esa-sceva/satcom-chunk-collection huggingface dataset:
# GNSS-Based Vertically Monitoring of Super-Tall Buildings
###### Abstract  
In the construction of super-tall buildings, it is rather important to control the verticality. In general, a laser plummet is used to transmit coordinates of reference points from the ground layer-by-layer, which can effectively control the verticality of super-tall buildings. However, the errors in transmission will accumulate with increasing height and motion of the buildings in construction. This paper presents a global navigation satellite system (GNSS)-based method to check the results of laser plumbing. The method consists of four steps: (1) Computing the coordinate time series of monitoring points by adjusting the GNSS monitoring network observations at each epoch; (2) Analyzing the horizontal motion of super-tall buildings and its effect on vertical reference transmission; (3) Calculating the deflections of the vertical at the monitoring point using an Earth gravity field model and a geoid model. With deflections of the vertical, the static GNSS-measured coordinates are aligned to the same datum as used by the laser plummet; and (4) Finally, validating/checking the result of laser plumbing by comparing it with static GNSS results corrected by deflections of the vertical. A case study of a 438-m high building is tested in Guangzhou, China. The result demonstrates that the gross errors of baseline vectors can be eliminated effectively by GNSS network adjustment of the first step. The two-dimensional displacements can be measured at millimeter-level accuracy; the difference between the coordinates of the static GNSS measurement and laser plumbing is less than \(\pm\)2.0 cm after correction with the deflections of the vertical, which meets the design requirement of \(\pm\)3.0 cm according to the Technical Specification for Concrete Structures of Tall Buildings in China.  
Global Navigation Satellite System (GNSS); super-tall buildings; motion; verticality monitoring; gross error elimination; deflections of the vertical 2018 8991; doi:10.3390/app8060991
# Research on Robust Day-Ahead Dispatch Considering Primary Frequency Response of Wind Turbine
###### Abstract  
With the large-scale integration of renewable energy sources (e.g., wind power), the system inertial response and primary frequency regulation are affected. The virtual synchronous generator technology, which makes it possible for wind power units to adjust the frequency, provides a new way of approaching this problem. In this paper, we set up the related constraints that fit the optimal dispatch framework with a primary reserve representing the primary frequency response between the conventional synchronous generator and the wind power units, and the technical parameters of the virtual synchronous generator. Meanwhile, we use the robust day-ahead optimization dispatch model considering the wind power integrated primary frequency control in the real-time operation with the scenario of the wind power output showing the uncertainty of wind power. Based on the model, we identify the key set using an iterative method and obtain the maximum power loss. Through the proposed model, we could provide the day-ahead unit output and real-time primary reserve, thus ensuring the reliable operation of the system. Finally, the effectiveness of the proposed method is verified by a computational experiment.  
primary frequency response; wind power; robust dispatch; primary reserve; virtual synchronous generator +
Footnote †: journal: Applied Sciences
[PERSON]  
1 Yunnan Institute of Geological Survey, Kunming 650216, China; [EMAIL_ADDRESS] (S.X. ); [EMAIL_ADDRESS] (X.Z. ); [EMAIL_ADDRESS] (Y.H. ); [EMAIL_ADDRESS] (Y.L. ); 13648894458163.com (Y.X.X. ); [EMAIL_ADDRESS] (X.S. ); [EMAIL_ADDRESS] (Z.C. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (Z.H. ); [EMAIL_ADDRESS] (Z.H. ); [EMAIL_ADDRESS] (Z.H. ); [EMAIL_ADDRESS] (Z.H. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (Z.H.) [PERSON]  
1 Yunnan Institute of Geological Survey, Kunming 650216, China; [EMAIL_ADDRESS] (S.X. ); [EMAIL_ADDRESS] (X.Z. ); [EMAIL_ADDRESS] (Y.H. ); [EMAIL_ADDRESS] (Y.L. ); 13648894458163.com (Y.X.X. ); [EMAIL_ADDRESS] (X.S. ); [EMAIL_ADDRESS] (Z.C. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (Z.H.) [PERSON]  
1 Yunnan Institute of Geological Survey, Kunming 650216, China; [EMAIL_ADDRESS] (S.X. ); [EMAIL_ADDRESS] (X.Z. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (Y.L. ); 13648894458163.com (Y.X. ); [EMAIL_ADDRESS] (X.S. ); [EMAIL_ADDRESS] (Z.C.C. ); l the Multi-Purpose Regional Geochemistry Survey (NMPRSG) [7], and the China Geochemical Baselines (CGB) projects [8; 9] have facilitated geochemical map contouring. There are three traditional methods of contouring geochemical maps: the cumulative frequency method, which depends on the cumulative distribution-free percentiles of the data [10; 11; 12; 13], the logarithmic interval method, which is based on the range of the data expressed in logarithmic values [12], and the Avg\(\pm\)k\(\ast\)Std (where Avg and Std are the abbreviations of average and standard deviation, and k is a multiple of the Std) method, which relies on the normal (or log-normal) distribution of the data [13]. However, with the increasing scope of the study area and cumulative data, the limitations of traditional methods, which depend on the amount of data, are exposed. To overcome these flaws in traditional methods, [PERSON] et al. [14] proposed a fixed-value method to contour the geochemical map of Cr. In the fixed-value method for the Cr geochemical map [14], Cr concentrations were divided into 26 levels on 25 fixed values ranging from 5 \(\mu\)g/g (corresponding to the detection limit) to 171,000 \(\mu\)g/g (corresponding to the cutoff grade of 25% for Cr\({}_{2}\)O\({}_{3}\) in ores). The 26 levels were mapped in six color tones. However, the fixed-value method was proposed by [PERSON] et al. [14] can only be applied to the geochemical Cr map as other elements have not been presented. In this study, three traditional methods were used to contour the Sn geochemical map in the Gejiu area in Southwest China. Then, we proposed and applied a fixed-value method for the Sn geochemical map in this case study. Finally, the geochemical maps contoured by the four methods were compared and discussed.
# Matching and Control Optimisation of Variable-Geometry Turbochargers for Hydrogen Fuel Cell Systems
###### Abstract  
The turbocharging of hydrogen fuel cell systems (FCSs) has recently become a prominent research area, aiming to improve FCS efficiency to help decarbonise the energy and transport sectors. This work compares the performance of an electrically assisted variable-geometry turbocharger (VGT) with a fixed-geometry turbocharger (FGT) by optimising both the sizing of the components and their operating points, ensuring both designs are compared at their respective peak performance. A MATLAB-Simulink reduced-order model is used first to identify the most efficient components that match the fuel cell air path requirements. Maps representing the compressor and turbines are then evaluated in a 1D flow model to optimise cathode pressure and stoichiometry operating targets for net system efficiency, using an accelerated genetic algorithm (A-GA). Good agreement was observed between the two models' trends with a less than 10.5% difference between their normalised e-motor power across all operating points. Under optimised conditions, the VGT showed a less than 0.25% increase in fuel cell system efficiency compared to the use of an FGT. However, a sensitivity study demonstrates significantly lower sensitivity when operating at non-ideal flows and pressures for the VGT when compared to the FGT, suggesting that VGTs may provide a higher level of tolerance under variable environmental conditions such as ambient temperature, humidity, and transient loading. Overall, it is concluded that the efficiency benefits of VGT are marginal, and therefore not necessarily significant enough to justify the additional cost and complexity that they introduce.  
fuel cell system; PEM fuel cell; turbochaninery; optimization; hydrogen vehicle; turbo matching; 1D modelling Article
# Lead Monoxide Nanostructures for Nanophotonics: A Review
## 3 Properties and Applications in Nanophotonics
### Bandgap Properties  
A variety of strategies, such as the density functional theory (DFT) and Tauc plots based on UV-Vis-NIR absorption spectroscopy, were performed to systematically study the electronic band structure in both monolayer and few-layer PbO. Because of the different characterization techniques, the \(E_{\mathrm{g}}\)s of the PbO with different thicknesses obtained from the experimental and theoretical results may have slight differences. In 2018, [PERSON] et al. [19] used DFT calculations to demonstrate that the \(E_{\mathrm{g}}\) of 2D PbO could be easily tuned by an external electric field with a huge Stark effect. The band structures of the monolayer (1L), double-layer (2L), triple-layer (3L), and bulk state of 2D PbO are shown in Figure 7a. The relationship between the \(E_{\mathrm{g}}\) and layer number (\(N\)) of 2D PbO can be well fitted as \(E_{\mathrm{g}}=1.66\times N^{-0.3}+1.9\), and shows that 2D PbO has a converged \(E_{\mathrm{g}}\) value as \(N\) reaches up to 7 (Figure 7b). It should be pointed out that the 2D PbO with an \(N\) ranging from 10 (2.73 eV) to 30 (2.50 eV) can absorb light with a wavelength of \(<\)500 nm, which is in good accordance with the optical result in Figure 6a. In addition, in 2018, [PERSON] et al. [89] reported  
Figure 5: The structural characterizations of 3D PbO nanostructures. (**a**) Typical SEM image of 3D PbO nanostructures prepared by thermal deposition at 420 \({}^{\circ}\)C for 30 min. Reproduced with permission from Reference [83]. Copyright 2012, Elsevier B. V. (**b**) TEM image of 3D PbO nanostars formed at the air/water interface with the subphase concentration of 1 \(\times\) 10\({}^{-4}\) mol L\({}^{-1}\) at 30 \({}^{\circ}\)C (inset showing the corresponding SAED pattern). Reproduced with permission from Reference [44]. Copyright 2011, Elsevier B. V.  
