered depth images is proposed in this paper. Firstly, the multilayer representation of the LDI is introduced, and the depth discontinuities of the edge of the occluded area are reasonably grouped, so as to determine the edge of the occluded area and inpaint the edge through the GAN. It is prepared for the information filling of the occluded area. Then, the information of color and depth in the occluded area is filled through the PConv network. Since the position information of the inpainted edge has been determined, the network efficiency is improved. Finally, the semantic segmentation information is added to the color inpainting network and the deep inpainting network, and Convolution-BatchNorm-ReLU blocks are adopted in the shared discriminator to optimize the virtual view. The results of the experiments show that in the 3D image sequences of the ballet and breakdancers provided by Microsoft Research Asia, the RMSE of the proposed method is 35.5% and 24.3% lower than the average value, the SSIM of the proposed method is 5.28% and 6.76% higher than the average value, and the PSNR of the proposed method is 10.1% and 12% higher than the average value. At the same time, the limit offset of the virtual view acquired by the monocular image is measured several times. Although the complexity and depth of the information contained in the images are different, the virtual view images estimated by the method proposed in this paper can be clearly viewed at the angle range of \(-30^{\circ}\) to \(30^{\circ}\) when the three-dimensional display is carried out. These results prove the superiority of the algorithm proposed in this paper. In terms of practical application, the method proposed in this paper can be applied to 3D movies, VR and smart medical technology so as to improve the three-dimensional expression ability and enable users to have a better visual experience. However, the method proposed in this paper also has some defects. To improve the quality of the virtual view image, the network structure adopted in this paper is relatively complex, and the computation is large. Therefore, to apply it to terminal devices such as mobile phones and tablet computers, the model in this paper will be lightweight in the future, so as to realize the comprehensive promotion of 3D display technology.  
Conceptualization, Q.W. and Y.P.; methodology, Q.W.; software, Q.W.; validation, Q.W.; writing--original draft, Q.W.; writing--review and editing, Q.W.; resources, Y.P.; project administration, Y.P.; funding acquisition, Y.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Project of the Jilin Provincial Science and Technology Department, grant number 20220201062 GX.
# On Unmanned Aerial Vehicles Light Show Systems: Algorithms, Software and Hardware
## 2 Formation Transformation in UAVs-LS  
In the process of UAVs-LS, one of the key steps is the formation transformation between an initial formation and a target one. Since the volume of UAVs cannot be ignored, collision-free trajectories must be planned for safety concerns. In general, the formation transformation can be decomposed into two subproblems:  
* TAP: for each UAV, a match between the initial formation and the target one is generated to satisfy certain criteria;
* Trajectory planning problem: for each UAV, a collision-free trajectory is planned based on the match from the TAP.  
An example of formation transformation is shown in Figure 1, where five UAVs transform from a wedge formation to a diamond one. The TAP step is to assign, for each node (i.e., UAV) of the wedge formation, a target node in the diamond formation. The second step is to plan a collision-free trajectory connecting the initial node and the target one.
# Ring-Overlap: A Storage Scaling Mechanism for Hyperledger Fabric
## 6 Simulation Experiment
### Experimental Design
#### 6.2.1 Experiment 1: Storage Consumed on a Single Node  
In Hyperledger Fabric, the ledger consists of two parts: the world state and the blockchain. The world state is the database that stores a set of current values, and the blockchain is the transaction log (transactions) that records all changes resulting in the current world state. If an asset (a record in the world state) only has one corresponding transaction, the storage space consumed by a node is unchanged when compared to Hyperledger Fabric; if an asset has multiple transaction logs, the storage space consumed by a single node will change in the new proposal when compared to Hyperledger Fabric. When each asset corresponds to more and more transaction logs, more and more blocks are generated, but the size of world state increases slowly, which means the proposed mechanism is more dominant, and it will consume less storage space on a single node compared to the traditional storage model on Hyperledger Fabric.  
In the network used for the experiments, set the data size \(S_{w}\) for one record of the world state, the data size \(S_{t}\) for one transaction and the block size \(S_{b}\), ignoring block header. When the number of transactions achieved the block size threshold, a new block is generated and sent to the network, and the peer nodes in the network save the block according to the rules of proposed scheme. Set two variables \(N_{w}\) and \(N_{t}\), where \(N_{w}\) denotes the number of records in the world state and \(N_{t}\) is the number of transactions. Increasing the value of \(N_{w}\) and \(N_{t}\) sequentially and continuously, until \(N_{t}\) is an integer multiple of \(S_{b}\), called a round, and records the value of Equation (1).
# A Credit-Based Congestion-Aware Incentive Scheme for DTNs
## 5 Performance Evaluation
### Performance Comparison  
CBCAIS is compared with the direct routing scheme, where each node only stores its own messages but does not forward messages to others; the SMART scheme [14]; the Multicenter scheme [15]; and the scheme proposed by [PERSON] [16], which we denote as GTA. We are interested in the following metrics for performance evaluation: packet delivery ratio, average delivery delay, overhead ratio, average energy consumption, cumulative utility, and number of failed transmissions due to short of credits. The delivery ratio is defined as the ratio of successfully delivered messages to total generated messages in the network. Delay is measured by the delay sum of all delivered messages divided by the number of delivered messages. Overhead ratio is defined as the ratio of the total number of forwarded messages to the number of delivered messages, which denotes how many times forwarding was needed to successfully deliver a message. Average energy consumption is the average energy consumed by each node in the simulation process. Cumulative utility is the total credits obtained by a node, including the credits to pay for delivered messages. We evaluate the impact of buffer size, TTL, message generation interval, and data transmission speed on performance.
