esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimization of a Permanent Magnet Synchronous Motor for e-Mobility Using Metamodels
## 1 Introduction
First, in previous studies, the reduction in the torque ripple based on the width and depth of the notch was studied by applying an elliptical-shaped notch, instead of a circular notch, to the stator teeth. In addition, the shape of the flux barrier was set as a design variable to compensate for the decrease in the average torque and efficiency of the motor when applying the notch. Second, in most previous studies, only one metamodeling technique was applied to approximate the optimization function. However, in this study, the function approximation was performed by applying six metamodeling techniques for each objective function and constraint. In addition, the optimal design was performed by selecting the best metamodel method obtained using the RMSE test. In this study, the shape optimization of a PMSM for e-mobility was performed. The objective function of the optimal design aimed to minimize the torque ripple, wherein the average torque and efficiency were set as constraints. Three design variables were selected to satisfy the objective function and the constraints. There are various methods such as full factorial, central composite design, and Plackett-Burman for the sampling strategy for DoE [17]. If there is the existence of nonlinearity in the relation between design variables and output variables, the prediction accuracy is better when the optimal Latin hypercube design (OLHD) technique is used [18]. Additionally, using the OLHD technique, 27 experimental points were determined for the DoE. The DoE for the selected experimental points were obtained using a finite element analysis (FEA) method. The correlations between the design variables and responses were investigated by applying a screening technique with the DoE results. Metamodels of the objective function and constraints were established using the DoE results, and the metamodels with the highest accuracy were selected using accuracy evaluations. These metamodels were combined with the sequential two-point diagonal quadratic approximate optimization (STDQAO) algorithm to find an optimal solution. Finally, the adequacy of the optimal design for the optimal point was verified using FEA.
# Research on Solidification Methods and Stabilization Mechanisms of Sulfate Saline Soils
## 4 Results and Analysis  
### Mechanical Performance Analysis  
The UCS and splitting strength of saline soils stabilized by lime, FA, and PAM after 28 d of curing are shown in Figure 4.  
As can be seen in Figure 4, after 28 d of curing, saline soils stabilized with FA, PAM, and lime increased their UCS by 55%, 23%, and 1068%, respectively, and their splitting strengths by 161%, 75%, and 2720%, respectively, compared to saline soils. These three binders improve the bond strength between the soil particles, fill the voids between the soil particles, and increase the mechanical properties of the stabilized soil. The strength of stabilized saline soils reached its maximum value when the concentrations of lime, FA, and PAM were 10%, 13% and 1.0%, respectively. PAM had the lowest stabilizing effect on saline soils, and lime had the best stabilizing effect on saline soils.  
The UCS of lime-stabilized saline soils increases gradually with increasing lime admixture within the required range. The main reasons for the series of physicochemical reactions involving lime in the soil were ion exchange, Ca(OH)2 crystallization, Ca(OH)2 carbonation, and reactivity with volcanic ash. Na2 SO4 is highly temperature-sensitive, and when it does not react with lime or FA, it crystallizes into Na2 SO4 \(\cdot\)10H2O crystals [7, 36]. During the FT's phase, these crystals interact with ice crystals to break up the gel between soil particles [37], resulting in soil failure. Na2 SO4 \(\cdot\)10H2O is almost three-times the volume of Na2 SO4, and the dilution of solubility leads to the destruction of soil structure and a decrease in density. It was found that the formation of salt crystals directly disrupts the cementation between soil particles, leading to the swelling of pores, and Na2 SO4 greatly reduces soil strength [38].
## 3 System Architecture and Modeling
### Appliance Dynamics Modeling and Setup
#### 3.3.3 Non-Thermal Load Appliances Modeling  
In the present work, a washing machine and a dishwasher are considered in the non-thermal load appliances category. Any non-thermal load appliance can be modeled in the same way since they have the same characteristics as described in Section 3.1.  
