esa-sceva/satcom-chunk-collection huggingface dataset:
# Thin CdTe Layers Deposited by a Chamberless Inline Process using MOCVD, Simulation and Experiment
## 3 Numerical Modelling  
Simplified 2D and 3D models of the coating head delivery system were developed, using a combined mesh not exceeding 100,000 cells for 2D and 700,000 cells for 3D to define the numerical model. In order to correlate simulation with experimental data, a surface chemical reaction was applied for the 2D model for simplification. The 3D model employed H\({}_{2}\) and N\({}_{2}\) as the mass species, presenting the deposition profile of H\({}_{2}\) on the substrate, determined by the CCF, RFO configuration and active exhaust extraction. A finer mesh, in the vicinity of the substrate, was employed to account for the influence of the temperature gradient and boundary layer formation. A no-slip boundary condition was prescribed on the domain walls, the exit of the system (i.e., exhaust) was defined as outflow, while the velocity out of the injector was defined as inlet velocity (i.e., based on total flow rate). In addition, any experimental apparatus walls that were controlled by water cooling were approximated as isothermal walls within the numerical models. A constant temperature condition was applied to the substrate surface. Pressure-velocity coupling was obtained using the SIMPLE [19] algorithm, with the discretisation scheme for pressure being second-order. To ensure stability, the momentum, energy and chemical species transport were set to first-order upwind. In order to derive the differential equations for expressing conservation of mass, momentum and energy, some assumptions were made: (1) the gas mixture is a continuum; (2) gas flows are laminar; (3) steady-state conditions prevail; (4) the equation of state obeys the ideal gas law. Under these assumptions, the differential equations were simplified as by [PERSON] et al. [16]. Further, due to the lack of detailed chemical data regarding the deposition of CdTe thin film from the gas mixture, one overall surface chemical reaction on the substrate was considered [16]:  
\[DIPTe(g)+DMCd(g)+H_{2}\to CdTe(s)+Res(g) \tag{6}\]  
where \(Res(g)\) represents all the by-products of the reaction. The following Arrhenius expression was used to express the rate of the reaction:  
\[k=AT^{\beta}e^{-\frac{E_{a}}{KT}} \tag{7}\]  
where \(A\) is the pre-exponential factor, which relates to the reaction frequency between the precursor molecules, \(E_{a}\) is the activation energy to initiate the reaction, \(R\) is the universal gas constant (8313 J/K\(\cdot\)mol) and \(\beta\) is the temperature exponent. The pre-exponential factor was set to \(A\approx\) 1016 s\({}^{-1}\)[20], the temperature exponent \(\beta\) was set to 0 and the activation energy \(E_{a}\) was set to 59.62 kJ\(\cdot\)mol\({}^{-1}\).  
All simulations were conducted on a Fujitsu Celsius W510 ProGREEN workstation, with a Quad-Core Intel Xenon, 3.3 GHz and 16.0 GB RAM, running the commercial CFD software ANSYS Fluent (ANSYS, Canonsburb, PA, USA).
# Adaptive Path Planning for UAV-Based Pollution Sampling
## 3 Materials and Methods  
The Adaptive Path Planner (APP) comprises two main components: the Global Path Planner (GPP) and the Local Path Planner (LPP). The GPP is responsible for generating a near-optimal solution based on the specific objectives outlined in the mission scenario. It outputs a set of sparsely positioned global waypoints that outline the path, as well as an initial route constructed from densely spaced local waypoints. The LPP operates at a lower level, recalculating collision-free paths connecting the global waypoints determined by the GPP. Its output is limited to local waypoints. The UAV's flight controller ensures low-level reactivity to dynamic obstacles. However, this component lies outside the scope of the APP. A similar framework was implemented by [PERSON] et al. in their chemotaxis-driven guidance system for multirotors. Their solution utilized a higher-level computer (Raspberry Pi) for guidance and a separate board (Pixhawk) to manage the UAV's controller [29]. While this approach was effective for multirotors, it is less suitable for fixed-wing UAVs, which operate under more stringent constraints.