## 3 Results
In cases 4 and 5, the converter is in the CV stage with \(V_{o}\) regulated at 120 V, and the output current is around 4 A (80% load) and 2.5 A (50% load). For Method I in Figure 8d,e, the phase-shift \(\phi\) is kept to be reduced, and the amplitudes of \(v_{p}\) and \(v_{s}\) are always the same with unity gain. For Method II in Figure 9d,e, \(v_{p}\) and \(v_{s}\) are always the same, and the resonant current is in phase with both voltages due to the resonance operation. Moreover, it is a fixed frequency and free-of-control CV stage. Figure 7: Simulation block diagram and experimental prototype  
Figure 8: Simulated (left) and experimental (right) waveforms of \(v_{p},v_{s},v_{c},i_{r}\) with Method I: (a) \(V_{o}=84\) V, CC; (b) \(V_{o}=108\) V, CC; (c) \(V_{o}=120\) V, \(I_{o}=5\) A; (d) \(I_{o}=4\) A, CV; (e) \(I_{o}=2.5\) A, CV. Figure 9: Simulated (left) and experimental (right) waveforms of \(v_{p},v_{s},v_{c},i_{r}\) with Method II: (**a**) \(V_{o}=84\) V, CC; (**b**) \(V_{o}=108\) V, CC; (**c**) \(V_{o}=120\) V, \(I_{o}=5\) A; (**d**) \(I_{o}=4\) A, CV; (**e**) \(I_{o}=2.5\) A, CV. In Figure 10, the drain-to-source voltage of switches in both bridges (\(S_{1}\) and \(S_{a}\)) and the resonant current are put together to show the soft-switching behavior. The necessary condition of ZVS operation can be confirmed if the turn-on drain-to-source current of the switch is negative. In Method I, all switches can work in the ZVS operation except for the secondary switch at rated output power case working at the boundary of ZVS. In Method II, the primary switches can always maintain ZVS in the CC range and work with ZCS in the CV stage. The secondary bridge actually works as a synchronous rectifier so that all secondary switches work at ZCS in both CC and CV stages.
# Fractional Order Viscoelastic Model for Stress Relaxation of Polyvinyl Chloride Geomembranes
## 2 Materials and Test Methods  
### Materials and Apparatus  
According to statistics by the International Commission on Large Dams (ICOLD) in 2010, PVC GMBs commonly used in MFRD higher than 150 m, generally have a thickness above 1.5 mm. The commercially available GMB selected in this paper is a 2.0 mm thick PVC GMB made using the calendaring technology, with a single roll of 45.0 m long and 2.0 m wide, manufactured by Hongxiang New Material Co., Ltd. The index properties of PVC GMBs are reported in Table 1. The chemical composition of PVC GMB is, respectively, PVC resin (47.4%), plasticizer (mainly dihexyl phthalate, 30%) stabilizer (2.1%), filler(20%) and antioxidant (0.5%).  
Figure 1: Anchorage of PVC GMBs in MFRD: (**a**) on the plinth of the dam abument; (**b**) on the top of the concrete antiseepage wall.  
The test setup (shown in Figure 2) consists of the temperature control system, the tensile testing machine for geosynthetics (TTMG), the controller, and the data acquisition system. The temperature control system can control the temperature in the range of 4 to 35 \({}^{\circ}\)C accurate to 0.5 \({}^{\circ}\)C. The TTMG (CMT-5000, Nss(Shenzhen) Laboratory Equipment Co., Ltd., Shenzhen, China) was employed to perform the tensile tests, with parameters as follows: maximum load of 30.0 kN, maximum stroke of 2.1 m and deformation measurement range of 0.2 to 100 mm with error in 0.5 mm. The data acquisition system (CJ-3600) was adopted with a frequency ranging from 200 to 2000 Hz. The test temperature was 20 \(\pm\) 1 \({}^{\circ}\)C, and stress relaxation was monitored for 48 h.
# Synergistic Potential of Optical and Radar Remote Sensing for Snow Cover Monitoring
## 3 Data and Methods
### Methods
#### 3.1.3 Assessment of the Synergistic Use of SAR and Optical Remote Sensing  
The potential use of the HRS&l SWS product to complement the SCA provided by MODIS in the Iberian mountains was evaluated, specifically focusing on assessing the additional SCA data from HRS&l SWS compared to MODIS in the Pyrenees. It is noteworthy that the HRS&l SWS product is available exclusively for this montane region within the Iberian Peninsula. This evaluation was conducted monthly throughout the snow season (November to May). Firstly, we aligned and rescaled the HRS&l SWS product to match the MODIS granule alignment and pixel size, ensuring accurate comparison between the two datasets. Subsequently, we developed an index called Probability of Wet Snow Additional Information (PWSAI), calculated as follows:  
\[PWSAI=\frac{N_{W}}{N_{T}}\times 100 \tag{2}\]  
where N\({}_{W}\) is the number of days with at least one additional pixel with wet snow (HRS&I SWS) under cloudy conditions in the MODIS product, and N\({}_{T}\) is the number of days with data available about snow cover in both products (HRS&I SWS and MODIS) on the same date. Secondly, we analyzed the respective contributions of each product to the total SCA. It is important to note that we only considered wet snow data under cloud cover conditions and ensured a correct comparison between the two products exclusively contrasting data from the same date (MODIS and HRS&I products have different temporal resolutions). Moreover, we evaluated the range of variability of the wet snow contribution to the total SCA for each month.