esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Numerical Analysis and FEA Model  
As stated above, a comprehensive stress analysis is carried out on a thick-walled rotating cylinder made of Al-SiC\({}_{\rm{p}}\) composite using both analytical and numerical methods. However, for the purpose of analysis and the implementation and validation of the formulated equations derived and to display some typical presentable numerical values and results, some typical values for the investigated parameters, dimensions, materials properties, pressure conditions, etc., are assigned. The typical depicted values used in the study are: cylinder material is made of Al-SiC\({}_{\rm{p}}\) composite containing 10 vol.% of SiC\({}_{\rm{p}}\), Inner radius: \(r_{in}\) = 300 mm, Outer radius: \(r_{out}\) = 450 mm, \(n\) = 1, \(B=1.0\times 10^{-85}(\rm{m}^{2}/\rm{N})^{\rm{h}}\), \(\rho=2900\) kg/m\({}^{3}\), \(P_{in}\) = 60 Mpa, \(P_{out}\) = 40 Mpa. The rotational speeds of 300, 500, and 1000 rad/sec were also depicted to display typical sample results.  
However, for the FEA method, a cylinder is modeled and meshed by an axisymmetric element (PLANE183 2D Structural Solid) in ANSYS(r) [39], as shown in Figures 1 and 2. Also, boundary conditions for the cylinder are free in the \(x\)-direction and fixed in the \(y\)-direction at both ends.  
Figure 1: PLANE183(Quadrilateral) Geometry.  
Figure 2: Cross-section of cylinder section meshed by 15 axisymmetric elements.  
It is important to state that, to get and extract the values of the equivalent creep strain, which is the independent dominant variable in the model, we have to determine first the equivalent creep strain and then apply it in the constitutive model (Norton Equation) to get the Von-Mises stress, and consequently substituting these values in material properties laws, all strains and strain rates will be attained. At this stage, it is recognized that the model analysis time is the main factor that affects the equivalent creep strain, and this time is greatly influenced by rotational velocity \(\omega\). Therefore, to identify the proper time model to be used to determine strain rate values, a series of trial-and-error tests to establish the relation between rotational velocity \(\omega\) and analysis time has to be conducted, as can be seen in Figure 3.
# A Hybrid-Cryptography Engine for Securing Intra-Vehicle Communications
## 4 Crypto-Engine Implementation in the EMERGE Project  
As a main target of the EMERGE project is to design and develop novel on-board units with security-by-design guarantees, the Crypto-Engine has been proposed and selected by the whole partnership as a native solution for securing the intra-vehicle non-GNSS sensor communications. In particular, the Crypto-Engine has been requested to provide source authentication for every communication as the primary task while supporting the encryption and decryption of sensor data as additional tasks.  
Given the loose latency requirements for non-GNSS communications, the \"EMERGE version\" of the Crypto-Engine has been developed and deployed entirely via software implementation in a separate single-board computer (SBC) platform (i.e., without additional hardware acceleration). Furthermore, authentication is provided with a custom EAP [65]-based authentication protocol in which the Crypto-Engine covers both the _Authenticator_ and _Authenticator Server_ roles.
## 5 Experiments and Results
### Overall Performance Comparison of Models
By effectively mitigating the class imbalance problem through fault sample generation, the model significantly outperforms unaugmented CNN, LSTM, and CNN-LSTM combinations, as well as traditional machine learning methods, in terms of both classification performance and robustness for power battery fault detection.
