esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Numerical Experiments and Results
### Example and Parameter Setting
#### 4.2.1 Effectiveness Analysis of the Improved Neighborhood Structure Set  
The classical swap, insert, 2-opt, 3-opt and three-point operators are used to form the traditional neighborhood structure set, which is compared with the improved neighborhood structure set. The optimal value, worst value and average value of the objective function value of the algorithm based on the improved neighborhood structure set are 2.4083, 0.2263 and 1.3227 lower than those of the algorithm based on the traditional neighborhood structure set, respectively. It can be observed that the solution quality of the two-stage VNS-TA based on the improved neighborhood structure set is higher. In addition, there is little difference in solution stability between the algorithm based on the improved neighborhood structure set and the algorithm based on the traditional neighborhood structure set. These results indicate that the constructed neighborhood structure performs better in obtaining high-quality solutions (Figure 3).
# Dynamic Analysis on the Parametric Resonance of the Tower-Multicable-Beam Coupled System
## 4 The Numerical Analysis
### The In-Plane Vertical Natural Vibration Mode  
To accurately analyze the natural vibration mode of the in-plane vertical mode, the MCS is also analyzed through the finite element method (FEM) by commercial software (MIDAS CIVIL). The tower and the beam are all performed by the beam element while the cable is performed by the truss element. The in-plane vertical natural vibration frequencies are selected in Table 5, while the vertical modal shapes of the first five orders are selected as shown in Figure 4, respectively.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameters (Unit)** & **C1\#** & **C2\#** & **C3\#** & **C4\#** & **C5\#** & **C6\#** \\ \hline \(\theta_{i}\) (rad) & 0.57 & 0.82 & 1.27 & 1.27 & 0.82 & 0.57 \\ \(L_{i}\) (m) & 148.41 & 109.67 & 83.82 & 83.82 & 109.67 & 148.41 \\ \(A_{ci}\) (cm\({}^{2}\)) & 99.43 & 70.18 & 53.49 & 53.49 & 70.18 & 99.43 \\ \(H_{ci}\) (MN) & 3.88 & 3.65 & 3.49 & 3.49 & 3.65 & 3.88 \\ \(m_{ci}\) (kg/m) & 81.04 & 57.20 & 43.59 & 43.59 & 57.20 & 81.04 \\ \(D_{ci}\) (m) & 0.51 & 0.16 & 0.03 & 0.3 & 0.16 & 0.51 \\ \(E_{ci}^{\mathrm{c}}\) (GPa) & 202 & 208 & 209 & 209 & 208 & 202 \\ The Irvine Parameter & & & & & & \\ \(\lambda\)[32] & 0.3848 & 0.0538 & 0.0017 & 0.0017 & 0.0538 & 0.3848 \\ \(\sqrt{\beta_{1}^{i}}\) & 0.7478 & 1.1542 & 1.6891 & 1.6891 & 1.1542 & 0.7478 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Basic parameters of stay cables.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters (Unit)** & **Tower** & **Parameters (Unit)** & **Bi\# Beam Portion** \\ \hline \(m_{t}\) (kg/m) & 850,000 & \(M_{t}\) (kg/m) & 250,000 \\ \(E_{bi}\) (MPa) & 500 & \(I_{bi}\) (m\({}^{4}\)) & 2.85 \\ \(d_{i}\) (m) & & 50 \\ \hline \(I_{t}\) (m\({}^{4}\)) & 3.0 & & B1\# & 0.2483 \\ \(L_{t}\) (m) & 80 & \(\sqrt{\gamma_{1}^{i}}\) & B2\# & 0.2582 \\ \(\sqrt{\alpha_{1}}\) & 0.2368 & & B5\# & 0.2582 \\  & & & B6\# & 0.2483 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Basic parameters of bridge tower and beam sections.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Mode No.** & **Abbreviation** & \multicolumn{3}{c}{_f (Hz)_} & **Error (\%)** \\ \cline{3-5}  & & **FEM** & **PMS** & \\ \hline
1 & V1 & 0.01308 & 0.01309 & 0.8 \\
2 & V2 & 0.01339 & 0.01340 & 0.7 \\
3 & V3 & 0.01780 & 0.01781 & 0.6 \\
4 & V4 & 0.02457 & 0.02459 & 0.8 \\
5 & V5 & 0.03452 & 0.03453 & 0.3 \\ \hline \hline \end{tabular}
\end{table}
Table 5: The in-plane vertical model properties of the MCS.  
