esa-sceva/satcom-chunk-collection huggingface dataset:
# A Nodal Analysis Based Monitoring of an Electric Submersible Pump Operation in Multiphase Flow
## 6 Conclusions and Recommendation  
We used nodal analysis to predict abnormal ESP operation when free gas at the ESP intake suddenly increases. The model was validated using various multiphase surging models (developed using experimental results) and field data (where the gas lock problem was reported). Our conclusions are:  
1. Nodal analysis precisely predicted ESP operating conditions by matching real-time downhole and surface sensor data trends. Nodal analysis can be used for real-time monitoring of ESP wells.
2. Nodal analysis can be used to manage future ESP wells; the normal operating ranges are based on the natural conditions of the well. Such proactive planning prevents uncertainties that might otherwise arise when an ESP is installed.
3. The nodal analysis allows quick diagnosis and interpretation of downhole sensor data, facilitating rapid responses to ESP conditions that might otherwise damage the pump.
4. We add to the current body of ESP well-monitoring knowledge.  
This work is novel in that we introduce (and define) reference, threshold, and normal operating ranges for the several distinct phases of ESP operation: the stable phase (when the operating points decrease in such ranges); the abnormal condition (a point outside of the normal range); and ESP shutdown (before an ESP returns to natural flow status). Existing methods consider only ESP failure.  
Despite the utility of the model, care is needed. The PIP, Pd, and flow rate can be changed due to the various production conditions (for example, a decrease in reservoir pressure, a decrease or increase in the productivity index). The reference threshold normal ranges must then be updated. The model will be particularly useful in oilfields where free gas is the major cause of potential ESP failure. Further studies are needed to determine whether the proposed model can be used not only in the high GOR condition but also to the other ESP failure conditions.  
Methodology and original draft preparation, J.I.; review writing, H.S.; software and review writing, Y.L.; supervision and review writing, J.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by an Energy Efficiency and Resources grant (No. 20192510102510) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), funded by the Korean Government Ministry of Trade, Industry, and Energy (MOTIE).  
Not applicable.  
The data presented in this study are available upon request from the corresponding author.  
The authors declare no conflict of interest.
## 4 Method for Assembling Numerical Schemes
### PDE Linearity  
Another crucial property to assess is its linearity. In this case, we disambiguate strictly linear, semilinear, quasilinear, and fully nonlinear equations, following the definition given in [PERSON] (1986):  
A \(k\)-th order partial differential equation of the form  
\[F(D^{k}u(x),D^{k-1}u(x),...,Du(x),u(x),x)=0\]  
is called  
1. Linear, if it has the form \[\sum_{|\alpha|\leq k}a_{\alpha}(x)D^{\alpha}u=f(x)\] for given functions \(a_{\alpha}(|\alpha|\leq k)\), \(f\). The PDE is homogeneous if \(f\equiv 0\).
2. Semilinear, if it has the form \[\sum_{|\alpha|=k}a_{\alpha}(x)D^{\alpha}u+a_{0}(D^{k-1}u,...,Du,u,x)=0\]  
Figure 4: Classification of PDEs up to second order by qualitative nature and types following [47].  
3. Quasilinear, if it has the form \[\sum_{|\alpha|=k}a_{\alpha}D^{\alpha}u(D^{k-1}u,...,Du,u,x)+a_{0}(D^{k-1}u,..., Du,u,x)=0\]
4. The PDE is fully nonlinear if it depends nonlinearly upon the highest-order derivatives.  
While linearity does not pose much of a problem for elliptic or parabolic equations, it plays an important role in whether a discretization is stable for hyperbolic equations. The theory of nonlinear flux limiters is, in general, well researched for DG methods and largely profits from extensive developments that originally stem from the FVM. However, accurate computation and implementation remain to be a hurdle in practice. There have thus been several approaches to circumvent this issue, for example, by switching to an FV scheme in regions where there might be problems regarding the stability of the solution [50,51].  
