esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Dune Sand on Drying Shrinkage Cracking of Fly Ash Concrete
## 4 Conclusions  
This study experimentally evaluated the drying shrinkage cracking characteristics of FA concrete for various unit water contents and DS/FA ratios. The results can be summarized as follows:  
1. In the mixture conditions of this study, the DS/FA ratio of 10% was optimal for compressive strength and split tensile strength. Depending on the DS/FA ratio, the difference in strength could occur by more than 10%.
2. In the average net time-to-cracking results, the mixtures with a DS/FA ratio of 20% showed the highest crack resistance. The risk of drying shrinkage cracking could be improved by up to about 24% by optimal replacement of DS.
3. The correlations of the shrinkage strain, shrinkage stress, and strain rate with the net time to cracking were not close in this study. In addition, the shrinkage stress at cracking was higher than the splitting tensile strength of the concrete. Therefore, to predict the shrinkage cracking of concrete, the complex actions of various factors must be considered.
4. The optimum DS/FA ratio for the strength and crack resistance of concrete is different. Therefore, it is necessary to consider DS replacement according to the required performance of concrete.
5. The restraint effect factors of the aggregates were analyzed based on the relationship between the volume change of each aggregate type and the change in net time to cracking. The restraint effect factor of CS was found to range from 0.71 to 0.98 and that of DS from 0.56 to 0.90 when the restraint effect factor of CA was 1 for all the mixtures.  
Conceptualization, E.L.; methodology, J.N.; validation, J.K., J.Y. and S.P.; formal analysis, E.L. and J.N.; investigation, E.L., J.K., J.Y. and S.P.; data curation, E.L.; writing--original draft preparation, E.L.; writing--review and editing, J.N.; supervision, S.P.; project administration, E.L. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. Not applicable. Not applicable. Not applicable. Data Availability Statement: Not applicable. Not applicable. Conflicts of Interest: The authors declare no conflict of interest.
# Prediction of Friction Resistance for Slurry Pipe Jacking
## 5 Influence of Design Factors on Lubrication Efficiency and Friction Resistance
### Influence of Design Factors on Friction Resistance  
The influences of design factors (\(h\), \(D_{p}\), and \(\Delta R\)) on the critical quantities of effective friction coefficient \(\mu\), normal force acting on the pipe \(N\), and friction resistance \(f\) are respectively shown in Figure 9a-c, Figure 9d-f, Figure 9g-i.  
It is evident that increasing buried depth and pipe diameter led to a double action for the increasing of friction resistance. Firstly, this increase then increased the possibility of contact between the pipe and soil, and, therefore, increase the effective friction coefficient \(\mu\) on the interface. Secondly, the increasing of buried depth increases the vertical soil stress, while the increasing of pipe diameter increases the contact area, both effects of them increase normal force \(N\) acting on the pipes. The main difference between the two is that buried depth causes both of the effective friction coefficient and normal force to slightly increase and then gradually stabilize, while they approximately linearly increase with pipe diameter. Especially for the normal force induced by pipe diameter, which is strongly increased from 29.83 to 991.34 kN, this leads to a notable increase of friction resistance from 0.34 to 48.16 kN/m. Thus, the additional friction is strongly affected by the pipe diameter but appears not to be greatly affected by the buried depth.  
Different from the buried depth and pipe diameter, the overcut with small values has no effect on the normal force (Figure 9h). However, it has a strongly negative effect on the effective friction coefficient on the interface (Figure 9g). In fact, it does determine the volume of injected lubricant  
Figure 9: The influence of factors of \(h\), \(D_{p}\), and \(\Delta R\) on the quantities of \(\mu\) (**a–c**), \(N\) (**d–f**), and \(f\) (**g–i**).  
slurry, which has a significant influence on the occurrence of the pipe-soil contact, and, therefore, determine the magnitude of the effective friction coefficient. Thus, it has a strongly negative effect on the friction resistance.