## 2 Methodology
### Pile Models  
Six steel pipes, 1.0 m long, with an outside diameter 4.2 cm and wall thickness 0.25 cm, were used as pile models. The layout of the pile models in the box is shown in Figure 3. Pipes used in testing were identified successively as 1, 2, 3, 4, 5, 6, which corresponded to the order they were installed (Figure 3). The pile heads were situated 20 cm above the top of the sand level, so 80 cm of the pipes were embedded in sand, with 40 cm between the end of the pipes and the bottom of the box. This ratio 40 cm/4.2 cm is close to 10; Polish codes of practice for piling works pay special attention to soil conditions within a layer thickness of 5D below the pile base, any deeper mineral layers are not considered in capacity analysis of a single pile. As all the piles were tested separately, not in a group, it was assumed that there were no bottom effects. A similar assumption was made concerning the distance from sandbox's walls. Again, Polish codes require that anchoring piles or the points of support of reference systems for displacement control should be out of the 4D-wide zone around the tested pile (it was more than 6D in the tests in Figure 3).  
The pile base included a steel cap, with a diameter equal to an external diameter of the pipe, loosely placed under the pipe during driving (Figure 4a). Additionally, all caps included a threaded bolt, enabling a steel pole to be screwed to them (Figure 4b).  
Pile models were driven using a light dynamic penetrometer to the depth of 0.8 m (Figure 5). While piles were driven, the number of necessary blows, \(\rm N_{10}\), to settle the pile by successive 10 cm increments was determined. The results for the successive pile models are given in Figure 6.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**LP**} & \multirow{2}{*}{**Sand Layer**} & \multirow{2}{*}{**Weight**} & \multicolumn{2}{c}{**Mean** Weight} & \multirow{2}{*}{**Volume**} & \multirow{2}{*}{**Soil Density**} & \multicolumn{2}{c}{**Degree of**} \\  & & & & & & **Compaction** \\ \cline{2-7}  & **cm** & **kg** & **kg** & **cm3** & **g/cm3** & **-** \\ \hline
1 & 40 & 4.18 & & & & \\
2 & 40 & 4.19 & 4.18 & & 1.64 & 0.94 \\
3 & 40 & 4.18 & & & & \\ \hline
4 & 70 & 4.26 & & & & \\
5 & 70 & 4.24 & 4.25 & 2545 & 1.67 & 0.96 \\
6 & 70 & 4.25 & & & & \\ \hline
7 & 100 & 4.30 & & & & \\
8 & 100 & 4.32 & 4.31 & & 1.69 & 0.97 \\
9 & 100 & 4.31 & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of soil density tests with cylindrical mould.  
Figure 4: (**a**) Steel bottom of model pile base. (**b**) Pole placed inside the pipe.  
Figure 3: Layout of pile models, 0.8 m embedded in the soil, in the box.  
Figure 5: Pile installation with a light dynamic penetrometer.  
Figure 6: Diagrams of the N\({}_{10}\), number of impacts necessary to achieve 10 cm of displacement, for each pile during installation.
# MoCoformer: Quantifying Temporal Irregularities in Solar Wind for Long-Term Sequence Prediction
## 4 Results
### Ablation Studies  
For module validation, univariate prediction experiments were conducted on the omni-Field-Magnitude dataset. The proposed models and their variants are summarized below for comparative analysis.  
* **MoCo-rM:** removed the Multi-Mode Decomp Block from the model.
* **MoCo-rMrSTL:** replaced the Multi-Mode Decomp Block with the STL decomposition module.
* **MoCo-rCrT:** substituted the Mode Independence Attention proposed in this chapter with the auto-correlation module from the Transformer model.
* **MoCoformer**: The original model proposed in this chapter.  
The experimental results of each module combined with the backbone network structure are shown in Table 3.  
The table illustrates the significance of the Multi-Mode Decomp Block in enhancing model performance across various prediction lengths, thereby underscoring its positive influence on long-term solar wind forecasting. Higher numerical values were observed upon replacement of the STL module with this block, indicating the challenge of capturing temporal irregularities through conventional trend-seasonal decomposition for comprehensive pattern comprehension. Furthermore, the substitution of Mode Independence Attention with the Transformer's auto-correlation module resulted in inferior outcomes in shorter prediction lengths, thereby underscoring the beneficial impact of the proposed Mode Independence Attention in solar wind prediction tasks.  
However, as the length of the predicted time series increases, the predictions of the two models converge. This indicates that as the complexity of the solar wind increases in longer time series predictions, the predictions of both modules gradually become more similar.