As the overarching goal of this method is to provide straightforward guidance for end users, we will omit such approaches that must in most cases be implemented in a custom and rather particular fashion in favor of simplicity.  
We thus recommend that, for equations where the solution is not likely to require many nonlinear iterations per time step, one may safely use a DG scheme. In other cases where stability cannot be assured universally, one should, rather, switch to a finite volume formulation that may be overly diffusive, but on the upside is guaranteed to yield a stable solution.
### Wavelet Transformation
#### 1.1.4 Multi-Resolution Analysis  
Wavelet analysis is a multi-resolution technique in both the time and frequency domains, offering good localization in both. It provides better time resolution for higher frequencies and better frequency resolution for lower frequencies, as shown in Figure 2a. High frequencies require good time resolution, achieved using narrow wavelets, while low frequencies spread over longer time durations, requiring wider wavelets for better frequency resolution [29].
## 3 Damage Analysis
### Analysis of Al Alloy Damage  
Under the Situation 1 incidence condition, the fragment penetrated the bottom skin and a debris cloud hit the rib of the structure. The fragment's main body with small-diameter debris intruded to generate an ellipsoidal rupture hole. The thinner part of the rib is torn and fractured by the impact, as shown in Figure 16.  
For Situation 2's incidence conditions, four sets of velocity gradient variables were set in the range of the actual fragment velocity. The debris cloud composed of small-diameter  
Figure 16: Top skin damage in Situation 1.  
Figure 14: Morphological features of the CFRP damage process. (**a**) Impact crater extrusion, (**b**) Shear intrusion, (**c**) Tensile intrusion, and (**d**) fiber fracture splashing.  
Figure 15: Morphology of damaged area in CFRP.  
carbon fiber particles formed by the fragment penetrating the bottom skin composite side does not have the energy to generate a distributed secondary image on the top skin side of the Al alloy. The top skin side damage is mainly caused by residual fragment penetration. The spherical fragments are separated into two parts by the erosion of composite laminate and the shearing effect of stringer, forming shear holes in the top skin. From the contact between the fragment and the top skin, the annular shear stress formed by the impact is much larger than the panel's ultimate strength, the annular shear zone then gradually accumulates and expands to the back of the panel to generate an annular shear surface. The shear punching is completed to generate a bulge, the radial tensile stress at the back of the back panel bulge then rises, with the depth of the intrusion, the tensile stress accumulates and expands, when the accumulation exceeds the ultimate strength of the panel, and the bulge fractures and breaks rapidly, forming a petal-shaped irregular fracture. The greater the initial velocity of the fragment, the greater the reaction force received in the impact process, and the farther apart the two separated parts will be. As the velocity decreases, the two holes are connected and eventually generate a single hole, as shown in Figure 17.  
Under Situation 3's incidence conditions, the top skin Al alloy exhibits a relatively regular spherical shape in the entire damage area under the high-shearing effect of the fragment's high-velocity impact, and its area is basically the same as the area of the orthogonal projection of the spherical fragments. The reinforced ribs develop a columnar erosion zone under the high-shearing effect of the fragment, and the edges show the typical metal cutting marks under the high-shearing effect and the ablation marks caused by the accumulated heat of impact, as shown in Figure 18.
# Privacy-Preserving Ride-Sharing System with Minimum-Detouring Route
## 4 Proposed Approach
### System Overview  
Given the locations of drivers and riders, the ride-sharing matching is to find the best combination of riders with minimum detouring time. The RS applies the matching between a driver and several riders who accept to share their ride with other passengers. Before the RS applies the ride-sharing matching, the system needs to finish the initialization. With the coarse locations of riders and drivers, the RS first executes a filtering algorithm and obtains several sets of nearby riders, which are divided in terms of the similarity of their trips.  
Then for each set, the RS traverses all feasible rider combinations of \(v\) riders and computes the encrypted \(ATT\) of each rider combination. To compare the ciphertexts without leaking privacy, the RS and the CS execute comparing protocols using [PERSON]'s GC together to compute the results securely. The combination with minimum \(ATT\) will be selected and matched to the driver. Finally, a secure communication channel will be established between the driver and selected riders for pick-up details.  
