esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Multi-Physics Coupled Method for the Temperature Field of Dry Clutch Assembly
## 3 Multi-Physics Coupled Simulation
### Fluid-Solid Coupling Model  
Since the dry clutch assembly is a more complex model, the hexahedral elements are used for relatively regular parts to improve accuracy and reduce the number of grids. The irregular structure parts are divided into tetrahedral unstructured grids to meet the grid quality and meet the convergence requirements of the numerical simulation.  
The dry clutch assembly model contains the pressure plate, diaphragm springs, rivets, and transmission plates. To determine the convective heat transfer coefficient of the dry clutch assembly with the ambient air under different angular velocities, the enclosure tool in SCDM code is used to create the external flow field region of the clutch. A cylindrical shape is set to simulate the spatial domain of the fluid, as shown in Figure 4. The entire assembly is meshed using tetrahedral unstructured grids, with a total of 59,642 nodes and 340,175 elements. The mesh partitioning effect is shown in the diagram below, in Figure 5.  
The determined fluid-thermal coupling boundary conditions and main parameters are as follows:  
1. To ensure computational convergence, a time step of 0.1 s is set with a total of 300 steps. The energy equation is enabled.
2. The realizable turbulence model and Enhanced Wall Treatment (EWF) are used.
3. The rotational speed is applied to the coupled wall surfaces covered by the fluid domain. The fluid domain rotates around the Y-axis at a speed of 1400 rpm.
4. The material properties of the pressure plate, friction plate, transmission plate, rivets, and diaphragm spring are defined according to Table 3. The fluid domain is set to default air gas.
5. The heat flux model based on the sliding power is applied to the friction surface of the pressure plate. The sliding power is calculated using the test bench data for each engagement-disengagement cycle. The convective heat transfer coefficient required for solving the neighboring wall surface heat transfer is obtained.
# Registration of Urban Aerial Image and LiDAR Based on Line Vectors
## 2 Methods
### Practical Procedure of Solving the Problem  
The proposed adjustment mode includes the following five parts, and all the data are associated automatically:  
(1) Representation of a Straight Line  
The unit line vector coordinate constituted by any two points \(G\) (\(X_{G}\), \(Y_{G}\), \(Z_{G}\)) and \(H\) (\(X_{H}\), \(Y_{H}\), \(Z_{H}\)) of a control line in the LiDAR data coordinate system is [19]:  
\[\begin{array}{c}l=X_{H}-X_{G},m=Y_{H}-Y_{G},n=Z_{H}-Z_{G}\\ r=Y_{G}Z_{H}-Y_{H}Z_{G},s=Z_{G}X_{H}-Z_{H}X_{G},r=X_{G}Y_{H}-X_{H}Y_{G}\end{array} \tag{8}\]  
Similarly, line vectors can be used to express two imaging rays \(Sh\) and \(Sg\).  
(2) Determination of Initial Values  
We can determine the original values of the unknown values \(q\) by inputting rotation parameters \(\omega\), \(\phi\), \(\kappa\), and translation parameters \(X_{L}\), \(X_{L}\), \(X_{L}\) into Equation (9):  
\[\begin{array}{c}q_{1}=-\sin\frac{\varphi}{2}\sin\frac{\varphi}{2}\sin\frac{ \varphi}{2}+\cos\frac{\varphi}{2}\cos\frac{\varphi}{2}\cos\frac{\pi}{2}\\ q_{2}=-\cos\frac{\varphi}{2}\sin\frac{\varphi}{2}\sin\frac{\pi}{2}+\sin\frac{ \varphi}{2}\cos\frac{\pi}{2}\cos\frac{\pi}{2}\\ q_{3}=-\cos\frac{\varphi}{2}\sin\frac{\varphi}{2}\cos\frac{\pi}{2}-\sin\frac{ \varphi}{2}\cos\frac{\pi}{2}\sin\frac{\pi}{2}\\ q_{4}=-\cos\frac{\varphi}{2}\cos\frac{\varphi}{2}\sin\frac{\pi}{2}-\sin\frac{ \varphi}{2}\sin\frac{\varphi}{2}\cos\frac{\pi}{2}\\ \left[\begin{array}{c}q_{01}\\ q_{02}\\ q_{03}\\ q_{04}\end{array}\right]=\left[\begin{array}{c}2q_{2}\ -2q_{1}\ -2q_{4}\ 2q_{3}\\ 2q_{3}\ 2q_{4}\ -2q_{3}\ 2q_{2}\ -2q_{1}\\ 2q_{1}\ 2q_{2}\ 2q_{4}\ 2q_{4}\end{array}\right]^{-1}\left[\begin{array}{c}X_{L}\\ Y_{L}\\ Z_{L}\\ 0\end{array}\right]\\ \end{array} \tag{9}\]  
(3) Establishment of the Error Equation  
For the least-squares adjustment, the coplanarity equations (Equation (5)) are linearized in the form:  
\[V=AX+F \tag{10}\]  
where the observations are the image coordinate measurements, and the unknowns are the registration parameters described by \(X\). \(V\) are the correction values of the observed values. \(F\) are the residual terms of the observed values, which are obtained by putting the approximate value of the unknown value on the left-hand side of Equation (5). \(A\) are the coefficient terms of the error equation.
