esa-sceva/satcom-chunk-collection huggingface dataset:
# Transient Response of Dynamic Stress Concentration around a Circular Opening: Incident SH Wave
## 6 Conclusions  
This study investigates the transient response of stress fields in circular apertures. The innovation of this paper is that a multi-frequency SH wave incident simulation method is proposed to simulate the impact scene, and the transient response of the circular opening stress field is investigated by simplifying the technique and using Fourier transform. Remarkably, considering the causal nature of both the wave field and the response, a rectangular function represents the temporal delay. This method can play an important role in seismic design, mineral exploration, nondestructive testing, blasting, and the application and progress of advanced composite materials.  
Considering the complexity of the DSCC expression, a theoretical calculation is performed using the wave function expansion method. The superposition of Bessel and Hankel functions represents displacement and stress. The undetermined coefficients can be determined by applying the boundary conditions associated with the circular aperture.  
Figure 10: Spatial and temporal distribution of stress peak coefficient with \(r=1\).  
Figure 9: The nephogram of DSCC overtime at the opening edge with the range (0, \(\pi\)).  
This strategy provides a solution for addressing similar challenges. The method presented in this paper is suitable for large boundary materials with circular openings. Materials with complex defects and boundaries need further investigation.  
More details can be obtained from numerical results:  
1. The radii of the circular opening significantly impact the DSCC. It is crucial to consider the dynamic stress concentration at the opening when designing structures or assessing the strength of materials.
2. The stress peak coefficient is primarily concentrated in the initial transient response in the light region. Therefore, when designing materials with openings in a multi-vibration environment, it is essential to consider and account for the maximum impact during the transient response.
3. As the radii of the circular opening increase, the sidelobe of the DSCC appears earlier. This means that the opening is subjected to alternating stress at an earlier stage, which can lead to fatigue damage. It is essential to consider the effects of alternating stress and fatigue when designing structures with larger circular openings.  
Conceptualization, Z.W. and C.Z.; methodology, J.W.; validation, R.L., R.Z. and Y.G.; formal analysis, W.P.; investigation, J.W. and R.L.; data curation, W.P.; writing--original draft preparation, J.W.; writing--review and editing, Z.W.; supervision, Y.G.; project administration, C.Z.; funding acquisition, R.L. and R.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Sichuan Science and Technology Program (No. 2022 YFG0274), National Natural Science Foundation of China (Grant No. 51875146).  
Not applicable.  
The authors confirm that the data supporting the findings of this study are available within the article.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Data Processing and Quantitative Models  
The spectral data often contain unexpected noise and exhibit systematic variations on the baseline due to the physical properties of the samples and other environmental noises. If the raw hyperspectral data are directly used to build the model, it might obtain low data modeling efficiency and poor model performance. The preprocessing of spectral datasets is necessary to remove non-chemical biases, such as scattering effects, due to the inhomogeneity of the surface, interference from external light sources, or random noise. Scattering correction can reduce the spectrum caused by the uneven distribution of sample particle size differences. Generally, common scattering correction includes multiplicative scatter correction (MSC), standard normal variate transformation (SNV), and smoothing. Meanwhile, the derivative algorithm can eliminate baseline drift and improve the resolution of overlapping peaks.  
Extending the PLS model by introducing a nonlinear kernel is an approach to solving nonlinear problems. KPLS regression is a mapped spectral input matrix to a high-dimensional feature space by a nonlinear function; the major advantage of the KPLS method is that it does not need nonlinear optimization by substitution of the inner product of the feature space with a kernel function, which was used to build calibration models [33; 34; 35]. Leave-one-out cross-validation (LOOCV) was employed to evaluate the established calibration models. The performance of the calibration models was also evaluated according to the root mean square error of calibration (RMSEC), the root mean square error of cross-validation (RMSECV), and the correlation coefficient (Rc).
