esa-sceva/satcom-chunk-collection huggingface dataset:
# Analytical Model to Calculate Radial Forces in Permanent-Magnet Synchronous Machines
## 4 Validation
### Analytical Results vs. FEM Results
#### 4.1.1 Magnetic Flux Densities  
First, flux densities calculated in different regions are shown in Figures 7-10. In Figure 7, the flux densities estimated in the air gap in open-circuit mode are shown for both machines. Meanwhile, in Figure 8, the same flux densities but in the load condition are plotted. It can be observed that the effect of the slots as considered by the analytical model was very similar to the effect computed by FEM.  
Figure 6: Surfaces on which magnetic pressures were analyzed: (**a**) base of a stator tooth; (**b**) outer surface of the rotor.  
In Figure 9, the armature flux density calculated in the rotor frame is plotted for the Qs48p8 machine. In Figure 9a, the spatial distribution of this variable is shown, while in Figure 9b, the spatial distribution of this variable is shown, while in Figure 9c, the spatial distribution of this variable is shown.  
Figure 8: The overall flux density in the air gap in load condition: (**a**) Qs48p8, (**b**) Qs36p15.  
Figure 10: Flux density created by stator coils on the rotor surface of the Qs24p10 machine: (**a**) temporal distribution, (**b**) spatial distribution.  
Figure 7: Flux density created by the magnets in the air gap in open-circuit condition: (**a**) Qs48p8, (**b**) Qs36p15.  
Figure 9: Flux density created by stator coils on the rotor surface of the Qs48p8 machine: (**a**) temporal distribution, (**b**) spatial distribution.  
Figure 9b, the temporal waveform at a point of the surface of the rotor over time is plotted. In Figure 10, the same results are shown for the Qs36p15 machine.  
In the fractional machine, there were fractional harmonics in the spectrum of the flux density in the rotor frame (Figure 11b), while in the spectrum of the flux density in the stator frame, there were only integer harmonics. In the case of the integer machine, both spectra of flux densities (in the rotor frame, Figure 11a, and in the stator frame) consisted of integer harmonics.  
According to the results obtained, it can be stated that the analytical model is able to compute flux densities in both a fixed stator frame and a rotor moving frame, with rather high accuracy. Considering that the model does not account for nonlinearities, the achieved accuracy can be considered very good.
## 2 Materials and Methods  
### System Description and Modeling  
A direct path exists for ultrasound to travel from the skin through the mastoid to the inner ear [22]. However, the temporal bone has characteristics that significantly attenuate ultrasound energy, resulting in energy loss as the ultrasound passes through the bone [23; 24]. To verify whether the ultrasound can stimulate the endolymph within SCC despite this attenuation, this study employed a simplified model consisting of the temporal bone and inner ear (particularly the endolymph and cupula).  
A simplified SCC model was used to simulate the ultrasound effect instead of a complete model that includes the horizontal, anterior, and posterior SCCs (Figure 1a). This simplified model allows for the easier observation of the fluid dynamics and cupula deformation within a single canal [25]. This approach is similar to those used in previous studies that investigated cupula deformation during the movement of the SCC [26; 27; 28; 29; 30]. As in those studies, we modeled the 3D structure, including the endolymph and cupula. Since the model is asymmetric, the 2D axisymmetric method could not be applied. To avoid excessive memory consumption, the simulation combined the finite element method (FEM) with the boundary element method (BEM) to calculate wave propagation. The model first calculates the acoustic field from the transducer using BEM. Then, the spherical region, which includes the SCC, is computed using FEM (Figure 1b). For visualization purposes, the FEM domain shown in the figure is halved.  
We assumed that the space between the ultrasound transducer and the temporal bone was filled with degassed water to ensure effective ultrasound propagation. The transducer in the model has a focal length slightly longer than the ear canal (42 mm) and a diameter of 54.4 mm. This transducer, emitting continuous ultrasound waves along the positive z direction with its aperture parallel to the xy-plane (z = 0), is a modified version of the one used in [PERSON] et al., with the focal length adjusted to 42 mm [31; 32]. The carrier frequencies of the transducer were chosen to be 400, 600, and 800 kHz, as commonly used in transcranial LIFU [33; 34; 35]. The arrangement of the transducer and the SCC was designed under the assumption that the ultrasound is emitted from the direction of the person's left ear.  