## 5 Conclusions  
In this work, different simulation methods of subgrade frost heave in the vehicle-track dynamic model were compared, and a novel FEM model based on an explicit algorithm was applied in the paper to evaluate the dynamic response of the vehicle-track system under subgrade frost heave. With a case of short-wavelength frost heave, the influencing mechanism of frost heave on the vehicle-track coupling system was studied in detail, and the influence of different ratios of wavelength to amplitude was also discussed. The research results could provide a reference for the management and maintenance of subgrade frost heave in high-speed railways. The following conclusions are drawn:  
1. The influencing mechanism of frost heave on the vehicle-track system can be separated into three parts: track irregularity, contact loss area underneath the structure and leverage effect of the bent slab track.
2. Track irregularity caused by frost heave produces a fluctuation in the vehicle dynamic response, and the affected distance of track irregularity determines the effect distance of the vehicle dynamics index.
3. A short-wavelength frost heave might cause a large amplitude of the contact loss area underneath the slab track. The contact loss area weakens the constraint of the slab track, which also produces an increase in slab track vibration. There is contact pressure in the contact loss area when the vehicle passes by.
4. The slab track is lifted by the crest of frost. We observed a leverage effect, which might cause larger dynamic irregularity and lead to a greater dynamic response in the wheel-rail system. The initial bending condition caused by frost heave and the weak vertical constraint of the slab track amplify the leverage effect.  
With the ratio of wavelength to amplitude increasing, the contact loss area and the leverage effect are reduced. The influence mechanism of frost heave on the vehicle-track coupling system gradually tends to be dominated by track irregularity.  
Conceptualization, L.G. and W.Z.; methodology, L.G.; validation, W.Z. and B.H.; investigation, Y.Z.; data curation, B.H. and Y.Z.; writing--original draft preparation, L.G., W.Z.; writing--review and editing, W.Z. and B.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Key R&D Program of China (2016 YFB1200402), Key Program of National Natural Science Foundation of China (U1734206), National Natural Science Foundation of China--National Major Scientific Research Instrument Development Project (51827813) and Open Fund of National Key Laboratory of Track Technology(China Academy of Railway Sciences Corporation Limited)(2019 YJ197).  
The authors declare no conflict of interest.
## 1 Introduction
(2018), among others, is the application of a model to predict future values based on historical data; it is also suitable for grouting power prediction. Currently, three main types of time series prediction models have been proposed: conventional statistical approaches, intelligent methods, and hybrid models [PERSON] et al. (2018). Conventional statistical approaches, including autoregressive (AR) models [PERSON] et al. (2018) and autoregressive moving average (ARMA) models [PERSON] et al. (2018), are linear regression models, and a linear relationship is supposed between future values and historical values. However, considerable nonlinearity exists in the grouting power time series. Therefore, it is difficult to use conventional statistical approaches to capture the characteristics hidden in the grouting power time series. Artificial intelligence algorithms with good capabilities have emerged recently and are extensively used in time series prediction. ANNs [PERSON] and [PERSON] (2018) and SVMs [PERSON] et al. (2018) have flexible nonlinear modelling capability; however, they still have their own drawbacks. For example, NN models have problems of overfitting and are time consuming; meanwhile, sensitivity to parameter selection exists in both NN and SVM models. To overcome the inherent drawbacks of a single model, hybrid models based on the concept of \"decomposition-prediction-integration\" have been proposed recently and have proven to perform better than any single model alone in various fields, such as in landslide displacement [PERSON] et al. (2018) and hydrology [PERSON] et al. (2018). Therefore, a novel hybrid model aiming at overcoming the limitations of single models and obtaining good prediction accuracy is proposed in this study for grouting power time series prediction. This prediction model integrates the merits of the empirical wavelet transform (EWT), the partial  
Figure 1: The representation of grouting procedures. autocorrelation function (PACF), SVR, and an improved (IJaya) algorithm and is supposed to achieve better accuracy. The reminder of this paper is organized as follows: current studies related to the hybrid models based on \"decomposition-prediction-integration\" are presented in Section 2. The overall research framework is described in Section 3. Section 4 introduces the required individual methodologies, including the EWT, the PACF, SVR, and the IJaya algorithm. In Sections 5 and 6, a case study is performed, and the superiority of the proposed model is verified in comparison with four other competitors. Section 7 highlights the conclusions.
