esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Effect of Pilot-Hole Size (Using 20-Pef Test Blocks)  
In the 2.7-mm pilot-hole group, the insertional torque for Cy/Co-S, Co/Co-S, Cy/Cy-S, Cy/Co-V, Co/Co-V and Cy/Cy-V was 2.85 \(\pm\) 0.04, 3.02 \(\pm\) 0.05, 3.02 \(\pm\) 0.09, 3.33 \(\pm\) 0.03, 2.85 \(\pm\) 0.04 and 2.48 \(\pm\) 0.10 N\(\cdot\)m, respectively, compared with 2.65 \(\pm\) 0.05, 2.77 \(\pm\) 0.04, 2.77 \(\pm\) 0.05, 3.09 \(\pm\) 0.09, 2.63 \(\pm\) 0.05 and 2.35 \(\pm\) 0.09 N\(\cdot\)m, respectively, in the 3.2-mm group, and 2.37 \(\pm\) 0.04, 2.59 \(\pm\) 0.03, 2.35 \(\pm\) 0.08, 2.74 \(\pm\) 0.09, 2.46 \(\pm\) 0.09 and 1.86 \(\pm\) 0.06 N\(\cdot\)m, respectively, in the 3.7-mm group (Figure 7). The highest and lowest insertional torques were found for Cy/Co-V and Cy/Cy-V in all experimental pilot-hole groups. The insertional torque was significantly higher for Co/Co-S and Cy/Cy-S than for Cy/Co-S in the 2.7- and 3.2-mm pilot-hole groups and significantly higher for Co/Co-S than for Cy/Co-S and Cy/Cy-S in the 3.7-mm pilot-hole group. When comparing insertional torque among the three pilot-hole sizes, the value significantly decreased as the pilot-hole size increased.  
In the 2.7-mm pilot-hole group, the Cy/Co-S, Co/Co-S, Cy/Cy-S, Cy/Co-V, Co/Co-V and Cy/Cy-V screw geometries showed a maximal pullout strength of 1756.65 \(\pm\) 41.36 N, 1627.30 \(\pm\) 60.92 N, 1745.22 \(\pm\) 99.86 N, 2285.76 \(\pm\) 45.09 N, 2259.89 \(\pm\) 68.89 N and 2195.99 \(\pm\) 68.72 N, respectively, compared with 1741.22 \(\pm\) 77.00 N, 1507.24 \(\pm\) 97.78 N, 1690.66 \(\pm\) 28.93 N, 2206.05 \(\pm\) 61.34 N, 2122.45 \(\pm\) 57.62 N and 2185.54 \(\pm\) 59.13 N, respectively, in the 3.2-mm pilot-hole group, and 1498.32 \(\pm\) 63.88 N, 1343.69 \(\pm\) 36.92 N, 1497.50 \(\pm\) 73.82 N, 2109.37 \(\pm\) 89.28 N, 1951.71 \(\pm\) 101.80 N and 1965.79 \(\pm\) 49.18 N, respectively, in the 3.7-mm pilot-hole group (Figure 8). The maximal pullout strength was significantly higher for the V-threaded screws than for the S-threaded screws for all three pilot-hole sizes. In the S-threaded group, the pullout strength was significantly lower for Co/Co than for the other two geometries for all three pilot-hole sizes. In the V-threaded group, the pullout strength was significantly higher for Cy/Co than Cy/Cy in the 2.7- and 3.7-mm pilot-hole groups and significantly higher for Cy/Co than Co/Co in the 3.2-mm pilot-hole group.  
Figure 6: Mean ultimate pullout strength for screws of various geometries inserted in a 3.7-mm pilot hole using 20-pcf and 30-pcf test blocks. Groups without significant differences are indicated with the “+” symbol.