## 6 Conclusions  
This work presents an improved version of the FA which happened to outperform the original version in terms of the GMPP tracking performance. Moreover, a high-voltage step-up converter was designed to raise an input voltage of 80 V to an output voltage of 400 V. This was done simply because the converter worked at a relatively low duty cycle, and the conversion efficiency was raised accordingly. Unlike in the original version of the FA, the step size was made adaptive to the slope of a P-V curve and the number of iterations. As a consequence, once having gotten trapped in a LMPP, the presented MPP tracker can easily escape from the trap and then succeed in tracking down the GMPP expeditiously as intended. The performance of the proposed MPP tracker was tested in five scenarios, and it has, accordingly, been validated as robust against various shading conditions. Subsequently, the TMS320F2809 digital signal processor (DSP) produced by Texas Instruments will be used as the control core for implementation in the future to ensure the effectiveness and robustness of the proposed method.  
[PERSON] planned, wrote, edited and reviewed the project. [PERSON] was responsible for using the Matlab software to simulate photovoltaic module arrays for maximum power point tracking and the PSIM software to simulate the high-voltage step-up converter. [PERSON] managed the project. All authors have read and agreed to the published version of the manuscript.  
The authors gratefully acknowledge the support and funding of this project by the Ministry of Science and Technology, Taiwan, under the Grant Number MOST 110-2221-E-167-067-MY2.  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{
\begin{tabular}{c} **No. of Peaks on** \\ **Respective P-V Curve** \\ \end{tabular} } & \multicolumn{4}{c}{**Tracking Efficiency (\%)**} \\ \cline{3-5}  & & **Conventional** & **Conventional** & **Improved FA** \\ \hline
1 & Single & 78.83\% & 98.32\% & 99.29\% \\ \hline \multirow{3}{*}{2} & Double & & & \\  & (MPP was on the right peak) & 79.25\% & 98.73\% & 99.09\% \\ \hline \multirow{3}{*}{3} & Triple & & & \\  & (MPP was on the rightmost peak) & 67.88\% & 93.23\% & 98.01\% \\ \hline \multirow{3}{*}{4} & Quadrup & & & \\  & (MPP was on the rightmost peak) & 42.48\% & 82.96\% & 96.74\% \\ \hline \multirow{3}{*}{5} & Quadrup & & & \\  & (MPP was on the leftmost peak) & 77.99\% & 76.1\% & 89.76\% \\ \hline \hline \end{tabular}
\end{table}
Table 9: A tracking efficiency comparison of the five scenarios.
## 6 Conclusions  
In this paper, we investigate the joint offloading location decision and bandwidth allocation problem in satellite-terrestrial edge computing networks. Given the potential privacy compromise caused by task offloading, we ask terminals to send random dummy tasks to protect their usage pattern privacy. Then, the DRTO algorithm is proposed to minimize the offloading cost based on current observed channel states. The simulation results show that our DRTO algorithm achieves near-optimal offloading cost performance like existing algorithms but significantly reduces runtime consumption, and the privacy protection scheme is sufficiently effective with a tolerable cost.  
Particularly, our privacy protection scheme is simple enough; thus, it can be applied to various terminals. Despite this, dummy tasks inevitably cause undesirable resource waste. In the future, we will further explore advanced coding techniques that encode dummy tasks to compensating packets, which can cope with fast-fading links in satellite-terrestrial networks and the resource consumption associated with privacy protection.  
Conceptualization, J.Z. and Z.Y.; Formal analysis, Z.X.; Investigation, J.S.; Methodology, P.X.; Resources, Y.L.; Validation, Z.G. and J.F.; Writing--original draft, S.Z.; Writing--review and editing, S.Z. All authors have read and agreed to the published version of the manuscript.  
The work in the paper is sponsored by science and technology project of state grid corporation of China: Research on critical technology of secondary system planning and design of distribution network for novel power system (No. 5400-202256273A-2-0-XG).  
Figure 11: Average energy consumption evaluation at different redundancy rates \(\omega\).  
Figure 12: Average latency consumption evaluation at different redundancy rates \(\omega\).
