esa-sceva/satcom-chunk-collection huggingface dataset:
# Laboratory Evaluation of Rejuvenating Agent on Reclaimed SBS Modified Asphalt Pavement
## 3 Results and Analyses
### Anti-Aging Property of Modified Asphalt Blends  
To examine the anti-aging property of modified asphalt blends, the thin film oven test (TFOT) was conducted. According to the recycling effect and economy of the above-mentioned three rejuvenating agents H, S, G, the proportion of rejuvenating agent for TFOT were set to 3%, 6%, 6% respectively. The test results are shown in Table 7.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Properties**} & \multirow{2}{*}{**Specification Requirement**} & \multicolumn{4}{c}{**Modified Asphalt Blends**} \\ \cline{3-5}  & & & **3\%H** & **6\%S** & **6\%G** \\ \hline Penetration/0.1 mm & 40–60 & 50.0 & 50.3 & 49.3 \\ Softening point/\({}^{\circ}\)C & \(\geq\)60 & 64.9 & 64.3 & 64.2 \\ Ductility/cm & \(\geq\)20 & 19.3 & 21.2 & 20.7 \\ Penetration ratio/\% & \(\geq\)65 & 78.0 & 78.3 & 79.3 \\ Incoming TFOT & Ductility/cm & \(\geq\)15 & 10.8 & 8.1 & 9.7 \\ Weight change/\% & \(\leq\)\(\pm\)1.0 & 0.302 & 0.438 & 0.369 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Anti-aging property of modified asphalt blends.  
Table 7 shows that the penetration ratio and weight change of modified asphalt blends after TFOT meet the requirements of China's specifications, except in terms of ductility. The results indicate that, although the properties of aged modified asphalt blended with rejuvenating agent can be recycled, the low-temperature property often cannot meet the requirements after aging, indicating that the modifier has lost part of the original modified effect.  
Therefore, modified asphalt recycling should focus on its low-temperature property, requiring rejuvenating agent not only to effectively recover the colloidal structure of aged modified asphalt, but also to repair and supplement the aged modifier. Ultimately, the objective is to recover both the low-temperature cracking resistance and high-temperature rutting resistance of modified asphalt.
## 6 A Simulation Study: Optimization of Micro-Algae Lipid Productivity
### Bifurcation Analysis  
Figure 2 and Table 3 provide the results of a bifurcation analysis. The concave steady-state manifold validates all the assumptions listed in Section 2. A Hammerstein model is therefore a valid representation even though other block-oriented structures could be considered as well (see for instance the discussion in [16] for the SISO case). These results also show that the optimum of \(P_{l}\) corresponds to a more concentrated outflow (higher biomass concentration for a smaller dilution rate) than the optimum of \(P\) and a smaller internal nitrogen quota (which can be linked to the production of lipid). For lipid extraction, it is desirable to work with a concentrated solution to improve the operations [40]. Furthermore, Figure 2 shows that the extremum of \(P\) (32) corresponds to operating conditions close to the wash-out of the reactor. Conversely, the extremum of \(P_{l}\) (33) offers a comfortable security margin.  
Figure 2: Steady-state productivity maps with respect to dilution rate \(D\) and incident light \(I\). Red ‘\(\ast\)’: Optimal values using \(P\) (32) and Blue ‘\(\ast\)’: Optimal values using \(P_{l}\) (33).
###### Abstract  
The advent of fiber optic technology in geophysics exploration has grown in its use in the exploration, production, and monitoring of subsurface environments, revolutionizing the way data are gathered and interpreted critically to speed up decision-making and reduce expense and time. Distributed Acoustic Sensing (DAS) has been increasingly utilized to build relationships in complex geophysics environments by utilizing continuous measurement along fiber optic cables with high spatial resolution and a frequency response of up to 10 KHz. DAS, as fiber optic technology examining backscattered light from a laser emitted inside the fiber and measuring strain changes, enables the performance of subsurface imaging in terms of real-time monitoring for Vertical Seismic Profiling (VSP), reservoir monitoring, and microseismic event detection. This review examines the most widely used fiber optic cables employed for DAS acquisition, namely Single-Mode Fiber (SMF) and Multi-Mode Fiber (MMF), with the different deployments and scopes of data used in geophysics exploration. Over the years, SMF has emerged as a preferred type of fiber optic cable utilized for DAS acquisition and, in most applications examined in this review, outperformed MMF. On the other side, MMF has proven to be preferable when used to measure distributed temperature. Finally, the fiber optic cable deployment technique and acquisition parameters constitute a pivotal preliminary step in DAS data preprocessing, offering a pathway to improve imaging resolution based on DAS measurement as a future scope of work.  
