esa-sceva/satcom-chunk-collection huggingface dataset:
# Analysis on Influences of Squeeze Film Damper on Vibrations of Rotor System in Aeroengine
## 1 Introduction
[PERSON] and [PERSON] [14] made a detailed theoretical study on the influence of SFD with a floating ring structure on the nonlinear dynamic characteristics of rotor systems. In recent years, a great deal of theoretical research has been carried out around the dynamics of the SFD-rotor system. [PERSON] [15] established the motion equation of a rotor-SFD system by using \(\pi\) oil film model with fluid inertia, and obtained the bifurcation equation of the rotor-SFD system by the averaging method. [PERSON] [16] established the nonlinear analytical equation of an SFD-rotor system, obtained the Floquet multiplier by numerical calculation, and studied the nonlinear response and bifurcation. In Refs. [17; 18], the influence of SFD  
Figure 1: Structure schematic of a bearing with SFD. on the spectrum of nonlinear vibration response is discussed. The contribution degree of connection nonlinearity and contact effect to the bistable state is compared. [PERSON] (2018) studied the effect of SFD in aeroengines with rub impact and misalignment, and found that SFD effectively reduced the vibration and strain of elastic support at the turbine disk caused by rub impact, in particular the vibration of double frequency caused by misalignment. [PERSON] (2018) analyzed the SFD effect of base excitations on a rotor system, revealing the way in which SFD affects the rotor passing through the unstable region. [PERSON] (2018) studied the influence of SFD on the nonlinear dynamic of dual-rotor systems supported by a rolling bearing. [PERSON] (2018) developed a new integral elastic ring squeeze film damper (IERSFD) and analyzed the vibration reduction principle. The overcritical vibration experiment of the rotor was carried out under the conditions of an IERSFD chamber filled with liquids with different viscosity damping. [PERSON] (2018) focused on the ability of the elastic ring of ERSFD to effectively adjust the dynamic pressure of oil film and suppress the nonlinear vibration of the rotor system. The influence of ring thickness, oil film thickness, and oil viscosity on vibration were studied. At present, most of the research on SFD-rotor systems focuses on the qualitative mechanistic analysis of nonlinear dynamics. There is a lack of research on the direct comparison of vibration behavior under different speed conditions and unbalance. Especially, the research on structural characteristics and dynamic characteristics of typical aero-engine rotor systems lacks pertinence. In this paper, the nonlinear stiffness and damping of SFD are introduced to establish the corresponding dynamic differential equation according to the typical structure and dynamics, particularity of the aeroengine rotor system. In order to reveal the bounded complex vibration and bistable vibration of the rotor system caused by SFD and the law of influence of unbalance on unstable vibration, the response of the rotor system under different unbalances and different rotational speeds were studied.
# Vector Approximate Message Passing Based OFDM-IM Detection for Underwater Acoustic Communications
## 3 Proposed Method
### VAMP Framework for IM Detection
Based on the above analysis, we can achieve the node message for \(t\)th iteration as follows:  
(1) Calculate \(b_{app}(\mathbf{x}_{2})\) with \(b_{sp}(\mathbf{x}_{2})\propto p\big{(}\mathbf{y}|\mathbf{H}\mathbf{x}_{2}, \gamma_{w}^{-1}\mathbf{I}\big{)}\,p\Big{(}\mathbf{x}_{2}|\mathbf{r}_{2t},\gamma _{2k}^{-1}\mathbf{I}\big{)}\), then  
\[\hat{\mathbf{x}}_{2}=\Big{(}\gamma_{w}\mathbf{H}^{H}\mathbf{H}+\gamma_{2t} \mathbf{I}\Big{)}^{-1}\Big{(}\gamma_{w}\mathbf{H}^{H}\mathbf{y}+\gamma_{2t} \mathbf{r}_{2t}\Big{)}, \tag{15}\]  
\[\beta_{2t}^{-1}=\gamma_{2t}\mathrm{var}[\mathbf{x}_{2}|\mathbf{r}_{2t}, \gamma_{2t}]=\frac{\gamma_{2t}\mathrm{Trace}\Big{(}\big{(}\gamma_{w}\mathbf{H }^{H}\mathbf{H}+\gamma_{2t}\mathbf{I}\big{)}^{-1}\Big{)}}{n}. \tag{16}\]  