In Table 5, the calculation errors with these two methods varied within a small margin. There is little difference between the first two modes of the dynamic system. Additionally, in Figure 4, the vertical mode shapes obtained by PMS fit those obtained by FEM well. It is illustrated that the fundamental vibration shapes and frequencies of the components occupying lower-order modes are not much different. Additionally, it is evident from the comparison of the results that the dynamic model and the numerical analysis in this paper can accurately simulate the CEB.
# Smart Patch for Structural Health Monitoring of Composite Repair
## 3 Damage Detection and Localization  
To verify if the smart repair patch embedded with diagnostic film and PZT transducers can monitor the integrity of the bonding quality, the damage index (DI) correlation coefficient and delay-and-sum (DAS) algorithm based on active sensing were used to detect and locate the bonding defects. In this section, two types of defects were studied, which were artificial delamination and surface-mounted artificial damage. In addition, blue contact gel was fully applied to the repair patch to bond it with the composite host structure as baseline signals (as is shown in Figure 4a). Here, the contact gel was used in DolphiCam C-Scan to improve the coupling on rougher surfaces. The reason for using this contact gel was that the repair patch could be easily removed at room temperature and used for further measurements. For simulating delamination and measuring the current signals, the repair patch was removed and two layers of KAPTON(r) films were inserted in the designated positions of the repair patch (shown in Figure 4b). The repair patch was then put back to the original position as close as possible. To detect the surface-mounted artificial damage, a weighted blue-tack was placed in designated positions on the surface of the repair patch and bottom of the host structure as the current signals.  
Figure 3: The EMI results of (a) imaginary and (b) real part of admittance for different PZT transducers.  
For measuring guided waves, a National Instrument (NI) PXIe-1073 and an arbitrary signal generator (NI PXI-5412) were used for signal generation, and a digitizer (NI PXI-5105) was used to record UGW signals. During the measurements, the time-of-arrival (ToA) of the A\({}_{0}\) mode could not be distinguished at 50 kHz due to the overlap between the crosstalk and the first wave packet of each measured signal. Therefore, a five-cycle Hanning-windowed toneburst signal at 250 kHz [42] was used as the actuation signal. The actuation amplitude and sampling frequency were 6 V and 100 MHz, respectively. Both baseline and current signals were measured at room temperature.
# Computational Fluid Dynamics Applied to
## 2 Background
### Rotating Reference Frame and Multi-Reference Frame  
The rotating reference frame (RRF) approach, as the SM approach, uses a mesh whose topology is fixed in the space and in the time. In this approach there are two reference systems (through which the equations of the boundary conditions can be referred), i.e., one is an absolute reference system while the second is rotating. The conservation equations have to be transformed into a RRF relative to a component motion. With the angular velocity of the component \(\omega\), the new equations are Equations (11)-(13).  
\[\frac{\partial\rho}{\partial t}+\
abla(\rho u_{rel})=0 \tag{11}\]  
\[\frac{\partial(\rho u_{rel})}{\partial t}+\
abla(\rho u_{rel}u_{rel})=-\
abla p +\
abla\big{[}\mu\big{(}\
abla u_{rel}+\
abla u_{rel}^{T}\big{)}\big{]}+\rho g +F-2\rho\omega\times u_{rel}-\rho\omega(\omega\times\mathrm{r}) \tag{12}\]  
where:  
\[u_{abs}=u_{rel}+(\omega\times\mathrm{r}) \tag{13}\]  
As can be observed, two additional terms appear in the momentum equation (Equation (12)), representing the centrifugal force and the Coriolis force.  
Through RRF, it is possible to simulate rotating single components, such as a gear. For instance, in [23] the windage power loss from an enclosed spur gear was studied. In this study, the RRF was centered on the gear axis. In this way, the rotating gear is modelled as a no-slip wall fixed in the RRF. The outer boundaries (shroud wall or free air) are modelled in the absolute reference system. Similar studies have been conducted in [24; 25], where the mesh was refined in critical areas, or in [26], where the object of the study was a bevel gear. However, most of these studies focus on calculating windage losses rather than simulating the interaction with the lubricant. The study of the gear-oil interaction using the RRF approach can be found [27].  
A step forward to the RRF approach is the multi-reference frame (MRF) approach. The MRF works mainly like the RRF but allows the use of multiple reference systems with specific motions. An example of this application is described in [28]. In this work, the windage losses in a planetary gearbox are studied through a CFD analysis in which the boundary conditions are set exploiting the MRF approach, i.e., a reference system in the center of each planet and one in the center of the sun. The MRF approach was used in [29] for simulating the lubricant flow in a needle roller bearing. The MRF approach is exploited also in [30] for studying the oil-air flow in an angular ball bearing. In this kind of bearing, the rolling elements rotate with an axis tilted with respect to the axis of the shaft.