The dynamics of a non-thermal load appliance is modeled in the following way:  
\[\zeta_{k+1}=\zeta_{k}+\psi_{k}, \tag{4}\]  
where \(\zeta\) is the variable defined to keep track of the duration up to which the appliance has run, and \(\psi\) is a binary integer variable which can have the values from the set [0,1]. It represents that if the appliance is running at time instant \(k\) then the value of \(\psi(k)\) will be 1 and if the appliance is halted, \(\psi(k)\) will be 0. In both the cases, the value of \(\psi\) is added to \(\zeta\). Therefore, for non-thermal appliances, Equation (4) can be represented in form of Equation (1), which subsequently gives \(\mathbf{x}=\mathbf{y}=\zeta\) and \(\mathbf{u}=\psi\). It should be noted that, whenever \(\psi\) take the value of 1, a certain amount of power is consumed by the appliance.
## 1 Introduction
[14] have considered the influence of fillet size in axial flow turbine stators. Small fillets, with a radius of about 5% of the chord, increased the efficiency by 1.4% compared with \(r_{\text{fillet}}/c=0\%\). It was anticipated that the increase in efficiency was due to the fillet, which has limited the corner separation; however, a further increase in fillet radius did not continue to increase in efficiency because of the additional associated profile drag. [PERSON] et al. [15] reported that in a compressor cascade, the addition of a fillet has increased the size of the separation region as well as the losses. [PERSON] et al. [16] have investigated the influence of fillet size on stator performance in a two-stage axial flow compressor using double circular arc blades. The result did not show any prominent effects related to the fillet size. From the aforementioned literature study, it has not been determined concisely if the fillet geometry will have a positive or negative influence on corner separation for different blade profiles. [PERSON] et al. [17] have conducted three radius of blade fillet in a high speed compressor cascade. 3D flow structures of the secondary flow have been found shifting towards the symmetry plane which producing higher losses in the middle of the passage, but less near the endwall. Due to the determinant effects of the corner separation, a significant amount of research has been done on various flow control techniques [18; 19; 20], but the passive control methods remain preferable because of their simplicity and cost effectiveness. For the research work of slot configurations, [PERSON] [21; 22] has explored the potential of passive control via slotted blades in linear cascade configurations under stall conditions. 2D numerical study was conducted and the effects of location, width, and slope of slots were analyzed to identify the optimum configuration. The obtained results for the 2D case showed that the maximum of about a 28% reduction in loss coefficient has been observed and the flow turning was increased to approximately 5\({}^{\circ}\) with the slot. [PERSON] et al. [23; 24] have conducted research on a whole span slot on a National Advisory Committee for Aeronautics (NACA) blade and reported that, within the majority of the area of flux, the jet flow from the slot can reduce, as well as control, the separation of the tail of the suction surface, which can increase the efficiency and the stability of the blade. The slot configuration at the root of the blade was imposed by [PERSON] et al. [25] to control the corner separation near the endwall. In this research, the magnitude of changes in solidity, aspect ratio, and blade fillet radius, combined with effect of slot configuration at the blade root has been investigated for a highly-loaded compressor cascade. The objective was to find out how the design parameters (e.g., solidity and aspect ratio), the real geometrical aspect (blade fillet), and the slot configuration influence the corner separation, and also the overall performance of the cascade.
## 3 Results and Discussion
### Hydrocracking Experiments
The changes in WHSV only affected the total amount of gas formation, but not the selectivity of the different products. For a detailed characterisation of the diesel fraction of the hydrocracked product, the organic phase was physically distilled and re-analysed to compare the properties in terms of EN590, together with aromatic composition [44] and GCxGC-MS analysis. Table 4 shows the results of this detailed characterisation. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Analysis** & **VGO** & **VGO:H-FTS** & **VGO:H-FTS** & **VGO:H-FTS** & **VGO:H-FTS** & **VGO:H-FTS** \\  & & **(10:90)** & **(20:80)** & **(30:70)** & **(40:60)** & **(50:50)** \\ \hline Density at 15 \({}^{\circ}\)C, kg/m\({}^{3}\) & 905.0 & 908.6 & 908.2 & 907.8 & 907.4 & 907.0 \\ \hline Kinematic viscosity at 100 \({}^{\circ}\)C, mm\({}^{2}\)/s & N/A & 10.30 & 8.87 & 7.73 & 6.67 & 5.51 \\ \hline Sulphur content, mg/kg & 1.92 & \textless{}0.05 & \textless{}0.05 & 0.18 & 0.26 & 0.63 \\ \hline Nitrogen content, mg/kg & 847 & N/A & N/A & N/A & N/A & N/A \\ \hline Elemental analysis (wt.%) & & & & & & \\ \hline Carbon content & 84.9 & 86.0 & 85.8 & 86.3 & 86.1 & 86.2 \\ \hline Hydrogen content & 12.1 & 14.0 & 14.0 & 13.9 & 14.0 & 13.7 \\ \hline H/C ratio & 1.4 & 1.94 & 1.95 & 1.92 & 1.94 & 1.89 \\ \hline Distillation & & & & & & \\ \hline IBP, \({}^{\circ}\)C & 284.0 & 315.1 & 303.7 & 298.2 & 294.2 & 293.8 \\ \hline FBP, \({}^{\circ}\)C & 510.3 & 719.3 & 719.7 & 708.4 & 689.0 & 643.7 \\ \hline BMCI/CI \({}^{\star}\) & N/A & 39.2 & 40.0 & 40.8 & 42.4 & 42.7 \\ \hline \hline \end{tabular}  
* * BMCI/CI = 473.7:SG – 456.8 + (48640/T\({}_{\text{b}}\)); (SG, specific gravity-kg/m\({}^{3}\); T\({}_{\text{b}}\), average boiling point-K).  