## 4 Hydrothermal Pre-Treatment
### Effect of Pre-Treatment on Cellulose  
Cellulose constitutes the 11-53% (dry basis) of the total lignocellulosic biomass [46]. The cellulose chains contain a number of hydroxylic groups, which leads to the formation of hydrogen bonds in the same chains or in the chains in the vicinity. Interlinking of cellulose chains by hydrogen bonds and van der Waals forces, results in high tensile strength microfibrils [49]. Cellulose molecules have different levels of crystallinity due to its different orientation throughout the structure-low or amorphous crystallinity and high or crystalline crystallinity [50]. If the crystallinity index of cellulose crystals is high, then it is difficult to degrade it and vice versa. The cellulose microfibrils are also attached to each other by pectin and hemicellulose, and they are covered by lignin. This complicated structure of cellulose makes it difficult to be degraded by chemical and biological attacks [51]. The bonds are so strong that they do not break even at high temperature boiling water [52]. The disruption of the inter and intra-hydrogen bonds by the hydrothermal pre-treatment can change the crystallinity structure of cellulose [53]. However, complete disintegration is not possible [54]. The cellulose crystal structure, amount of bound water and the degree of intermolecular regularity determines the intensity of the hydrogen bonds [52]. [PERSON] et al. [55], reported that cellulose begins to decompose at temperature of 230 \({}^{\circ}\)C, and the reaction was completed at 295 \({}^{\circ}\)C. [PERSON] et al. [56] stated that cellulose got hydrolysed to glucose in 120 s at temperature of 300 \({}^{\circ}\)C, and pressure of 8.9 MPa. [PERSON] et al. [57] studied the hydrothermal pre-treatment of cellulose at temperature of 200 \({}^{\circ}\)C and 400 \({}^{\circ}\)C and reaction time of 5 min to 2 h, whereby, the solubilised products contained aldehyde, sugars, phenols, ketones, and acid groups. [PERSON] et al. [58], studied the batch thermophilic anaerobic digestion of Giant need, hydro-thermo-chemically pre-treated at temperature of 150 \({}^{\circ}\)C and 180 \({}^{\circ}\)C, time of 10 min and 20 min, and with/without sulphuric acid (2% _w/w_) as catalyst. The catalyst addition was done in two ways: one immediately before the hydrothermal treatment and another as 24 h prior to the steam cooking. Cellulose, owing to its crystalline and thermal-resistant structure, dissolved just modestly in the pre-soaking thermo-chemical pre-treatment. Whereas hemicellulose dissolved to a great extent at the same temperatures (150 and 180 \({}^{\circ}\)C).  
Figure 2: Effect of hydrothermal pre-treatment on the lignocellulosic biomass: (**a**) biomass without pre-treatment; (**b**) hydrothermal pre-treatment of lignocellulosic (adapted with permission from [PERSON] et al. [48]. Copyright (2009) American Chemical Society).
## 1 Introduction  
Emission of nitrogen oxides (NO\({}_{x}\)) will lead to severe environmental problems. NO\({}_{x}\) is considered to be responsible for the formation of photochemical smog, acid rain, tropospheric ozone, ozone layer depletion, and a variety of health problems for human beings [1; 2; 3].  
Selective catalytic reduction (SCR) technology is one of the most efficient approaches to reduce NO\({}_{x}\) emissions [4; 5; 6]. Reducants such as urea or ammonia (NH\({}_{3}\)) are injected into the flue gas from an ammonia injection grid (AIG) [7; 8; 9]. The typical SCR reactions include [10; 11]:  
\[4\text{NO}+4\text{NH}_{3}+\text{O}_{2}\to 4\text{N}_{2}+6\text{H}_{2}\text{O} \tag{1}\]  
\[4\text{NO}+6\text{NH}_{3}\to 5\text{N}_{2}+6\text{H}_{2}\text{O} \tag{2}\]  
The SCR-deNO\({}_{x}\) efficiency is influenced by reaction temperature, residence time, space velocity, and the uniformity of both flue gas velocity and NH\({}_{3}\) concentration [12; 13]. Therefore, to achieve high NO\({}_{x}\) reduction efficiency and low NH\({}_{3}\) slip, optimal design of the flow field and non-uniformed NH\({}_{3}\) injection strategy should be carried out for the SCR-deNO\({}_{x}\) facilities [14].  
The SCR-deNO\({}_{x}\) facilities are usually divided into \(\pi\) type and tower type according to their overall shapes. So far, many studies have been conducted on the optimization of flow field for the \(\pi\) type SCR-deNO\({}_{x}\) facilities. The baffles geometry and the corresponding configuration have been investigated [15; 16; 17]. Attempts have also been made to reduce difficulties in performing the non-uniformed NH\({}_{3}\) injection strategy and to achieve a more homogeneous distribution of NH\({}_{3}\)[18; 19]. However, research on the optimal design of the tower type SCR-deNO\({}_{x}\) facilities are scarce. A tower type SCR-deNO\({}_{x}\) facility usually has fewer turnings and a huge expansion duct, which implies a large sectional area and less turbulence. Nowadays, with an increasing number of tower type SCR-deNO\({}_{x}\) facilities [20; 21], it is necessary to implement flow regulation and ensure optimal design. In the meantime, spatial constraints are common due to the compact configuration. Hence, it is more challenging to find an effective way to optimize the tower type SCR-deNO\({}_{x}\) facilities.  
