esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Mechanical Properties of SFRC Exposed to High Temperature
### Residual Flexural Properties  
Studies regarding the residual flexural properties of SFRC are limited. The flexural testing of SFRC has been performed on prisms, but the specimen sizes used previously varied because of the lack of standardized test specifications, including 150 mm \(\times\) 150 mm \(\times\) 550 mm [56], 150 mm \(\times\) 150 mm \(\times\) 600 mm [25], 100 mm \(\times\) 100 mm \(\times\) 400 mm [33], and 100 mm \(\times\) 100 mm \(\times\) 500 mm [57]. [PERSON] and [PERSON] [33] concluded that the flexural properties of concrete reinforced with 1% steel fiber were better than those of concrete without steel fiber when the maximum exposure temperature ranged from 105 to 800 \({}^{\circ}\)C. However, non-fiber mixtures and SFRC differed in terms of residual flexural strength when the mixtures were exposed to temperatures beyond 800 \({}^{\circ}\)C. This may be due to the steel fibers, which provided a considerable degree of ductility when concrete was heated below 800 \({}^{\circ}\)C. However, as the temperature increased further, the mechanical properties of the steel fibers appeared to be degraded owing to oxidation and corrosion [58; 59], resulting in insufficient ductility. The residual flexural strength of different fiber-reinforced concrete (FRC) has been proposed by [PERSON] et al. [56].In their study, a concrete mixture was reinforced by hybrid fibers with a volume content of 1.5%, in which the percentages of steel and propylene fiber were 100% and 0%, 75% and 25%, 50% and 50%, 25% and 75%, and 0% and 100%. The data results are shown in Figure 4. It is evident from Figure 4 that the single steel-fiber-reinforced concrete has a higher residual flexural strength than the hybrid steel and polypropylene fiber FRCs and single polypropylene FRC when the specimens were exposed to high temperatures of 200 \({}^{\circ}\)C and 400 \({}^{\circ}\)C. This is similar to the results of [PERSON] et al. [60] and [PERSON] et al. [57], in which the heating temperatures were 300 \({}^{\circ}\)C and 280 \({}^{\circ}\)C, respectively.
# Moment-Based Stochastic Analysis of a Bistable Energy Harvester with Matching Network
## 3 Energy Balance Equation, Output Average Power and Power Efficiency  
The total energy stored within the harvester is the sum of the kinetic energy of the inertial mass, of the elastic potential energy of the beam, of the energy stored in the piezoelectric transducer, and, possibly, of the electric energy stored in the reactive elements of the matching network.  
The instantaneous power absorbed by the piezoelectric transducer is the sum of the power transferred from the mechanical part to the transducer, and of the electrical power transferred form the transducer to the electrical load. Using the passive sign convention,  
Figure 2: (a) Resistive load. (b) Matched load composed of a resistor and of a low-pass L-matching network.  
and taking into account that the force exerted by the mechanical part is \(f_{\text{tr}}(t)=\alpha\,e=\alpha\,Z_{3}\), we have  
\[p_{\text{tr}}(t)=f_{\text{tr}}(t)\,\dot{x}-e\,I_{\text{L}}=C_{\text{pz}}\,e\, \dot{e} \tag{7}\]  
where the last result is derived using (2b). The energy stored in the transducer is \(E_{\text{tr}}(t)=\int p_{\text{tr}}(t)\,dt=C_{\text{pz}}\,Z_{3}^{2}/2+K_{E}\), where \(K_{E}\) is an arbitrary energy constant.  