# Laboratory Testing and Analysis of Clay Soil Stabilization Using Waste Marble Powder
## 3 Results and Discussion  
### The Physical Behavior of Stabilized and Unstabilized Soils  
#### 3.1.1 Specific Gravity  
In Figure 5, we observe how variations in soil clay content can be used as a proxy for the physical behavior of soils amended with varying amounts of marble powder. When the percentage of marble powder added to the clay soil increases to 45% (X4), the specific gravity increases from 2.73 to 2.83. However, when the percentage of marble powder is increased beyond 45%, there is no difference. The results of this study are consistent with those of Ref. [38]. The initial increase in specific gravity results from the increased density of the soil melange caused by the addition of marble powder. Marble powder is denser than clay soil, and when combined with soil, it fills voids and reduces the amount of air in the soil. As such, it causes an increase in the overall density of the soil, increasing its specific gravity [39]. Nevertheless, the specific gravity remains unchanged after the addition of a certain percentage of marble powder. This phenomenon is due to the saturation limit of the  
Figure 4: The flowchart mechanism of the neural network.  
soil, beyond which the addition of marble powder has no appreciable effect on the specific gravity [40].
## 6 Python Implementation and Usage
### Code Usage  
Upon executing the code, ABAQUS(r) will create a series of prompt dialogue boxes. This allows the user to select the model database file (.cae), structural part, material, problem  
Figure 1: Sequence of operations performed by the topology optimization code implemented in this manuscript.  
statement, optimization algorithm, and internal parameters to be considered during the topology optimization.  
Besides being fully functional, the ABAQUS(r) model does not require any specific formatting, except for the following considerations:  
* Within the same part, the user can define specific elements to be optimized, dividing the part into two regions: one with editable elements and another with elements that should not be included in the optimization process (i.e., passive elements, from this point onward referred to as \"frozen region\" or \"frozen elements\"). To do so, the user should create a set named \"editable_elements\", containing the elements to be edited. If this set does not exist, the whole part will be optimized. Note that the name \"editable_elements\" is case sensitive. This is performed in order to promote the optimization only of the targeted area and also to reduce the computational cost.
* The region to be optimized should not have a material section assigned to it, as the code will automatically assign the material properties and sections directly to the elements. Therefore, if the user defined a set with the editable elements, only the elements not included (frozen elements) should have a material section assigned to them.
* It is possible to allow the frozen elements to be considered during the filtering operations. To do so, the user should create a second element set with the case-sensitive name \"neighbouring_region\".
* If multiple copies of the part to be optimized are included in the model assembly, only the first copy will be optimized.
# AI-Driven Pilot Overhead Reduction in 5G mmWaveMassive MIMO Systems
## 2 System Model  
### Hybrid Beamforming and Pilot Placement  
#### 2.1.1 Hybrid Beamforming System  
Hybrid beamforming (HB) can be categorized according to parameters such as required CSI within the analog beamforming segment, carrier frequency, and complexity. The optimal design or algorithm for a specific application strikes a delicate balance between these factors.  
Figure 1 illustrates the transmitter/receiver architecture for the hybrid beamforming system in the m-MIMO setup. The structure includes RF chains connected to the antenna array through constant modulus phase shifters. On the transmitter side, various operations are performed on the digital baseband signal to prepare it for transmission.  
These operations include modulation, encoding, multiplexing, and pilot placement, which are critical for efficient communication. The RF chains enable the hybrid beamforming process, combining analog and digital techniques to optimize performance while reducing hardware complexity.  
In the proposed system, the signal received at a mobile station MS in a hybrid beamforming mmWave system is expressed as follows [14]:  
\[y_{u_{m}}=(w^{u_{m}}_{rf})\ \times\ \{(H_{u_{m}}F_{rf}F_{bb}S)+n_{u_{m}}\} \tag{1}\]  
where \(u_{m}\) is the MS (the user) being served by the station, \(y_{u_{m}}\) is the received signal at the MS \(u_{m}\), \(w^{u_{m}}_{rf}\) is the RF combiner for the \(u_{m}\) MS, \(H_{u_{m}}\) is the channel between the BS and MS \(u_{m}\), \(n_{u_{m}}\) is the noise component, and \(F_{bb}\) and \(F_{rf}\) are the digital and analog pre-coding weights. On the other hand, the received signal of the \(jth\) user can be given as follows [2]:  
\[Y_{k}=\sum_{k=1}^{j}B_{k}^{H}H_{k}F_{rf}F_{bb_{k}}s_{k}+B_{k}^{H}n_{k} \tag{2}\]  
where \(B_{k}^{H}\) is the linear receiver beamforming vectors used to detect the transmitted signal. Additionally, \(N_{RF}^{T}\) represents the number of RF chains at the transmitter, \(N_{RF}^{R}\) represents the number of RF chains at the receiver, and \(W_{BB}\) represents the baseband combining matrix. These components collaboratively contribute to achieving efficient channel estimation and hybrid beamforming, which are integral to the proposed system's superior performance.  