fiber optic technology; distributed acoustic sensing (DAS); single-mode fiber (SMF); multi-mode fiber (MMF)
# Dynamic Response of Copper Plates Subjected to Underwater Impulsive Loading
## 4 Conclusions  
Experimental investigations on the non-linear dynamic responses of circular copper plates subjected to underwater impulsive loading using a fluid-structure interaction experimental setup were presented. The different types of copper plates, with and without pre-notches, were studied and analyzed. The shock pressure histories were successfully measured by the dynamic pressure transducers at locations A and B. A stereoscopic camera system combined with a 3D DIC technique was utilized to monitor the out-of-plane deformation, velocity, and in-plane maximum principal strain of the copper plates. Results showed that dynamic deformation is the interaction effect of the initial underwater shock wave and water medium flow.  
For the clamped circular specimens without a pre-notch, a dimensionless deflection was performed to further investigate the relationship between the impulsive wave intensity, thickness of the specimens, and the final deflection. The linear relation between the normalized final deflection and the dimensionless impulse was observed.  
The effects of the impulsive wave intensity, geometric dimension of the specimens, and the dimension of the pre-notch on the failure modes of the copper plates were also studied. Based on the observation of the current experiments, a large ductile deformation (mode I) was observed for the plate without a pre-notch, and other four typical failure modes, including large ductile deformation with local necking (mode Ic), splitting (mode II), splitting and tearing(mode IIc), and fragment (mode III) were found for the plates with different pre-notches.  
This study provides insight into the relationship between the impulsive wave intensity, geometric dimensions of specimens and pre-notches, and the non-liner dynamic responses of copper plates subjected to underwater impulsive loading. This discussion will be helpful in understanding failure processes and predicting failure modes.  
Conceptualization, P.C.; experimental design and measurement, K.D., H.L., B.G. and D.X.; data analysis, K.D., H.L. and B.G.; writing-original draft manuscript, K.D.; Writing-review and editing, P.C. and J.R.  
The present work was supported by the National Natural Science Foundation of China under Grants 11472047, 11472054 and 11521062.  
The authors declare no conflict of interest.  
Figure 18: Microstructures of different fracture surfaces of the C2# specimen.
# An Overview of Hybrid RANS-LES Models Developed for Industrial CFD
## 3 Global Hybrid RANS-LES Models
#### GEKO-Based SBES  
When running global hybrid models in standard mode, the boundary layer is covered entirely by the RANS model. This saves large amounts of computational power but carries the uncertainties of RANS modeling into the hybrid simulation. The main issue is obviously the ability of the RANS model to accurately capture separation. Our research group recently developed a new RANS model, termed the Generalized k-\(\omega\) (GEKO) model ([PERSON] et al. [40, 41]). It allows the re-calibration or fine-tuning of the model through user-exposed coefficients. The coefficients are designed in such a way that changing them (within defined limits) does not alter the basic model calibration for the flat plate. This allows non-turbulence experts to adjust the model to their applications. An example of such an approach is the simulation of an automotive configuration with the goal of computing the noise from the side-mirror and the A-pillar of car onto the window, as reported by [PERSON] and [PERSON] [42]. For the A-pillar noise, the correct separation prediction of the pillar vortex is essential. Figure 14 shows the region of interest. Two GEKO settings are used, one with the free coefficient GEKO1 with C\({}_{\text{SEP}}\) = 1.0 and GEKO2 with C\({}_{\text{SEP}}\) = 2.0. C\({}_{\text{SEP}}\) is the main parameter in the GEKO model controlling separation onset. C\({}_{\text{SEP}}\) = 1.0 corresponds to a k-\(\epsilon\) model (with known late separation) and C\({}_{\text{SEP}}\) = 2.0 is \"aggressive\" in predicting separation (even earlier separation prediction than SST). The difference between these two settings is clearly visible for the A-pillar vortex (red arrow), where the vortex is shifted downwards for the C\({}_{\text{SEP}}\) = 1 configuration.  
