esa-sceva/satcom-chunk-collection huggingface dataset:
# Power Quality Issues and Mitigation for Electric Grids with Wind Power Penetration
## 3 PQ Mitigation Techniques
### Traditional Methods
#### Active Power Filters (APFs)  
APFs use power electronics to mitigate the harmonic current components produced by the non-linear loads. APFs have more advantages than the passive filters as they help suppress the supply current harmonics and the reactive currents. There are two types of APFs: shunt and series APFs.  
Shunt APF: Shunt APF consists of controllable voltage or current source. Voltage source inverter-based shunt APF is more commonly used as it simple and easier to install. The configuration of a VSI-based shunt APF consists of a DC-bus capacitor, power electronic switches, and an inductor. It operates by injecting a compensation current equal to the distorted current in the circuit leading to harmonic free source current.  
Series APFs: Series APFs are connected to the distribution line through a matching transformer. The configuration of a series APF is similar to a shunt APF with a VSI used as the controlled source. It isolates the harmonics from the non-linear load and the source by feeding harmonic voltages across the interfacing transformer. A pure sinusoidal voltage waveform is maintained across the non-linear load by varying the injection of harmonic voltage. Series APFs must handle large load current which increases their current rating considerably as compared to the shunt APF, especially in the secondary side of the transformer interfacing it. This increases \(I^{2}\)R losses. One of the benefits of the series APFs over shunt is that they are ideal for voltage harmonics elimination. APF makes use of fast switching transistors resulting in switching frequency noise appearing in the compensated current which in turn adversely affects sensitive equipment. To mitigate this problem, hybrid APFs are designed to reduce switching noise and EMI.  
Hybrid APF: Hybrid APF is a combination of the basic APFs and passive filters. The conventional APF filters out the low order harmonics and the HPF filters out the higher-order harmonics. The two most commonly used configurations of the hybrid APF are the shunt APF with a shunt passive filter and a series APF with a shunt passive filter [15]. Hybrid APF acts as a harmonic isolator to improve the filtering capabilities of harmonic content while being cost-effective. In a hybrid shunt APF, the APF and the passive filter are connected in parallel with the nonlinear load. In a hybrid series APF, the APF is coupled in series with the distribution line via the interfacing transformer. In addition to the series APF, one or more single LC tuned filters are present. The series APF offers very high impedance for all higher-order frequencies other than the fundamental and the shunt passive filter filters out all the lower order harmonics.
## 2 System Model
### Signal Model  
The forward link of the LDACS system is modulated by OFDM. Assuming the subcarrier modulation scheme is QPSK, the baseband OFDM signal can be expressed as follows  
\[r(t)=\sum_{l=-N/2}^{N/2}r_{l}(t)=\sum_{n}\sum_{l=-N/2}^{N/2}c_{l,n}q(t-nT_{0}-t _{0})e^{j2\pi l\Delta f(t-nT_{0}-t_{0})}, \tag{1}\]  
where \(N\) represents the number of subcarriers, \(T_{0}\) denotes the length of the OFDM symbol as well as the pulse width, and \(T_{0}=T_{s}+T_{g}\). Here, \(T_{s}\) is the useful symbol length of the OFDM signal, and \(T_{g}\) is the length of the cyclic prefix. Additionally, \(\Delta f=1/T_{0}\) is  
Figure 1: Block diagram of OFDM receiver for LDACS system.  
the subcarrier frequency interval, \(q(t)\) is the shaping pulse, and \(t_{0}\) is the initial time. \(c_{l,n}\) represents the \(n\)th modulation symbol on the \(l\)th subcarrier, assumed to be a zero-mean independently and identically distributed source with a variance of \(\sigma_{c}^{2}\).  
The modulated OFDM signal is then represented as  
\[\begin{array}{ll}x_{0}(t)&=\text{Re}\Big{\{}r(t)\cdot e^{i2\pi f_{c}t}\Big{\}} \\ &=\frac{1}{2}[r^{*}(t)e^{-i2\pi f_{c}t}+r(t)e^{i2\pi f_{c}t}].\end{array} \tag{2}\]
# Design and Construction of a Low-Cost Test Bench for Testing Agricultural Spray Nozzles
## 2 Materials and Methods
### