esa-sceva/satcom-chunk-collection huggingface dataset:
# Multi-Objective Optimization of LCC-S-Compensated IPT System for Improving Misalignment Tolerance
## 2 Design and Analysis of LCC-S Compensation Topologies
The load ranges from 50 \(\Omega\) to 100 \(\Omega\) were investigated. Table 1 summarizes and lists the system specifications. The two LCC-S resonant topologies were designed with identical voltage/current levels. The power transfer capacities with varying coupling coefficients and loads are shown in Figure 3.  
As can be observed from Figure 2(a), the output voltage of LCC circuit was proportional to the coupling coefficient. For the results of CCO-type topology in Figure 2(b), the power transfer showed a rapid ascent in misalignment condition. The currents flowing through the power supply would be large enough to damage the inverter if drastic misalignment occurs. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Input DC voltage \(U_{\text{d}}\) & 100 V \\ Nominal output level \(U_{\text{RO,D}}/I_{\text{RO,D}}\) & 100 V/1 A \\ Switching frequency\(f_{\text{s}}\) & 85 kHz \\ Coupling range & 0.25–0.5 \\ Load range & 50–100 \(\Omega\) \\ Inductance of transmitting coil \(L_{\text{P}}\) & 270 \(\mu\)H \\ Inductance of receiving coil \(L_{\text{S}}\) & 270 \(\mu\)H \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Specifications of the IPT system. Figure 3: The power transfer properties of LCC-S topology under misalignment: (**a**) the results of CVO-type topology; (**b**) the results of CCO-type topology. In order to indicate the misalignment tolerant capability of the system, the output voltage fluctuation range \(h_{\text{UR}}\) is defined by (12), where \(U_{\text{RO,max}}\) and \(U_{\text{RO,min}}\) are the maximum and minimum output voltages of the LCC-S-compensated IPT system within the whole coupling coefficient and load range. Similarly, the output current fluctuation range \(h_{\text{IR}}\) is defined by (13), where \(I_{\text{RO,max}}\) and \(I_{\text{RO,min}}\) are the maximum and minimum output currents. From Figure 3, voltage and current fluctuations of 33.3% appear with a coupling range from over 0.5 to 0.25. The two LCC-S resonance compensations make the system severely sensitive to coupling variations. Therefore, improving the IPT system performance, including both the coupling and load change throughout the operation, is important. \[h_{\text{UR}}=(U_{\text{RO,max}}-U_{\text{RO,min}})/(U_{\text{RO,max}}+U_{\text {RO,min}})\times 100\% \tag{12}\]  
\[h_{\text{IR}}=(I_{\text{RO,max}}-I_{\text{RO,min}})/(I_{\text{RO,max}}+I_{\text {RO,min}})\times 100\% \tag{13}\]
## 3 Measurement Results
### Temperature Variations  
To ensure the system functionality at extreme conditions, we performed the measurement under different temperatures. Figure 13 demonstrates the effect of temperature variations on the system functionality at \(-27\)\({}^{\circ}\)C (Figure 13a) and 68 \({}^{\circ}\)C (Figure 13b). The digital isolator system is tested under the operational frequency of 250 MHz. The PCB is placed inside the chamber, and the temperature is gradually varied to monitor the waveform on the oscilloscope. The variation rate of the propagation delay from its typical value of 800 ps at room temperature is 9.7 ps/\({}^{\circ}\)C, for temperature variations from 27 \({}^{\circ}\)C and 68 \({}^{\circ}\)C, as shown in Figure 13b. Therefore, the propagation delay is insensitive to temperature variations.
# Design and Implementation of a Six-Degrees-of-Freedom Underwater Remotely Operated Vehicle
## 2 Mathematical Model
### Kinematic Equations  
Since two coordinate systems are utilized in the ROV model, a coordinate transformation matrix is used to transfer the ROV's motion representation from the BF frame to the EF frame or vice versa. Hence, the kinematic equations for an ROV are expressed as follows:  
\[\dot  
\[J_{2}(\eta_{2})=\begin{bmatrix}1&s\phi t\theta&c(\phi)t\theta\\ 0&c\phi&-s\phi\\ 0&s\phi/c\theta&c\phi/c\theta\end{bmatrix} \tag{4}\]  
where s, c, and t denote sin, cos, and tan, respectively.