Figure 15 shows the sound pressure levels at the locations of the window affected by the A-pillar vortex. The positions in Figure 14 refer to the side-window locations--only  
Figure 14: Instantaneous 3D turbulent wake structures (Q-criteria iso-surfaces), colored in line with the instantaneous velocity magnitude, for an Alfa Romeo Giulietta baseline mirror configuration: (**a**) GEKO1 (C\({}_{\text{SEP}}\) = 1); (**b**) GEKO2 (C\({}_{\text{SEP}}\) = 2). Arrows point to differences in A-pillar vortex locations (courtesy of FCA Italy).  
Figure 13: Profiles of the mean velocity for SBES and IDDES models for channel flow for two Reynolds numbers.  
positions 8, 9 and 10 are depicted, as they are the ones affected by the A-pillar vortex. The more aggressive setting using CSEP = 2.0 (GEKO2) is in much better agreement with the data than CSEP = 1.0 (GEKO1). This illustrates the advantage of combining a tunable RANS model with a hybrid RANS-LES method. This is important, as contrary to LES, the performance of the RANS part of the model cannot be improved by mesh refinement.
## 4 Comparison of Pseudo-Dynamic Test Results and Non-Linear Dynamic Analysis Results
### Comparison of Non-linear Dynamic Analysis and Pseudo-Dynamic Test Results
When the input seismic acceleration was 300 cm/s\({}^{2}\), the maximum seismic response load and displacement of PD-CFT-MF were 662.5 kN and 26.7 mm, respectively, in the non-linear dynamic analysis and 613.3 kN and 25.1 mm, respectively, in the pseudo-dynamic testing (Figure 23 and Table 7). The two methods provided similar results. When the input seismic acceleration was 400 cm/s\({}^{2}\) as well, i.e., when a large-scale earthquake was assumed, the maximum seismic response load and displacement were 712.4 kN and 39.4 mm, respectively, in the non-linear dynamic analysis and 773.9 kN and 40.6 mm, respectively, in the pseudo-dynamic testing (Figure 24 and Table 7). The anchor bolts connecting the existing RC members with the CFT-MF reinforcing bars were assumed to follow the bi-linear elastic model, as shown in Table 6. These anchor bolts exhibited elastic behavior over the entire seismic ground motion range. These results confirmed that the non-linear dynamic analysis model and methodology developed in the present study were able to effectively simulate the seismic behavior of the CFT-MF system and RC frames retrofitted with the system. This led to the conclusion that the seismic retrofitting performance of the CFT-MF system developed in the present study could be effectively evaluated via non-linear dynamic analysis based on the analytical models and methods established in Section 4.1. The contribution of the seismic response load of each member (including the CFT-MF system developed in the present study and the RC test frame retrofitted with the CFT-MF system) to the seismic response displacement at a seismic ground motion of 300 cm/s\({}^{2}\) is presented in Table 8 and Figure 25. The contribution ratios of the lateral load of the CFT-MF system were 72.0%, 72.3%, and 73.5% when the displacement was 10 mm, 20 mm, and 30 mm, respectively. These results indicate that the CFT-MF system is an effective seismic retrofitting measure to significantly enhance the strength of RC structures. This superior seismic retrofitting method by strength increase is considered to efficiently increase the strength of middle- and low-rise RC structures with non-seismic details, and especially those with poor ductility.
# Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications
###### Abstract  
This paper provides a study of the smart grid projects realised in Europe and presents their technological solutions with a focus on smart metering Low Voltage (LV) applications. Special attention is given to the telecommunications technologies used. For this purpose, we present the telecommunication technologies chosen by several European utilities for the accomplishment of their smart meter national roll-outs. Further on, a study is performed based on the European Smart Grid Projects, highlighting their technological options. The range of the projects analysed covers the ones including smart metering implementation as well as those in which smart metering applications play a significant role in the overall project success. The survey reveals that various topics are directly or indirectly linked to smart metering applications, like smart home/building, energy management, grid monitoring and integration of Renewable Energy Sources (RES). Therefore, the technological options that lie behind such projects are pointed out. For reasons of completeness, we also present the main characteristics of the telecommunication technologies that are found to be used in practice for the LV grid.  
smart grid; smart grid projects; telecommunication technologies; smart metering solutions +
Footnote †: journal: Energy Society Reviews
## 4 The Algorithm  
### Obtaining the Global Middle Path and the Beams  
Using the potential field, a global path consisting of points in the middle of the free space from the start point to the goal point through obstacles is generated. It is essential to smooth this path, which is done by means of windowing. Figure 5 shows a portion of this smooth path numbered as 2 and positioned in the middle of the free space. In this figure, the obstacles are numbered as 1 and the right beams are numbered as 3 and the left beams are numbered as 4. This path contains all the data required for the path planning of the manipulator.  
