esa-sceva/satcom-chunk-collection huggingface dataset:
# Multi-Objective Optimization of LCC-S-Compensated IPT System for Improving Misalignment Tolerance
## 3 Multi-Objective Optimization of Compensation Parameters  
As previously mentioned, the design optimization problems of the IPT system often require the optimization of conflicting objectives. A widely used method in the optimization of multi-objective problems is the Pareto optimality algorithm [37]. The Pareto optimal algorithm maximizes one of the objectives while maintaining other conflicting objectives at their maximum possible. The output of a Pareto optimization algorithm includes a solution vector and its corresponding objective function, called the Pareto front. In order to broaden the charging region and reduce the output fluctuations, a multi-objective optimization framework based on the PSO algorithm was utilized to search for the optimal solutions from the Pareto front. The PSO method was first put forward by [PERSON] and [PERSON] in 1995 [38]. For the PSO algorithm, at each iterative exploration, the candidate solutions are diversified or incorporated and replaced with new candidate solutions to improve the quality of the current generation of population. As a result, the suitability of the population is improved by iteration. The targets of the system performance and the practical constraints were considered as follows.
## 3 Results
### Performance of Five-System PPP Time Transfer at Locations with Limited Sky View
The corresponding MDEV value of the three time links under a cut-off angle of 40\({}^{\circ}\) can reach 8.30 \(\times\) 10\({}^{-15}\), 1.41 \(\times\) 10\({}^{-14}\), and 9.86 \(\times\) 10\({}^{-15}\) at an average time of 10\({}^{4}\) s. Thus, the MDEV value of the three time links at an elevation mask of 40\({}^{\circ}\) still remains within a reasonable range, and the corresponding PPP time transfer results can still have satisfactory frequency stability. Figure 18 illustrates the average MDEV values over a week and all 12 time links at an average time of 10\({}^{2}\), 10\({}^{3}\), and 10\({}^{4}\) s under environments with limited sky view (at an elevation cut-off angle of 20\({}^{\circ}\), 30\({}^{\circ}\), and 40\({}^{\circ}\)). Based on the average MDEV values, the frequency stability of five-system integrated PPP time transfer can be 1.17 \(\times\) 10\({}^{-13}\), 9.64 \(\times\) 10\({}^{-13}\), and 8.42 \(\times\) 10\({}^{-12}\) under the elevation cut-off angle of 20\({}^{\circ}\), 30\({}^{\circ}\), and 40\({}^{\circ}\) when the average time is 10\({}^{2}\) s; the corresponding frequency stability can be 2.19 \(\times\) 10\({}^{-14}\)  
Figure 15: MDEV values of three time links under an elevation cut-off angle of 20\({}^{\circ}\) on DOY 252, 2021. \(1.29\times 10^{-13}\), and \(4.80\times 10^{-13}\) when the average time is \(10^{3}\) s; the corresponding frequency stability can be \(8.85\times 10^{-15}\), \(2.40\times 10^{-14}\), and \(3.46\times 10^{-14}\) when the average time is \(10^{4}\) s. According to these results, it can be concluded that the five-system combination can still provide a stable PPP time transfer service even in the case of observation conditions with limited sky view.
## 5 Conclusions  
Focusing on Indonesia, this article presents various rainfall data from instrumentation and estimation models. Rainfall is a significant meteorological parameter that has a direct impact on many aspects of life, such as agriculture, transportation, and energy. Rainfall can be directly measured with a rain gauge or indirectly estimated using weather radar and satellites. In Indonesia, the tipping bucket is the most widely used type of rainfall sensor. The tipping bucket sensor can measure rainfall per point directly near the ground's surface, is relatively accurate, and is often used to validate remote rainfall sensors. Moreover, Indonesia has a national weather radar network that can provide data with high spatial and temporal resolution, which can improve rainfall representation. Weather satellites are also used to observe atmospheric dynamics globally. Various approaches to rainfall estimation in Indonesia tend to rely on the quality and characteristics of the data. With advancements in technology, ensemble learning-based approaches have been implemented to improve the accuracy of rainfall estimation in Indonesia. Future research challenges will of course be oriented toward more accurate and universal rainfall estimates. Further efforts are needed, including data merging and selection, the use of universal ensemble learning, hyperparameter tuning, and product resolution improvement.  