The 3D geometry of the SCC was generated using the MATLAB r2024b curve-fitting tool and COMSOL Multiphysics 6.1. MATLAB r2024b was used to convert the inner and outer diameter data of the horizontal SCC, obtained from reference [36], into a mathematical function. COMSOL Multiphysics 6.1 was then used to create the SCC model and a cylindrical cupula structure with a thickness of 403 \(\upmu\)m [28; 37; 38]. To ensure the fidelity and precision of the model, the mesh was iteratively refined, and the final model consisted of 1068,280 tetrahedral elements, ranging in size from 20 to 232 \(\upmu\)m.
# Novel Real-Time Acoustic Power Estimation for Dynamic Thermoacoustic Control
## 2 Materials and Methods
### Average Power Estimation  
The RC load method has been widely adopted as a reliable approach for measuring acoustic power in thermoacoustic systems [17]. This method utilizes the phasor representation of the volumetric flow rate across the resistance, derived from the pressure oscillations within the compliance, \(C\), assuming the short duct length approximation:  
\[U=j\omega CP_{C}=j\omega\frac{V}{\gamma P_{m}}\ P_{C}, \tag{8}\]  
where \(U\) represents the volumetric flow rate, \(P_{C}\) the pressure measured at the compliance and V, \(P_{m}\), and \(\gamma\) correspond to the compliance volume, mean pressure, and specific heat ratio, respectively [1].  
Using this relationship, the dissipated acoustic power at the resistance is determined by analysing the two key pressure signals, \(P_{C}\) and \(P_{E}\), in terms of their amplitude, phase, and angular frequency:  
\[\dot{E}_{load}=\frac{1}{2}\frac{\omega V}{\gamma P_{m}}Im\left(P_{E}\bar{P}_{ C}\right)=\frac{1}{2}\frac{\omega V}{\gamma P_{m}}|P_{E}||P_{C}|sin\theta_{EC}, \tag{9}\]  
where \(\theta_{EC}\) is the phase angle between the \(P_{C}\) and \(P_{E}\) pressure signals. The short duct length approximation allows this method to be consistently expressed in terms of the compliance of geometric and thermodynamic parameters [33].  
The RC load method determines the dissipated acoustic power as the time-averaged product of the volumetric flow rate through the valve and the pressures \(P_{C}\) and \(P_{E}\) across it [30].
###### Abstract  
The rise of CubeSats has unlocked opportunities for cutting-edge space missions with reduced costs and accelerated development timelines. CubeSats necessitate a high-gain antenna that can fit within a tightly confined space. This paper is primarily concerned with designing a compact Ku-band offset cylindrical reflector antenna for a CubeSat-based Earth Observation mission, with the goal of monitoring Arctic snow and sea ice. The development of a Ku-band offset cylindrical reflector, with a compact aperture of 110 \(\times\) 149 mm\({}^{2}\) (6.33 \(\times\) 8.5\(\lambda\)), is described alongside a patch array feed consisting of 2 \(\times\) 8 elements. The patch array feed is designed using a lightweight Rogers substrate and is utilized to test the reflector. Adopting an offset configuration helped prevent gain loss due to feed blockage. Analyzing the reflector antenna, including the feed, thorough simulations and measurements indicates that achieving a gain of 25 dBi and an aperture efficiency of 52% at 17.2 GHz is attainable. The reflector's cylindrical shape and compact size facilitate the design of a simple mechanism for reflector deployment, enabling the antenna to be stored within 1U. The array feed and reflector antenna have been fabricated and tested, demonstrating good consistency between the simulation and measurement outcomes.  
CubeSats; cylindrical reflector; high-gain antenna; low-Earth orbit; microstrip patch antenna +
Footnote †: journal: Accepted: 24 November 2024
# Metalens Antenna Based on an Ultrathin Dual-Polarized Double-Layer Huygens' Metasurface
###### Abstract  
This work proposes an ultrathin dual-polarized double-layer Huygens' meta-atom, capable of generating Huygens' resonance and achieving nearly 360\({}^{\circ}\) phase coverage and high transmission simultaneously. Two metalenses are designed based on the proposed meta-atom. The first is a dual-polarized metalens antenna with excellent directional radiation performance, achieving a peak gain of 30.4 dBi, an aperture efficiency of 47.8%, and a 3 dB bandwidth of 8.4% at 25 GHz. The second is a two-channel focusing metalens, with focusing efficiencies of 52.4% for \(x\)-polarization and 48.6% for \(y\)-polarization. The proposed meta-atom exhibits excellent transmission performance and offers a more flexible approach for designing transmissive devices, demonstrating significant application potential in the field of microwave communications, wireless power transfer, and imaging.  