Figure 4: Benchmark environment.  
Figure 3: Interpolation in 3D environment.  
Having the path, the beams are generated. Each beam starts from its path point and ends at the obstacle border. The angle between the beam and the path is 90\({}^{\circ}\). In Figure 6, a right beam is shown. The same procedure is applied to the left beams. If the beam reaches its maximum length before reaching an obstacle border, it ends at that length. Especially critical regions generate short beam lengths. As seen in Figure 5, the area the beams cover is free space where the manipulator must be confined. However, since the tight maneuvering is required, only some portions of this free space must be used.
# 6G Mobile Networks: Key Technologies, Directions, and Advances
## 6 Implementation of Security in 6G Network
### Security Challenges Associated with 6G Network
* Identity attack: Using vulnerabilities in identification & authorisation procedures for gain Harvested API keys are utilized as credentials. Unprotected E2E domain orchestration services are taken advantage of to alter settings in such an effort to violate service level agreements as well as to launch new instances that consume a lot of network resources [90]. * Man-in-the-middle attack: Through starting false failure occurrences & intercepting domain control messages, MITM assaults can redirect traffic through rogue endpoints [91]. * DDoS attacks: For 6G, DDoS assaults are anticipated to be significantly severe. Numerous vulnerable Internet of Things (IoT) devices might send enormous amounts of harmful traffic toward intruders. Edge servers that are frequently accessed, though, have less effective DDoS mitigation features. DDoS assaults can potentially be harmful to end devices [92]. * Deception attack: The 6G network's transmitted data will be manipulated on purpose [93]. * Data leakage: Obtaining data about unauthorised parties' intentions to undermine system security goals such as privacy and confidentiality, etc. Additional assaults might start as a result of all this. * Improper configurations: Intent-based links, which are comparable to Zero-touch Ntwworks & Service Management (ZSM) in that they may be open to data uncovering, may be used by 6G networks, opening them up to assaults including unwanted configurations & strange behavior. Unwanted setup of intent-based interfaces, like switching the security level from high to low or altering the linking of intent to action, might risk the security of the entire management architecture [94].
## 5 Other Characterization of the Dielectric Gas Mixture
### Synergistic Effect of HFO-1336 mzz (E)  
The synergistic effect characterizes the gas mixture's dielectric strength, as mixing two gases results in higher or lower breakdown voltages than in their pure form. To analyze the synergistic effect of the HFO-1336 mzz (E)/CO\({}_{2}\) gas mixture, a coefficient \(S\) is introduced, as can be seen in Equation (12) [28]. In the equation, \(V_{buffer}\), \(V_{base}\), and \(V_{mix}\) show CO\({}_{2}\) breakdown voltage, HFO-1336 mzz (E), and their mixture, where \(m\) denotes the percentage mixture of HFO-1336 mzz (E) in the gas mixture.  
\[V_{mix}=V_{buffer}+\frac{m\left(V_{base}-V_{buffer}\right)}{m+(1-m)S} \tag{12}\]  
\[V_{base}>V_{buffer}\]  
Figure 14 shows the synergistic effect of HFO-1336 mzz (E) with CO\({}_{2}\) gas. If \(S=0\), it means there is no synergistic effect, i.e., the breakdown of the mixture is equal to a weighted sum of the component gases and shows a linear effect of \(V_{mix}\) with \(m\). If \(S>0\), it means the gas mixture weighted average is greater than the component gases and is known as a negative synergistic effect. If \(S<0\), it means the gas mixture weighted sum is less than the  
Figure 13: Liquefaction temperature of HFO-1336 mzz (E)/CO\({}_{2}\).  
component gases and is known as the positive synergistic effect. If \(0<S<1\), it shows a synergistic effect.  
