esa-sceva/satcom-chunk-collection huggingface dataset:
# Force Performance Analysis and Numerical Simulation of Assembled Ribbed-Slab Abutments
## 4 Parametric FE Analysis of Assembled Ribbed-Abutments
### Analysis of the Impact of the Number of Screws  
According to the results of the shear test, it can be concluded that the connection between the flanges primarily relies on bolting, with the number of bolts being an important factor affecting the structural load-carrying capacity. In this subsection, bolts with a diameter of 52 mm were used, and five working conditions were set for the parametric analysis: 18 bolts (18 LS), 16 bolts (16 LS), 14 bolts (14 LS), 12 bolts (12 LS), and 10 bolts (10 LS). According to the Bridge Regulation (JTG D62) [23], the shear capacity of the midspan section of the cast-in-place abutment model with the same reinforcement rate was calculated to be 6073.83 kN. The shear capacities with different numbers of bolts are listed in Table 6, and the corresponding load-deflection curves are shown in Figure 16. The trends of the load-displacement curves of the flange models with different numbers of bolts are shown in Figure 16. The load-displacement curves of the models with different numbers of flanges exhibited the same trend. The ultimate displacements of the ARBA with 18 LS flanges increased by 5.3 and 17.6% compared with those of the ARBA with 16 LS and 14 LS flanges, respectively, and decreased by 4.1 and 3.5% compared with those of the ARBA with 12 LS and 10 LS flanges, respectively. We hypothesized that, in case of fewer bolts in the flange, the stiffness of the structure decreased, leading to an increase in its ultimate displacement. The ultimate load-carrying capacity of the ARBA with 18 LS flanges increased by 1.5, 3, 3.7, and 8.3%, compared with the ARBA with 16 LS, 14 LS, 12 LS, and 10 LS flanges, respectively.  
Figure 15: Load–displacement curves for different stiffener rib thicknesses.  
The strength of the flange plate is a very important parameter for the assembly of ribbed bridge abutments connected by the flange plate, which directly affects the stiffness of the flange nodes. If the strength of the flange is too small, it will cause the end plate to form plastic hinges in advance at the point of maximum stress, resulting in node failure. Excessive flange strength can waste material performance as well as increase the node britteness. The results in Figure 16 show that, when 12 or more bolts were used in the flange, the rate of increase in the ultimate load-carrying capacity of the structure decreased; therefore, it is not recommended to use less than 12 bolts in the flange connection to avoid the excessive weakening of the load-carrying capacity of the structure. Moreover, when the number of bolts in the flange exceeded 12, the increase in the number of bolts versus the increase in the ultimate load-carrying capacity of the structure approached a linear relationship.
# Mechanical and Dielectric Properties of Aligned Electrospun Fibers
###### Abstract  
This review paper examines the current state-of-the-art in fabrication of aligned fibers via electrospinningning techniques and the effects of these techniques on the mechanical and dielectric properties of electrospun fibers. Molecular orientation, system configuration to align fibers, and post-drawing treatment, like hot/cold drawing process, contribute to better specific strength and specific stiffness properties of nanofibers. The authors suggest that these improved, aligned nanofibers, when applied in composites, have better mechanical and dielectric properties for many structural and multifunctional applications, including advanced aerospace applications and energy storage devices. For these applications, most fiber alignment electrospinningning research has focused on either mechanical property improvement or dielectric property improvement alone, but not both simultaneously. Relative to many other nanofiber formation techniques, the electrospinningning technique exhibits superior nanofiber formation when considering cost and manufacturing complexity for many situations. Even though the dielectric property of pure nanofiber mat may not be of general interest, the analysis of the combined effect of mechanical and dielectric properties is relevant to the present analysis of improved and aligned nanofibers. A plethora of nanofibers, in particular, polyacrylamide(PAN) electrospun nanofibers, are discussed for their mechanical and dielectric properties. In addition, other types of electrospun nanofibers are explored for their mechanical and dielectric properties. An exploratory study by the author demonstrates the relationship between mechanical and dielectric properties for specimens obtained from a rotating mandrel horizontal setup.  
electrospinning; aligned nanofibers; molecular orientation; mechanical; dielectric +
Footnote †: journal: Physics Letters
# A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery
## 4 Applications of AI in Early Fault Diagnosis of Rotating Machinery  
### Knn  
In a KNN-based fault diagnosis algorithm, the signal is first processed by other techniques to extract the fault features, aiming to constructing the fault feature vector. Then the fault feature vector is taken as the input of KNN to identify early fault of rotating machinery. [PERSON] et al. [150] transformed the raw signal into a discrete component, which was represented by a histogram form summarizing the occurrence of the chosen symbols. The histogram was taken as the input of KNN for fault location and severity identification of rolling bearing. [PERSON] et al. [151] combined S transform with morphological pattern spectrum for feature extraction, and then KNN was used to identify bearing faults. [PERSON] et al. [152] used EEMD to extract features. Then a hybrid binary bat algorithm combined with a machine learning algorithm was used to reduce the dimensionality and select the predominant features. Finally, KNN was used to identify gear faults at an early stage. [PERSON] et al. [153] proposed a squeezing and stretching method to preprocess the signal, and then a hidden Markov model was built. The parameters of this model were used as input of KNN for fault detection and diagnosis in synchronous motors. [PERSON] [154] proposed filter bank methods to decompose bandwidth-limited signals into a set of narrow-band components. The similarity between the input signal and each extracted narrow-band component was used as fault features and KNN was used to identify different types of faults. The above mentioned methods are summarized in Table 10.