It is noteworthy that no precise locations are exposed to other entities except the user himself. All sensitive information such as location and time deadline are submitted in ciphertext form.
## 2 SGP System Description
### System Requirements  
The method proposed herein is based on electronic devices with a built-in clock which maintains a relatively accurate account of time and date. Digital clocks are built into most electronic hardware and can run for many years on one single battery with limited drift. It is therefore assumed that at any time the object can enquire the current time \(t\) and date \(d\). It is assumed that the time is set to Universal Time (UTC) which makes the calculations presented herein simple and is represented in decimal form in the range from 0 to 24. Issues such as daylight saving time are thus avoided. Next, the date \(d\) is represented as the day of the year, where 1 January is day 1, _etc_.  
Next, the strategy requires that the device has some form of light sensor that is capable of measuring the lighting condition \(e\). The simplest possible device is a light intensity sensor which gives a voltage directly proportional to the incident light intensity. This type of sensors consume no electrical energy since they actually change the light energy into electrical energy without any power source. Some other devices could be used, for instance a simple and low cost exposure value meter such as those built into most low-cost digital cameras [17; 18; 19] or it could be a low cost camera (CCD-chip). In the cases of exposure values (EV) then \(e\) is a real value between 0 to approximately 20 [20; 21]. If a camera is used a simple representation of exposure can be obtained simply using:  
\[e=\frac{1}{XY}\sum_{x=1}^{X}\sum_{y=1}^{Y}I_{x,y} \tag{1}\]  
where \(I_{x,y}\) is the pixel intensity for the pixel located at \((x,y)\) in the image and \(X\) and \(Y\) are the numbers of image pixels in columns and rows correspondingly. To reduce computation a small subset of these points can be sampled throughout the image using some two dimensional sampling pattern.  
The system proposed in this paper is designed to be as simple as possible. Therefore, apart from the light sensor, a microprocessor is required in order to analyze the data given by the sensor. This element consumes most of the energy in the system.  
A feasible option for implementing the proposed system is to use _mote_ technology [22]. These motes are small, low-cost electronic devices which includes sensor support, small microprocessors, wireless and serial communications. This kind of technology is being used during the last years in sensor networks. Furthermore, some of these motes are designed to be energy-efficient and their energy consumption allows to use these devices with single batteries for a long time.  
Figure 1: SGPS flowchart showing what steps are done by hardware and what by software.  
The SGPS operation is summarized in the flowchart presented in Figure 1. Also, an Arduino-based implementation is suggested in Figure 2. The system can be designed in a more complex way, including other data measuring devices or using a more powerful microprocessor, but the system proposed herein is focused in a simple measuring strategy, with low-cost, energy-efficient components.
## 2 Materials and Methods
### Heating  
The Design of Experiments (DoE) aimed to evaluate different parameter setups in terms of their heating effect of the substrate temperature and its influence on the dependent variables, tensile strength, and modulus. In the full factorial design, the traversing velocity \(v_{TCP}\) and the substrate temperature \(T_{sub}\) without active heating were chosen as the independent variables. The velocities of 0.080 m/s and 0.160 m/s represent two common velocities in our industrial applications, with 0.160 m/s being close to the maximum traversing speed that the KUKA KRC2 robot can reach during manufacturing. The substrate temperature without heating was set to 110 \({}^{\circ}\)C, 130 \({}^{\circ}\)C, and 150 \({}^{\circ}\)C, which are all below the process window for optimized fusion bonding [12]. Here, 110 \({}^{\circ}\)C represents the lowest temperature at which sufficient bond strength for basic geometric stability is achieved.  