Computational fluid dynamics (CFD) simulation is nowadays commonly applied to the flow field regulation of SCR-deNO\({}_{x}\) facilities [22; 23]. In this paper, the optimal design of the tower type SCR-deNO\({}_{x}\) facility for a 1000 MW coal-fired power plant is presented. A combination of crossed baffles and small-sized arc-shaped baffles are used to deal with the spatial constraints and to regulate the flow field. The influence of flow regulation at the AIG is evaluated. In addition, pressure loss and the consumption of steel plate are considered. A flow model test (FMT) is carried out to verify the CFD simulation results. This may provide an effective approach to optimize the tower type SCR-deNO\({}_{x}\) facilities.
# Nanofiltration of Simulated Acid Mine Drainage: Effect of pH and Membrane Charge
## 2 Materials and Methods
### Membrane Filtration Experiments  
NF experiments were performed using an in-house custom-built flat sheet cross-flow filtration membrane coupon tester (CT) (Figure 1), capable of testing 6 membrane coupons concurrently.  
The CT consisted of 6 membrane coupon filtration cells arranged in a series configuration (feed originates from the reetentate of the upstream adjacent cell), each with a membrane area of 26.55 cm\({}^{2}\). The installation consists also of a 60 L feed tank and a high-pressure centrifugal pump.  
Nanofliltration experiments were carried out in a batch recirculation mode (total permeate recovery of about 0.1%). By efficient cell design and appropriate hydrodynamic conditions, the effect of concentration polarization (see Figures 1 and 2 in Appendix A) was rendered negligible during all filtration experiments. As such, the ion rejection and permeate flux were calculated using the following Equations:  
\[R_{upp}=\left(1-\frac{c_{p}}{c_{f}}\right), \tag{5}\]  
\[\Pi=iMRT, \tag{6}\]  
\[\Delta\Pi=\Pi_{f}-\Pi_{p}, \tag{7}\]  
\[J_{v}=A(\Delta P-\Delta\Pi)=\frac{V_{p}}{A_{m}t}, \tag{8}\]  
in which the symbols and subscripts have their common meanings as specified in Appendix B.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Ion** & **Concentration (mg/L)** & **pH** \\ \hline Calcium, Ca\({}^{2+}\) & \(250\pm 10\) & \\ Copper, Cu & \(370\pm 10\) & \\ Magnesium, Mg\({}^{2+}\) & \(2400\pm 100\) & \\ Manganese, Mn & \(490\pm 10\) & \\ Sodium, Na\({}^{+}\) & \(3200\pm 100\) & \\ Sulfate, SO\({}_{4}\)\({}^{2-}\) & \(8700\pm 200\) & \\ Chloride, Cl\({}^{-}\) & \(5000\pm 200\) & \\ Nitrate, NO\({}_{3}\)\({}^{-}\) & \(930\pm 50\) & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Model AMD solution feed composition used in the present study.  
Figure 1: Cross flow nanofiltration setup.  
The target salts were added into the feed tank and recirculated to ensure their complete dissolving and homogenous mixing within the system. Feed sampling was performed before the start of each experiment and, if necessary, adjusted accordingly to the targeted concentrations. The salt concentrations throughout the system were assumed to be constant since the volume loss by permeate sampling (approximately \(6\times 50\) mL) was negligible compared to the feed volume (60 L).  
The feed recirculation flow rate was measured by a flow meter after the last filtration cell. Three valves were used to adjust the fluid flow to the desirable operating conditions. The pressure was measured using a pressure gauge at the retentate of the third filtration cell. This pressure was regarded as the imposed operating pressure, \(\Delta P\), as the pressure drop across the 6 membrane coupon filtration cells was insignificant (below 0.05 bar). Lastly, the temperature was maintained at 25 \({}^{\circ}\)C using a heat exchanger.  
All filtration experiments were first run at 10 bar for 1 h for membrane compaction. After that, permeate samples were collected. The sampling time for all the experiments was 30 min.