(2) Calculate \(b_{app}(\mathbf{x}_{1})\) with \(b_{app}(\mathbf{x}_{1})\propto p(\mathbf{x}_{1})p\Big{(}\mathbf{x}_{1}|\mathbf{ r}_{1t},\gamma_{1t}^{-1}I\Big{)}\), then one key step is to define the prior \(p(\mathbf{x}_{1})\). Without any assumptions, the prior \(p(\mathbf{x}_{1})\) is unknown; therefore, the shrinkage function \(\eta(\cdot)\) and the divergence \(\big{\langle}\eta^{{}^{\prime}}(\mathbf{r}_{k},\gamma_{k})\big{\rangle}\) are unknown. The problem is solved in the next subsection. (3) Calculate the edge message \(\mu_{x_{1}\to\delta}(\mathbf{x}_{1})\) with \(\mu_{x_{1}\to\delta}(\mathbf{x}_{1})\propto\frac{b_{app}(\mathbf{x}_{1})}{\mu_ {\delta\to x_{1}}(\mathbf{x}_{1})}\propto\frac{\mathcal{CN}\big{(}\mathbf{x}_ {1};\hat{\mathbf{x}}_{1t},\beta_{1t}^{-1}\mathbf{I}\big{)}}{\mathcal{CN} \big{(}\mathbf{x}_{1};\hat{\mathbf{x}}_{1t},\gamma_{1t}^{-1}\mathbf{I}\big{)}}\), then its mean and precision are given by \(\mathbf{r}_{2t}=\frac{\beta_{1t}\mathbf{x}_{1t}-\gamma_{1t}\mathbf{r}_{1t}}{ \beta_{1t}-\gamma_{1t}}\) and \(\gamma_{2t}=\beta_{1t}-\gamma_{1t}\). With the forward-and-back message passing, the iterations are converged until the true belief is approximated. The non-loopy factor graph in Figure 2 provides interpretable message scheduling with ease of implementation.
## 5 Integration of Pruning for Stream-Lined Control
The minimum error pruning method, however, only incurs 1.03% error with 223 removed weights and 257 weights can be removed while still incurring less than 5% error. Another interesting trend is that the percent change in all three methods did not always incrementally increase. In some instances, removing additional weights actually improved the performance of the network. This was particularly true for the minimal-value deletion pruning and OBS, but was still evident to a smaller extent in the minimum error method. The minimum error method significantly outperformed the other two methods and, in some cases, a negative percent change was observed, indicating that the pruned network performed better than the full-state network. The pruned states resulting from minimal-value deletion pruning and OBS never performed better than the full-state network. When considering the number of removed filters versus the number of removed weights (Figure 8b), all three methods exhibited very similar trends. Initially, the number of removed filters remained at zero, even as the number of removed weights increased, because a filter was only removed when it was no longer connected to any controller units. However, once a significant portion of weights have been removed, the number of removed filters rapidly increases as connections are removed. Removing filters is a competing metric with the incurred error, as shown in Figure 8a. It is desirable to remove more filters as this results in a more streamlined control algorithm, but as more filters are removed, the control effectiveness degrades as indicated by an increase in percent error. Therefore, determining the optimal number of weights to remove is a balance between these two metrics and requires some subjectivity.
## 1 Introduction
The FO-KC autotuning method eliminates this drawback. The design is based on using the iso-damping property and the phase margin \(PM\) requirement to define a forbidden region in the Nyquist plane that the loop frequency response should avoid. Moreover, to ensure the iso-damping property, the optimal FO-PI controller is determined such that the difference between the slope of the loop frequency response and the slope of the forbidden region border is minimum. The FO-KC auto-tuning method has been presented before [17], however, it has only been tested under simulations. The main contribution of the present paper is to offer an experimental validation of the method and this represents the original element of the present work. The paper is structured as follows. Section 2 details the auto-tuning principle behind the FO-KC method. Section 3 presents the case study considered for the experimental validation of the method. The last section concludes the paper.