The total energy stored in the harvester is (obviously, the last two terms are not present for the harvester with resistive load)  
\[E(t)=\frac{1}{2}m\,Z_{2}^{2}+U(Z_{1})+\frac{1}{2}C_{\text{pz}}\,Z_{3}^{2}+ \frac{1}{2}L_{S}\,Z_{4}^{2}+\frac{1}{2}C_{P}\,Z_{5}^{2}+E_{0} \tag{8}\]  
where \(E_{0}\) is an arbitrary energy constant. Taking the differential, using the SDEs system (5), and applying [PERSON]'s lemma, we obtain  
\[dE=\bigg{(}-\gamma Z_{2}^{2}-G_{\text{L}}Z_{5}^{2}+\frac{\varepsilon^{2}}{2m} \bigg{)}dt+\varepsilon\,Z_{2}\,dW_{t} \tag{9}\]  
After taking the stochastic expectation and using the martingale property of [PERSON] stochastic integral, we have (the same formulas hold for both the power balance and the power efficiency for the resistive load, with \(Z_{5}\) replaced by \(Z_{3}\))  
\[\text{E}\bigg{[}\frac{dE(t)}{dt}\bigg{]}=-\gamma\,\text{E}\Big{[}Z_{2}^{2} \Big{]}-G_{\text{L}}\,\text{E}\Big{[}Z_{5}^{2}\Big{]}+\frac{\varepsilon^{2}}{ 2m} \tag{10}\]  
Equation (10) represents a power balance equation. At a steady state, the harvester reaches a state where the average power injected by ambient vibrations \(P_{\text{in}}=\varepsilon^{2}/(2m)\) equals the average power (dissipated by internal friction plus that absorbed by the load) \(P_{\text{out}}=\gamma\,\text{E}\big{[}Z_{2}^{2}\big{]}+G_{\text{L}}\,\text{E} \big{[}Z_{5}^{2}\big{]}\).  
The power efficiency \(\eta\) is defined as the ratio between the average power absorbed by the load and the average power injected by the ambient vibrations, so that  
\[\eta=\frac{2m\,G_{\text{L}}}{\varepsilon^{2}}\,\text{E}\Big{[}Z_{5}^{2}\Big{]} \tag{11}\]
# Usage of Barkhausen Noise for Assessment of Corrosion Damage on Different Low Alloyed Steels
###### Abstract  
This study deals with corrosion damage of low alloyed fertile steels of variable strength. Three different steels of nominal yield strength 235, 700 and 1100 MPa were subjected to the variable degree of corrosion attack developed in the corrosion chamber under a neutral salt spray (NSS) atmosphere. The corrosion damage was investigated by the use of conventional metallographic observations when the thickness of corroded layer was quantified. Moreover, non-destructive magnetic technique, based on Barkhausen noise, was also employed. It was found that the rate of corrosion damage decreases along with the increasing number of days in the chamber. The similar evolution can be also found for Barkhausen noise emission and the extracted parameters from the emission. It can be reported that conventional rms value of Barkhausen noise signal as well as _FWHM_ (full width at half maximum of Barkhausen noise envelope) can be linked with the corrosion extent, especially in the early phases of corrosion attack. The _PP_ (peak position of Barkhausen noise envelope) values exhibit poor sensitivity.  
corrosion; Barkhausen noise; magnetic anisotropy; low alloyed steels Article  
Usage of Barkhausen Noise for Assessment of Damage on Different Low Alloyed Steels  
11  
[PERSON]  
1 Research Centre, University of Zilina, Univerzitina 1, 01026 Zilina, Slovakia; [EMAIL_ADDRESS]  
[PERSON]  
1 Research Centre, University of Zilina, Univerzitina 1, 01026 Zilina, Slovakia; filip.pastorek@rc.  
Barkhausen noise, which is a product of domain walls (DWs), jumps when the surface made of ferromagnetic matrix is exposed to magnetic field altering in time [10, 11]. Magnetic Barkhausen noise (MBN) is the only component of produced emission which--since the acoustic emission produced by DWs--can be detected as well. DWs alignment is affected by the stress state [12, 13, 14]. However, magnetostriction in complex steel structures is quite weak [15, 16]. Therefore, the major role, in many cases, takes microstructure expressed in term of precipitation, dislocation of non-ferromagnetic or hard magnetic phases [17, 18, 19], etc. Presence of non-ferromagnetic or hard magnetic phase (for instance Fe oxides [10]) tends to attenuate MBN emission [9]. The increasing height of surface irregularities makes propagation of electromagnetic pulses more difficult [20]. Furthermore, a non-ferromagnetic layer on a ferromagnetic body makes weaker magnetising field which in turn decreases amplitude of acquired MBN pulses [21]. According to this, MBN emission is a promising tool for monitoring of ferromagnetic bodies, which are exposed to corrosion, and this study deals with corrosion damage of low alloyed steels of variable strength.