###### Abstract  
Active wake management (AWM) via yaw control has been discussed in recent years as a potential way to improve the power production of a wind farm. In such a technique, the wind turbines will be required to work frequently at misaligned yaw angles in order to reduce the vortices in the wake area behind the turbines. However, today, it is still not very clear about how yaw operation affects the dynamics and power generation performance of the wind turbines. To further understand the effects of yaw operation, numerical research is conducted in this paper. In the study, the optimal size of the flow field used in the computational fluid dynamics (CFD) calculation was specifically discussed in order to obtain an efficient numerical model to quickly and accurately predict the dynamics and the performance of the turbines. Through this research, the correlation between the blade loads during yaw and non-yaw operations is established for aiding yaw control, and the blade loads and power generation performances of the wind turbine during yaw operation under different wind shear and blade deflection conditions are analyzed for understanding the effects of yaw operation. It is found that the optimal size of the flow field for performing efficient and accurate CFD calculations does exist. The misaligned yaw operation generally tends to decrease the loads acting on the blade. However, the aerodynamic energy captured by the turbine rotor and blade loads during yaw operation is not only dependent on the yaw angle of the rotor but is also affected by wind speed, rotor speed, the pitch angle of the blades, blade deflection, and wind shear. Particularly, it is interestingly found that wind shear can cause undesirable fluctuation of the power, which will challenge the power quality of the wind farm if no measures are taken.  
active wake management; yaw operation; wind turbine; computational fluid dynamics +
Footnote †: journal: Applied Physics Letters
## 1 Introduction
### Leak Detection Methods
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Objective** & & **Advantage** & **Disadvantage** \\ \hline \multicolumn{5}{c}{**Visual Inspection**} \\ \hline \multirow{3}{*}{\begin{tabular}{c} Closed-circuit television \\ (CCTV) \\ \end{tabular} } & \multirow{3}{*}{Inspects the inner surface of the pipe.} & a. & Applied to sewer and storm & a. & Requires a pan and a tilt. & The carrier speed of the \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multirow{3}{*}{\begin{tabular}{c} Laser scan \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} Measures the inner pipe distance \\ by laser. \\ \end{tabular} } & a. & Used for relatively longer & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multicolumn{5}{c}{**Electromagnetic Methods**} \\ \hline \multirow{3}{*}{\begin{tabular}{c} Ultra-wideband (UWB) pulsed \\ radar system: P-scan \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} Inspects the condition of the pipe \\ by transmitting and receiving \\ electromagnetic pulses in the \\ nano and pico-second ranges. \\ \end{tabular} } & a. & Potential for pipe condition & & \\  & & & & assessment & Pre-commercial prototype of this \\ \hline \multicolumn{5}{c}{**Acoustic Methods**} \\ \hline \multirow{3}{*}{\begin{tabular}{c} Sonar profiling system \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} Inspects precise pipe \\ cross-sections and potential \\ leakages. \\ \end{tabular} } & a. & Accurate measurements are & a. & High-frequency sonar has \\  & & & attained & b. & Low-frequency sonar has \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multirow{3}{*}{\begin{tabular}{c} Impact echo \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} Inspects pipe thickness based on \\ the use of impact-generated stress \\ waves. \\ \end{tabular} } & a. & Applied to materials such as & a. & Frequency domain analysis \\  & & & concrete, stone, plastic, & \\  & & & masonry materials, wood, & \\  & & & and some ceramics & \\  & & & & \\  & & & & \\ \hline \multicolumn{5}{c}{**Ultrasound Methods**} \\ \hline \multirow{3}{*}{\begin{tabular}{c} Guided wave ultrasound \\ \end{tabular} } & \multirow{3}{*}{\
\begin{tabular}{c} Inspects pipe cross-sections based \\ on propagating a wave for a long \\ distance. \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} Used to characterize metal loss due \\ to the corrosion \\ \end{tabular} } & a. & Only suitable for pipes \\  & & & above 5 cm in diameter and \\ \cline{1-1}  & & & & with wall thicknesses of up \\ \cline{1-1}  & & & & to 4 cm. \\ \hline \end{tabular}
\end{table} 
Table 1: Non-destructive techniques adapted from Liu and Kleiner [7]. the measured reflected pressure waves [8; 9]. It is worth noting that with respect to other techniques, TTBTs are very attractive since the duration of the test is very short and they allow for detecting also devious defects (e.g., partial blockages and illegal branches) which do not give rise to any exterior sign. Moreover, small but sharp amplitude pressure waves allow for reliable fault detection [10].