# Micro-Satellite Systems Design, Integration, and Flight
## 4 Attitude Control System (ACS) Development
### Battery Voltage Offset Correction
Also, the magnetometer was on to sense the constant offsets surrounding the sensor. With these sensors active, the resulting values could be read by other software. The software used was called \"Motion Sensor Calibration Tool\". Downloading this tool allowed for the hard iron offsets to be calibrated by rotating the CubeSat around the IMU. Datapoints were collected as the CubeSat was rotated. A trajectory path was drawn with each rotation. Once enough of the surface area had been drawn, offset values were shown. Figure 48 below shows a snapshot of the process. Figure 49 shows a clear contour that demonstrates the rotational field of the IMU. The upper right-hand corner displays the hard iron magnetic offsets. The experiment was repeated five times, and the values were averaged. Table 9 below shows the results of each trial. The motion sensor calibration tool gave very accurate and consistent measurements, as shown in Table 9. These values met the requirement 6.0 in Table 5. The soft iron offsets were added to these values to achieve the total iron offsets. \begin{table}
\begin{tabular}{c c c c} \hline
**Trial** & **X Offset** & **Y Offset** & **Z Offset** \\ \hline
1 & \(-14.80\) & \(35.81\) & \(7.13\) \\
2 & \(-13.10\) & \(36.68\) & \(7.04\) \\
3 & \(-13.50\) & \(36.80\) & \(6.30\) \\
4 & \(-13.70\) & \(34.78\) & \(7.46\) \\
5 & \(-13.15\) & \(36.22\) & \(6.71\) \\ \hline avg & \(-13.65\) & \(36.058\) & \(6.928\) \\ \hline \end{tabular}
\end{table} 
Table 9: Hard iron offsets recorded to calibrate the IMU of static EM radiation from onboard electronics.
## 4 Engineering Application of Roadway Expansion Using SCA  
### Scheme Design of Roadway Expansion  
For this mine, due to the need to add an additional transportation track to the 2\(\#\) coal-centralized transportation lane, the current lane width does not meet the requirements for installation, hence an expansion is needed. The specific design of the lane expansion is shown in Figure 9. The lane has a rectangular cross-section with a 5.3 m width and 3.3 m height. The expanded section has a height of 2.3 m, a depth of 1.5 m, and a length of 30 m.  
Figure 8: Monitoring results of hole perimeter stress. (**a**) 300 m hole spacing; (**b**) 400 m hole spacing; (**c**) 500 m hole spacing; and (**d**) comparison of different hole spacings.  
Figure 9: Roadway support and expansion details.  
When applying static cracking agents to rock fracturing projects, the hole diameter should not be less than 20 mm and should not exceed 50 mm, and drilling with diameters of 35 mm and 42 mm is widely used. Multiple expansion stress tests and field practice have verified that 42 mm hole diameter drilling is less likely to experience blowouts; when using static cracking agents to fracture rock, the construction area must have a free face. Larger hole diameters result in more severe blowout phenomena, using 42 mm diameter downward drilling can prevent hole flushing and slurry leakage [26]. In this project, the expansion drilling layout is determined by the on-site rock mechanical properties and geometric dimensions. A borehole diameter of 42 mm is selected. To provide a free surface for SCA roadway expansion, a chamber measuring 2300 mm in height, 1500 mm in depth, and 1000 mm in length needs to be generated at the end of the lane. Subsequently, boreholes are drilled into the chamber end and charged with SCA. A borehole diameter of 42 mm and a drilling depth of 1500 mm are selected. To facilitate grouting and prevent leakage, drilling is conducted at a 10\({}^{\circ}\) downward angle. In a workday, a total of 28 boreholes are constructed. The drilling layout design is shown in Figure 10.  
Based on Section 2, the static cracking agent with 0.3 water-cement ratio is selected. Considering underground construction conditions, a 300 mm hole spacing is selected to ensure fracturing effectiveness. The amount of static cracking agent used per hole is calculated according to Equation (2):  
\[Q=(1+\sigma)*S*L*q \tag{2}\]  
where \(Q\) is the quantity of static cracking agent per hole (g); \(\sigma\) is the loss rate of the static cracking agent; \(S\) is the area of the borehole bottom (cm\({}^{2}\)); \(L\) is the depth of the borehole (cm); and \(q\) is the required quantity of cracking agent per unit volume (cm\({}^{3}\)).  
On-site, the drilling depth is 150 cm, and the area of the borehole bottom is approximately 13.85 cm\({}^{2}\). Considering factors such as drilling fluid leakage, the loss coefficient of static cracking agent is taken as 0.2. Calculating according to Equation (2), the required amount of static cracking agent for a single borehole is approximately 5 kg.