## 1 Introduction
[26] experimentally investigated the effects of surface roughness on the skin friction coefficient with a mixture of freezer oil and glycerol water when one of the inner and outer walls of shaft-type gap was rotating and the other was stationary. These authors found that the skin friction coefficient depended on the Reynolds number and surface roughness when the outer wall rotated, but was only related to surface roughness and not the Reynolds number when the inner wall rotated. To the best of our knowledge, the current studies have mainly focused on the skin friction coefficient under the assumption of smooth walls, and few reports have investigated the impacts of surface roughness. In addition, according to a previous study [5], a large Reynolds number is known to influence windage loss and the flow characteristics in the shaft-type gap. Thus, the effects of the high density of sCO\({}_{2}\) and high rotational speed of TAC units, which results in a Reynolds number larger than \(10^{5}\)[27], on the skin friction coefficient are significantly crucial. Finally, few researchers have paid attention to the influence of the radius ratio on TC flow and shaft-type windage loss. Based on the deficiencies of the current research, the influences of surface roughness and radius ratio on windage loss and flow in a shaft-type gap of generator with critical CO\({}_{2}\) are studied in this paper. Firstly, the skin friction coefficient versus Reynolds number is presented. Then, the impacts of surface roughness and Reynolds number on flow state are analyzed in detail. Finally, the effects of the radius ratio are discussed at a surface roughness of 0.8 \(\upmu\)m. The conclusions of this paper can help develop a model for predicting the skin friction coefficient for shaft-type gaps with rough walls, which is beneficial for the design and operation of smaller sCO\({}_{2}\) power devices, including TAC units.
## 2 Fiber Optic Nerve Systems for Structural Health Monitoring
This function provides us with simultaneous dynamic strain measurements at the arbitrarily selected multiple points. The \"random accessibility\" is the unique feature that cannot be realized by the time-domain technologies. Performance enhancement schemes have been  
Figure 2: Varieties of fiber optic nerve systems. (**a**) Multiplexed fiber optic sensing; (**b**) distributed fiber optic sensing; and (**c**) quasi-distributed fiber optic sensing. proposed and demonstrated for--for example--a longer measurement range, shorter spatial resolution, larger strain measurement dynamic range, and higher measurement speed [3]. Superior performances, such as a spatial resolution of 1.6 mm, a measurement speed of 5000 points/s with random accessibility, and a strain dynamic range of 7000 \(\mu\varepsilon\), have already been demonstrated individually. Of course, these superior performances cannot be realized at the same time. These have mutual relations, which restrict the total performance of the sensing system. In this paper, such an aspect is also discussed briefly. Application trials have already been performed using the BOCDA systems for the SHM of--for example--aircraft bodies, civil structures, and so on. In 2008, we also proposed and demonstrated \"Brillouin optical correlation domain reflectometry\", BOCDR for short, in which the spontaneous Brillouin scattering that is caused along the sensing fiber is measured position-selectively [9]. In BOCDR, the random accessibility can also be realized. The performance enhancement schemes for BOCDR have been developed, which are similar to those for BOCDA. The ratio between the measurement fiber length and the spatial resolution of 134,000 has recently been demonstrated in a BOCDR system with the performance enhancement schemes. In 2010, a discriminative and distributed strain/temperature measurement scheme was also proposed and demonstrated [18], using both the BOCDA scheme and \"Brillouin dynamic grating (BDG)\", which is a phenomenon that is associated with the stimulated Brillouin scattering process [19; 20]. Ways to improve the measurement performances have also been proposed and demonstrated, including the spatial resolution improvement in the distributed BDG measurement by the BOCDA scheme. In this paper, the principles, functions, and applications of SOCF, BOCDA, BOCDR, and BDG-BOCDA technologies are reviewed, including these historical aspects. Recently, varieties of research studies and developments related to optical correlation-domain distributed fiber sensors have been accumulated in various institutions, and these examples are also shown briefly.