\end{table} 
Table 3: Basic characterisation of VGO and its mixtures with the heavy fraction of distilled Fischer–Tropsch waves. Figure 4: Properties of hydrocarbons products obtained during VGO:H-FTS co-processing at T = 420, \({}^{\circ}\)C, WHSV = 0.5–1.0 h\({}^{-1}\), P = 10.0 MPa; (**a**) Density at 15 \({}^{\circ}\)C (kg/m\({}^{3}\)) vs. TOS (h); (**b**) Sulphur content (mg/kg) vs. TOS (h); (**c**) Nitrogen content (mg/kg) vs. TOS (h). Figure 5: (**a**) Product distribution (wt.%) for WHSV 0.5 and 1.0 h\({}^{-1}\); (**b**) Boiling point distribution of the organic phase (wt.%—operating conditions: T = 420 \({}^{\circ}\)C, P = 10.0 MPa). As expected by the experiment monitoring, the fuel quality of the diesel fraction produced at WHSV of 0.5 h\({}^{-1}\) was much better than at WHSV of 1.0 h\({}^{-1}\) in terms of cetane index and relative parameters. Moreover, the resulting transportation fuel fulfils the essential EN590 standards for diesel, including sulphur content, nitrogen content, and CFPP. The lower aromatics and paraffin content of the diesel fraction obtained at WHSV 0.5-1 h
## 2 A General Overview on SSNs
### Fundamental Requirements for Building SSNs
Thus, it should have solid mobility management solutions for achieving these goals. * Legacy Support: is the compatibility with the older versions of hardware and software, in SSNs, this compatibility can theoretically be obtained by grouping them in a separate VSN. * System Recovery: in the case of system failure or errors in the logical representation of the hosted VSNs, how could SSNs recover the affected VSNs? Additionally, how much time is required to retrieve its original status? It should have mechanisms for resource and service discovery, resource allocation, and task allocation and scheduling. * Support for application/service priority: apps/services should have prioritized execution mechanisms.
# Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval
## 3 Geo-DMP Mobile System
### Naming  
Only with a simple naming convention can regions be easily and uniquely identified in practical use. Meanwhile, it should also be hierarchically appropriate to make this naming consistent with the three-layer map segmentation. We make use of the administrative division codes for statistical use [106] (ADC), published by the National Bureau of Statistics of China, as the foundation for naming. As Figure 13 demonstrates, the ADC of a subdistrict region is a 12-digit number. Following this naming pattern, we append two digits to the subdistrict names for community names, and two more digits to the community names for block names. The general order of the encoding is from west to east and north to south. To be more specific, the region at the northwest corner is labeled as number one. Then we sequentially designate serial numbers to the regions along the horizontal direction until reaching the east border. Then the next number is given to the region which lies adjacent to region number one in the south, and so forth. In this way, the hierarchical relationship is implicitly involved in names. The name of a region in the upper level can be inferred directly from the names of smaller regions it covers.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer** & **Number of Regions** & **Area Size (km2)** \\ \hline subdistricts & 29 & 10.238 \(\pm\) 10.97 \\ communities & 155 & 1.965 \(\pm\) 1.002 \\ blocks & 435 & 0.708 \(\pm\) 0.882 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The statistics of map segmentation.  