## 3 Results and Discussion
### Modeling of Material Properties  
#### 4.1.1 Concrete  
The concrete was modeled using concrete damage plasticity (CDP). Due to the model's combination of compressive plasticity and isotropic tensile plasticity, it can simulate the concrete in the inelastic zone. The elastic modulus values, the Poisson's ratio, characterization of compressive and tensile behavior, and the plastic damage parameters, are necessary for the plastic damage model. In the concrete damage plasticity model (CDP), the plastic damage parameters are the dilation angle, the flow potential eccentricity, the ratio of initial biaxial compressive yield stress to initial uniaxial compressive yield stress, the ratio of the second stress invariant on the tensile meridian to that on the compressive meridian, and the viscosity parameter which defines viscoplastic regularization. The final four parameters for defining concrete material damage are described in Table 5.  
The experimental compressive stress-strain curve for concrete as illustrated in Figure 4 was used in the FE program. The concrete tensile strength was equal to 2.1 MPa. The modulus of elasticity of concrete (\(E_{c}\)) was 26,985 MPa according to the compressive stress-strain curve (See Figure 4, Section 2.3.1). Two primary failure modes are considered for concrete according to (CDP): compressive crushing and tensile cracking. The stress-strain response under uniaxial tension followed a linear elastic relationship up until a value of the failure stress was attained.  
The initiation of microcracking in the concrete material is correlated with failure stress. A softening stress-strain response was used to illustrate the propagation of microcracks beyond the failure stress. Therefore, elastic modulus, \(E_{c}\), and tensile strength, \(f_{t}\), are required to define the first part of the relationship. For descending branch, the fracture energy \(G_{f}\) approach was used to define the post-peak tension failure behavior of concrete, as shown in Figure 18. The area beneath the concrete's tensile curve following the peak value was the fracture energy \(G_{f}\).  
\begin{table}
\begin{tabular}{c c} \hline \hline Dilation Angle (\(\
abla\)) & 35\({}^{\circ}\) \\ Eccentricity (e) & 0.10 \\ \(f_{bo}/f_{co}\) & 1.16 \\ \(K\) & 0.66 \\ Viscosity Parameter & 0.00005 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Concrete damage parameters (CDP).
# An Improved Ciphertext-Policy Attribute-Based Encryption Scheme in Power Cloud Access Control
## 6 Experiment Analysis
### Time Consumption of the Encrypt and the Decrypt Phase  
In this section, the PCAC scheme has been compared with RAAC in the Encrypt and the Decrypt phase. The result is shown in Figure 7.  
As can be seen in the figure, the time cost in the Encrypt and the Decrypt phase increased with the increase of the number of secret-sharing parties. In the Encrypt phase, the secret-sharing parties were mapped to the SKs directly, instead of using other elements to mark the KSs. Therefore, the Decrypt phase of the PCAC scheme consumed relatively less time.
# Panoramic Digital Image Correlation for 360-Deg Full-Field Displacement Measurement
## 3 Experiments and Discussions
### Evaluation of Separate Camera Parameters Calibration Method
#### 3.2.2 Extrinsic Parameters Details  
In order to estimate the extrinsic parameters of each stereo camera pair in the experimental setup as shown in Figure 3, three sets of images were acquired with three stereo camera pairs from a scene containing the log with the natural texture on the surface. The regions of interest were selected and a number of feature points (approximately 400,000 feature points per camera pair in this paper) were determined in the reference images of the left camera of each set of stereo camera pair, and the distortion parameters calculated in the previous step were used to correct the distortion on the detected image control points. The registrations were established in the current image of the right camera according to the method in Section 2.3.1. By employing the extrinsic parameters estimation method given in Algorithm 2, three sets of optimal relative rotations (obtained by the Rodriguez transform of the rotation matrix) and normalized translation vectors were obtained, respectively, and are listed in Table 2, where the reprojection errors are 0.08 pixels, 0.06 pixels, and 0.12 pixels, respectively, which are very low error levels.
## Materials and Methods
### Establishment and Evaluation of the Models
#### 2.4.3 Optimal Wavelengths Selection  
To remove irrelevant information or noise for adulteration detection, the selection of important wavelengths carrying the most useful information was recommended. The regression coefficients (RC), i.e., the \(\beta\)-coefficients of the optimal PLSR models, were considered as possible feature-related or important wavelengths for the respective component [25]. Coefficients with the highest absolute values are deemed to be key wavelengths for adulteration. Thus, RC was further utilized to select representative wavelengths in carrageenanan adulteration levels determination in our study. With the limited key wavelengths, the PLSR models established using full wavelengths were simplified. All the wavelengths selection steps were executed in Matlab software (R2013b, The Mathworks Inc., Natick, MA, USA).