# Group Authentication Scheme for Neighbourhood Area Networks (NANs) in Smart Grids
###### Abstract  
A Neighbourhood Area Network is a functional component of the Smart Grid that interconnects the end user domain with the Energy Services Provider (ESP) domain. It forms the \"edge\" of the provider network, interconnecting homes instrumented with Smart Meters (SM) with the ESP. The SM is a dual interface, wireless communication device through which information is transacted across the user (a home) and ESP domains. The security risk to the ESP increases since the components within the home, interconnected to the ESP via the SM, are not managed by the ESP. Secure operation of the SM is a necessary requirement. The SM should be resilient to attacks, which might be targeted either directly or via the network in the home. This paper presents and discusses a security scheme for groups of SMs in a Neighbourhood Area Network that enable entire groups to authenticate themselves, rather than one at a time. The results show that a significant improvement in terms of resilience against node capture attacks, replay attacks, confidentiality, authentication for groups of SMs in a NAN that enable entire groups to authenticate themselves, rather than one at a time.  
Smart Grid; authentication; Smart Meters; key management Article
# Smart Topology Optimization Using Adaptive Neighborhood Simulated Annealing
## 6 Conclusions  
A new method for TO of mechanical structures is proposed in this work. The proposed method uses the concept of SA with crystallization heuristic to determine the optimal shape. The crystallization heuristic improved the search in the generation of the new candidate. Although this algorithm is non-gradient based and derivatives of the objective functions are not required, the algorithm uses a feedback action, depending on whether the new candidate is accepted or rejected, the crystallization factor is modified accordingly. A density filter is also applied when the thermal equilibrium is reached to smoothen the borders. Applying the proposed method to the classic problem of compliance minimization in the cantilever beam and MBB beam showed good agreement with the results from the literature. Similarly, the proposed method for the problem of minimizing heat transfer compliance showed good agreement with results from the literature. It shows that this method can be used for any type of problem regardless of the existence of sensitivity information.  
Since this method is new, a considerable amount of research and developments are required to improve and prepare it for commercial use. Future work could reduce the computational costs by the calculation of the objective function in different ways. This method could also be applied to multi-objective TO problems.  
Conceptualization, M.S.G.T., T.C.M. and A.B.; methodology, H.R.N., T.G.G. and M.S.F.; software, H.R.N. and T.G.G.; validation, H.R.N. and T.G.G.; writing-original draft preparation, H.R.N. and T.G.G.; writing-review and editing, M.S.G.T. and A.B.; supervision, M.S.G.T., T.C.M. and A.B.; project administration, T.C.M.; funding acquisition, T.C.M. All authors have read and agreed to the published version of the manuscript.  
[PERSON] is partially supported by the CNPq (grant 311.195/2019-9). [PERSON] was supported by FAPESP (grant 2019/03453-2). [PERSON] is supported by CAPES. The paper has support from CAPES/PROAP--grant 817.757/38.860.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
TO Topology Optimization  
SA Simulated Annealing  
OC Optimally Criteria  
SIMP Solid Isotropic Materials with Penalization  
MMA Method of Moving asymptotes  
GA Genetic Algorithm  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Volume Fraction** & **Compliance from [(8)]** & **Compliance from the Proposed Method** \\ \hline
0.5 & 250.75 & 224.56 \\
0.6 & 211.83 & 196.44 \\
0.7 & 189.88 & 182.27 \\
0.8 & 180.18 & 173.51 \\
0.9 & 170.89 & 169.11 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Minimized heat transfer compliance for different volume fractions from the literature and the method proposed herein.
# Design and Optimization of a Toothed-Plate Single-Roller Crushing Device for Waste Plastic Film
## 3 Design and Theoretical Analysis of the Crushing Component
### Crushing Roller Vibration Frequency Analysis  
The rotating crushing roller is prone to vibration, and these vibrations will cause fatigue damage to the crushing components, affecting the service life and even causing accidents. Therefore, ANSYS was used to perform modal analysis on the T\({}_{1}\), T\({}_{2}\), and T\({}_{3}\) crushing rollers to analyze their excitation frequencies and maximum deformation. The numerical simulation results are shown in Figure 5 and Table 1.  