## 1 Introduction
Moreover, anisotropy significantly influences both indirect and direct tensile tests, as well as the tensile mechanical behavior of rocks. Currently, the effect of anisotropy on the indirect tensile behavior of rocks has been extensively studied, but the direct tensile behavior remains incompletely understood. Furthermore, the influence of anisotropy on rock tensile behavior is not consistent, and the differences between direct and indirect tensile strengths have seldom been systematically examined. To address these research gaps, we conducted the Brazilian splitting test (BST) and a novel direct tensile test (DTT) proposed by [PERSON] et al. [23] on Longmaxi layered shale under various loading angles, combined with acoustic emission (AE) monitoring. This study aimed to clarify the impact of anisotropy on the direct and indirect tensile strengths and failure modes of layered shale, while also examining the discrepancies between direct and indirect tensile strengths across different rock types. The findings of this research are intended to establish a theoretical foundation and provide practical insights for addressing engineering challenges, such as wellbore stability and hydraulic fracturing in anisotropic formations.
# Method for Measuring Surface Charge on Insulating Materials Based on the Vibrating Capacitor Method
## 3 Results and Discussion
### Relationship between Measured Potential and Charged Area  
When the tested material is a dielectric substance, due to its low conductivity, surface charges adhere to the material surface. Different measured potentials exist at different distances between the probe and the charges. Therefore, by establishing a two-dimensional axisymmetric model as shown in Figure 1a, with the lower surface of the probe maintained at a distance of 2 mm from the upper surface of the tested material, when the surface charge density of the charged region is set to 7.08 \(\times\) 10\({}^{-6}\) C/m\({}^{2}\) as \(\sigma_{ex}\), the results, as shown in Figure 4, indicate that the measured potential rapidly increases within a radius of 10 mm as the charged area gradually increases from a radius of 0.5 mm to the entire lower surface with a radius of 145 mm uniformly distributing positive charges. When the radius of the charged area is 10 mm, the measured potential value approaches a peak of 3438.75 V. After the radius of the charged area exceeds 10 mm, the measured potential gradually decreases, reaching close to 2000 V as the charged radius reaches its maximum. According to Formula (4) in the parallel plate capacitor model, it can be calculated that the measured voltage is 2000 V when the lower surface of the tested material carries the currently set surface charge density under ideal conditions. It can be observed that the measured potential in the simulation experiment gradually approaches the theoretical value as the radius of the charged area increases. Furthermore, it is found that when the charge density is constant, the measured potential of the area with a radius of 10 mm is significantly greater than that of the entire lower surface with uniformly distributed charges. We speculate that this phenomenon, where a region with a smaller charge quantity exhibits a larger measured potential, is due to edge effects caused by uneven electric field line distribution.  
Figure 4: Relationship between measured potential and size of charged region below the probe.
# FE-Study on the Effect of Gradient Concrete on Early Constraint and Crack Risk
## 2 Finite Element Model and Material Properties Used in Analysis (Materials and Methods)
### Material Properties
#### 2.2.4 Requirements for Low Hydration Energy Core Concrete  
The concrete in the core has different requirements to the concrete on the surface. The number of freeze-thaw cycles in the concrete decreases from the surface to the center, therefore the necessary freeze-thaw resistance decreases. The prevention of concrete carbonation is relevant to the concrete cover, since carbonation starts on the outer surface and leads to carbonate-induced corrosion of the reinforcement. If the carbonation front reaches the first reinforcement layer, actions must be taken. There is no need for concrete with high resistance to carbonation below the reinforcement. Therefore, the core of the concrete does not need to fulfill the criteria for the exposure classes XF3 and XC4.  
The thermal energy released during cement hydration is dependent on the cement content, the type of cement and its grinding fineness. Hence choosing a cement with low heat generation or the use of additions with latent hydraulic activity (type II according to [2]) are possibilities to reduce the hydration energy [13; 14; 15]. A cement with low hydration energy (CEM III/B) is chosen for the core concrete. CEM III/B consists of 20-34% clinker and 66-80% blast-furnace slag. The durability requirements in the core do not have as high requirements on cement content and the maximum w/c ratio. In mass concrete, the released thermal energy of the concrete is a major problem causing restraining stresses in the concrete and leading to crack formation. From a durability point of view, the cement content could be lower than in the exposed surface layer. In a mass concrete member the function of the concrete in the core is mainly the mass of the concrete and to a certain degree the concrete stiffness and its compressive strength. If the cement content in the core is reduced and w/c ratio is kept constant the water content might be too low to produce a processable concrete. Because of a decreased requirement of durability in the concrete core, the w/c ratio could be increased. A change of the w/c ratio should consider the relevant consequences (for example on the concrete compressive strength or on shrinkage). The consistence class depends mainly on the cement content and in the admixture of concrete plasticizer, if the w/c ratio is limited. The main defined material properties for the concrete in the core are displayed in Table 2. The requirements of concrete compressive strength in core zones of mass concrete structures are often rather low (C25/30 to C30/37 according to [41; 42]) in relation to common required concrete compressive strengths reached by durability criteria (C40/50 and higher).
## 4 Results and Discussion
### Localization Results Using Linear Regression
Initially, the model demonstrated a high R\({}^{2}\) value of 0.9361 and a low RMSE of 1.4614. As features were progressively removed, the R\({}^{2}\) value gradually decreased, and the RMSE increased, indicating a reduction in the model's explanatory power and accuracy. It should be noted that the R\({}^{2}\) value remained stable until the ninth feature was removed, after which a more significant decline was observed. This suggests that the first eight features removed had a comparatively limited impact on the performance of the linear regression model, and the remaining features were more influential in predicting the label. In summary, these findings suggest that all features contribute to the prediction of the impact location and should be retained in the linear regression model. Figure 7: The rank of features in ascending order.
## 3 Methods and Modeling
### Decentralized Decision in the Supply Chain (DD)  
In this scenario, merchants base their decisions on the principle of maximizing their own profits, forming a dynamic oligopolistic market game model, specifically, the Stackelberg game. Given that the implementation of advanced IT incurs service improvement and additional costs, and to avoid being at a disadvantage in the price war, Merchant 2 opts to set its prices after Merchant 1. The sequence of the game is as follows: first, Merchant 1 formulates a strategy to maximize its own profit, and then Merchant 2 determines its profit level based on Merchant 1's pricing. However, Merchant 1 is aware of Merchant 2's behavior, so Merchant 1 will make its final strategy based on Merchant 2's reaction function and its own pricing. The inverse deducing method is employed to calculate the optimal solution of the model. The optimal pricing, the profit, and the optimal service differentiation in DD are as follows (the derivation process is provided in Appendix A.3).  
The optimal pricing strategies \(p_{i}^{*}\) for the merchants are as follows.  
\[\left\{\begin{array}{l}p_{1}^{*}=\frac{\beta(4\delta_{1}-3\delta_{2})\Delta s +(4\delta_{1}-\delta_{2})\Delta\delta}{4\pi[2\delta_{1}-\delta_{2})}\\ p_{2}^{*}=\frac{\delta_{2}(\Delta s-\delta_{2})\Delta s}{2\pi(2\delta_{1}- \delta_{2})}\\ \end{array}\right. \tag{7}\]  
The profit of merchants \(\pi_{i}^{d}\) and the overall cross-border supply chain \(\pi^{d}\) are as follows.  
\[\left\{\begin{array}{l}\pi_{1}^{d}=\frac{(K_{2}\Delta\delta)^{2}+2\delta K_ {2}K_{3}\Delta\delta s+(\beta^{2}K_{1}^{2}-8\alpha\eta K_{1}^{2}\Delta\delta)( \Delta s)^{2}}{16\pi K_{1}^{2}\Delta\delta}\\ \pi_{2}^{d}=\frac{\delta_{2}(\Delta\delta_{2}-\Delta\delta)^{2}}{8\pi K_{1} \Delta\delta}\\ \pi^{d}=\frac{K_{4}(\Delta\delta)^{2}+2\beta K_{5}\Delta\delta s+(\beta^{2}K_ {6}-8\alpha\eta K_{1}^{2}\Delta\delta)(\Delta s)^{2}}{16\pi K_{1}^{2}\Delta \delta}\\ \end{array}\right. \tag{8}\]  
In Equation (8), \(K_{1}\sim K_{6}\) are represented as follows.  
\[\begin{array}{l}K_{1}=2\delta_{1}-\delta_{2}\\ K_{2}=4\delta_{1}-\delta_{2}\\ K_{3}=4\delta_{1}-3\delta_{2}\\ K_{4}=16\delta_{1}^{2}-4\delta_{1}\delta_{2}-\delta_{2}^{2}\\ K_{5}=16\delta_{1}^{2}-20\delta_{1}\delta_{2}+5\delta_{2}^{2}\\ K_{6}=16\delta_{1}^{2}-20\delta_{1}\delta_{2}+7\delta_{2}^{2}\\ \end{array} \tag{9}\]  
The optimal service differentiation \(\Delta s^{d}\) can be determined as follows.  