# FOG De-Noising Algorithm Based on Augmented Nonlinear Differentiator and Singular Spectrum Analysis
###### Abstract  
A novel algorithm based on singular spectrum analysis (SSA) and augmented nonlinear differentiator (AND) for extracting the useful signal from a noisy measurement of fiber optic gyroscope (FOG) is proposed in this paper. As a novel type of tracking differentiator, augmented nonlinear differentiator (AND) has the advantages of dynamical performance and noise-attenuation ability. However, there is a contradiction in AND, i.e., selecting a larger acceleration factor may cause faster convergence but bad random noise reduction, whereas selecting a smaller acceleration factor may lead to signal delay but effective random noise reduction. To overcome the contradiction of AND, multi-scale transformation is introduced. Firstly, the noisy signal is decomposed into components by SSA, and the correlation coefficients between each component and original signal are calculated, then the component with biggest correlation coefficient is reserved and other components are filtered by AND with designed selection criterion of acceleration factor, finally the de-noising result is obtained after reconstruction process. There are mainly two prominent advantages of the proposed SSA-AND algorithm: (i) Compared to traditional tracking differentiators, better de-noising ability can be achieved without signal delay; and (ii) compared to other widely used hybrid de-noising methods based on multi-scale transformation, a parameter determination method is given based on the correlation coefficient of each decomposed component, which improves the reliability of the proposed algorithm.  
fiber optic gyroscope; de-noising; augmented nonlinear differentiator; singular spectrum analysis +
Footnote †: journal: Applied Physics Letters
## 3 Results  
### Meteorological Conditions and Irrigation Demand in the Selected Region  
An analysis of Figures 4 and 5 reveals that the peak irrigation demand occurs between the months of May and October. This period is characterized by minimal precipitation, elevated solar irradiation levels, and relatively low wind speeds.  
The meteorological data, including solar irradiation, wind speed, and ambient temperature, were sourced from the NASA Surface Meteorology and Solar Energy (SSE)  
Figure 4: Average monthly solar irradiation, wind speed, and temperature for the period 2001–2022.  
Figure 5: Monthly average precipitation (data obtained from local weather station).  
database [28]. The data were obtained by inputting the geographic coordinates of the study area into the SSE web interface, which generated monthly averaged climatic parameters for a specified time frame.  
Figure 4 presents the monthly mean values of the wind speed, solar irradiation on a tilted surface, and ambient temperature. The solar radiation data represent monthly averages over a 20-year period (2001-2022). During the May-October window, solar irradiation varied between 3.82 kWh/m\({}^{2}\)/day and 6.41 kWh/m\({}^{2}\)/day, with a maximum value of 7.34 kWh/m\({}^{2}\)/day recorded in July.  
In contrast, the wind speed demonstrated limited variability throughout the year, with an average of approximately 4.35 m/s, and this was calculated over a 22-year period (2001-2022). These observations highlight a temporal complementarity between solar and wind resources, thereby supporting the hybrid integration of photovoltaic (PV) and wind turbine systems. Nonetheless, solar energy remained the predominant renewable source during the irrigation-intensive months.  
Precipitation patterns are inherently location-dependent. The climate of northern Algeria--typical of Mediterranean regions--is marked by hot and arid summers. As illustrated in Figure 5, precipitation in the selected study area ranged between 32.83 mm and 49 mm during May and October, with the lowest monthly average of 4.76 mm observed in July. These values are insufficient to meet the agricultural water requirements, thereby necessitating the implementation of supplemental irrigation strategies.  
**Note:** In his work, [PERSON] [27] established a wind map of Algeria. His results showed that, in Algeria, wind speeds vary between 1 and 5.5 m/s at 10 m from the ground, and the latter increases from 1 to 7 m/s at 25 m from the ground. From an energy point of view, he concluded that installing wind turbines at altitudes greater than or equal to 25 m from the ground makes energy applications interesting.