Keywords:Huygens' metasurface; metalens antenna; dual-polarization; multifunctional; high-gain +
Footnote †: journal: Applied sciences
# Regional Analysis of Dust Day Duration in Central Iran
## 3 Results
### Parameters Affecting Dust Day Duration  
In order to investigate the most important parameter affecting the durability of dust, 8 different properties were used. These spatial characteristics of the stations included longitude, latitude, elevation, average daily temperature (tm), dew point (td), wind altitude (u), maximum wind speed (ff max), and direction of the fastest wind (dd max). As expected, each of the features used has a different importance in the k-NN classification, which is shown in Figure 16. ffmax (maximum wind speed) was by far the most important  
Figure 14: Dust day duration in the 25-year return period in the study area.  
Figure 15: Dust day duration in the 50-year return period in the study area.  
parameter associated with spatial variability in DDD, consistent with the key role of wind in lofting and transporting dust.
## 5 Evaluation of Material Factors and Performance Indicators by One-Way Standard Deviation and GRA
### GRA-Based Evaluation of Impact Factors
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Groups**} & **Initial** & **Final Setting** & **Flowability** & **Bleeding** & **Compressive** & **Weighted** & **Normalized** \\  & **Setting Time** & **Time** & **Rate** & **Strength** & **Total Score** & **Weighted Score** \\ \hline
8 & 0.045 & 0.000 & 0.788 & 0.882 & 0.925 & 0.533 & 0.107 \\
9 & 1.116 & 0.645 & 1.112 & 1.078 & 0.960 & 0.982 & 0.196 \\
10 & 2.455 & 1.383 & 1.240 & 1.471 & 1.017 & 1.507 & 0.301 \\
12 & 1.071 & 1.916 & 0.939 & 0.833 & 1.001 & 1.150 & 0.230 \\
13 & 0.313 & 1.056 & 0.921 & 0.735 & 1.097 & 0.828 & 0.166 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Normalized weighted total scores for grouting materials. The priority given to compressive strength over the other factors is due to the primary objective of grouting being the enhancement of the load-bearing capacity of silty mudstone slopes. When the compressive strength is inadequate, the slopes may fail under loading even if the other parameters meet the requirements. The final setting time needs to be reasonably controlled to avoid slurry loss, but a slightly longer period of time is acceptable to meet the construction schedule and to achieve the required strength. Flowability determines whether the slurry can be injected smoothly, but focusing on it alone and ignoring strength is not effective for reinforcement. Similarly, the bleeding rate and initial setting time have an effect, but to a lesser extent than the strength when the basic properties and construction operations are ensured. Considering the relative importance of these factors, the weight of each performance indicator in determining the grouting effectiveness was comprehensively assessed. The optimum ratio was determined using the indicator weights from Group 10, with a zeolite powder:GGBFS:CL:NaOH ratio of 30:70:5:7 and a water-binder ratio of 0.6.
# Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage
## 5 Experiment and Results
### Experiments
Positional diversity was calculated with the implemented algorithms based on [52]:  
\[\text{Diversity}=\frac{1}{NP}\sum_{i=1}^{N}\sqrt{\sum_{d=1}^{D}(x_{i}^{d}-\bar{x}^ {d})^{2}} \tag{19}\]  
\[\bar{x}^{d}=\frac{1}{N}\sum_{i=1}^{N}x_{i}^{d} \tag{20}\]  
where N is the number of search agents (flies, chromosomes or particles), D is the dimensionality of the problem, \(x_{i}^{d}\) is the value at dimension \(d\) for agent \(i\) and \(\bar{x}^{d}\) is the average value of dimension \(d\) for all search agents. The diversity vs FE graph in Figure 3a is in line with similar experiments conducted in [48]. In this implementation of DA-RAN, PSO and DE decrease in diversity as function evaluation increases, while DFO diversity stays relatively higher owing to its disturbance threshold that enables the flies/search agents to be re-initialized to the search space. The lack of such a technique in PSO and DE can create a problem where low diversity can cause lower exploration in certain scenarios leading to the algorithms being stuck on a particular solution and no exploration of other potential solutions in the search space as depicted in Figure 4a. Since diversity changes with changes in the environment and path loss threshold, the results could be more skewed towards DFO implementation. To solve this problem, a phased restart strategy has been introduced to re-initialize the search agents in the search space after each FE segment to promote exploration and reduce the probability of the search agents being stuck on the local minima. Figure 2: Coverage probability for all environments with default parameters. Plotting the diversity again using the phased restart strategy in Figures 3b and 4b shows that the diversities of all algorithms are comparable throughout the process, only becoming low at the end of each segment where the probable best solution has been found. It is to be noted that DFO inherently does not require a phased restart, but it has been implemented in DFO as well to make sure that all the algorithms are on par with each other. To further optimize the effectiveness of the algorithms, meta-meta-heuristic parameter tuning has been conducted on all the environments for all path loss thresholds to gather the best suitable parameter for each combination of environments.