Conceptualization, M.P.; methodology, M.P.; validation, M.S.R. and D.H.; formal analysis, M.P., M.S.R. and D.H.; investigation, M.P., M.S.R. and D.H; resources, M.P.; data curation, M.P.; writing--original draft preparation, M.P.; writing--review and editing, M.P., M.S.R. and D.H.; visualization, M.P.; supervision, M.S.R. and D.H. All authors have read and agreed to the published version of the manuscript.  
The second author is funded by the Faculty of Mathematics and Natural Sciences, Universitas Indonesia under the Publication Grant Scheme 2024.  
Data Availability Statement: Data are available upon request.  
The authors are grateful to the Meteorology, Climatology, and Geophysics Agency (BMKG) for providing data and facilities for this research.  
The authors declare no conflicts of interest.
## 4 Results and Discussion
### Single Tubes  
The force-displacement profiles and the progressive deformation stages derived from lateral crush testing of aluminum and carbon fiber-reinforced polymer (CFRP) single tubes are illustrated in Figure 2. It is imperative to underscore that the force profiles for both aluminum and CFRP tubes exhibit congruence with prior studies documented in the literature, notwithstanding the observation that each material's force profile presents distinct characteristics, albeit homogeneity within their respective groups is observed. A notable aspect is the rapid increase in force profiles at the onset of the experiments, characterized by a steep slope. This rate of force escalation at the experiment's commencement inversely correlates with the diameter of the tubes, irrespective of the material composition. Consequently, the initiation of deformation in the specimens was observed at the lowest force value in the tube possessing the largest diameter, similar to results in the literature [46]. This phenomenon, where a higher moment--and therefore force--is necessitated to initiate deformation in tubes of diminishing diameters, accounts for the aforementioned force variation. In contrast to CFRP tubes, aluminum tubes maintained their load-bearing capacity post the initial deformation. The diminished load-bearing capability observed in CFRP tubes can be ascribed to the inherent layered structure of composite materials and their comparative brittleness compared to metal counterparts. Indeed, while brittle composite tubes exhibiting lower deformability commenced deformation at elevated force values relative to their metallic counterparts, they subsequently underwent a near-complete loss of load-carrying capacity within a brief duration. This phenomenon markedly influenced the energy absorption metrics of the tubes, with absorbed energy values in aluminum tubes delineating a decrease from 56.4 J, 55.7 J, and 51.1 J across specimens of increasing diameters (T\({}_{\text{S}}\)-T\({}_{\text{M}}\)-T\({}_{\text{B}}\)), to 22.1 J, 29.4 J, and 32.4 J in CFRP tubes. This attenuation in load-carrying capacity engendered a reversal in the trend in energy absorption behavior, which in aluminum tubes escalated with decreasing diameter, a trend that was inverted in CFRP tubes. If the characteristics of metal and composite curves are examined, aluminum tube structures absorb energy due to the high ductility behaviors and superior plastic deformation capabilities of metals, while the curves are formed in a smooth form. However, composite materials absorb crushing energy with damage mechanisms such as matrix cracking, local buckling of fibers, fiber breakage, and delamination. Due to these fiber breaks, oscillations occur in the curves of composite structures [47; 48].