# A Lightweight Secure and Energy-Efficient Fog-Based Routing Protocol for Constraint Sensors Network
## 2 Related Work
In [27], the authors proposed a framework for data collection from WSN towards the cloud using elements of mobile fogs. It uses the factors of distance and residual energy for the formation of routing paths and decreases the level of energy consumption and latency ratio. The simulation-based experiments demonstrated that the proposed framework outperforms routing performance compared to traditional solutions. However, the proposed framework did not notice the network threats that may be risky for data transmission and their effects on data privacy and its integrity. Moreover, the routing paths are chosen without an in-depth analysis of uncontrolled links, which results in increased response time and communication cost. In [28; 29], the authors proposed fog-based routing solutions for improving energy efficiency and trust management. The proposed solution reduces energy consumption and increases network throughput in the wireless scenario. However, they overlooked the measurements of the transmission links, and, as a result, in large size nodes distribution, the end-to-end latency increases. Also, the overburden links cause frequent data loss and unnecessary data-retransmissions, which results in network overheads. Table 1 illustrates the contributions and limitations of the existing work and proposed SEFR protocol. The background work shows the contribution of the IoT paradigm integrated with WSNs to ease different applications. Due to their dynamic and easy infrastructure, different fields obtain environmental data on time. The distributed low powered sensor nodes perform a key role for data collection and routing towards remote users for their necessary actions. However, the limited restrictions on network resources set remarkable research challenges for energy constraints and time-sensitive applications. Moreover, some solutions integrated the cloud paradigm for data management in terms of storage and processing. Such solutions increase network performance in IoT applications for cost efficiency and data management. However, such solutions encountered latency for large-scale distribution regions and additional energy consumption problems. It is also seen that some cloud-based solutions do not consider optimal forwarding, and thereby result in data disruption and insufficient time management. Although fog computing offers a distributed environment to collaborate with cloud and IoT sensors, most of the solutions result in exposure to security problems in terms of confidentiality and authentication, which is harmful to sensitive and real-time sensors' data. Also, most of the fog-based solutions ignored the valuation of data links and as a result, route breakages increase with additional route re-discoveries requests. Based on the findings from related work, it is observed that developing a lightweight secure and energy-efficient routing protocol for constraint sensor networks with the integration of fog computing is a demanding problem to ease time-sensitive and quality assurance applications [30; 31; 32].
# Diagnosing Phosphorus Limitation in Subtropical Forests in China under Climate Warming
## 4 Discussion
### Limitations and Further Studies  
While great efforts have been made to reduce the uncertainties in the diagnosing of the P limitations in subtropical China, there are still some sources of uncertainty that were not taken into account in this study. First, the synergistic effect of N and P is neglected, which may result in higher estimation of AAPD in N-limited areas. Second, ecosystem-level manipulation experiments have shown that climate warming will gradually change the C:P ratios in ecosystems [1; 56; 57], while human activities, such as fertilization and pollution, also changes C:P ratios in ecosystems [1; 56; 57]. However, the C:P ratios for plant organs are assumed to be constant during the study periods. Third, the allocations of vegetation carbon to roots, stem and leaves are assumed to be constant, but are changed with nutrient availability [58].  
Further studies are needed to better understand and quantify the effects of N-P interactions, dynamic C:P ratios and vegetation carbon allocations on the P limitation. A comprehensive sensitivity analysis would help us to improve our understanding of the uncertainties, and will be an important part of our future research. In addition, the distribution of current ASP in subtropical China has large heterogeneity [59], and is a major factor affecting the degrees of P limitation, and, hence, further studies need to conduct more field investigations to understand the spatial distribution of ASP and P limitation in subtropical China.