## 2 Data and Methods
### The Experimental Design  
To differentiate the impacts of climatic factors and LAI/FPAR on GPP/ET estimations, we design four experimental groups and take GPP as an example: (1) the original MODIS-GPP products; (2) using in-site meteorology data, MODIS-FPAR and maximum light use efficiency in MOD17 LOOKUP table to estimate GPP (GPP_MOD); (3) using in-site meteorology data, GLASS-FPAR (FPAR = 1 - (exp(-K*GLASS - LAI)) [16], K is set as 0.5 [27].) and maximum light use efficiency in MOD17 LOOKUP table to estimate GPP (GPP_GLA); (4) using in-site meteorology data, GLASS-FPAR and optimized maximum light use efficiency [28] to estimate GPP (GPP_GLA2).
###### Abstract  
The \(p\)-\(y\) curve method can be used to describe the stress-strain relationship of soil under elastic, elastoplastic, and plastic states, and is more accurate than other methods in dealing with the nonlinearity of pile-soil interaction. However, the \(p\)-\(y\) curve method also has several limitations. First, when constructing the \(p\)-\(y\) curve, undrained shear strength \(C_{u}\) is taken to be constant, and the diversity of soil layers around the pile side are also not considered. Second, in the analysis of the internal forces and deformation of the pile, the influence of the vertical load from the top of the pile and the self-weight of the pile, are both ignored. Third, in the analysis of internal forces and deformation, the pile side soil is set equivalent to a homogeneous soil layer, and the layering of the soil is not considered at all. In order to study the nonlinear problem of internal forces and deformation of a single pile in layered soil in greater detail, this paper analyzes a calculation model based on [PERSON]'s calculation model, and compares several commonly used \(p\)-\(y\) curve calculation models. An internal force and deformation analysis model for a laterally loaded single pile, that explicitly considers the second-order effect is then established, by considering the differences between \(p\)-\(y\) curves of different soil types, as well as the change in \(C_{u}\) with depth. The differential equation of pile deflection for a single pile in layered soil is also presented, together with the corresponding finite differential solution algorithm program. This model was validated using a horizontal load test of a pile, and comparison of the calculated results with the measured results shows that the method outperforms existing \(p\)-\(y\) curve methods for deformation and internal force analysis of horizontally loaded piles.  
\(p\)-\(y\) curve; layered soil; laterally loaded piles; internal force; deformation; second-order effect; undrained shear strength +
Footnote †: journal: Applied Sciences
## 5 Real Vehicle Experiments and Analysis of Results
### Collection of Private Datasets  
Before collecting private datasets, it is necessary to calibrate the intrinsic and extrinsic parameters of each sensor. The intrinsic parameters determines the accuracy of the sensor detection results, which can be obtained directly or determined by a simple algorithm. The extrinsic parameters describe the relative positional relationship between the sensor and other coordinate systems. As shown in Figure 5, the open source unmanned driving software Autoware is used to calibrate the extrinsic parameters between the LiDAR and the camera. The calibration tool developed by the Autonomous Driving Laboratory of the Swiss Federal Institute of Technology in Zurich [38] is used to obtain extrinsic parameters between the LiDAR and the IMU. Only when the accurate intrinsic and extrinsic parameters are obtained can the fusion and coordination between the various sensors be realized, and the ability of the entire system to perceive the environment be improved, which is very important for the follow-up work.  
Two groups of experimental datasets were collected to verify the performance of the system. The first group was an outdoor large-scale scene, as shown in Figure 6a, which collects a scene driving around a teaching building. It includes buildings, pedestrians, trees, and moving vehicles. The walking trajectory is shown as the green path in the bird's-eye view satellite map in Figure 6b. The second group was a dimly-lit long corridor environment inside a teaching building, as shown in Figure 6c, the geometric features on the white walls on both sides of the corridor are lacking and the scene repeatability is high,  
Figure 4: Electric tracked chassis data acquisition platform, which is arranged with 16-line LiDAR, ZED2i camera, IMU, and GNSS.  
Figure 5: Get extrinsic parameters between LiDAR and IMU using a checkerboard and calibration tool.  
which is in line with the degradation scenario. The experimental car was controlled to move in the above two scenarios and collect datasets.
## 4 Results
### Mediation Result  
To examine whether the effect of EO on FP through ITC is explained through the mediating effect, a bootstrapping approach was used, a resampling procedure that does not assume the normality of the sample distribution. Figure 2 shows that EO has a significant total effect on FP. When the mediator is added (see Figure 3), EO experiences a reduction in effect but still maintains a significant direct effect on FP.  