A rectangle was chosen as the part geometry, with one side hanging over the manufacturing base to allow constant extrusion during the required holding times, which were implemented to achieve long layer durations at a constant heat chimney. Two infrared emitters of type 1 \(\times\) 150 W, 17 V, 9A by OPTRON GmbH, Garbsen, Germany, were installedin line with the long sides of the rectangle. One heater preceded the deposition nozzle by 100 mm, and one followed it at 100 mm distance with a focus point directly on the substrate surface and constant 100% emitter power. They were spaced with an additional 50 mm in each direction followed the two-infrared pyrometer LT-CF1-CB15 by Micro-Epsilon Messtechnik GmbH & Co. KG, Ortenburg, Germany, as shown in Figure 1. Previous investigations already determined correction factors across the entire 20-300 \({}^{\circ}\)C temperature range for the infrared pyrometers in relation to much more accurate tactile measurements. These correction factors were applied to all infrared temperature data collected throughout this study. The screw speed was set to identical extrusion velocities as traversing velocities, so that the strand is neither pulled nor pushed, creating forced flow.  
The extrusion and heating zone temperatures, as well as the layer height of 1.0 mm, were kept constant at the already optimized levels for a robust process. The build space remained unheated and experienced a \(\pm\)2 \({}^{\circ}\)C variation in ambient temperature during the manufacturing process, which is also the most significant disturbance variable in the industrial FEAM process. Since the substrate is heated once more between the preceding infrared pyrometer and the actual deposition of the next layer, the impact of the last heater was determined numerically in separate experiments based in relation to the temperature recorded by the preceding pyrometer. For each temperature-velocity setup, a corresponding part was manufactured with multiple samples in the longitudinal x-direction cut in the first long side of the rectangle, while multiple samples in the transverse z-direction were cut from the second long side.
# Coordinated Control Strategy of CU-MTDC under Abnormal Conditions Considering Power Supply Security
## 2 Basic System Structure of CU-MTDC
### Control Structure of CU-MTDC
#### 2.2.1 Calculation Layer of the Operation Modes  
When CU-MTDC is in operation, the main responsibility of this layer is twofold:  
1. Operation mode calculation under normal condition. Under this condition, the active power reference value of the CCUP grid converter should be calculated since the reference value is relative to the droop coefficient calculation and affects the control directly. In addition, the reference value should ensure the N-1 security criterion and offshore wind power integration;
2. Operation mode calculation under abnormal condition. Under this condition, the active power output of the CCUP grid converter should be calculated to ensure the power supply security and avoid cascading failures of interconnected critical lines. Moreover, the influence of offshore wind farms is also considered.  
It should be noticed that only CCUP grid converters are considered during the calculation procedure because the active power variation of other converter has little influence on the power flow of the critical AC line of the center CUP grid (less than 1%). In order to simplify the calculation process, it can be neglected.  
Figure 2: The control structure of CU-MTDC.
## 5 Discussion  
The large-scale foundation pit at the Hongshaquan second open-pit mine in Xinjiang served as the basis for the research in this paper. The deformation mechanism of the surrounding surface was thoroughly investigated by building generic numerical simulation models with varying excavation depths, offering a clear foundation for comprehending the deformation process of foundation pit excavation. An elastic analytical approach for the deformation of the surrounding surface under the disturbance of foundation pit excavation was effectively achieved by utilizing elastic theory and the Fourier integral method. This theoretical accomplishment offers fresh ideas and approaches for the study of related topics in addition to providing a strong basis for future investigations into the deformation law of the surrounding surface during foundation pit excavation.  
However, this study also has certain limitations. This research did not directly focus on a situation with lateral support. However, the deformation laws of the surrounding surface and the mechanical reactions of rock and soil masses discovered during foundation pit excavation provide the groundwork for further examination of the impact of lateral support. Follow-up research can incorporate the lateral support structure into the model and systematically simulate the deformation under different support forms and parameters to improve the research on complex excavation projects in urban areas and make the research results more suitable for the requirements of such projects.  
Furthermore, the method based on elastic theory in this study did not take into account the stability issues caused by plastic deformation. Future research can introduce the elastoplastic theory, establish an elastoplastic model, and deeply analyze the development process of the plastic zone around the foundation pit excavation and its influence mechanism on slope stability, thus making up for the shortcomings of the elastic solution and providing more accurate theoretical support and technical guarantees for engineering practice.