The challenge with HB rises with the need of estimating the channel conditions between the transmitter and receiver. Channel estimation is crucial for adaptive modulation and coding techniques, which dynamically adjust the data rate and error correction based on the current channel state to optimize system performance. To achieve accurate channel estimation, effective pilot placement techniques are essential. This concept is discussed in the next paragraph.
## 2 Background
### Conceptual Framework for Air-to-Air Refueling
Either the tanker aircraft programs the desired amount of fuel to transfer or the receiver pilot monitors the fuel quantity to determine the desired amount has been transferred. Once complete with the transfer of fuel, the receiver will begin separation by decreasing the energy state of the receiver to increase the distance between the tanker and receiver. As the receiver begins increasing the range from the tanker, the hose will begin to unreel to increase the length available until the hose reaches the maximum length attainable. Upon reaching the maximum length of the hose, the probe tip will disengage from the coupler and the receiver aircraft begins to transition to right echelon to either hold until the wingmen are complete or complete final administrative procedures prior to transitioning to the next phase of the mission (Figure 7). Aerial refueling requires experienced pilots to identify objects in free space, such as the drogue, probe tip, and coupler, prior to maneuvering the receiver aircraft into close proximity of the tanker aircraft to complete an engagement of an object approximately 3 to 4 inches in diameter into a coupler of slight larger proportions. This challenging task can only be completed by adapting the inputs that are dependent on a multitude of environmental factors. While not impossible to automate, a UA capable of A3R would require multiple sensors to provide information to the UA. As of the date of this publication, only demonstrations of this capability have been accomplished.
## 5 Discussion
### Initial Damage Threshold Value of Different Strain Rates  
The damage threshold of a non-destructive rock is the minimum damage variable when macroform cracks appear in the rock. Figure 14 shows the analysis of the relationship between the damage variables and compressive strength. It can be seen from Figure 14 that:  
1. The peak compressive strength remains stable when the initial damage is minor. When the initial damage value reaches a particular value, the corresponding compressive strength begins to decrease dramatically, and the initial damage value reaches an inflection point, which is the initial damage threshold value, as shown by a red dotted line. The initial damage threshold values of the two loading strain rates (\(\bar{\varepsilon}=100\) s\({}^{-1}\), \(2\times 10^{-4}\) s\({}^{-1}\)) are \(D^{1}_{thr}\) and \(D^{2}_{thr}\), and the values of \(D^{1}_{thr}\) and \(D^{2}_{thr}\) are 0.2 and 0.18, respectively.
2. When the damage variable meets \(0<D<D_{\rm thr}\), the microcracks of the limestone expand stably, and the stress-strain curve is OB, which is shown in Figure 8. Furthermore, the compression peak stress point C is entered as the loading stress level increases. Moreover, when \(D>D_{\rm thr}\), the damage deterioration of the rock enters the macroscopic crack formation stage, which belongs to an unstable damage development stage.  
In conclusion, when \(D<D_{\rm thr}\), the microcracks inside the rock determine the degree of initial damage, and its compressive strength is almost unchanged. However, for \(D>D_{\rm thr}\)  
Figure 14: Plot of the damage threshold versus the initial damage curves for limestone from \(2\times 10^{-4}\), \(100\) s\({}^{-1}\) levels of strain rate.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **No** & \(R_{\rm c}\) **(mpa)** & \(\varepsilon\) \\ \hline \multirow{4}{*}{\(D_{\rm V}\)} & 0.043 & 130.56 & 0.0043 \\  & 0.357 & 106.37 & 0.0045 \\  & 0.625 & 95.51 & 0.0052 \\  & 0.754 & 81.23 & 0.0064 \\  & 0.044 & 127.43 & 0.0042 \\  & 0.361 & 97.69 & 0.0044 \\  & 0.628 & 94.89 & 0.0051 \\  & 0.759 & 82.56 & 0.0061 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Compressive strength and destructive strain of \(D_{\rm E}\) and \(D_{\rm V}\).  
the macroscopic form crack determines the initial degree of damage of the rock; thus, decreasing the extent of the rock's compressive strength and the initial degree of damage increases. Hence, the rock's main stage of damage deterioration is the unstable expansion stage of the macroform cracks.