Figure 4: The three types of crushing rollers: (**a**) T\({}_{1}\), (**b**) T\({}_{2}\), and (**c**) T\({}_{3}\). The grids represent the arrangement of the toothed plates, the black points represent the toothed plates, and the horizontal lines represent the position of the toothed-plate holders, 1, 2 and 3 represent the serial number of the toothed-plate holders.  
From Figure 5, it can be observed that in the first five modes, the locations of maximum deformation are similar for all three types. However, in mode 6, the T\({}_{3}\) crushing roller exhibits maximum deformation mainly on both sides, while the T\({}_{1}\) and T\({}_{2}\) crushing rollers show maximum deformation mainly in the middle. Table 1 shows that the minimum excitation frequency of the T\({}_{1}\), T\({}_{2}\), and T\({}_{3}\) crushing rollers in the first six orders are 401.71 Hz, 400.73 Hz, and 400.75 Hz, respectively, and the maximum deformation values are 2.89 mm, 2.86 mm, and 4.12 mm, respectively. Through calculations using Formula (2), it can be determined that the minimum excitation rotation speeds for the T\({}_{1}\), T\({}_{2}\), and T\({}_{3}\) crushing rollers are 24,103 r/min, 24,044 r/min, and 24,045 r/min, which are far greater than the design maximum rotation speed of 900 r/min. Therefore, all three types of crushing rollers are not expected to generate severe vibrations during operation.  
\[\omega_{e}=60f_{e} \tag{2}\]  
where \(\omega_{e}\) is the excitation rotation speed of the crushing roller, r/min, and \(f_{e}\) is the excitation frequency of the crushing roller, Hz.
# The ConTAD Project: Detection of Multi-Container Loss for Safety of Navigation +
## 4 Closing the Technological Gap: The ConTAD Approach
### No Hardware Installation on Board of Ships  
For quick adaptation of the proposed tracking unit, no further requirements, such as additional hardware on board ships, should be needed. This will keep the market entry costs low and increase the acceptance of the proposed tracking unit.
# Design and Implementation of Attitude Stabilization System for Marine Satellite Tracking Antenna
## 6 Conclusions  
A high performance attitude stabilization system is designed and implemented in this paper for the Ka-band MSTA. The system diagram is given and two important self-made electronic boards, the attitude sensor board and stepper motor control and drive board, are introduced with details. The robust velocity controller based on \(\mathcal{H}_{\infty}\) loop shaping is designed and the detailed design procedure is given. The designed attitude stabilization system was tested on a Stewart platform, which was used as a ship simulator. From the experimental results, it can be seen that the performance of designed attitude system is very high and the tracking angle error is less than 0.15 deg when the maximum velocity disturbance from Stewart platform is 26.2 deg/s. The performance of the designed robust controller has only been validated in the laboratory and not in the real ship environment, where hasher conditions can be expected. Thus, the designed controller needs to be further tested on a real ship to further validate its performance. Moreover, the MSTA usually continuously works for several months. In such case, the properties of the electronic and mechanical components would change, which can result in the variation of the nominal model used for robust controller design. Thus, a system performance decrease can be expected, which has not been analysed yet. Furthermore, only the pitch control loop is designed and implemented in this paper. However, there are actually totally three control loops (roll, pitch and yaw). The control loop design and implementation of the roll and yaw, together with the coupling effects between them, are left for future works.  
Figure 16: Running results of attitude stabilization system of MSTA in simulation environment.  
**Author Contributions:** [PERSON] contributed to defining the overall problem and proposed the core scientific idea to solve it. Y.W. student designed and implemented the hardware experiments to validate the proposed strategy. [PERSON] wrote the entire draft version of the paper, and revised it according to co-authors' comments. [PERSON] assisted in careful reviewing of the paper and proposed various refinements to the draft proposal made by the PhD student. [PERSON] helped review and improve the paper. [PERSON] had many valuable discussions with [PERSON] about the control system design.  
**Funding:** This work was supported by Innovation Fund Denmark under the project STAR2 COM (Jnr.060-2013-3)  
**Acknowledgments:** Authors would like to thank Innovation Fund Denmark for financial support. Thanks also go to SpaceCom A/S for providing assistance.  
**Conflicts of Interest:** The authors declare no conflict of interest.