## 7 Conclusions  
In this paper, a three-dimensional (3D) finite element model of dynamic rock breaking with an innovative 3-RDE cutter has been established. The extended Drucker-Prager criterion is used as the constitutive model of rock. The accuracy of the numerical model was verified by experimental results. The effects of back-rake angle, cutting depth, rotational angle and rock properties on the rock breaking efficiency were analyzed. The difference of rock breaking mechanism between the 3-RDE cutter and the conventional cutter was also studied. The following conclusions can be drawn:  
1. Due to the different shape, the rock breaking mechanism of conventional PDC cutter is mainly shear failure, while the 3-RDE cutter not only shears the rock in the same way as the conventional cutter, but also delivers a crushing action similar to a roller cone insert with a higher rock breaking efficiency. The cutting edge and working face of conventional cutter synchronously interact with the rock, while the 3-RDE's convex edge and working surfaces asynchronously break the rock. The forces required by the 3-RDE cutter are smaller, and the cutting process is more stable and efficient.
2. The cutting forces and their fluctuations, as well as MSE, of 3-RDE cutter increase with the increase of the back-rake angle. A small back-rake angle should be selected for the design.
3. With the increase of cutting depth, the cutting forces and their fluctuations, as well as MSE, of 3-RDE cutter increase. Reasonable cutting depth facilitates the rock breaking.
4. With the increase of the rotational angle, the cutting forces and theirs' fluctuations, as well as MSE, of 3-RDE cutter increase gradually. When designing or manufacturing the 3-RDE PDC bit, the rotational angle should be set at 0\({}^{\circ}\) to ensure that the 3-RDE cutter's convex edge is perpendicular to the rock surface.
5. Simulation results and field trials show that compared with the conventional cutter, the 3-RDE cutter is easier to penetrate into the formation and more stable with less torque required. The use of 3-RDE cutter in hard abrasive heterogeneous formation can achieve a higher ROP and save costs.  
Combined with the content of this paper, works in the future will focus on the optimization of the structure parameters and the cutting geometry of the 3-RDE cutter in order to have a better inspection for 3-RDE PDC bit design.  
Figure 21: Pictures of bits after field trials: (**a**) 3-RDE PDC bit in gravel formation; (**b**) Hybrid bit in gravel formation; (**c**) 3-RDE PDC bit in granite formation; (**d**) Conventional PDC bit in granite formation.  
**Author Contributions:** Conceptualization and methodology, Y.K.; methodology, H.X.; software, J.L.; formal analysis and writing, J.L. and H.X.; validation. H.Z. and C.Q.  
**Funding:** This research was supported by the National Oil and Gas Major Project of China (Grant No. 2016 ZX05038005-001).  
**Conflicts of Interest:** The authors declare no conflict of interest.
# An RTK UAV-Based Method for Radial Velocity Validation of Weather Radar
## 2 Materials and Methods
### UAV Routes Design Based on Radar Geographic Information
#### 2.3.2 Calculation of the Altitude of the Two Endpoints on the UAV Route  
The first step is to determine the slant distances \(L_{start}\) and \(L_{end}\) between the two endpoints of the route and the radar. The distance of the start point \(L_{start}\) needs to be greater than the range of the radar far-field, and \(L_{end}\) needs to be determined based on the radar range resolution and the UAV constant motion range bins (\(N\) usually \(\geq\)5).  
\[L_{end}=L_{start}+N\times\text{Resolution} \tag{8}\]  
Second, based on the radar elevation angle and the slant distance between the UAV route endpoints and the radar, the actual flight altitude of the two endpoints is calculated. It is worth noting that the experiment required the UAV to always remain within the main radar beam and as close to the center as possible. Therefore, considering the altitude restrictions of the UAV, the theoretically calculated altitude of the main beam center point is determined as the optimal altitude for the UAV route.  