\[\Delta s^{d}=\frac{\beta K_{5}\Delta\delta}{8\alpha\eta K_{1}^{2}\Delta\delta- \beta^{2}K_{6}} \tag{10}\]
# Performance and Control Strategy of Real-Time Simulation of a Three-Phase Solid-State Transformer
## 2 SST Topology  
The Figure 1 shows the three-phase SST considered; the converter is integrated by three conversion stages (\(VSC_{i}\), \(DAB\) and \(VSC_{o}\)). \(VSC_{i}\) operates as an Active Front End (AFE) and regulates the voltage across the capacitor \(C_{i}\). The DAB (Dual Active Bridge) stage is a DC-DC high/medium frequency isolated converter operating in a phase shifted modulation scheme (CPS), as an effect of the higher commutation frequency the magnetic coupling transformer reduces its volume and size. Finally \(VSC_{o}\) operates as an inverter to achieve the power transfer to the output feeders. Due to the structure of each module, active power transfer can be transferred bidirectionally, and the \(VSC\) converters add the capabilities to develop ancillary functions as reactive power compensation, harmonics mitigation, power factor correction, among others.  
In addition, the incorporation of the SST to the AC networks is using an LCL filter. The grid side inductor is estimated from the grid short circuit power (\(S_{CC}\)), and all the inductor elements associates a series loss resistance estimated for a quality factor \(Q_{f}\geq 20\). The values of the filter inductors are chosen to achieve the direct location of the resonance frequencies of the filter (\(f_{1}\) and \(f_{2}\)) and achieve the proposed nominal power for the converter which is 1 MW.
## 3 Empirical Results and Analysis
### Robustness Test  
#### 3.2.1 The Placebo Test  
In order to exclude the impact of other unknown factors on the selection of policy pilot provinces, it is essential to carry out a placebo test to ensure that the conclusion of this study is caused by the implementation of the APCP Action Plan policy. The Placebo test is a regression consistent with the benchmark regression by randomly selecting several virtual treatment groups in the whole sample, thus providing a robust guarantee for the conclusion of this study [8]. In this paper, 10,000 times of sampling are conducted in 30 provinces in China. In each sampling, 11 provinces were randomly selected as the virtual treatment group, and the remaining 19 provinces as the control group. Regression analysis was performed according to Panel OLS-DID and fixed-effect model.  
In the kernel density distribution diagram of the core explanatory variable Policy, i.e., Figures 2 and 3, the \(x\)-axis is the \(t\)-value of the policy coefficient of the core explanatory variable estimated from 11 provinces randomly selected for 10,000 times as the virtual treatment group, and the y-axis is the corresponding \(p\)-value. The curve represents the \(t\)-value distribution of the core explanatory variable policy coefficient. As can be seen from the above figure, the absolute values of the t value of most of the sampling estimation coefficients are less than 2, and the \(p\) values are above 0.1, which indicates that the APCP Action Plan has no significant effect in these 10,000 times random sampling. Therefore, the conclusion of this paper can be concluded as robust through the placebo test.
## 4 Results
### Trade-Off Study  
Concept models have to be evaluated on the basis of part mass, its structural features, but also on a technological point of view. Many actual design efforts aim at combining both structural and economical aspects [25]. In this way, a first analysis includes the design performance (structural aspect) and a second one, the industrialisation (economical aspect). Figure 11 summarises the performed trade-off study based on both the product and process elements, considering the four concepts (a in its third refinement version (V3), b, c, and d).  
The first analysis is based on KPIs such as mass, part compliance and elastic strain energy minimisations; in addition, a structural score has been calculated. The result, as expected, is that concept (a) shows the best topology and the best performance: while not the lightest in mass, it has the best stress state, stiffness and the lowest strain energy. Subsequently, the volume of each part, including its supports, has been considered to quantitatively evaluate changes in material, energy and  
Figure 11: Key performance indicators (KPIs) matrix involved in the trade-off study step: the four concepts (**a–d**) are compared in the columns.  
Figure 10: Industrialisation study of concepts (**a–d**).  
machine time usage. Then, the calculated score has been added to the first to obtain a total score for concept selection, taking into account even production costs. Results from the first analysis change, for example concept (a), which showed the best structural score, is the one with the maximum material usage. In particular, concept (c), despite having quite lower features with regard to stiffness, stress state and strain energy, shows lower mass (just higher than concept (d)) and strongly requires less support material, so the estimated build time is reduced by 14%. Considering both analyses, the best total score is assigned to (c) and thus it has been selected for the final design.