## 4 Simulation
### Performance Evaluation of Experiment 1  
In this experiment, three radar emitters with the same working mode and the same modulation type are selected for validating the recognition capability of the SMR feature; the working mode is PRI staggering, the modulation type is CW, and the three radar emitters are placed in three directions close to each other. Signal parameters are shown in Table 4.  
If the typical five parameters and the intrapulse feature are utilized for emitter identification, it is easily misjudged that these pulses are from the same radar emitter. When SMR is combined with the existing five parameters for recognition, the accuracy of REID using SMR in different SNRs is shown in Figure 8.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Emitter** & **PA** & **CF(MHz)** & **AOA** & **PW(\(\mu\)s)** & **PRI(\(\mu\)s)** & **Pulse Number** \\ \hline Emitter 1 & 1 & 30 & 49.8\({}^{\circ}\) & 5 & 46, 50, 54 & 180 \\ Emitter 2 & 1 & 30 & 50\({}^{\circ}\) & 5 & 46, 50, 54 & 180 \\ Emitter 3 & 1 & 30 & 50.2\({}^{\circ}\) & 5 & 46, 50, 54 & 180 \\ \hline \end{tabular}
\end{table}
Table 4: Simulation parameters.  
Figure 7: Sketch map of using SMR in radar emitter identification (REID).  
From Figure 8, it can see that using SMR in REID can easily distinguish these three radar emitters and that the recognition accuracy has been improved.
## 3 Status and Application
### Repeat-Pass Interference  
A spaceborne SAR system generally uses a single antenna to collect signals. As shown in Figure 2, for a local area, only one SAR image can be obtained by one satellite flight. Satellite radar repeatedly images the area with a certain time interval and slight orbital deviation, and SAR images obtained twice can form an interference pair. This configuration is called a single-antenna repeating orbit interference system. After acquiring the initial data of the spaceborne radar system, SAR images can be formed only after computer focusing and filtering [20]. With the in-depth study of InSAR technology, the concept and idea of Differential Interferometric SAR (D-InSAR) was born.
## 1 Introduction
[18] employed a Tuned Viscous Mass Damper (TVMD) to enhance the low-frequency vibration isolation performance of floating slab track systems. By integrating TVMD elements into the vehicle-track coupled system, the method not only preserved the vibration attenuation performance in the medium- and high-frequency ranges, but also effectively broadened the isolation bandwidth and significantly reduced the acceleration levels within the 2-8 Hz frequency range. Numerous studies have shown that inerters with properly tuned parameters can effectively reduce vibrations across different frequency ranges in track structures. However, most of these investigations primarily concentrate on the vibration control performance of the superstructure, overlooking the potential impact of inerters on the underlying substructure. [PERSON] et al. [19] observed that when applied in vehicle suspension systems, inerters exhibit a frequency-dependent behavior characterized by \"attenuating low-frequency vibrations while transmitting high-frequency ones.\" Consequently, when the track structure is subjected to high-frequency excitations, the use of inerters to suppress vibrations in the rail may inadvertently amplify vibrations in the underlying components, such as the track slab and bridge, thereby accelerating their degradation and reducing their service life. To address this research gap, the present study establishes a hybrid FE-SEA model of a vehicle-track-bridge system. Short-wavelength irregularities (0.01-1 m) are introduced as high-frequency input to simulate realistic excitation conditions. The dynamic responses of the rail and track slab are computed for a train traveling at 80 m/s. TIDs are installed between the rail and slab, and the influence of their parameters--inertance, stiffness, and damping--on the system's vertical acceleration, RMS value, and stabilization time is investigated. The study also reveals the adverse effects of TIDs on track slab vibration. Finally, a multi-objective optimization model is constructed, taking the vertical acceleration amplitudes of the rail and slab as dual control objectives. The optimal TID parameters are determined using a multi-objective genetic algorithm (MOGA). The proposed framework aims to achieve simultaneous vibration suppression across structural layers, providing practical guidance for the design and application of TIDs in railway vibration control.