## 2 Preamble
### Finite Element Model of the Brake System under Study
The reduced matrices for each contribution of the FEM brake system are given by  
\[\mathbf{M}=\mathbf{T}_{l}^{\dagger}\mathbf{M}_{CB}\mathbf{T}_{r}=\mathbf{T}_{ l}^{\dagger}\mathbf{T}^{\dagger}\mathbf{M}_{init}\mathbf{T}\mathbf{T}_{r} \tag{3}\]  
\[\mathbf{K}=\mathbf{T}_{l}^{\dagger}\mathbf{K}_{CB}\mathbf{T}_{r}=\mathbf{T}_{ l}^{\dagger}\mathbf{T}^{\dagger}\mathbf{K}_{init}\mathbf{T}\mathbf{T}_{r} \tag{4}\]  
\[\mathbf{C}=\mathbf{T}_{l}^{\dagger}\mathbf{C}_{CB}\mathbf{T}_{r}=\mathbf{T}_{ l}^{\dagger}\mathbf{T}^{\dagger}\mathbf{C}_{init}\mathbf{T}\mathbf{T}_{r} \tag{5}\]  
\[\mathbf{F}_{NL}=\mathbf{T}_{l}^{\dagger}\mathbf{F}_{NL,CB}=\mathbf{T}_{l}^{ \dagger}\mathbf{T}^{\dagger}\mathbf{F}_{NL,init} \tag{6}\]  
\[\mathbf{F}_{ext}=\mathbf{T}_{l}^{\dagger}\mathbf{F}_{ext,CB}=\mathbf{T}_{l}^{ \dagger}\mathbf{T}^{\dagger}\mathbf{F}_{ext,init} \tag{7}\]  
where the subscript \({}_{init}\) refers to the initial data of the problem without condensation. \(\mathbf{A}^{t}\) denotes the transpose of a matrix \(\mathbf{A}\). \(\mathbf{T}\) defines the transfer matrix between the initial reference model and the C&B condensed model. \(\mathbf{T}_{l}\) and \(\mathbf{T}_{r}\) correspond to the left and right eigenmodes of the interface degrees of freedom. They are associated with the transition from the C&B condensed model to the final reduced model that includes both C&B and DMS reductions. In the following section, the convergence study versus the two reduction techniques will be discussed as follows:* The C&B technique is performed by condensing the internal degrees of freedom of each substructure (i.e., the disc and the two pads) and by keeping the physical degrees of freedom situated at the two frictional interfaces. The number of fixed interface modes is chosen so that the reduced model is valid for a given frequency range of interest (i.e., \([0;f_{max}]\) with \(f_{max}=20\) kHz in the present case). To reach such an objective, the convergence study is performed on the control parameter \(\gamma\), selected for each substructure: the fixed interface modes whose frequencies are less than \(\gamma f_{max}\) are kept;
* The DMS technique consists in the condensation of all the degrees of freedom at the two frictional interfaces. The control parameter for the DMS reduction is set by the number of interface modes kept (denoted \(N_{DMS}\)).
# Preventing Black Hole Attacks in AODV Using RREQ Packets
## 4 Preliminary Experiment  
### Summary  
We experimentally reproduced the proposed method on the ns-3 network simulator; the results verified its validity. We conducted this experiment to verify whether black hole attacks can be reproduced by ns-3, which is a validation of the simulator rather than an experiment to gain new knowledge. Therefore, we prepared an environment in which communication is definitely not possible if there is a black hole node and another in which communication is definitely possible if there is not a black hole node. The simulation time was 10 s, and the source node sent a ping message to the destination node every second. Black hole nodes ware configured to reply to all received RREQ packets with forged RREP packets and to not relay RREQ packets. The arrival rate of packets to the destination node and routing table of each node were verified at the end of the simulation to determine whether the destination node could send data while avoiding black hole nodes.  
Figure 3: Handling of RREP packets.