Figure 12: Segmentation result of community regions.  
6. Local Database  
To support the access of regional information continuously with real-time GPS coordinates under the offline mode, we develop a local database based on SQLite [107] and Spatialite [108] (an extension to SQLite with advanced spatial capabilities). The database is a compact single file of only about 5 MB. Regardless of the platform, as soon as one node is configured with SQLite and Spatialite, the file can be copied to the node and it is ready for use. We have tested the access performance on Intel Galileo board (Intel Quark SoC X1000 400 MHz, 256M DRAM) and it only takes about 0.25 s for one query. This database is combined with the map interface as the map adaptor module. The overall picture of the steps stated above is shown in Figure 14.  
Figure 14: The production procedure of the map adaptor module.  
Figure 13: An example of region naming.
# Evaluating and Ranking SCPMS Enablers Using ISM and SWARA
## 2 Literature Review
A complex hierarchy with different levels of aggregation may be employed to measure the SCPM using various approaches [43]. A review of the literature was carried out according to the various criteria of perspective-based, process-based, and hierarchical-based approaches [10]. A further comparison of existing performance measurement systems was also carried out. Various approaches to leanness, agility, innovation, and responsiveness are vital in SC performance measurement. Research looking into how controlling quality, agility, and innovation affect SC performance concluded that they had a favorable impact [44]. A study revealed the enablers of SC agility and described how it affects organization performance using feedback from 266 electronics companies in China [45]. SC is badly affected by volatile and unpredictable market demand that demands proactive actions for leagility [46]. Various studies involving SC activities, processes, and approaches are listed in Table 1. \begin{table}
\begin{tabular}{c c} \hline
**Supply Chain Activities/Processes/Approaches** & **References** \\ \hline Plan & Order lead time, total order cycle time, or order to delivery cycle time [2] \\ \hline Source & Sourcing of purchasing items, subcontracting components [2; 47], and supplier evaluation \\ \hline Make/assemble & Manufacturing components [28], capacity utilization, effectiveness of scheduling techniques, and range of products and services [2] \\ \hline \end{tabular}
\end{table} 
Table 1: Metrics and measures for SCPM.
## 2 Materials and Methods
### Evaluation and Assessment of Parameters Using AHP
#### 2.4.3 Verification of the Consistency of Judgments and Conclusions according to Results  
AHP's quality output was related to the consistency of the pairwise comparison judgments. This step was essential to identify the consistency of the assessment by computing the consistency ratio (CR) before a decision was completed. However, if the problem was expected during deliberation for choosing the best alternative, the CRs for matrices were computed initially before the alternatives' overall relative weights were calculated. After which, calculations were performed to obtain the largest eigenvalue, consistency index (CI), CR, and normalized values for each criterion and alternative.  
The last mathematical process normalized and identified the relative weights per matrix. The right eigenvector gave the relative weights (\(w\)) conforming to the highest eigenvalue (\(\lambda_{max}\)), as shown in Equation (3).  
\[A_{w}=\lambda_{max} \tag{3}\]  
If the pairwise comparisons were consistent, the matrix \(A\) was ranked one and \(\lambda_{max}=n\), so the weights can be taken by normalizing any of the rows or columns of \(A\)[32]. The relativeness between the entries determines the consistency, and the \(CI\) was calculated using the equation below:  
\[CI=(\lambda_{max}-n)/(n-1) \tag{4}\]  
The final \(CR\), which enables the decision-maker to accomplish whether the assessments were adequately coherent, was computed as the \(CI\)'s and the random index (\(RI\)) quotient using Equation (5).  
\[CR=CI/RI \tag{5}\]  
One recommendation for this step was: if the proportion exceeds 0.1, the judgment was considered inconsistent. Therefore, a consistency ratio must be below 0.1 or 10%. The process was reiterated if the evaluation was unpredictable until the CR was within the wanted scale. The user formulated a conclusion according to the assessment results [32].
## 2 Materials and Methods
### Microcapsule Morphology and Size  
The morphology of the microcapsules was evaluated using a scanning electronic microscope (SEM) (Zeiss EVO 40, Carl Zeiss AG, Oberkochen, Germany). The size distribution of the microcapsules was measured using a Mastersizer 2000 (Malvern Panalytical GmbH, Herrenberg, Germany) using isopropanol as the dispersion medium.