## 1 Introduction
#### Thin-Walled Elasticity Theory  
In a minor departure from the original [PERSON] theory [7; 8], the co-ordinates \(z\) in this paper refers to length and \(x\) and \(y\) to the section's centroid as an origin. The general equations to be applied in this work refer to the two thin-walled sections of a cantilever beam shown in Figure 1a,b. In the \(x\)-symmetric section of Figure 1a transverse horizontal and vertical forces, \(F_{x}\) and \(F_{y}\), respectively, are applied at centroid G of a thin-walled cantilever beam in which \(x\) and \(y\) are centroidal axes at G (see Figure 1a). When \(F_{x}\) and \(F_{y}\) are applied at shear centre E as shown, then the section is subjected to transverse shear and bending without torsion. Loading at point E in free space may not be achieved easily in practice. Usually the forces are referred to the section's centroid at G. Then, with transverse forces displaced from shear centre E to centroid G, the bending, shear and torsion of the beam arises [9]. A corollary applies that when pure axial torsion applied at E twists and does not bend the cross-section. Point E is then referred to as the _centre of twist_, i.e., the point in the section that does not rotate. Therefore, pure axial torsion is applied to longitudinal axis \(z\) through shear centre E [10; 11]. Similar features apply to E and G for the thin-walled non-symmetric section shown in Figure 1b, provided axes \(u\) and \(v\) replace \(x\) and \(y\) as the section's principal centroidal axes. Here, the axial stress due to bending is applied to the thin section's principal axes \(u\) and \(v\). Axes \(u\) and \(v\) will coincide with \(x\) and \(y\), with \(x\) as a symmetry axis for standard channel sections mounted with a vertical web and equal flange lengths. However, if the applied transverse forces are displaced from G to any arbitrary point, O, in the cross-section, then a transformation is required between in-plane axes at E, G and O for the bending, torsion and transverse shear stress calculations under each of these three actions. In Ref. [1], it was shown how to calculate net axial stress and the net shear stress for this condition when O lies at the centre of the vertical web for each of the three symmetrical channel cantilever beams. In this paper, with all loading applied at G, these transformations are restricted to apply between G and E.  
Figure 1: Principal axes (**a**) coincident and (**b**) not coincident with shear force directions.
## 4 Case Studies
### The Impacts of the Capacity of Each Tie Line on the Consumption of Renewable Energy  
The impacts of tie line capacity on the consumption of renewable energy are compared and analyzed in Table 7. Since there is no abandoned WT and PV power in both the office area and the commercial area in various situations, only abandoned WT and PV power in the residential area and the industrial area is listed in Table 7. It can be seen from Table 7 that when the tie line capacity is increased, the abandoned WT and PV power in the residential area and the industrial area is decreasing, while the reduction of the residential area is more obvious. Because the electric loads and the heating loads of the residential area are not high during the daytime, the output of PV in the residential area is relatively high during this period, and the excess power of PV could be transmitted to other functional areas where the electric loads and heating loads are relatively high through the three tie lines. Therefore, the consumption rate of renewable energy in the residential area has been significantly improved with the increase of the capacity of tie lines.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \(\alpha_{r,k}^{\min}\) & \
\begin{tabular}{c} **Abandoned WT and PV power** \\ **in Residential Area/(MW)** \\ \end{tabular} &
\begin{tabular}{c} **Abandoned WT and PV power** \\ **in Industrial Area/(MW)** \\ \end{tabular} \\ \hline
0.7 & 12.73 & 18.37 \\
0.4 & 11.03 & 17.95 \\
0 & 10.88 & 17.67 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Abandoned WT and PV power in functional areas under different charging coefficients.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \begin{tabular}{c} **Penetration Rate** \\ **of EVs** \\ \end{tabular} & \
\begin{tabular}{c} **Abandoned WT and PV power** \\ **in Residential Area/(MW)** \\ \end{tabular} &
\begin{tabular}{c} **Abandoned WT and PV power** \\ **in Industrial Area/(MW)** \\ \end{tabular} \\ \hline
2\% & 12.73 & 18.37 \\
6\% & 9.66 & 15.63 \\
10\% & 6.88 & 14.29 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Abandoned WT and PV power in functional areas under different penetration rates of EVs.  