# Progressive Dynamic Registration Method for Tile Maps Based on Optimum Multi-Features
## 4 Experimental Results and Applications
### Method Accuracy Verification and Comparison
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**ID**} & \multirow{2}{*}{**Scale**} & \multicolumn{2}{c}{**The Method of This Paper**} & \multicolumn{2}{c}{**SURF + RANSAC**} & \multicolumn{2}{c}{**Coordinate System Conversion**} \\ \cline{3-7}  & & **RMSE** & **Offset Value** & **RMSE** & **Offset Value** & **RMSE** & **Offset Value** \\ \hline
1 & 12 & 1.224 & [\(-\)639.01, \(-\)179.24] & 6.066 & [\(-\)845.39, \(-\)33.63] & 1.541 & [\(-\)694.99, \(-\)203.51] \\
2 & 12.5 & 1.527 & [\(-\)681.77, \(-\)154.08] & 586 & [14892.15, \(-\)5420.31] & 1.695 & [\(-\)694.99, \(-\)203.51] \\
3 & 13 & 1.526 & [\(-\)688.78, \(-\)165.73] & \(\times\) & \(\times\) & 1.105 & [\(-\)694.99, \(-\)203.51] \\
4 & 13.5 & 1.105 & [\(-\)679.20, \(-\)198.53] & \(\times\) & \(\times\) & 1.732 & [\(-\)694.99, \(-\)203.51] \\
5 & 14 & 1.699 & [\(-\)684.53, \(-\)185.83] & \(\times\) & \(\times\) & 1.452 & [\(-\)694.99, \(-\)203.51] \\
6 & 14.5 & 1.452 & [\(-\)692.79, \(-\)199.13] & \(\times\) & \(\times\) & 1.563 & [\(-\)694.99, \(-\)203.51] \\
7 & 15 & 1.291 & [\(-\)698.72, \(-\)208.52] & \(\times\) & \(\times\) & 1.414 & [\(-\)694.99, \(-\)203.51] \\
8 & 15.5 & 2.108 & [\(-\)698.72, \(-\)208.52] & \(\times\) & \(\times\) & 1.943 & [\(-\)694.99, \(-\)203.51] \\
9 & 16 & 2.397 & [\(-\)699.74, \(-\)205.39] & \(\times\) & \(\times\) & 2.091 & [\(-\)694.99, \(-\)203.51] \\
10 & 16.5 & 2.298 & [\(-\)696.56, \(-\)206.49] & \(\times\) & \(\times\) & 2.329 & [\(-\)694.99, \(-\)203.51] \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Registration results of three methods in vector maps of Beijing. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**ID**} & \multirow{2}{*}{**Scale**} & \multicolumn{2}{c}{**FDR**} & \multicolumn{2}{c}{**SURF + RANSAC**} & \multicolumn{2}{c}{**Coordinate System Conversion**} \\ \cline{3-7}  & & **RMSE** & **Offset Value** & **RMSE** & **Offset Value** & **RMSE** & **Offset Value** \\ \hline
1 & 12 & 1.768 & [\(-\)610.08, 414.25] & 1.760 & [\(-\)618.52, 408.70] & 1.732 & [\(-\)528.19, 391.93] \\
2 & 12.5 & 2.031 & [\(-\)534.30, 424.22] & 8.062 & [\(-\)732.92, 392.56] & 1.369 & [\(-\)528.19, 391.93] \\
3 & 13 & 1.581 & [\(-\)515.19, 405.11] & 145.710 & [1226.34, 2516.97] & 1.767 & [\(-\)528.19, 391.93] \\
4 & 13.5 & 2.168 & [\(-\)555.72, 364.57] & 605.070 & [\(8619.72, 4837.16] & 1.581 & [\(-\)528.19, 391.93] \\
5 & 14 & 3.000 & [\(-\)546.17, 374.
## 3 Results
### An Example of Estimates of Probabilities of True and False SC Recognitions  
We used one-minute-averaged data from INTERMAGNET observatories [2]: ASP, BEL, BFO, BLC, BMT, BOU, BRW, BSL, CLF, CSY, CTA, DOU, EBR, ESK, EYR, and FCC. The total number of observatories in the calculation was \(P_{0}=16\). We analyzed the 1-minute-sampled data for the whole period of 2015 \(H_{rp}(T(i))\), \(r=0,1,\ldots,3\), \(p=1,\ldots,P_{0}\), \(P_{0}=16\), comprising \(TN_{f0}=T\cdot 1440\cdot 365=T\cdot 5.265\cdot 10^{5}\) minutes. The local intervals \(i_{1l}\), \(i_{2l}\), \(i_{1l}=1+\Delta i_{0}(l-1)\), \(i_{2l}=\Delta i_{0}l\), \(l=1,\ldots,l_{f}\), \(\Delta i_{0}=10\) were determined; \(l_{f}=5.265\cdot 10^{4}\) is the number of local intervals.  