Figure 3: Model with two-step mediation design; **\(p<0.01\); ***\(p<0.001\).  
Figure 2: Model with total effect; ***\(p<0.001\).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Hypothesis** & **Path** & **Path Coefficient** & \(p\)**-Value** & **Result** \\ \hline H1 & EO \(\rightarrow\) FP & 0.426 & *** & Supported \\ \hline H2 & EO \(\rightarrow\) ITC & 0.592 & ** & Supported \\ \hline H3 & ITC \(\rightarrow\) FP & 0.271 & ** & Supported \\ \hline \hline \end{tabular}  
* \({}^{\text{st}}\)\(p<0.001\); ***\(p<0.001\).  
\end{table}
Table 8: Results of Hypothesis.  
The assessment of the mediation results according to the procedures suggested by [PERSON] et al. [66] indicates that the proposed mediator represents a partial mediation, specifically a complementary partial mediation. This validates Hypothesis 4, corroborating that a portion of the effect of EO on FP is mediated by ITC, while EO continues to explain a portion of FP that is independent.
# 1-Bit Reconfigurable Transmitarray Antenna with Out-of-Band RCS Reduction +
## 3 Element Design
### Low RCS 1-Bit RTA Element  
The element of the low RCS 1-bit RTA is constructed by integrating the AFST and 1-bit RTA according to the design concepts in Section 2, as shown in Figure 10. The AFST and RTA layers are separated by an air layer with a thickness \(h\) of 6 mm, which is the result of an optimization that balances the low- and high-frequency absorption performance. Meanwhile, the biasing lines of the RTA are given in Figure 10. For each receiver-transmitter structure, the middle portion of the active receiving dipole is grounded through the passive transmitter dipole, while a \(+2.5/-2.5\) V DC biasing voltage is applied to both ends of the active receiving dipole to control the pin diode states. The open-ended radial stubs on the receiving layer are designed to choke the RF leakage. The biasing point is positioned close to the zero point of the electric field to minimize the influence of the bias lines on the RF performance. The remaining parameters of the structure are listed as follows: \(L_{top}=12.2\) mm, \(W_{p}=2\) mm, \(L_{btm1}=6\) mm, and \(L_{btm2}=3\) mm. The diameter of the coupling metallic via-hole is \(D_{via}=0.4\) mm. Its position is 1.2 mm away from the center of the top dipole and located in the center of the bottom dipole.  
The element of the proposed low-RCS 1-bit RTA was simulated using HFSS simulation software, and the amplitudes and phases are illustrated in Figure 11. From Figure 11, it is found that the out-of-band reflection coefficient is less than \(-10\) dB, which indicates that the incident wave is effectively absorbed, whether it is \(x\)- or \(y\)-polarization. Therefore, the designed structure realizes wideband dual-polarization absorption. Additionally, it exhibits a good trans-polarized transmission performance and 1-bit phase reconfiguration around 7.5 GHz for \(y\)-polarization incidence. Consequently, the design is capable of suppressing out-of-band scattering and achieving in-band high-gain radiation and beam scanning performance.  
Figure 10: Element of the proposed low-RCS 1-bit RTA: (**a**) perspective view, (**b**) bottom view.  
Figure 9: Simulated current distribution of the RTA at 5.3 GHz (**a**) without and (**b**) with shorted via-hole, and (**c**) the simulated S parameters with shorted via-hole.
###### Abstract  
The voltage inverters have the high-frequency switching characteristic, which will generate massive high-frequency harmonics in the motors. Especially, the inductance of the high-speed permanent magnet synchronous motor (HPMSM) is designed to be small, and the high-frequency harmonic content will be higher than that of ordinary motors, which adversely affects the system. To overcome this problem, this paper proposed a harmonic suppression method based on the LC filter and the adaptive notch filter for HPMSMs. The LC filter is connected between the inverter and the HPMSM to filter out high-frequency harmonics, however, at the cost of the system resonance. Therefore, the adaptive notch filter with the frequency tracking capability is designed to offset specific resonant peaks by constructing an antiresonant peak. The least mean square adaptive algorithm automatically adjusts the filter parameters according to the variation of the input signal to ensure accurate filtering in complex cases. Simulation and experiment results prove the practicability and effectiveness of the proposed scheme. The harmonic contents of HPMSM are significantly reduced, and the dynamic response performance of the control system is improved.  
adaptive notch filter; current harmonic suppression; high-speed permanent magnet synchronous machine (HPMSM); LC filter; resonance
# Parameter Optimization Method for Metal Surface pBRDF Model Based on Improved Strawberry Algorithm
## 3 Improved Strawberry Optimization Algorithm
### Improved Algorithm  
Usually, there exist many microstructures with a certain random distribution pattern and many grooves on a metal surface after mechanical treatment. In order to accurately retrieve the parameters of the metal surface pBRDF model, it is necessary to make, as much as possible, the initial population more diverse and distribution more uniform and balance the global search and local search ability to avoid the algorithm falling into local optima. Therefore, Tent mapping and Levy flight were introduced into SBA.