## 1 Introduction  
Thermechanically controlled processing (TMCP) followed by direct quenching is considered the most powerful and effective processing route to obtain the best combination of the yield strength, good ductility, low-temperature toughness with a good hardenability in the low-carbon microalloyed steels [1]. The final microstructure of the hot-rolled steel is considered the key factor for getting the targeted combination of the mechanical properties and it is controlled by the quenching process following the TMCP. Hence, the microstructures and mechanical properties of low-carbon microalloyed steel can be improved significantly by designing a suitable accelerated cooling/direct quenching process, following the hot deformation schedule [2]. Depending on the chemical composition of the steel and the cooling path, the accelerated cooling rate may promote the formation of bainite with or without the formation of ferrite.  
Low-carbon bainitic steels are used in many structural applications as a result of their good combinations of strength and toughness. Use of structural steels for weight critical applications such as mobile frames and crane booms is desirable to minimize the carbon footprint and save energy. Different alloying elements like Cr, Nb, Mo, and B are used to improve the strength and toughness through promoting the formation of bainite and refining the microstructure [3]. Bainitic ferrite and granular bainite represent the two main microstructure constituents in low-carbon bainitic steels and they are associated with distinct mechanical properties [4; 5; 6]. Cr is widely used to improve the hardenability and thereby promote the formation of bainite by suppressing the formation of high temperature transformation products [7; 8; 9; 10; 11; 12; 13; 14].  
The main objective of the current work is to develop a low-carbon steel with 700 MPa yield strength in combination with good ductility and toughness. To help reach this goal, the effect of Cr and preceding hot deformation of austenite on the continuous cooling transformation (CCT) diagrams of a candidate composition was studied. Following this, the effect of Cr on the microstructures, tensile properties, and impact toughness of hot-rolled and direct-quenched low-carbon bainitic steel plates was investigated.
# Low-Cost Software Evaluation of Communication Delays in Networked Industrial Systems
## 7 Example: DUT Evaluation  
As an example, we used the measurement system to test an off-the-shelf commercial 5-port Ethernet switch [34] as DUT in the \(\mathcal{T}_{DUT}\) topology. In this test the DUT auto-negotiated a speed of \(100\,\mathrm{Mb/s}\) because \(SW\) was so configured. This type of device represents a significant benchmark to evaluate our method, as it is expected to introduce a small average delay with a narrow distribution and small delay variability. Therefore, it might be difficult to tell apart the actual DUT's delay and delay variability from the background measurement noise that the measurement system itself introduces.  
Measurements \(X_{\delta}\) and \(X_{\delta^{\prime}}\) were performed in the \(\mathcal{T}_{\text{base}}\) and \(\mathcal{T}_{DUT}\) topologies--for system calibration and DUT evaluation, respectively--using packet streams consisting of \(m_{l}=10^{5}\) packets of \(l=64\,\mathrm{B}\) bytes each, generated every \(\omega=150\)\(\,\mathrm{\SIUnitSymbolMicro s}\). Table 4 contains the summary statistics of the results and Figure 5 depicts the corresponding delay distributions. As before, the absolute values of the delays are not shown in the table because they are of no particular significance, whereas their difference enables us to evaluate the DUT's behavior.  
As expected, this DUT does not dramatically affect network performance because it introduces a delay of around 8 us, as roughly indicated by the distance between the mode of the two distributions shown in Figure 5. At the same time, its limited effect on delay variability becomes visible when looking at the shape of the those distributions, and even more clearly in the larger values of \(s_{\omega}\) and range listed in Table 4 for \(\mathcal{T}_{DUT}\) with respect to \(\mathcal{T}_{base}\).
## 3 Results and Discussion
### Validation of the Test Setup
#### 3.1.3 Electrode Array with Angular Distances of 90\({}^{\circ}\)  
The second series of three specimens was produced with four electrodes at each height level, corresponding to angular distances of 90\({}^{\circ}\) and so, more electrode arrays for the measurement were possible (see Figures 8 and A1 in Appendix A). According to the investigations described above, the electrical resistivities in the horizontal and vertical direction were determined too. For the plain concrete, it is again visible that the electrical resistivity in both directions is almost identical, while for the fibre reinforced concrete, especially with a fibre content of 40 kg/m\({}^{3}\), the resistivity in the vertical direction is higher than that in the horizontal direction. For the specimens with a higher fibre content, this phenomenon is not visible at the age of 9 days, while at a specimen age of 38 days, the maximum values of the resistivity in the vertical direction are at least higher than those in the horizontal direction. Nevertheless, based on the higher fibre content, a more three-dimensional fibre distribution and orientation can occur and so, the differences in the horizontal and vertical directions will be exalted at medium fibre contents, such as 40 kg/m\({}^{3}\).  