## 5 Results and Discussion
### Calculation Examples  
The proposed link budget script has been developed to calculate the received signal power by a transmitter and is used to determine the performance of wireless connection between two points. Additionally, with this tool we can also determine the difference between the minimum expected power (which is received) and the receiver's sensitivity, known as link margin for each station. Certain constraints, such as transmission power, free space loss, antenna gain, and cable loss at the transmitter, are taken into account for the design of any transmission system. Therefore, link budgeting is often used to determine the sustainability of the design in order to overcome these constraints and for the system to meet the required specifications. In order to achieve the ability to communicate effectively between the transmitter and the receiver, the signal strength of the receiver must be greater than or equal to the receiver sensitivity.  
In this project, the theoretical calculations that are used from the proposed tool are described in Equations (1), (2), and (5).  
For example, in the first scenario, the Tx power is 24 dBm, the Tx cable loss is 0 dB, the Gt antenna gain is 29 dBi, the Gt antenna gain is 29 dBi, and the total path loss is 122.35 dB. At a distance of 6.175 km, the receiver signal power is calculated, 40.35 dBm, and the link margin is 49.65 dB, as shown in Figure 4.  
In the second scenario, the Tx power is 24 dBm, the Tx cable loss is 0 dB, the Gt antenna gain is 29 dBi, the Gt antenna gain is 29 dBi, and the total path loss is 129.36 dB. At a distance of 6.175 km, the receiver signal power is calculated as \(-47.36\) dBm and the link margin as 42.64 dB, as shown in Figure 5.  
The mathematical formula for each field has been defined and is always shown in the interface, so that the user can input the necessary data for the completion of the formulas, and, by clicking on \"Calculate\", they can generate the results. These results are highlighted by the yellow background, as shown in Figures 6 and 7.  
Figure 4: Theoretical calculation of the link budget at 5 GHz.  
Figure 5: Theoretical calculation of the link budget at 11 GHz.  
Figure 6: Received power calculation, gas attenuation, and total path loss involved at 5 GHz by proposed tool.
## 3 Results and Discussion
### Adsorption Efficiency of LPD Biomass
#### 3.2.8 Adsorption Thermodynamics  
The thermodynamic parameters, including \(\Delta G^{\circ}\), \(\Delta H^{\circ}\), and \(\Delta S^{\circ}\), can be obtained from the van't Hoff equation, Equation (8), as shown in Figure 6 and Table 6. The positive values of the three parameters indicate an endothermic and nonspontaneous process. However, the adsorption system is greatly dependent on adsorption temperature, becoming spontaneous at high temperature where \(T\Delta S\) outweighs \(\Delta H\). The positive value of \(\Delta S^{\circ}\) also suggests an increase in the randomness at the solid-liquid interface during the adsorption.  
Figure 5: Linearized Langmuir (**a**) and Freundlich (**b**) isotherm equations. Conditions: 10–550 ppm Pb\({}^{2+}\) concentration, 50 mL Pb\({}^{2+}\) solution volume, 0.2 g LPD adsorbent dose, pH 6, 25 \({}^{\circ}\)C adsorption temperature, and 150 rpm agitation speed.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**adsorbent** & \multicolumn{4}{c}{**Langmuir**} & \multicolumn{4}{c}{**Freundlich**} \\ \hline \multirow{2}{*}{LPD} & \(q_{m}\) (mg/g) & \(K_{L}\) (L/mg) & \(R^{2}\) & \(R_{L}\) (at C\({}_{0}\) (mg/g) = 165, 550) & \(K_{F}\) & \(1/n\) & \(n\) & \(R^{2}\) \\ \cline{2-9}  & 91.32 & 0.0074 & 0.884 & 0.450, 0.024 & 2.722 & 0.662 & 1.511 & 0.989 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Parameters obtained from Langmuir and Freundlich isotherm models for adsorption of Pb\({}^{2+}\) ion onto LPD.  
Based on the discussed overall results, the adsorption mechanism is an endothermic, PSO, chemical process governed by the Freundlich heterogeneous surface, and is more favorable at high temperature.  
_Lavandula pubescens_ is abundantly available in Saudi Arabia, particularly in the western region, and can be collected for free as a raw, low-cost material for, e.g., medical, pharmaceutical, and environmental applications [20,21]. However, as _Lavandula pubescens_ biomass used in this work is an abundant wild plant, it can be assumed as a low-cost material, and recovery of the spent adsorbent may be costlier, compared to the raw material itself; therefore, reusability experiments were not further pursued.