As shown in Figure 2, assuming that the radar elevation angle determined by the volume scan data is \(\alpha\), the antenna feeds altitude is \(H_{1}\), and \(L\) is the slant distance between the UAV route point and the radar, the altitude of the radar beam center point \(H_{2}\) is given by the equation.  
\[H_{2}=L\sin\alpha+H_{1} \tag{9}\]  
It should be noted that the effective input to the UAV is the altitude of the target location, so the UAV route altitude needs to be calculated by incorporating the antenna feed altitude information rather than the actual elevation information.
## 2 Dynamic Modeling and Linearization  
In the design of vibration-suppression-oriented control strategies for robotic manipulators, an accurate dynamic model serves as a critical foundation for parameter identification and model-based compensation. To establish a high-precision dynamic model suitable for parameter identification under vibratory conditions, the Newton-Euler method is employed to derive the rigid-body dynamic equations. Subsequently, the technique of minimal parameter set construction is applied to formulate a linear regression form suitable for identification. In addition, the influence of unstructured disturbances such as friction and joint flexibility is taken into account, leading to a matrix representation of the mass matrix. This formulation provides a theoretical basis for the integration of nonstructural compensation models in subsequent sections.  
The modeling framework adopted in this paper builds upon classical rigid-body dynamics and joint flexibility representations commonly used in robotic systems [3]. While the fundamental equations follow established principles, the overall modeling process, including the combination of flexible joint dynamics, zero-boundary Fourier excitation trajectories, and subsequent data-driven disturbance modeling is independently designed and implemented by the authors to support the proposed identification method.
# Wide-TSNet: A Novel Hybrid Approach for Bitcoin Price Movement Classification
## 5 Results and Discussion
### Experimental Results
#### 5.2.1 Different Image Generation and Classifier Techniques
Despite their lower Accuracy and F1 score, this reduced computational requirement makes them a more efficient choice in scenarios where computational resources are limited. Finally, the EfficientNet models required a minimum of 14.924 GiB and took an average of 10 min and 48 s for a 40-epoch run. While they exhibited a slightly higher computational requirement than SqueezeNet, they still balanced performance and efficiency. \begin{table}
\begin{tabular}{c c c c c} \hline
**Model** & **Accuracy** & **F1 Score** & **Precision** & **Recall** \\ \hline Wide-TSNet & 0.939614 & 0.900686 & 0.901232 & 0.900054 \\ \hline Wide ResNet + GASF & 0.888235 & 0.776290 & 0.775972 & 0.776608 \\ Wide ResNet + GADF & 0.890196 & 0.778253 & 0.768930 & 0.787805 \\ Wide ResNet + MTF & 0.874510 & 0.710430 & 0.711149 & 0.709712 \\ \hline SqueezeNet + GASF & 0.848403 & 0.735559 & 0.732773 & 0.738366 \\ SqueezeNet + GADF & 0.821536 & 0.737268 & 0.734545 & 0.740011 \\ SqueezeNet + MTF & 0.803628 & 0.639979 & 0.640627 & 0.639332 \\ \hline EfficientNet + GASF & 0.875887 & 0.764666 & 0.751254 & 0.778566 \\ EfficientNet + GADF & 0.875688 & 0.765998 & 0.765684 & 0.766312 \\ EfficientNet + MTF & 0.860341 & 0.698523 & 0.699230 & 0.697817 \\ \hline \end{tabular}
\end{table} 
Table 2: The experimental results as compared to Wide-TSNet. \begin{table}
\begin{tabular}{l l l} \hline
**Model** & **Memory (GiB)** & **Training Time (40 Epochs)** \\ \hline Wide ResNet & 15.36894 & 13 min 36 s \\ SqueezeNet & 13.10000 & 10 min \\ EfficientNet & 14.92400 & 10 min 48 s \\ \hline \end{tabular}
\end{table} 
Table 3: Computational and time performance of CNN models.