## 2 Results  
### Transcript Levels of terpenoid Biosynthetic Genes  
We determined differential organ-specific expression patterns of terpenoid biosynthetic genes in _V. fauriei_ using qRT-PCR (quantitative real time polymerase chain reaction). The results are shown in Figures 2 and 3. The height of each bar and the error bar indicate the mean and standard deviation based on three independent measurements. The Y-axis represents transcript levels normalized to _18S_ expression. Most genes related to the MVA pathway showed the highest expression levels in the stem, except for _VfHMS_ and _VfHMR_. The expression patterns of _VfAACT_, _VfMK_, _VfPMK_, _VfMVD_, and _VfPDS_ were fairly similar, with the highest levels occurring in the stem, followed by the root and the flower or the leaf. Interestingly, in roots, _VfAACT_ and _VfPDS_, which are involved in the first and last steps of the MVA pathway, were expressed at similar levels to the stem. Among MVA biosynthetic genes, the expression of _VfAACT_, _VfMK_ and _VfMVD_ was high relative to _18S_, while expression of _VfPDS_ was the lowest relative to _18S_. _VfIDI_, which produces the enzyme that catalyzes the isomerization of IPP to DMAPP in both the MVA and MEP pathways, was expressed most abundantly in the stem, followed by the flower, root, and leaf. According to analyses of MEP biosynthetic gene expression levels, most genes, including _VfCMK_, _VfMDS_, _VfHDR_, and _VfGDS_, had the highest expression levels in the stem, whereas _VfDXR_ and _VfHDS_ were highly expressed in the leaf. _VfMCT_ had similar expression levels in all organs of _V. fauriei_. The lowest expression levels of _VfDXR_, _VfMDS_, _VfHDS_, and _VfHDR_ were displayed in the root. In contrast, _VfDXS_ transcripts, which are involved in the start of the MEP biosynthetic pathway, had their highest level in the root. Expression levels of terpenoid backbone biosynthetic genes, which lead to IPP and DMAPP production, were primarily high in stem of _V. fauriei_.
# Fuzzy Logic-Based Performance Enhancement of FSO Systems Under Adverse Weather Conditions
## 2 Modeling of Rain and Fog Impairments in FSO System
### Fog
\begin{table}
\begin{tabular}{c c} \hline
**Weather Condition** & **Attenuation (dB/km)** \\ \hline Thin fog & 9 \\ \hline Light fog (LF) & 13 \\ \hline Medium fog (MF) & 16 \\ \hline Heavy fog (HF) & 22 \\ \hline Light haze (LH) & 1.537 \\ \hline Medium haze (MH) & 4.285 \\ \hline \end{tabular}
\end{table} 
Table 2: Haze and fog conditions and their attenuation.
## 2 Experimental Descriptions  
### Experimental Apparatus  
The complete experimental system is composed of two modules: the compressive loading module and the sieving module. The former is used to compress the gangue specimens and record the data for analysing the compression features of the gangue particles. The breakage degree of the compressed gangue particles is quantitatively analysed based on the sieving system to reveal the particles' fractal characteristics.  
The loading module comprises a WAW-1000D electro-hydraulic servo universal test machine as the control centre and a self-developed steel barrel holding the gangue materials. As shown in Figure 1, the test machine can offer a maximum axial force of 1000 kN and has a stroke range of 0-250 mm. It is equipped with data acquisition software by which mechanical parameters such as load and displacement can be measured. The steel barrel has a square cross-section and an inner cuboid chamber of 200 mm \(\times\) 200 mm \(\times\) 300 mm (length \(\times\) width \(\times\) h eight). Mesh-shaped reinforcing bars with a thickness of 10 mm and a height of 28 mm are arranged at the outer sidewalls of the barrel to prevent deformation and limit the lateral displacement of the gangue materials. The outer dimensions of the barrel are 304 mm \(\times\) 304 mm \(\times\) 322 mm.  
Figure 1: Compressive loading module and the test system.  
The sieving module mainly consists of a sieving device and weighing device. The sieving device includes standard square-holed sieves and a vibrating classifier. According to the national industry standard JGJ52-2006 \"Standard for technical requirements and test method of sand and crushed stone (or gravel) for ordinary concrete\" [39], and in combination with the test scheme, sieves screens with different nominal diameters (1.25, 2.5, 5, 10, 16, 20, 25 mm) were used in this experiment. The weighing device is an electronic scale with a measuring range of 0-3000 g and a precision of 0.01 g.
# Two-Step Multiuser Equalization for Hybrid mmWave Massive MIMO GFDM Systems
## 6 Conclusions  
In this paper, we considered the design of a hybrid analog-digital MU equalizer with a simple analog precoder scheme for mmWave mMIMO GFDM-based systems. Herein, the GFDM waveform  
Figure 8: Performance comparison of the proposed hybrid AoD-based precoder after applying the shadowing effect.  
Figure 7: Performance comparison of the proposed hybrid AoD-based precoder between theoretical and simulation cases for \(N_{tx}=16\) and \(N_{rx}=64\).  
technique is proposed to overcome the high PAPR and OOB emissions of OFDM. At the transmitter, the phase shifter network is used as a simple analog precoder, where two types of precoders based on the availability of the CSI knowledge at the transmitter are used: random- and AoD-based precoder. At the receiver, a hybrid digital-analog equalizer was designed to efficiently separate users. The analog coefficients were obtained by minimizing the MSE between the hybrid structure and the full digital counterpart, noting that the GFDM structure and ZF are used in the digital part. The performance results showed that the performance gap between the hybrid equalizer and the full digital scheme decreases as the number of RF chains increases.  