There is abandoned WT and PV power during 5 a.m.-7 a.m. in the industrial area, and the electric loads, the heating loads, and the cooling loads of other functional areas are not high and the output of renewable energy of other functional areas is rich during this period. Meanwhile, there is only one tie line in the industrial area, so the renewable energy cannot be completely consumed through the tie line. In summary, the tie line capacity of the industrial area could be expanded or tie lines between the industrial area and other functional areas could be established to reduce the abandonment of WT and PV power in the industrial area.
## 3 Dynamic Model of Synchronous Generator
### Overall System Dynamics  
The overall state-space model of the system combines the dynamics of the synchronous generator, governor, and gas turbine. The state-space representation includes the following state variables:  
\(\delta\): Rotor angle  
\(\omega\): Rotor speed deviation  
\(E^{\prime}\): Internal voltage  
\(y_{g}\): Valve position  
\(F_{f}\): Fuel flow rate  
\(P_{ct}\): Compressor-turbine power  
The state vector (x) is defined as:  
\[X=\left[\delta,\omega,E^{\prime},y_{g},F_{f},P_{ct}\right]^{T} \tag{11}\]  
The state-space equations can be written as:  
\[\frac{dX}{dt}=AX+Bu \tag{12}\]  
\[y=CX+Du\]  
where:  
\[u=\left[E_{f},y_{g_{cr}}\right]^{T} \tag{13}\]  
where matrix \(A\) represents the relationship between the current states and their derivatives. For this system, \(A\) would be:\[A=\left[\begin{array}{cccccc}0&1&0&0&0&0\\ -\frac{VE^{\prime}\cos(\delta)}{2 HX_{d}}&-\frac{D}{2H}&\frac{Vsin(\delta)}{2 HX^{ \prime}}&0&0&0\\ 0&1&\frac{-1}{T}&0&0&0\\ 0&\frac{R}{T_{g}}&0&\frac{-1}{T_{g}}&0&0\\ 0&0&0&\frac{1}{T_{g}}&\frac{-1}{T_{g}}&0\\ 0&0&0&\frac{K_{f}}{T_{el}}&\frac{-1}{T_{el}}&0\\ \end{array}\right] \tag{14}\]  
Matrix B represents how the inputs affect the state derivatives. For this system, B would be:  
\[B=\left[\begin{array}{ccc}0&0\\ 0&0\\ \frac{1}{T}&0\\ 0&\frac{1}{T_{g}}\\ 0&0\\ 0&0\\ \end{array}\right] \tag{15}\]  
Matrix C maps the state variables to the output variables. For this system, assuming the outputs are \(\delta,\omega,P_{e}\) and \(P_{m}\):  
\[C=\left[\begin{array}{cccccc}0&1&0&0&0&0\\ 0&1&0&0&0&0\\ \frac{VE^{\prime}\cos(\delta)}{X_{d}}&0&\frac{Vsin(\delta)}{X^{\prime}}&0&0&0 \\ 0&0&0&0&0&0\\ \end{array}\right] \tag{16}\]  
Matrix D represents the direct effect of the input on the output. For this system, typically, \(D=0\), meaning there is no direct feedthrough from the input to the output.  
\[D=\left[\begin{array}{ccc}0&0\\ 0&0\\ 0&0\\ 0&0\\ \end{array}\right] \tag{17}\]
## 1 Introduction
### Robustness of Demagnetization Fault Identified Signal  
#### 2.4.1 Effect of Load on Demagnetization Fault Identified Signal  
The load of the machine is variable in actual applications. To diagnose the demagnetization faults under different loads, the fault identified signal needs to be robust to the load. This part is focused on the study and analysis of the demagnetization fault identified signal under different loading conditions (the speed of the test machine is rated speed, the demagnetization severity is 10%). Six different load conditions are studied, including no-load, 25% rated load, 50% rated load, 75% rated load, rated load, and 125% rated load. Take Mode 3 as an example to analyze the waveforms of SIm under different loading conditions, which are depicted in Figure 8.  
As shown in Figure 8, even when the mode of demagnetization severity is 10%, \(SI_{\text{m}}\) are almost the same curve pattern under different loading levels, with small differences. Consequently, \(SI_{\text{m}}\) is almost insensitive to the variation in the loading conditions. The  
Figure 8: \(SI_{\text{m}}\) under different loading conditions of the machine.  