# A Low Phase Noise Frequency Synthesizer with a Fourth-Order RLC Loop Filter
## 2 PLL Principle and Chip Introduction
### Introduction of Loop Filter  
Loop filters include the RC integral filter, the passive proportional-integral filter, and the active proportional-integral filter, as shown in Table 1. The RC integral filter is also known as the lagging filter due to its phase lag characteristics. Its output voltage is approximately proportional to the input voltage integral for sufficiently high frequencies, and the phase tends to be 90\({}^{\circ}\). This type of filter has rarely been utilized in the literature. The passive proportional-integral filter maintains a fixed proportional input-output voltage relationship in the high-frequency range, with the phase asymptotic to 0\({}^{\circ}\). When the phase increases, it exhibits the phase lead correction effect, improving the closed-loop stability. The proposed frequency synthesizer employs this type of filter. The active proportional-integral filter has the characteristics of a low-pass filter, and the same period phase frequency characteristics also have the role of lead correction. Generally, the higher the order of the loop filter, the better the phase performance [15].
## 3 Survey Results of the Use of Ornamental Flowering Plants in CWs
### Common Ornamental Plants Used in CWs
#### 3.1.1 Canna Spp  
This perennial herb belongs to the family Cannaceae (Figure 1a). It can grow in full sun or semi-shaded areas and in loamy soils, with plant heights varying from 0.75 to 3.0 m under tropical and subtropical conditions. It reportedly originated in Central and South America and spread throughout Europe, North America and many tropical regions of the world. The _Canna_ genus includes 8-10 wild species and over 1000 hybrids that are used as garden ornamentals. During the last two centuries of cultivation and improvement, _Canna_ has been transformed into an attractive OFP, with variability in flower colours (yellow, orange, red and salmon, achieved using colored stains) and other positive attributes [113; 114].  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & \multicolumn{6}{c}{**America**} \\ \cline{4-8}  & **Asia** & **Europe** & \multicolumn{2}{c}{**North America**} & \multicolumn{2}{c}{**Central and South America**} & \multicolumn{2}{c}{**Africa**} & \multicolumn{1}{c}{**Total**} \\ \cline{4-8}  & & **USA** & **Mexico** & \multicolumn{2}{c}{**America**} & & \\ \hline _Canna_ & 22 & 4 & 5 & 4 & 2 & 2 & 39 \\ \hline _Iris_ & 5 & 5 & 4 & 2 & 2 & & 18 \\ _Heliconia_ & 4 & & & 4 & 4 & & 12 \\ _Zantedeschia_ & & 2 & 1 & 13 & 3 & 1 & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Four most commonly genera plants used in CWs around the globe, identified during the 87 survey studies in 21 countries, grouped by continents.  
Figure 1: Popular Ornamental flowering plants used in CWs (constructed wetlands). (**a**) _Canna_ sp._;_;_ (**b**) _Iris_ sp., (**c**) _Heliconia_ sp. and (**d**) _Zantedeschia_ sp.
# A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations
## 6 Evaluation and Results
### Comparison to Previous Works
#### 6.3.2 \(k\)-Means Algorithm  
Regarding the algorithm implemented in [16], it is developed for a scenario where the UAVs assist an already existing terrestrial network. This strategy is defined by two stages, being the first one independent from the terrestrial network. This first stage, which is the \(k\)-means clustering algorithm, has been used here in order to compare this algorithm with the proposed positioning strategy. Again, this algorithm is developed for a set of users placed at discrete positions instead of a continuous spatial distribution of users. However, in this case, this algorithm cannot be adapted and, as a consequence, a discretization of the spatial distribution \(\lambda(x,y)\) has been carried out.  
Figure 5 bottom shows the placement of the UAVs using the \(k\)-means algorithm in the scenario described previously. In this case, as the convergence of the \(k\)-means depends on the initialization, different initializations are carried out and the solution with the lowest within-cluster sums of point-to-centroid distances is selected. The results are analyzed in the following subsection.