## 3 Measurement and Discussion  
The antenna model is fabricated and tested to verify the actual performance of the designed antenna. The processed object is shown in Figure 13, a vector network analyzer measures the VSWR of the antenna, and the far-field pattern of the antenna is measured in an anechoic chamber. Figure 14 shows the simulated and measured VSWR and S11 of the designed antenna. The green line is the data obtained from the antenna simulation using HFSS, the blue line is the data obtained from the antenna equivalent circuit model simulation using ADS, and the red line is the measured data. It can be observed that the center frequency of the notch in the actual measurement has a certain frequency offset, which may be caused by the tolerance generated during manufacture and the welding of the antenna connector. The measurement shows that the antenna can achieve frequency coverage of 2.9-11 GHz and produce four band rejections of 3.38-3.75 GHz, 5.01-5.25 GHz, 5.63-5.86 GHz, and 7.45-7.82 GHz. Figure 15 shows the antenna patterns in the three frequency bands of 6 GHz, 8 GHz, and 10 GHz, respectively. In these frequency bands, the radiation pattern of the X-Z plane antenna is almost omnidirectional. A dipole-like radiation pattern can be observed on the Y-Z plane, but the antenna pattern is not entirely symmetrical. The unsymmetrical pattern is because the two interdigital inductance slots etched at the ground are not identical, making the antenna itself asymmetrical. Figure 14: Simulated and measured of the proposed antenna. (**a**) VSWR. (**b**) S11. Figure 13: Photos of the antenna prototype. (**a**) The front of the antenna. (**b**) The back of the antenna. Figure 15: Simulated and measured radiation patterns. X-Z Plane (**left**) and Y-Z Plane (**right**). (**a**) 6 GHz, (**b**) 8 GHz, and (**c**) 10 GHz. In addition, the gain of the antenna is given in Figure 16. The antenna's gain decreases rapidly in the notch band frequency, reaching minimum points at 3.5 GHz, 5.1 GHz, 5.7 GHz, and 7.63 GHz, respectively. Furthermore, the antenna's maximum gain reaches more than 4 dBi, which proves that the antenna realizes the quadruple band stops. Finally, it can be seen from Table 2 that the deviation of the filtering frequency of the antenna used in this paper can be controlled by 3%. The bandwidth of narrow band-stops can be controlled at 0.24 and 0.23 GHz, and the available frequency band 5.25-5.63 GHz is reserved. The antenna shows good performance in both frequency errors and bandwidth errors.
## 3 Numerical Simulations
### Orbit Determination Refinement
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \(\varepsilon_{p,OD}^{\$0\%$}\) & \(\sigma_{p,OD}^{\$50\%$}\) & \(\varepsilon_{v,OD}^{\$50\%$}\) & \(\sigma_{v,OD}^{\$50\%$}\) & \(\varepsilon_{p,free}^{\$0\%$}\) & \(\sigma_{p,free}^{\$50\%$}\) & \(\varepsilon_{v,free}^{\$50\%$}\) & \(\sigma_{v,free}^{\$50\%$}\)refinement (black line), with Doppler-only UKF (green), and range-Doppler measurements (blue) for object NORAD ID 00730. Squares and triangles represent the errors at the beginning and at the end of each UKF process, respectively. As can be seen, while the accuracy of the state estimate at the end of the first UKF is similar for Doppler-only and range-Doppler OD refinement, the evolution in time is very different: the Doppler-only estimate accuracy rapidly decreases, and after the second UKF the results become unreliable. With range-Doppler measurements, instead, the error remains limited and below what can be obtained without performing OD refinement, and the average accuracy increases as the number of processed passages increases. Table 4 shows the same comparison shown in Table 3. In this case, range-Doppler measurements are considered. As can be seen, now the use of the UKF allows us to reduce the errors in position and velocity of a factor 3 and obtain an overall reduction of the size of the covariance of around one order of magnitude. These results provide a general overview of the possible performance of BIRALET sensor for space objects tracking: Doppler shift measurements alone cannot grant accurate results for the OD refinement process, the OD improvement obtained with the UKF is rapidly lost as the error evolves in time, i.e., the growth of the error is larger than what would be obtained without OD refinement. Conversely, the combined use of Doppler shift and slant range measurements guarantees a significant improvement.