Investigation, J.K., and M.M.; Supervision, D.C., A.S., and R.D.; Validation, P.P., A.G.; Writing--original draft, J.K., and M.M.; Writing--review & editing, R.M., D.C., A.S., and R.D. All authors have read and agreed to the published version of the manuscript.  
This work is supported by FCT/MEC through national funds, under Project MASSIVE5G (PTDC/EEI-TEL/30588/2017), and by the European Regional Development Fund (FEDER), through the Competitiveness and Internationalization Operational Programme (COMPETE 2020), and Regional Operational Program of Lisbon (CENTRO 2020) - PES3N.: Solucoes Energeticamente Eicientes para Redes de Sensores Seguras - POCI-01-0145-FEDER-030629.  
The authors declare no conflict of interest.
# A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Turkiye
## 1 Introduction
Additionally, records obtained during some medium and large earthquakes that occurred after 2007 were compiled under the RESORCE project [25]. In Turkiye, the National Strong-Motion Network (TR-NSMN) is operated by the Earthquake Department of AFAD (Disaster and Emergency Management Presidency). The observation activities of TR-NSMN, which started with 76 analog instruments in the early 1970s, experienced a significant increase in capacity after the major Kocaeli (\(M_{W}\) 7.6). and Duzce (\(M_{W}\) 7.2) earthquakes in 1999. Over the past decade, hundreds of new modern digital instruments and high-standard free-field strong-motion stations have been installed throughout Turkiye. The replacement of analog devices with digital ones, the installation of numerous new stations, and the transition of all stations to free-field conditions have significantly enhanced both the quantity and quality of the data. Especially after 2010, the number of stations in TR-NSMN has increased significantly, reaching 1103 (887 active and 216 passive) as of 2024. In recent years, there has been a significant increase in the acceleration record archive due to the increasing number of stations and major earthquakes in Turkiye. In particular, thousands of new acceleration records, obtained from near sources and representing rare examples on a global scale, were added to the data archive during the main shocks and aftershocks of the Van earthquake on 23 October 2011 (\(M_{\rm W}\) 7.1), the Sivrice-Elazig earthquake on 24 January 2020 (\(M_{\rm W}\) 6.8), the Aegean Sea earthquake on 30 October 2020 (\(M_{\rm W}\) 7.0), the Duzce earthquake on 23 November 2022 (\(M_{\rm W}\) 5.9), and the Pazarck (\(M_{\rm W}\) 7.8) and Elbistan (\(M_{\rm W}\) 7.7) earthquakes centered in Kahramanmaras on 6 February 2023 [26; 27; 28]. AFAD has developed the web-based TADAS (Turkish Accelerometric Database and Analysis System) platform to enable the querying, analysis, and sharing of all data from past to present over the Internet. All data are available to researchers through this portal (TADAS, [[https://tadas.afad.gov.tr](https://tadas.afad.gov.tr)]([https://tadas.afad.gov.tr](https://tadas.afad.gov.tr))). The strong-motion data archive of Turkiye, which is constantly gaining more high-quality data, provides a wide dataset for shallow crustal earthquakes, enabling the development of up-to-date GMPMs.
## 4 Results
### Pore System and Pore Size
#### 4.3.3 Fractures  
High-angle fractures, low-angle fractures, and fractures parallel to bedding are observed in the Yanchang shale at outcrop, core, and pore scales (Figure 11). The high-angle fractures are primarily structural joints, with dips generally greater than 75\({}^{\circ}\) (Figure 11A,D). These predominantly trend in the near east-west direction (approximately 260-280\({}^{\circ}\)), and some north-south-trending (approximately 0\({}^{\circ}\)-20\({}^{\circ}\)) high-angle fractures, nearly perpendicular to the east-west trending fractures, can be observed in the Yanchang shale (Figure 10B). The spacing for the east-west-trending high-angle fractures ranges from 6 to 174 cm, with an average of 54 cm (Figure 11C). In contrast, the pacing of the north-south-trending high-angle fractures ranges from 10 to 228 cm, with an average of 62 cm (Figure 11C).  
Figure 11: Photographs of fractures in the Yanchang shale from outcrops and cores. (**A**) Fractures (joints) in Yanchang shale at an outcrop in Yanhe. (**B**) Rose diagram showing the trend directions of high-angle fractures from outcrops. (**C**) Frequency histogram of fracture spacing for fractures in Yanchang shale outcrops. (**D**) Core photograph of a high-angle fracture, well Y8. (**E**) Core photograph of bed-parallel fracture, well Y10. (**F**) A bed-parallel fracture filled with calcite, well Y2. (**G**) An open bed-parallel fracture, well X1. (**H**) Low-angle fracture filled with calcite, well Y11. (**I**) Low-angle and high-angle fractures, well F4. (**J**) SEM image of an open bed-parallel fracture filled with bitumen, well Y8.  