A total of \(N_{SC}=17\) global SC events were identified by the International Service on Rapid Magnetic Variations [11] at the INTERMAGNET observatory EBR (Ebro, Spain). The number of sub-intervals where SC were absent was \(N_{0 SC}=l_{f}-N_{SC}=5.2633\cdot 10^{4}\).  
For assigned iteration bounds \(H_{Nd,0 mx}=1000\), \(H_{Nd,0 mn}=200\), and \(m_{f}=5\) a sequence of threshold values \(H_{Nd,0}(m)\) was calculated. Estimates of the probability of correct and false SC recognition were then obtained using Equation (6). Figure 3 shows the probabilities \(\beta=\beta_{RD}^{\circ}(H_{Nd,0}(m))\) and \(\alpha=\alpha_{FD}^{\circ}\) (\(H_{Nd,0}(m)\)), as a function of the threshold value \(H_{Nd,0}=H_{Nd,0}(m)\).  
Our calculations show that if the probability of a false SC recognition is limited to \(\alpha_{0}=0.05\), the optimal threshold value is \(H_{Nd,0}^{\circ}\approx 800\) nT/min; in this case, the probability of correct SC recognition turned out to be \(\beta_{RD}=0.75\). These probabilities indicate that our method for detecting SC events is quite effective. The method can be improved due to the optimal choice of the quantity of the analyzed datasets from magnetic observatories and increasing the temporal interval of observations.  
Figure 2: Results of calculating the derivatives of the components and the modulus of the geomagnetic field (nT/min), ASP observatory.
# Coproduction as an Approach to Technology-Mediated Citizen Participation in Emergency Management
## 2 Conceptual Foundations: From Community-Based EM to Coproduction
Table 1 summarizes two different perspectives of EM as described in [16]: the classical top-down approach initiated and led by organizations versus a community-level approach where EM is built on the basis of social capital as a basic resource to cope with disasters. In the table each cell specifies the goals that are pursued from each perspective at each of the phases of EM. For instance, in the classical top-down approach, during the _preparation phase_ the governmental agencies are in charge of designing plans and train first responders to be ready to act in case of an event, whilst in a _participatory_ perspective what has to be done is to strengthen existing social structures and connections so that they can be mobilized in case of an event [28]. Whilst the first one strongly relies on the role of professional EM workers, the second one tries to capitalize or reinforce the resources that already exist or might exist in a community of citizens. In this case, citizens are not only reactive to the crisis; they can also be proactive and be prepared to be less vulnerable. In this work we assume the [PERSON]'s conception of social capital that highlights the role of civic engagement in creating good government by promoting coordinated action [29] with a view of conceiving EM as a coproduction service. Reproduction is way to provide public services in partnership with citizens and by positing that EM should be envisioned as a coproduction service we are recognizing that citizen participation is not an option, but a requirement, to adhere to FEMA's definition of the of role of EMAs previously introduced [25]. Indeed it has been demonstrated that successful experiences in coproduction increases civic engagement in other community activities, and hence contributes to develop social capital [30]. According to [PERSON], coproduction faces three basic challenges: existence of social capital outside the organization, existence of social capital within the organization, and coordination among citizens and the organizations [14]. The existence of social capital and digital social capital has been already discussed in the literature [1; 3; 17; 27; 28]. In this work we will focus on how social and mobile computing can contribute to improve coordination among citizens and organizations taking into account the perspective of the organizations, EMAs, which are the ones who hold the social responsibility on EM. In particular, we aim at understanding how technological tools can substantively empower both citizens and institutions to act in an integrated and coordinated coproduction service. In the next section we describe a design case use that based on a participatory design process where EMA workers and decisions makers perceptions and ideas were used to envision social and mobile computing technologies that could eventually help to move the EM process towards a coproduction service.
# Design and Analysis of a Novel Floating Docking Mechanism for On-Orbit Refueling
## 3 Mechanical Properties of an Elliptical-Helical Pipe  
An elliptical-helical pipe with bias loading has a lower axial stiffness than a circular-helical pipe traditionally as a refueling pipe, which is beneficial for the driving force. However, there is no derivation of the mechanical properties of elliptical-helical pipes. In this section, the expression of the axial stiffness and the strength checking of elliptical-helical pipes are derived to guide the design of this type of pipe.