# Travel Time Prediction on Long-Distance Road Segments in Thailand
## 3 Materials and Methods
### Experiments
#### 3.4.1. Experiment: Choosing a Suitable Baseline  
This experiment was conducted to compare four techniques from related works to determine our baseline. These techniques were ARIMA [7], SVR [25], LSTM [26], and ConvLSTM [14]. The tuned hyperparameters of these techniques were as follows:  
* ARIMA: \(p\), \(q\), and \(d\) were based on observations of the data of each road, such as the settings of the highway number 1 being \(p=7\), \(q=0\), and \(d=12\).
* SVR: sliding window size = 24, kernel = RBF (Radial Basis Function), C (for L2 Regularization) = 1, epsilon = 0.1, gamma = 0.1.
* LSTM: input of LSTM units = 24, number of LSTM layers = 1, hidden LSTM size = 256, and dropout = 0.25.
* ConvLSTM: The setting of the ConvLSTM was reused from the LSTM. Additionally, the settings of the convolutional layer were 3 convolutional layers with size = 32, kernel size = 2, and max pooling size = 2.  
The results of this experiment are shown in Section 4.1. It shows that the LSTM provides the best performance among the models from the related studies, so the LSTM model was chosen as the baseline. In the subsequent experiments, improvements to and comparisons against the LSTM were performed.
# Moving Surface Boundary-Layer Control on the Wake of Flow around a Square Cylinder
## 3 Results and Discussion
### Analysis of Influence of \(D/L\) and \(h/D\) Parameters
Figure 7: Statistical values of lift and drag coefficients, Strouhal number, and control effects under different \(h/D\) values, (**a**) Statistical values of \(C_{l},\ C_{d}\), and \(S_{t}\), (**b**) Control effects of \(C_{l},\ C_{d}\). Through comparative analysis, we can see that the smaller the spacing (\(h\)) between the rotating circular cylinders and the square cylinder, the better the control effect of the MSBC method on the wake of the square cylinder. As the spacing ratio \(h/D\) decreases from \(3/8\) to \(1/8\), the results of \(E_{C_{l}}\) and \(E_{C_{d}}\) are increased by \(9.38\%\) and \(13.35\%\), respectively, which are less than the increasing extents of \(E_{C_{l}}\) and \(E_{C_{d}}\) with increase of \(D/L\) and are especially far less than the increasing extent of \(73.99\%\) for \(E_{C_{l}}\), as shown in Table 2. It can be seen that the influence of the diameter of the rotating circular cylinders on the control effect of the wake of the square cylinder is greater than the influence of the variation of the spacing between the rotating circular cylinders and the square cylinder on the control effect. Compared with the control effects of \(D/L=0.3\) and \(h/D=1/4\), when \(D/L\) continues to increase from \(0.3\) to \(0.4\), the improvements of the control effects \(E_{C_{l}}\) and \(E_{C_{d}}\) of the controlled square cylinder are not obvious, only increased by \(2.19\%\) and \(0.84\%\). As the \(h/D\) is decreased from \(1/4\) to \(1/8\) continually, the \(E_{C_{l}}\) is only increased from \(97.25\%\) to \(99.73\%\), and the \(E_{C_{d}}\) is only increased by \(7.22\%\) at the same time. On the contrary, the fluctuation of the drag coefficient \(C_{d,c}\prime\) is increased from \(6.3\%\) to its maximum of \(26\%\) of \(C_{d}\prime\) for the uncontrolled standard square cylinder. From the above analysis, it can be concluded that \(D/L=0.3\) and \(h/D=1/4\) are the better combination of the parameters to achieve a better control effect on the wake of flow around the square cylinder.