Low-angle fractures and fractures parallel to bedding are commonly developed at the transition zones between sand-silt intervals and mudstones (Figure 11E-J). Fractures in the Yanchang shales are usually filled with calcite, solid bitumen, and liquid hydrocarbons (Figure 11D-J).
# Emerging Applications of Machine Learning in 3D Printing
## 4 Discussion  
The state of the art in the use of ML in 3D printing, presented in previous publications, includes advanced applications in design, process optimization, and quality control. ML-based generative design enables the creation of complex, lightweight structures optimized for strength and material performance, often used in the aerospace and automotive industries. Real-time monitoring systems with ML integration are able to detect anomalies during printing, enabling immediate corrections to reduce waste and improve print quality. ML models are used to predict and optimize print parameters, such as temperature and speed, to improve the precision and consistency of different materials. Breakthroughs in predictive maintenance and predictive material behavior demonstrate the potential of machine learning to further automate and improve the 3D printing ecosystem, making processes more reliable and cost-effective.
# Three-Level Hybrid Envelope Tracking Supply Modulator with High-Bandwidth Wide-Output-Swing
## 2 Supply Modulator System Level Design
### High Efficiency Switching Modulator  
The switching regulator employs two pairs of complementary switching transistors as shown in Figure 2. The voltage at the \(\mathrm{V_{SW}}\) node is 0 to \(V_{DD}/2\) or \(V_{DD}/2\) to \(V_{DD}\), under the ideal conditions, the voltage range across the transistor is maintained at \(V_{DD}/2\). Therefore 3L-SWR can use thin gate-oxide transistors with lower parasitic and lower on-resistance. Compared with the standard two-level buck converter, this converter can reduce the inductor current ripple to 1/4 and the output voltage ripple to 1/8, thus achieving lower switching losses [26].  
The power losses in the switching stage include conduction losses and switching losses. Assuming that under the same voltage, the relationship between 3L-switching loss and 2L-switching loss is expressed in [24]  
\[\frac{P_{3L\_swloss}}{P_{2L\_swloss}}=\frac{4\times\frac{1}{2}C_{P3L}V_{SW3L }^{2}f_{SW3L}+C_{FP}V_{SW3L}^{2}f_{SW3L}}{2\times\frac{1}{2}C_{P2L}V_{SW2L}^{ 2}f_{SW2L}} \tag{5}\]  
where \(C_{P3L}\) and \(C_{P2L}\) are the parasitic capacitors of the transistors in 3L-SWR and 2L-SWR, respectively. \(V_{SW3L}\) is the switching voltage and \(f_{SW3L}\) is the switching frequency of a parasitic capacitor in the 3L-SWR, \(V_{SW2L}\) and \(f_{SW2L}\) correspond to the parameters in the 2L-SWR. The flying capacitor has parasitic capacitor \(C_{FP}\), as given in [25]. The relationship between \(C_{FP}\) and \(C_{F}\) is \(C_{FP}=\alpha C_{F},\;\alpha<1\), therefore the switching loss is related to the size of the capacitor \(C_{F}\).  
The conduction loss and ripple loss are caused by the on-resistance of pMOS and nMOS. The ratio of conduction loss and ripple loss of the 3L-SW and 2L-SW is given as  
\[\frac{P_{con3L}}{P_{con2L}}=\frac{2\times R_{on3L}I_{13L}^{2}\times(1+I_{73L}) }{R_{on2L}I_{2 LL}^{2}\times(1+I_{72L})} \tag{6}\]  
where \(R_{on3L}\) and \(R_{on2L}\) are the on-resistance of the single device in 3L-SWR and 2L-SWR, respectively. \(I_{13L}\) and \(I_{12L}\) represent the average inductor currents for 3L-SWR and 2L-SWR, assuming they are equal. \(I_{r}\) is the ratio of the inductor current ripple to the average inductor current, while \(I_{73L}\) is four times smaller than \(I_{72L}\) at the same inductance L and the same \(f_{SW}\) as shown in [19]. In Equation (6), the ratio can be less than one. If the inductor current ripple is very small, \(P_{con3L}/P_{con2L}\) is only related to the on-resistance, so the 3L-buck converter using thin gate oxide transistors has an advantage over the 2L-buck converter.  
Therefore, a 3L-SWR is used to ease the design difficulty of the LA for wideband applications. The detailed circuit design is analyzed in Section 3.