# Using Financial Instruments to Transfer the Information Security Risks
## 5 Requirements for Information Security Derivatives  
World Economic Forum identified that risk markets were one of the two ways to deal with systemic risk in information security domain [77], shown in Figure 4. Risk markets can provide a variety of financial instruments such as indemnification, insurance, and _structured risk-transfer solutions_ for an organization to address the information security risks [76].  
An alternative to \"statistical\" approach of cyber-insurance is to hedge the cyber risks through an \"economic\" approach. The economic approach is most suited for correlated risks. The principle behind the economic hedge mechanism is the concept of negative correlation. The hedger takes a position that is correlated with the risk but in the opposite direction (negatively correlated). The economic hedge mechanism is different from the statistical hedge mechanism in a way that it does not require a large number of people. Furthermore, there is no need of an actuarial table with  
Figure 4: Cyber Risk Framework (adapted from [77]).  
the frequency of the underlying event (risk). Thus instead of pooling (insurance) the risks, the risks are traded in a market (exchange or over-the-counter).  
Thus, based on the problems identified in Section 4, and the review of literature on risk-hedging financial instruments [4; 5; 61; 7; 31; 62; 63; 64; 78; 79] we have identified the following fourteen requirements for the information security derivatives:  
1. The financial instrument should allow an effective and efficient hedging mechanism for the risk exposure to the underlying information security event. The information security derivatives should perform better than the cyber-insurance products on the following properties.
2. Increased information elicitation and aggregation
3. Strong manipulation resistance
4. Increased market products and size
5. Increased scalability
6. Rapid implementation
7. Increased liquidity
8. Reduced transaction cost
9. Increased price transparency
10. Reduced cost of capital
11. Reduced risk to the issuer or market operator
12. Reduced settlement and clearing costs
13. Diversification of counterparty credit risk
14. Increased data generation  
A mapping of problems in cyber-insurance products and corresponding functional requirements in ISD to address the aforementioned problems is shown in Table 5.
## 1 Introduction  
Double-shell tanks (DSTs) are a critical part of the infrastructure at the U.S. Department of Energy's Hanford site, where a large volume of defense-related nuclear waste is being managed and processed toward ultimate storage in an immobilized state. Hanford DSTs have been used for interim storage of partially liquid nuclear waste since their construction in years 1971-1986. They are expected to continue to serve this function until 2050, which is the target date for completion of the immobilization process for all Hanford nuclear waste. If this target is reached, DSTs will have been used 14-15 years beyond their original projected lifetime [1]. Consequently, for the next approximately 30 years, the integrity of Hanford DSTs for storage of nuclear waste will need to be monitored.  
Under the direction of the U.S. Department of Energy's Office of River Protection (DOE-ORP), the Pacific Northwest National Laboratory (PNNL) has partnered with Hanford Tank Operations contractor Washington River Protection Solutions (WRPS) to develop a robotic non-destructive evaluation (NDE) technology for DSTs. The NDE process is expected to have two phases. The first phase will use a low-resolution electromagnetic acoustic transducer (EMAT) sensor [2, 3] developed by the Southwest Research Institute [4] to scan large regions of the primary tank bottom. These scans will be used to prioritize air slots, designed for cooling, for deployment of a robot-driven high-resolution guided wave phased array (GWPA) sensor [5] developed by Guidedwave [6, 7].  
Continuous monitoring of the robot's position as it navigates the narrow air slots in the confined space between primary and secondary tanks is critical for the decision support to operators and will ultimately allow robot control to be automated. It is also necessary for interpretation of the high-resolution ultrasonic data from multiple locations. Knowing these locations with a precision of \(\pm 0.5\) inches allows a map to be constructed of regions of interest for repeated inspection. Methods under development to track robot location with this precision include sound-wave reflections, length of cable laid out to the robot, and the optical methods discussed in this paper.  
Due to poor illumination of the air slot, location tracking by video analysis is limited to relative measurements of short distances. Absolute location obtained by chaining these short movements together can lead to a large accumulation of error. Laser ranging does not suffer from these limitations but may fail due to motion of the robot that moves the laser off target. Videos can detect these failures and initiate tracking by image analysis based on the last valid laser-ranging data. The return of the laser to the target resets the absolute location. This combination of optical techniques was investigated in a laboratory mockup of air slot and robot.