## 2 Materials and Methods
### Machine Learning Algorithms Used in the Study
#### 2.5.6 Artificial Neural Networks  
Artificial neural networks (ANN) constitute a computational framework comprised of artificial neurons designed to mimic information transfer processes akin to the human brain, enabling knowledge acquisition. They create sophisticated input-output models capable of discerning intricate relationships within multidimensional data, finding applications across various engineering disciplines [80; 81]. ANN displays diverse network configurations, encompassing single and multiple layers. For instance, the feedforward back propagation neural network (FFBP) features an input layer for data reception, an intermediate hidden layer, and culminates in an output layer providing outcome-specific insights in response to input stimuli. Key hyperparameters governing the performance of ANN models include learning_rate, batch size, hidden layers function, and linkage between the hidden layer and the ultimate output layer function. The learning_rate determines the step size during optimization, influencing the convergence speed and model stability. Batch size regulates the number of samples processed before updating model parameters, impacting both computational efficiency and model generalization. The choice of the hidden layers function dictates the activation function applied to neurons within the hidden layers, shaping the network's ability to capture complex patterns. The linkage function between the hidden layer and the ultimate output layer is pivotal in defining how information flows through the network, determining the model's capacity to map inputs to accurate outputs. Figure 11 depicts an ANN model with four neurons in the input layer, two hidden layers with five neurons in each, and an output layer.  
In the realm of machine learning, hyperparameters play a pivotal role in shaping the behavior and performance of models. These parameters serve as configuration settings, influencing how a model learns patterns from data. The careful adjustment of hyperparameters is crucial to achieving optimal model accuracy and overall effectiveness in solving specific tasks. A thoughtful tuning of hyperparameters is, therefore, essential to harness the full potential of machine learning algorithms, enabling them to adapt and perform well across diverse datasets.
# An Improved Channel Estimation Technique for IEEE 802.11p Standard in Vehicular Communications
## 3 Overview of Current Channel Estimation Schemes  
Recently, a number of channel estimation schemes have been devised for the IEEE 802.11p. The pilot symbols placement in the time-frequency plane is very important for the estimation of the channel. However, the placement of pilots in the current IEEE 802.11p standard appears to be insufficient for tracking under the rapid motion of vehicles. One of the main reasons is that the two LTSs cannot provide enough information in the frequency domain. Two kinds of channel estimation scenarios are discussed in the literature. The first scenario demands modification in the IEEE 802.11p standard and the second scenario does not require such modification. The IEEE 802.11a chips are low cost and readily available in the market. These chips can be modified in a cost-efficient way if we follow the second kind of scenario.
# Laboratory Tests on Swelling Properties of Field-Coring Gypsum Rock in Tunnels
## 2 Preparation  
### Sample Preparation  
In this study, the original rock of the sample is collected from a tunnel jobsite in Lvliang City, Shanxi Province, China. The tunnel structure has suffered a rock swelling disaster. The destruction of the tunnel is shown in Figure 1. According to the X-ray diffraction analysis, the main mineral composition of the gypsum rock is 75% gypsum, 19.8% anhydrite and 5.2% quartz, as shown in Figure 2.  
Figure 1: Swelling disaster of Dugongling tunnel in Shanxi province.  
Rock core-cutting technology was adopted to process the samples, and dry-wind cooling was used to avoid pre-swelling of the sample during processing. The gypsum samples to be tested were drilled from an original rock in parallel directions to avoid the influence of rock structures of different layers.  
Three groups of samples are used in this study, as shown in Figure 3, for the free-swelling ratio test, the lateral restricted-swelling ratio test and the lateral restricted-swelling pressure test. The left column in Figure 3 shows group 1, with a diameter of 50.0 mm and a height of 50.0 mm, for the free-swelling ratio test, numbered PA-1, PA-2 and PA-3, respectively. The middle column in Figure 3 shows group 2, with a diameter of 50.0 mm and a height of 25.0 mm, for the lateral restricted-swelling ratio test, numbered PB-
## 3 Data and Methodology
### Research Methods
#### 3.2.3. OBIA-CNN Integration Frameworks
For example, each image patch can be filtered based on the dominant image object that covers or contains the image patch with some filtering methods, such as variance filtering. The obtained filtered image patches are then used in CNNs as same as they are used with the traditional patch-based CNN methods.