that manganese (Mn)-doped PbO films were successfully fabricated by an ultrasonic spray pyrolysis, and the \(E_{\text{g}}\) of Mn-doped PbO films calculated by the Tauc plot based on the absorption spectra varied with the increase in the Mn doping level. As seen in Figure 7c, there was an initial increase in the \(E_{\text{g}}\) for the Mn-doped PbO films with a smaller doping level of Mn, followed by a significant reduction in the \(E_{\text{g}}\) at a higher doping level of Mn. It can be observed that the \(E_{\text{g}}\) value of Mn-doped PbO films improves as the Mn doping level reaches \(<\) 2 mol% compared with that of the pure PbO film. However, with the further enhancement in the Mn doping level, the \(E_{\text{g}}\) value largely decreases. The \(E_{\text{g}}\) value has a minimum value of 1.66 eV as the Mn doping level further increases to 10 mol%, which is mainly attributed to the structural deformation in the PbO films induced by the Mn ion substituting Pb ions in the PbO lattice. This phenomenon is in good accordance with the fact that the crystallinity of PbO thin films gradually declines as the concentration of doped Mn increases [89].
# 2D Phase-Based RFID Localization for On-Site Landslide Monitoring
## 2 Instrumentation and Methods  
### Experimental Site: Harmaliere Landslide  
The Harmaliere landslide (Sinard, Isere, France) is located in the Trieves area about 50 km south of Grenoble in the western Praelps (see Figure 1). Trieves appears as a sedimentary plateau eroded by the Drac river; the plateau is formed by Quaternary carved clays and alluvial materials deposited in a glacially dammed lake during the Wurm period [44]. Quaternary sediments also include silts, sometimes with a morainic cover, and rest on either interglacial Riss--Wurm period glacifluvial materials (gravels and sands) or on the underlying Jurassic carbonate bedrock. The thickness of the clay deposits can vary from 0 to a maximum of 200 m [45]. The landslide is southeast oriented, 400 m wide at the top, narrowing to 150 m at the toe. It develops from an altitude of 735 m (asl), down to the Monteynard Lake (480 m), over a distance of about 1.5 km. It was abruptly activated in 1981 and has remained active ever since, with new peaks of activity in 2016 and 2017 [46]. The slow moving landslide shows regressive behaviour, the headscar retreating at an average velocity of 1 m/year, with very strong variations from year-to-year (including almost a decade of rest). The central body of the landslide is moving at velocities ranging from cm/year to m/year, with possible dramatic acceleration phases (m/day). A variety of research subjects are currently investigated in connection with it [46; 47].
# Theoretical Derivation and Optimization Verification of BER for Indoor SWIPT Environments
## 3 Resource Allocation Problem Formulation
### Optimization Problem Formulations  
The problem formulation in our indoor SWIPT system aims to maximize the efficiency of energy harvesting and to provide reliable communication in the network. The problem formulation is defined as  
\[\begin{array}{ll}\text{maximize}:&\eta_{eff}(w),\\ \text{constraint}:&\text{BER}\leq W_{BER}\end{array} \tag{23}\]  
The system objective in Equation (23) is maximizing the efficiency of the energy harvesting of the system. \(W_{BER}\) is the constraint for the system parameter, which denotes the required BER to maintain the data quality [18].