Again, a higher concrete age leads to a higher variation that is caused by differences in the hydration and drying of the different parts of the specimens, where the outer surface shows the fastest drying process and the core of the sample has the highest saturation over time (see Figure A1 in Appendix A).
## 2 Materials and Methods
### Key Input Data for BEPS Simulation
To map crop biomass in the study area, the annual crop inventory map products (in 30 m resolution) from Agriculture and Agri-Food Canada (AAFC) are used [66]. \begin{table}
\begin{tabular}{c c c c} \hline
**Date** & **Tile 14 UNA** & **Tile 14 UNV** & **Field Sampling** \\ \hline
1 May & X & X & \\
26 May & X & X & \\
10 June & X & X & \\
13, 15, 18, 20 June & X & X & X \\
23 June & X & X & \\
27, 28 June & & & X \\
5–6, 11–12, 17, 20–21 July & & & X \\
02 August & X & Partially covered & \\
22 August & X & Partially covered & \\
28 September & X & X & \\ \hline \end{tabular}
\end{table} 
Table 1: Dates of 2016 Sentinel-2 images used in this study for tiles 14 UNA and 14 UNV. “X” indicates a Sentinel-2 image that covers the entire study area. Field sampling was conducted on 13 different dates, 13, 15, 18, 20, 27, and 28 June, and 5, 6, 11, 12, 17, 20, and 21 July.
# A Novel Energy-Saving Route Planning Algorithm for Marine Vehicles
## 4 Computational Simulations  
The ant colony algorithm is improved to realize the path planning of the ship in the marine environment. We use the ocean current model to calculate the current velocity and direction at different times and improve the pheromone update rules by considering the ocean current environment, and finally add the energy consumption factor of the ocean current field to the comprehensive cost function.  
The study area is Lianyungang and its adjacent sea areas, whose boundary is Huangdao and Yancheng. The north-south span of the model is 172 km, while the east-west span is 90 km. The number of model mesh nodes is 6289 and the number of mesh elements is 11,836. The mesh resolution gradually increases from Lianyungang to the sea, and the mesh is the sparsest at the open boundary. Meanwhile, the mesh resolution ranges from 14 m to 4300 m.  
The model validation of the study is carried out by using the tide table data provided by the National Oceanographic Information Center. The tide level station is the Lianyungang Station (34\({}^{\circ}\)45\({}^{\prime}\) N, 119\({}^{\circ}\)25\({}^{\prime}\) E) located inside the Lianyungang Harbor, and the tidal height base level is 290 cm. The comparison of measured data and computed data of water level is manifested in Figure 2. We use the tide table data in December 2021 for validation, and introduce the efficiency coefficient proposed by [PERSON] [28] to evaluate quantitatively the pros and cons of the model calculation results, and the evaluation formula is as follows.  
\[Skill=1-\frac{\sum\limits_{i=1}^{N}\left|P_{i}-O_{i}\right|^{2}}{\sum\limits_ {i=1}^{N}\left(\left|P_{i}-\overline{O}\right|+\left|O_{i}-\overline{O}\right| \right)^{2}} \tag{24}\]  
where \(P\) is the predicted value, \(O\) is the observed value, and \(\overline{O}\) is the average of the observed value.  
The efficiency coefficient SKILL of the model simulation is 0.94 and the evaluation result is excellent, which shows that the effect of model simulation is great, as shown in Figure 3.  
The research area of this paper is Lianyungang and its adjacent waters, which are bounded by Guangdong and Yancheng. Taking it as the original chart data file as shown in Figure 4a, we consider the seaweed farming area in this sea area [29] as an obstacle and rasterize the chart of the sea area. The blue area is the shallow point in the experiment, and the red area is the obstacle, as shown in Figure 4b.  
Figure 4: (**a**) A sea area in EC, and (**b**) grid map of the sea area.  
Figure 3: Validation of water level.  
Figure 2: Study area and mesh.  
The established dynamic ocean current model of Lianyungang has a north-south span of 172 km and an east-west span of 90 km. In simulation test for ships, the marine vehicle used is a bulk carrier, whose length, breadth, and draft are 185.0 m, 32.26 m, and 12.0 m, respectively.