## 3 Results and Discussion
### Impact of Drought on Cereal Yields
The SPEI-based CHIRPS precipitation data and the Era5-Land temperature data have demonstrated better performances in monitoring and characterizing the drought impacts on cereal yield. Their strengths include extensive spatial coverage, enabling the accurate evaluation of drought effects on agricultural production across vast areas, even in data-scarce regions [80]. Additionally, the SPEI-CHIRPS offers a standardized drought measurement and comprehensive impact assessment by integrating precipitation and evapotranspiration data [31]. These capabilities enhance drought risk management, decision support systems for early warning, yield forecasting, and water resource management and contribute significantly to assessing food security under drought conditions [81]. Figure 7: Heatmap of Pearson correlation coefficients (\(r\)) between SYRS and SPEI at different timescales and months (December, January, April, and June) for each province in MS region (2003–2018).
## 4 Numerical Simulation Analysis and Results  
### Finite Element Model of the Metallic Braided Corrugated Hose  
The material used in the braided corrugated hose is 304 stainless steel in ASTM/AISI. The thickness of the bellows is 0.25 mm, and the total length of the bellows is 200 mm. The thickness of the bellows is much less than the length, and a shell element can be applied when the effect of thickness is not taken into account in numerical simulation. Therefore, the shell element is adopted for the bellows and the 0.25 mm mesh is applied to ensure the quality of the mesh. In order to create face-to-face contact, the solid element is applied to mesh the braided wires and the size is 0.5 mm. The total mesh elements are 288,596 and the nodes are 710,596.  
The mesh element simulates the curved shapes of the braided corrugated hose with good agreement. The contact type between the braided wires and the bellows is frictional with a frictional coefficient of 0.2 and a face-to-face contact detection method. The contact type between the braided wires is bonded to limit the large relative movement between wire and wire in a different strand. In element analysis software, the fixed joint was used at the end of the braided tube and the bellows to ensure the braided tube and the bellows can move simultaneously. One end face has constrained freedom in x, y, and z axes, and the other end face has constrained freedom in x and y axes. In this way, this end face can only move in z-direction. A 5 mm axial displacement is applied on this end face. Thus, the Finite Element Model of the braided corrugated hose can be constrained, as shown in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & **d** & **D** & **T** & **t** & **r1** & **r2** & \(\delta\) & **H** & **L** \\  & /mm & /mm & /mm & /mm & /mm & /mm & /mm & /mm & /mm \\ \hline DN25 & 25.4 & 31.5 & 3.7 & 2.1 & 0.8 & 0.8 & 0.25 & 2.8 & 200 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The dimensions of the DN25 bellows.  
Figure 8: Geometry model of DN25 braided corrugated hose.  
Figure 7: The structure of the DN25 bellows.
# A Semantic Framework for Decision Making in Forest Fire Emergencies
## 4 Ontology Overview
### Representation of Alerts and Recommendations  
After the analysis of data from ONTO-SAFE's sources (sensors, weather forecasts, earth observations, etc.), the creation of alerts and recommendations facilitates decision support during forest fire disaster incidents. Having the proper information at the right time is critical while managing a disaster event. Therefore, the ultimate goal is to increase the efficiency of decision making while decreasing the required time. In this way, the representation of alerts and recommendations in order to assist decision support is essential. Figure 5 depicts the ontology's core constructs for these entities.  
Figure 4: Representation of weather conditions of the prescribed burning process in a specific location.  
Figure 5: Representation of alerts and recommendations.  
Alerts and recommendations could be used to activate communication (via class _Communication_) to all citizens and also to activate missions (via class _Mission_) and assign these missions to first responders. The alert (via class _Alert_) is a quick notice for unusual and potentially dangerous or difficult circumstances and it is a Common Alerting Protocol (CAP)-compliant entity. On the other hand, the recommendation (via class _Recommendation_) is a purposed action suggested as suitable or appropriate, and it is a more text-based entity. Both entities can provide communication to a citizen or a professional and for certain actions or missions they can activate a mission. Moreover, alerts and recommendations can assist in the decision-making process by using the developed services. Citizens can be informed about dangerous situations in their area, and decision makers will be able to identify new incidents where there might be risk and decide the best solution for handling different types of alerts and recommendations.  
Figure 6 depicts how the recommendation can activate communication in order to inform the professionals, if the conditions are appropriate, to conduct prescribed burning plan activities or not.