# Detection of Forest Windstorm Damages with Multitemporal SAR Data--A Case Study: Finland
## 4 Results
### The Damage Map Along with Area and Area Error Estimates  
An example of the predicted damages in a map form was made using the ik-NN method. The damage was predicted only to forests in which the volume of growing stock exceeded 75 m\({}^{3}\)/ha. Ten Sentinel-1 scenes with the dates of 16 January, 28 January, 9 February, 2 July, 14 July, 21 July, 26 July, 2 August, 19 August and 20 August were used.  
A good practice with poststratified estimators was used in estimating the area of the damage categories (Section 3.6). The area of the classified forestry land (forest land, poorly productive forest land and unproductive land) was 799,000 ha. The severe damage was predicted for an area of 97,600 ha that corresponds to 12% of the mapped area and slight damages for an area of 76,200 ha (9.5% of the mapped forestry land area). Some individual pixels with wrong damage predictions increase the area of the damages. The large-scale damage patterns generally follow the windstorm patterns on 12 August 2017 (Figures 9 and 10). The poststratified estimates of the relative errors were 9% and 10%, respectively.
## 3 Experimental Results and Discussion
### In-Plane Test
#### 3.2.3 Comparison of Quasi-Static and Dynamic Behavior  
To avoid uncertainties related to size effects [17], the results of specimens of the same size under quasi-static and dynamic tests are compared in Figure 31. The dynamic behavior was different from the quasi-static behavior. One different feature is that the stress-strain relationship of the quasi-static loading was firstly non-linear and then linear, while the stress-strain relationship of the dynamic loading seems to be firstly linear and then non-linear. Another different feature is that, after fracture, the stress-strain curve showed a sudden drop in the quasi-static loading, while the stress-strain curve dropped gradually in the dynamic loading. There were also some similar features between dynamic  
Figure 30: The fracture stress and strain of different specimens.  
Figure 29: The fitted modulus of the \(8\times 8\times 8\) specimens.  
and quasi-static behavior. During both quasi-static and dynamic loading, the stress increased as the strain increased, and finally the specimen failed at the fracture point. In addition, the specimen could still hold the loading to some extent after fracture in both quasi-static and dynamic loading [28].  
With regard to the fracture stress shown in Figure 32a, the dynamic fracture stress was higher than the quasi-static fracture stress. The dynamic fracture stress kept increasing as the strain rate increased. With regard to the fracture strain shown in Figure 32a, the dynamic fracture strain was lower than the quasi-static fracture strain. The dynamic fracture strain rate increased with the increasing strain rate. With regard to the modulus shown in Figure 32b, the modulus under dynamic loading was higher than the modulus under quasi-static loading. The dynamic modulus decreased slightly with the increasing strain rate. Table 5 shows the quantitative results of the \(8\times 8\times 8\) specimens.
## 6 Experiments  
In the following section, we will showcase the practical benefits of our method while providing an in-depth comparison between its behavior and that of traditional GANs. Specifically, this part consists of five subsections:  
1. We conducted a series of controlled experiments on two real-world datasets [30,31]. On the one hand, we verified the effectiveness of the dynamic borderline softening mechanism proposed in Section 4. On the other hand, we demonstrated the qualitative and quantitative superiority of the SoftGAN compared to other algorithms [2, 14, 18, 23, 32, 33, 34, 35, 36, 37, 38, 39] under the same architecture configurations.
2. The learning goal of the generative model is to implicitly approximate the distribution of the real data. We used qualitative and quantitative methods to visualize the distribution distance change between real data and generated data during training. It verified the effectiveness of the dynamic borderline softening mechanism of our SoftGAN.  
Figure 3: The influence of different \(\beta\) values to the discriminator \(D\). \(\beta\) is proportional to the uncertainty of the soft borderline.  
3. The mode collapse in GAN training is one of the research focuses of the SoftGAN. With the help of the Geometry Score [13], we quantitatively compare the mode coverage ability and the mode discovery efficiency of our SoftGAN with other methods [2,14] in the training process.
4. Evaluating the mode coverage of a generative model on datasets with limited categories poses challenges. However, on datasets containing numerous categories, a generative model boasting robust mode coverage capabilities is expected to generate samples from a broader range of categories. As a result, we employed a classifier model [40] to assess, specifically on the ImageNet dataset [41], whether our model's generator exhibits enhanced coverage across all 1000 categories. This evaluation indirectly serves as evidence of the SoftGAN's mode exploration prowess.