# Characterization of a Modified Clinical Linear Accelerator for Ultra-High Dose Rate Beam Delivery
###### Abstract  
Irradiations at Ultra-High Dose Rate (UHDR) regimes, exceeding 40 Gy/s in single fractions lasting less than 200 ms, have shown an equivalent antitumor effect compared to conventional radiotherapy with reduced harm to normal tissues. This work details the hardware and software modifications implemented to deliver 10 MeV UHDR electron beams with a linear accelerator Elekta SL 18 MV and the beam characteristics obtained. GaChromic EBT XD films and an Advanced Markus chamber were used for dosimetry characterization, while a silicon sensor assessed the machine's beam pulses stability and repeatability. The dose per pulse, average dose rate and instantaneous dose rate in the pulse were evaluated for four experimental settings, varying the source-to-surface distance and the beam collimation, i.e., with and without the use of a cylindrical applicator. The results showed a dose per pulse from 0.6 Gy to a few tens of Gy and an average dose rate up to 300 Gy/s. The obtained results demonstrate the possibility to perform in vitro radiobiology experiments and test new technologies for beam monitoring and dosimetry at the upgraded LINAC, thus contributing to the electron UHDR research field.  
ultra-high dose rate; FLASH radiotherapy; LINAC; dosimetry; electron beam; silicon sensors; GaChromic films Article
# SHPB Experiment and MPM Simulation on Dynamic Properties of Unsaturated Clay Under Impact Loading
## 3 MPM Simulation on SHPB Test of Unsaturated Clay
### Numerical Simulation Validation  
Figure 9 shows the comparison of experimental and simulated stress-strain curves of unsaturated clay at different strain rates. As can be seen, the simulated stress-strain curve has a similar variation trend to the experimental results. Additionally, the testing and simulated dynamic peak stresses are almost the same. However, as the strain rate increases up to 541 and 590 s\({}^{-1}\), there are some differences between the testing and simulated curves in the plastic flow and failure stages. For numerical simulation, the update of volumetric strain and stress follows the strict theoretical formula. But for the SHPB tests, the experimental results may be affected by various factors, such as microscopic pore characteristics and saturation conditions. Especially for high loading rate conditions, local saturation or stress concentration is likely to occur as the pore pressure develops rapidly and cannot dissipate in time [22]. These uncertainties may account for the observed differences between the experimental and simulated stress-strain curves. Anyhow, the comparison results demonstrate the potential of the modified MPM to effectively simulate the dynamic properties of unsaturated soil with a reasonable accuracy.  
Figure 8: Model description of SHPB test.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Type** & **Description** & **Parameter** & **Value** \\ \hline \multirow{4}{*}{Pysical} & Density & \(\rho\) (g/cm\({}^{3}\)) & 1.74 \\  & Moisture content & \(\omega\) (\%) & 40.3 \\  & Specific gravity & \(G_{s}\) & 2.69 \\  & Porosity & \(e\) & 1.27 \\ \hline \multirow{4}{*}{D-P model} & Young modulus & \(E\) (MPa) & 5 \\  & Poisson’s ratio & \(\
u\) & 0.25 \\  & Cohesion & \(c\) (kPa) & 202.47 \\  & Friction angle & \(\varphi\) (\({}^{\circ}\)) & 5.94 \\ \hline \multirow{4}{*}{VG model} & Maximum degree of saturation & \(S_{max}\) & 1 \\  & Minimum degree of saturation & \(S_{min}\) & 0.01 \\  & Reference pressure & \(P_{0}\) (RPa) & 1950 \\  & Fitting parameter & \(\lambda\) & 0.4 \\ \hline \multirow{2}{*}{CS model} & Intercept & \(C\) & 56 \\  & Slope & \(P\) & 0.8 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Material parameters of unsaturated clay used in simulation.
## 1 Introduction
The settlement caused by the aforementioned traffic vibration loads is quite substantial, similar to the primary consolidation settlement caused by a large additional static load increment. Analyzing the reason for this significant subsequent settlement using the stress-strain constitutive relationship and phenomena like creep, rheology, and secondary consolidation established by the indoor dynamic triaxial test method [3, 4, 5, 6, 7, 8] proves challenging. Accurately predicting the post-construction settlement is also difficult. Additionally, the vibration frequencies used in these experimental studies are relatively low, typically ranging from 0.05 Hz to 1 Hz, which hardly encompasses the frequency range of traffic vibration loads. Current research on dynamic triaxial tests primarily focuses on the changes and developmental trends of soil under cyclic loading. Numerous mathematical models have been established to predict the variation of cumulative plastic strain [9, 10, 11, 12] and cumulative pore water pressure [13, 14, 15, 16] of soil with the number of cycles. However, there is a lack of effective summarization regarding the final changes experienced by the soil under these dynamic loads. Therefore, references [17, 18] proposed investigating the reconsolidation behavior of soft clays under vibration loads (cyclic loads without an overall compressive or tensile tendency within a cycle) after consolidation under static loads. Employing a novel indoor testing method, the study delved into the reconsolidation phenomenon induced by vibration loads. The research revealed that the reconsolidation behavior of soft clays is very evident. Vibration loads propagate through the foundation in the form of waves. The dynamic response of the entire roadbed-foundation system under traffic vibration loads may vary depending on the specific characteristics of the foundation [19]. This study first analyzed the vibration response in different roadbed-foundation systems using numerical simulations to investigate the distribution pattern of vibration loads within the foundation. Next, vibration reconsolidation tests were conducted to explore the reconsolidation behavior of soft clays under vibration loads. The influence of vibration load frequency and amplitude on the reconsolidation effect was briefly analyzed. Finally, combining the analysis of the consolidation mechanism of soft clays under vibration loads, the paper explored the reasons behind the significant post-construction settlement of roadbeds on soft clay foundations under traffic vibration loads from both the perspectives of wave propagation and vibration.