## 3 Results and Discussion  
### Failure Characteristics  
During the initial stage of loading, the concrete of the wallboard was not cracked, and the specimen was in an elastic stage. As the load increased, tiny cracks began to appear at the bottom surface of the specimens, especially the corresponding positions of the four loading columns. With the continued applied force, the developed cracks start to connect along the loading column and radial cracks perpendicular to the edge of the specimens developed. To about 0.8 \(F_{\mathrm{u}}\) (punching ultimate load), annular surface cracks formed largely on the top surface of the wallboard, but due to the incomplete development of a \"plastic hinge.\" bending failure did not occur at this stage. When the load increased to the specimens' punching ultimate load \(F_{\mathrm{u}}\), with an obvious crackling noise, the specimen could not continue to withstand the load and was damaged by punching. The characteristic point load obtained from the tests are shown in Table 5  
The normal aggregate concrete specimens and recycled coarse concrete specimens had similar punching shear failure modes (based on the experimental observation, a partial bending deformation is considered), but crack development was different in the different samples. In the compressive area of the ordinary concrete specimens, the cracks were more fully developed, indicating that the integrity of the recycled aggregate concrete specimens was relatively low when the specimens were punched and destroyed. The damage forms of RAC specimen (BD4-40-1, BD4-40-2, and BD4-40-3) and ordinary FAC specimen (PD4-40-1, PD4-40-2, and PD4-40-3) are shown in Figures 6 and 7. The deformation of the normal aggregate concrete specimens was more symmetrical when destroyed, so the deformability of the recycled coarse aggregate concrete specimens is relatively low. Moreover, it can be seen that the specimen with smaller spacing has better deformation ability when the concrete material type is the same.  
Figure 5: Loading device and arrangement of measuring points. (**a**) Loading sketch map; (**b**) Loading field.  
\begin{table}
\begin{tabular}{c c c c} \hline
**NO.** & \(F_{\mathrm{e}}\)**/**kN** & \(F_{\mathrm{y}}\)**/**kN** & \(F_{\mathrm{u}}\)**/**kN** \\ \hline BD4-40-1 & 4.4 & 23.9 & 25.2 \\ BD4-40-2 & 3.8 & 18.4 & 20.2 \\ BD4-40-3 & 3.1 & 14.4 & 16.0 \\ PD4-40-1 & 4.7 & 25.8 & 26.3 \\ PD4-40-2 & 4.0 & 20.8 & 23.1 \\ PD4-40-3 & 3.5 & 15.4 & 16.8 \\ BD5-40-1 & 5.4 & 30.1 & 31.7 \\ BD5-40-2 & 4.7 & 25.3 & 27.8 \\ BD5-40-3 & 4.0 & 20.9 & 23.3 \\ PDS-40-1 & 5.7 & 30.2 & 31.8 \\ PDS-40-2 & 5.3 & 27.0 & 29.7 \\ PDS-40-3 & 4.4 & 21.9 & 24.3 \\ \hline \end{tabular}
\end{table}
Table 5: Test results of wallboard.
## 6 Results and Discussions
### Diagnosis of Combined BRB and 2% of ITSC Faults Using ANFIS Based on AR Model  
The _qd_ signals are applied to the Auto-Regressive (AR) model for feature extraction. The number of parameters of the AR model is 5. Therefore, the number of features is 10; 5 features for _lq_ signal and 5 features for _ld_ signal. The length of _lq_ and _ld_ signals is 125,000 samples in each winding condition. The 125,000 samples are divided into 200 sections, with 625 samples for each section which are used to compute AR features in each winding condition. Thus, feature samples are equal to 200 samples for one winding condition. The data set is the summation of all feature samples. It is equal to 1000 samples. The training data set is 500 samples, and the testing data set is 500 samples, as shown in Table 4.  
This data set is applied to the ANFIS model. The training and testing ANFIS outputs are given in Figures 13 and 14. The RMSE is analyzed to assess the models' performance as given in Table 5.  
It is observed that ANFIS based on the AR model gives a lower performance than ANFIS based on DWT. ANFIS based on the AR model has a limitation. The input data to ANFIS are high, which are 10 features. ANFIS takes a long time for training because the number of rules and its tenable parameters increase exponentially when the number of inputs is large. While the input data to ANFIS have 2 features, in the case of ANFIS based on DWT, it achieves high accuracy.