Figure 7: Corresponding relationship between the pole pair number and the electric cycle number of DFISs.  
behaviors of \(SI_{a1}\) and \(SI_{a2}\) are similar to \(SI_{\rm m}\). As a result, \(SI_{\rm m}\), \(SI_{a1}\), and \(SI_{a2}\) are considered robust and discriminant signals to accurately diagnose demagnetization faults under different loading conditions.
# A Method for Evaluating the Spatial Layout of Fire Stations in Chemical Industrial Parks
## 4 Conclusions  
A method is presented for evaluating the rationality of fire station layouts in chemical industrial parks, and this is demonstrated using an engineering example. This method classifies the PTBRs in chemical industrial parks based on fire risk assessments. It determines the required fire rescue time for each PTBR based on their fire risk levels, and it conducts layout assessments which consider the variations between rescue objects. This leads to more accurate analysis results. The method evaluates the response time of fire rescues based on the actual road network in chemical industrial parks. It fully considers the impact of irregularities in the road path, leading to a more objective evaluation result. The fire station coverage rate in the engineering instance is estimated to be 92.6%, which meets the requirements. However, the overlap-coverage rate is estimated to be 62%, which exceeds the upper limit of the requirements. This method can be directly applied to the rational analysis and planning of fire station layouts in chemical industrial parks. It serves as the theoretical basis and foundation for fire protection.  
This study reveals the significance of accurately estimating the speed of fire engines. Future research should prioritize the precise estimation of fire engine speed. It is feasible to estimate the speed of fire engines separately by considering various road sections encountered during the path, such as urban streets, expressways, highways, bridges, tunnels, etc. Additionally, another crucial factor that should be comprehensively investigated is the influence of fire station levels on the evaluation outcomes.  
Conceptualization, L.L. and N.L.; methodology, L.L. and X.W.; validation, B.L. and X.W.; investigation, L.L. and B.L.; data curation, X.W.; writing--original draft preparation, L.L.; writing--review and editing, N.L. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the China Special fund for basic scientific research business expenses of central public welfare scientific research institutes.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
Figure 8: Comparison between the “Circle-drawing method” and this study.  
**Acknowledgments:** The authors would like to acknowledge [PERSON] for providing valuable technical support in completing this study.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 2 Methods  
### ECT Measurement Principle  
The three primary elements of a capacitance tomography imaging system are a capacitance tomography imaging sensor, a data acquisition system, and an image reconstruction system. A typical 12-electrode capacitance tomography imaging system is shown in Figure 3. The capacitance chromatography imaging system measures the capacitance value inside the closed pipe based on the capacitance sensor array, and transmits it to the computer for secondary calculation after being processed by the data acquisition system, and finally the medium distribution image inside the pipe is reconstructed. The working principle is that when the medium concentration or medium distribution in the measured field changes, the capacitance sensor array detects the change in capacitance value, and the data acquisition system filters, transforms, and amplifies the capacitance value and then transmits it to the computer, which presents the projection distribution in the pipe according to the image reconstruction algorithm.  
An array of ECT sensors is formed by adding electrodes uniformly on the outside of a multiphase flow pipe and applying electricity to the electrodes in turn to detect the capacitance values between the different electrodes to form the initial measurement data. Most of the current ECT capacitance sensors are 8 electrode, 12 electrode, and 16 electrode. This study is based on a typical 12-electrode ECT system, whose physical structure is shown in Figure 4 in cross-section.  
ECT capacitive sensors work with voltage excitation and capacitive output. The conventional single-electrode excitation method is used in this study. The internal electrode number of the capacitor sensor is shown in Figure 4. In general, for an ECT system with \(N\) electrodes, \(M\) separate capacitance values will be accepted, and it is written as:  
\[M=\frac{N(N-1)}{2} \tag{1}\]  
Figure 3: The composition of the ECT system.