Figure 14 above shows the \(S\) value for HFO1336 Mzz (E)/CO\({}_{2}\) and HFO1336 Mzz (E)/N\({}_{2}\) for pressure ranges from 0.05 to 0.3 MPa and a mixing ratio ranging from 70 to 90% of base gas proportion in the gas mixture. It is evident from the figure that for all mixture compositions, the \(S\) values for HFO1336 Mzz (E)/CO\({}_{2}\) are lower than HFO1336 Mzz (E)/N\({}_{2}\). In the case of HFO1336 Mzz (E)/CO\({}_{2}\), the mixture composition of (90/10%) for all pressure ranges shows the \(S\) coefficient value close to zero, indicating a positive synergistic effect. Moreover, the HFO1336 Mzz (E)/CO\({}_{2}\)\(S\) values are 0 to 0.7, while the HFO1336 Mzz (E)/N\({}_{2}\) values range from 0 to 0.8.  
Therefore, even though the two types of buffer gases have almost equivalent dielectric strength, the dielectric breakdown strength of HFO1336 Mzz (E)/N\({}_{2}\) is inferior to HFO1336 Mzz (E)/CO\({}_{2}\) mixtures, as validated through synergistic effect analysis.
## 3 Results
### Force Characteristics Results of Initial Support  
#### 3.2.1 Impact of Tunnel Burial Depth on the Force Exerted on Initial Support  
The Poisson's ratio is the ratio of the absolute value of the transverse positive strain to the axial positive strain when a material is subjected to unidirectional tension or compression. In geotechnics, Poisson's ratio is one of the parameters used to evaluate the properties of soils due to its sensitive response to the physical and mechanical state of the soil.  
With the other simulation parameters held constant, the force on the initial support was calculated at different buried depths of H = 24, 26, 28, 30, 32, 34, and 36 m. The details of the force changes are illustrated in Table 3 and Figure 6a. The bending moment of the initial support was the highest at the top and bottom of the support ring and increased as the buried depth of the tunnel increased. The initial support section was under compressed, with the maximum axial force was located at the waist of the support ring. By controlling the variables, it was observed that the internal force of the initial support changed in the same manner, positively correlated with the buried depth of the tunnel. As the depth increased, it contributed to an increase in the maximum axial force.
# Investigating 2-D and 3-D Proximal Remote Sensing Techniques for Vineyard Yield Estimation
## 3 Results  
### Reference Measurements  
Results of the reference measurements indicated a strong relationship between mass and volume at bunch-level (r\({}^{2}\) = 0.971) and plant-level (r\({}^{2}\) = 0.996). The established relationships between mass and volume served as the basis for the subsequent experiments, which were used to evaluate the 2-D and 3-D techniques.
## 2 Materials and Methods
### Physical Characterization of LIP and Plasma Longitudinal Expansion
#### 2.2.3 Measurement of Laser Plume Longitudinal Expansion Velocity  
A streak camera was used for the laser plasma expansion velocity measurement. The experimental set up is depicted in Figure 2. The laser beam was focused by the lens\({}_{1}\) (\(f=0.6\) m) on the target surface, thereby creating the ablation plasma. The plasma light coming out of the chamber through an optical window was collected by the lens\({}_{2}\) (\(f=0.5\) m), and projected via an aluminum mirror on the entrance slit of the streak camera with magnification \(M=1\). There were two filters positioned in front of the camera--a neutral ND filter for the optimization of the light intensity level, and a cutoff filter for the laser beam radiation. The position and angle of the mirror were precisely set so that the central region of the plasma plume (yellow line in Figure 2) was projected on the entrance slit (\(50\) um) of the streak camera.  
The temporal evolution of the plasma radiation passing through the entrance slit along the \(z\)-axis (representing the distance from the target) is shown in Figure 3, panel A. The main direction of the plasma plume longitudinal expansion is depicted by a red vector in Figure 3, panel B, and the longitudinal expansion velocity is then calculated as the ratio of the corresponding values of \(\Delta z\) and \(\Delta t\). After the maximum value in time is reached, the signal gradually fades because of the plasma plume expansion in the transverse direction. However, this expansion could not be measured with the selected experimental setup.  
Figure 2: Experimental setup for the measurement of the laser plume longitudinal expansion velocity.