5. Our work introduces a flexible dynamic borderline softening mechanism, which seamlessly integrates into pre-existing GAN frameworks. By combining this mechanism with diverse architectures [1,19,20,42] and varied adversarial losses [1,3,14,20,23], we have successfully demonstrated that the SoftGAN can enhance the target model's capabilities without compromising the quality of the generated outputs, as evidenced by qualitative and quantitative indicators. Additionally, the parameter sharing approach for shallow layers effectively alleviates computational burdens, further enhancing the efficiency of the model.  
All experiments are conducted on four Nvidia GeForce RTX 3090 graphics cards with 24 GB implemented in Pytorch [43]. For the hyperparameter \(\beta\), we use its theoretical upper bound (as shown in Proposition 4) as the initial value in all experiments. And the demo implementation is available at Github ([[https://github.com/liweileev/SoftGAN](https://github.com/liweileev/SoftGAN)]([https://github.com/liweileev/SoftGAN](https://github.com/liweileev/SoftGAN)), accessed on 23 August 2023).
## 3 Proposed TFR Approach
### Operations
#### 3.2.1 Detecting the Fault Occurrence  
In the case of a fault occurrence in the network, such as a link failure between the MC and the SCs, the SCs detect the failure by using the Link-Alive timer. Each OC and BC in the network starts this specific timer to identify the failure in the network segment. After this duration, the slave ports identify the fault occurrence and start activating all the ports of the node, including the passive state ports, and they broadcast a Link-Alive message through all the ports toward the MCs in the same network segment. The Link-Alive message targets the MCs in the network exclusively as the sources of the synchronization in the PTP networks. Consequently, the Link-Alive message includes information to identify the slave nodes that receive this specific message and request a new synchronization mechanism from the MCs. The fields of the Link-Alive message are addressed as follows:  
* Link-Alive flag: identifies the port state of the transmitting node as either a slave port (\(\text{flag}=1\)) or a master port (\(\text{flag}=0\)).
* Clock-Request flag: identifies the port of the transmitting node requesting clock synchronization (\(\text{flag}=1\)).
* PortID: identifies the port identifier of the transmitting node (slave port).  
Figure 4: The TFR process. TFR: timing fault recovery.  
In this case, the slave ports identify the Link-Alive flag (\(\text{flag}=1\)) and the Clock-Request flag (\(\text{flag}=1\)), and they use their specific port identifiers. This specific message, as shown in Figure 5, uses the PTP message header [5] and the Signaling message type.
# Internet of Spacecraft for Multi-Planetary Defense and Prosperity
## 4 Planetary Defense: State-of-the-Art
### State of the Art Space Objects Detection
#### 4.3.2 Detection and Early Warning  
Generally speaking, the current detection capability of NEOs is highly related to both the dimension and perihelio distances of NEOs. Theoretically, the smaller a NEO's dimension or perihelio is, the harder it can be to detect. The current detection system and detection range are mainly intended for near-Earth asteroids/comets with a maximum perihelio distance of 1.3 AU.  
It will be more challenging to survey and locate non-NEO asteroids/comets such as in the MAB, the Kuiper belt, or even further regions of the solar system. However, these asteroids/comets can potentially become NEOs when a collision or gravitational disturbance flings them inward [143]. Authors in [120] have conducted an in-depth analysis of possible escape routes for asteroids to enter the near-Earth space.  
On the other hand, there are possibly billions of comets that are orbiting the Sun and located in the Kuiper Belt and even more distant Oort Cloud. However, only 3743 of them so far have been discovered according to NASA [123]. The comets' orbits could be potentially altered due to gravitational disturbance, solar flare burst, collision, etc. As a result, it would not be a rare scenario for a comet to enter near-Earth space at high speed. 'Oumuamua is a typical case, and it was only 0.22 AU away from Earth when we discovered it [134]. Furthermore, it has been reported by NASA astronomers that 6 months' warning is not enough, and 5 to 10 years of preparation may be needed to stop an asteroid from hitting Earth based on the simulated exercise conducted by the 2021 Planetary Defense Conference [144]. Consequently, it will be critical and necessary to enhance the detection capability so that more preparation time could be obtained for humanity.