# Dynamic Handwriting Analysis for Neurodegenerative Disease Assessment: A Literary Review
## 1 Introduction
### Motivations and Purposes
Although several advancements have been so far obtained through the analysis of static characteristics of handwriting, i.e., the ones that can be analyzed after the writing process has already occurred, with the advent of new technologies, novel, dynamic features of handwriting have been available to the research community. These features concern the _dynamic_ characteristics of handwriting that can be acquired while the writing process still occurs. Typical acquisition tools are inexpensive commercially available digitizing tablets and/or electronic pens. Through these devices, one can measure not only temporal and spatial variables of handwriting but also the pressure exerted over the writing surface and measures of pen inclination and pen orientation. Moreover, these devices can capture pen movement not only while the pen is in contact with the writing surface but also when the pen is in close proximity of the surface, i.e., \"in-air\". In the context of neurodegenerative diseases assessment, dynamic handwriting analysis has been employed for studying several issues and has attracted considerable research interest from psychologists to neuroscientists and from physicians to computer scientists. A large part of the literature on this topic investigated fine motor control in healthy and unhealthy people. Examining changes in the handwriting of impaired patients, in fact, facilitates the understanding of the brain-body functional relationships and can lead to identifiable patterns of the sensorimotor dysfunction associated with PD or AD. Several other studies focused on the effects of medication on handwriting: these changes can provide a useful tool for monitoring and tracking disease progression. More recently, an increasing research effort has been made towards the development of an automatic tool for the discrimination between impaired subjects and healthy controls on the basis of dynamic handwriting features. The goal is to provide a complementary approach to the pathology evaluation performed by expert clinicians that is quantitative, noninvasive, and very low-cost. This paper aims at providing an overview of the most relevant literature investigating the application of dynamic handwriting analysis to the assessment of neurodegenerative disorders. In particular, PD and AD, as the two most widespread and most extensively investigated disorders, are taken into account.
# Edible Packaging: A Technological Update for the Sustainable Future of the Food Industry
## 3 Results
### Production of Edible Films and Coatings
#### 3.3.1 Wet Process  
The wet process, mainly comprising the casting method (or solvent casting), is the most commonly used method for the production of films on a laboratory or pilot scale. In the wet process, the film-forming contents are homogenized with a solvent and dried to obtain a film. This process involves three steps. Dissolving or dispersing the biopolymers in solvents is typically the first step that needs to be carried out to generate films. Additives like antimicrobial agents, plasticizers, and flavoring or coloring agents [11] are added to the matrix material to boost these materials' durability and flexibility [3]. Adjusting the pH and heating the solutions above their melting point to increase their solubility is a possible requirement. This film-forming solution is then cast onto a flat surface and dried at the proper temperature and relative humidity; the resulting film can then be used to wrap the food products [6]. In the casting step, the film-forming solution is poured into a predefined mold or Teflon-coated glass plate. The drying step allows for solvent evaporation, which makes a mold-attached polymer film. In this step, air driers like hot air ovens, tray dryers, microwaves, and vacuum dryers are used for the casting of films [13]. Figure 1 shows a schematic representation of the casting process for edible film production.  
A significant advantage of the casting method is that it can be easily employed without special equipment. Additionally, as many food-processing materials cannot withstand higher temperatures, lower temperatures during the processing steps can be beneficial. The casting process, on the other hand, has drawbacks such as a longer drying time, which makes it unsuitable for commercial manufacturing. In addition, moving film production from the laboratory to large-scale production presents a challenge due to the possibility of variations in quality and a risk of limiting the constant development of commercial operations caused by factors like heating, speed, and temperature [13].
# Utilization of Partially Liquefied Bark for Production of Particleboards
The thermal analysis showed that the adhesives based on hydrochloric acid-catalyzed liquefied wood had a higher maximum temperature, a greater height of exothermic peak, and a larger quantity of exothermic heat at thermosetting than the adhesives based on sulfuric acid-catalyzed liquefied wood. Particleboard made with resol adhesives based on liquefied Taiwan acacia bark catalyzed by sulfuric acid had the best mechanical properties and the lowest thickness swelling among all particleboard panels. A complete moderate-acid catalyzed liquefaction process of biomass in alcohols or phenols takes approximately 90-120 min under constant stirring and heating [9; 12]. The obtained compounds require further purification stage to retrieve liquids for applying in adhesive formulations, which is time- and energy-consuming. Therefore, present work explores a novel approach at the production of partially liquefied bark (PLB) and its further utilization in manufacturing particleboard panels. Changes in the chemical characterization structure, thermal stability, and water vapor sorption behavior of bark due to partial liquefaction process were determined by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and automated vapor sorption (AVS) apparatus, respectively on the solid residues of PLB. The effect of PLB on the physical, mechanical, and microscopic structure of particleboard made with or without MUF adhesives were then analyzed. It was hypothesized that bark was partially solvolyzed after liquefaction generating PLB, which is a chemical-activated particle that can be incorporated for better compatibility with wood particles, and can thus enhance the physical and mechanical properties of the particleboard.