# Before and After: A Multiscale Remote Sensing Assessment of the Sinop Dam, Mato Grosso, Brazil
## 2 Materials and Methods
### Analysis  
#### 2.6.1 Satellite Image Classification  
The satellite image mosaics from the four time periods (Table 1) were classified with eCognition Developer 9.4 (Trimble Geospatial, Sunnyvale, CA, USA) using a Geographic Object Based Image Analysis (GEOBIA) approach. GEOBIA classification is often more effective and efficient for imagery with high spatial detail and low spectral resolution [61; 62] than pixel-based classification. It aims to replicate human interpretation of imagery by exploiting patterns, texture, and recognition of objects [63; 64]. The four mosaics were first segmented with the multiresolution segmentation algorithm using the following parameters: scale = 50, shape = 0.1 and compactness = 0.5. Training samples of objects representing _water_, _closed canopy forest_, _crops_, _soil_, _open canopy forest_, _inundated forest_, and _other_ throughout the study area were manually selected (Figure 7). The \"_other_\" class included, clouds, cloud shadows, and built-up areas. We included object level mean and standard deviation values of brightness (i.e., average of the means of the bands), maximum difference (i.e., maximum difference between bands), and the reflectance from each band in the nearest neighbor feature space for training data for a nearest neighbor classification.  
The resulting individual classes were simplified to water (including open water and inundated forest), soils and agriculture, and forest (including closed and open canopy forest) in ArcMap 10.7 (ESRI, Redlands, CA, USA). The polygon layers were inspected through an overlay with the corresponding mosaic and erroneous class labels were corrected manually (e.g., dark shadows along the boundary between forest and soil classes). For the few areas where small clouds obstructed the classification of the reservoir margins of the high-water mosaic (Jan-Feb 2020), the polygon vertices were edited to trace the shoreline of the reservoir without cloud cover. The final edited polygon layers from each mosaic were dissolved to classifications representing water, forest, and soil/agriculture.  
Figure 7: Examples of classes selected for the land cover classification. The left panel of each pair (with the red dots) illustrates the land cover through a 33 \(\times\) 33 pixel window (\(\sim\)1 ha) from a Dove PS image (3 m pixel size). The right panels (with the blue dots) illustrate a subset of the corresponding land cover as seen from a UAS photograph (not to scale).  
Three hundred sixty-nine random points (distance \(\geq 30\) m) were generated within the footprint of the high-water reservoir extent in ArcMap. The associated land cover class was manually interpreted for each point from the low water, pre-inundation satellite image mosaic (2014), and used to assess the accuracy of the classifications of the land cover within the footprint of the reservoir.
## 2 Development of Beam Element-Based Simulation
### Model Description
#### 2.1.1 Element Activation  
Elements are activated as they are printed through a two-step process. It is assumed that just-printed elements contribute self-weight but not stiffness to the structure as shown in Figure 3. Element activation times, corresponding to when the centroid of an element is printed and easily derived from G-code, are input to the model. During the first time step after activation, the self-weight of the new elements is applied. In the next time step, new nodes corresponding to the new elements are activated with an initial vertical position based on the deformed position of the nodes below. Then the new elements are added to the model and their self-weight is applied to the centerline of these new elements. New elements are assigned an initial displacement based on the current position of their nodes, which does not cause stress or strain in the element.  
Figure 3: Element activation.
## 4 Protocols Protecting Terminal Devices in Zero-Trust Networks
### Security Analysis in Zero-Trust Networks
#### 4.3.3 Replays, Man-in-the-Middle, and Side Channel Analysis  
Both replays and the man-in-the-middle attack disturb normal operations and should be mitigated. The opponents intercept several subkeys Kr thus preventing the terminal device from receiving them. Subsequently, the opponent sends these subkeys, but not necessarily in the right order, which could have a catastrophic impact. The mitigation of such attacks add a feedback loop to inform the controlling server that the signal was well received by the terminal device at the right time. Adding a code at the end of each file that the terminal device has to send back to the controlling server is an effective implementation. Protection against the side channel analysis should be implemented. The protocol has several advantages from that standpoint: the noise injected in the network during the transmission of Kr can disturb the side channel analysis and the subkeys are only used once.