## 4 Conclusions  
In this investigation, a novel metallized carbon fiber composite material was developed, from which a lightweight electromagnetic shielding chassis boasting commendable shielding efficacy was engineered. Numerical simulations were utilized to compute the time-domain shielding effectiveness (SE) of chassis fabricated from metal, carbon fiber, and the newly developed composite, under varying different hole array structures and polarization modes. Additionally, comprehensive analyses concerning the weight and thermal dissipation capabilities of the chassis constructed from these three distinct materials were conducted. The following main conclusions were drawn from this study:  
1. In a double-shielded construction chassis, the newly designed lightweight electromagnetic shielding chassis provides better shielding performance than conventional metal-based counterparts. Notably, the chassis constructed from carbon fiber alone demonstrated the least effective electromagnetic shielding among the materials tested.
2. In terms of weight, the lightweight carbon fiber composite chassis closely mirrors the carbon fiber chassis in heft. However, when benchmarked against the metal chassis, a significant weight reduction ranging between 71.43% and 76.25% was observed, highlighting the composite's advantage in lightweight design.
3. Thermal analysis shows that the metal chassis has optimal thermal performance with negligible change in surface temperature, while the carbon fiber chassis has the fastest rise in temperature, slow heat conduction, and the worst thermal performance. Compared with the metal chassis, the surface temperature of the carbon fiber composite chassis increases slightly, but compared with the carbon fiber chassis, the thermal performance has a significant improvement.  
These conclusions underscore the efficacy of the composite chassis developed in this study, which combines excellent electromagnetic shielding with notable advantages in weight reduction and thermal management. The findings validate the potential of metallized carbon fiber composites as superior materials for electromagnetic shielding applications. Furthermore, this research provides a solid foundation for the future application of carbon fiber composites in electromagnetic protection and paves the way for the design of lightweight shielding enclosures capable of operating within complex electromagnetic environments.  
Conceptualization, L.C., G.-H.D. and X.-Q.L.; methodology, L.C., C.-Z.Y. and H.-W.Y.; validation, T.-Y.Z. and C.-Z.Y.; writing--original draft preparation, C.-Z.Y. and H.-W.Y.; writing--review and editing, L.C. and X.-Q.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the National Natural Science Foundation of China (Grants No. 62101433), China Postdoctoral Science Foundation (Grant No. 2019M653634), and Natural Science Basic Research Plan in Shaanxi Province of China (Grant No. 2019Q-797).  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflicts of interest.
# Radiation from a Cavity-Backed Circular Aperture Array Antenna Enclosed by an FSS Radome
## 4 Conclusions  
The radiation from a cavity-backed circular aperture array antenna enclosed by a multi-layer FSS radome has been investigated using the hybrid technique combining the mode matching method, the ray tracing technique, and Huygens's principle. The equivalent magnetic surface currents on the apertures are derived from the aperture fields, which are calculated based on the mode matching method. Then, rays are generated from the equivalent magnetic surface currents, which are used in an analysis of the multi-layer FSS radome by using the ray tracing technique. After obtained from both the mode matching method and the ray tracing technique, electromagnetic fields on an outermost radome are transformed into the equivalent electric and magnetic surface currents using [PERSON]'s principle. The radiated fields are computed from the equivalent electric and magnetic surface currents and compared with the measured data to validate our computation. We analyze the aperture array antenna enclosed by the FSS radome having a practical size and conduct the experiment for validation as a future work. Also, we plan to compare our results with other analytical models for more reliability of our method and to optimize our structure to improve the performance of the FSS radome through parametric studies.  
The present work was conducted in cooperation with all authors. [PERSON] and [PERSON] analyzed the problem and performed numerous simulations; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] contributed to the conceptualization, fabrication, and measurement; [PERSON] and [PERSON] wrote a draft which was edited by all co-authors.  
This research received no external funding.  
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. 2017R1A2B4001903) and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2015R1A6A1A0303 1833).  
The authors declare no conflict of interest.