# Trajectory Planning with Time-Variant Safety Margin for Autonomous Vehicle Lane Change +
## 4 Conclusions  
The research proposes a safety and comfort-oriented trajectory planning algorithm for autonomous ground vehicles to perform lane changes on a straight driveway. The algorithms is designed to solve the issues of mutual interactions between the host vehicle and the surrounding cars. In this paper, a complete algorithm flow for lane change maneuver are considered with three parts: gap evaluation, trajectory planning and trajectory correction. A Gray Prediction Model is employed as the gap evaluation method to select an appropriate time instance for lane change. By using the QP-based optimization algorithm, a continuous trajectory planning is designed to achieve both safe and comfortable lane change maneuver. Moreover, a trajectory re-planning control algorithm with condition-triggered safety margin function is proposed. The time-variant safety margins is designed by the consideration of both the longitudinal and the lateral planning in a dynamic traffic. This method can improve the success rate of lane change, and also reduce the computational complexity.  
The effectiveness of the algorithms is verified in the simulations with random traffic and specified traffic. By the comparative analysis of the experimental results, the proposed condition-based trajectory re-planning method has a stronger robustness to deal with the unexpected road events, while not  
Figure 9: Simulation results for Scenario III. From top to bottom, the graphs of host vehicle \(V_{H}\) are: 2-D trajectory, longitudinal velocity, longitudinal acceleration, lateral position, lateral velocity, lateral acceleration and host vehicle’s distance to the nearest front/rear vehicle.  
inducing too heavy calculated load. By the adjust of time-variant safety margin, the driving model with comfortable or aggressive characteristic can be realized. This opens a potential research topic for the autonomous driving with different individual driver behaviors in future work.  
Conceptualization and methodology, X.W.; simulation and validation, B.Q.; writing-original draft preparation, B.Q.; writing-review and editing, X.W.; supervision and administration, C.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Natural Science Foundation of China under Grant 51775331.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
LC lane change  
CBRP condition-based re-planning  
TBRP time-based re-planning
## 3 Outage Performance Analysis
### Diversity Order Analysis  
In this subsection, we express the diversity order to evaluate the OP in high SNRs (i.e., \(\rho_{PB}\rightarrow\infty\)) to obtain more insight into the proposed network. The diversity order is given by [27]  
\[d=-\lim_{\rho_{PB}\rightarrow\infty}\frac{\log(P^{\infty}(\rho_{PB}))}{\log( \rho_{PB})} \tag{22}\]  
where \(P^{\infty}(\rho_{PB})\) denotes the asymptotic OP of IoT users  
**Corollary 1**.: _In high SNR (\(\rho_{PB}\rightarrow\infty\)), we can approximate as \(K_{1}(x)\approx\frac{1}{x}\). Thus, the expression asymptotic OP of FU is expressed as_  
\[P_{FU}^{\infty}\approx 1-e^{-\frac{2\gamma_{FU}\left(1-\varepsilon^{2} \right)}{\varepsilon^{2}\left(\varepsilon_{F}-\gamma_{FU}\mu_{N}\right)}} \tag{23}\]  
**Remark 1**.: _Corollary 1 gives some useful insights: (i) the main parameters that affect the OP of FU are the target rate of FU \(\gamma_{FU}\), the power allocation (\(\alpha_{F},\alpha_{N}\)), and the channel correlation factor \(\varepsilon\); (ii) upon substituting (23) into (22), the diversity order of FU is zero._  
**Corollary 2**.: _The expression asymptotic OP of NUI is expressed as_  
\[P_{NU}^{\infty}\approx 1-e^{-\frac{2\gamma_{NU}\left(1-\varepsilon^{2} \right)}{\varepsilon^{2}\alpha_{N}}} \tag{24}\]  
**Remark 2**.: _Corollary 2 gives some useful insights: (i) the main parameters that affect the OP of NUI are the target rate of NUI \(\gamma_{NU}\), the power allocation (\(\alpha_{F},\alpha_{N}\)), and the channel correlation factor \(\varepsilon\); (ii) upon substituting (24) into (22), the diversity order of FU is zero._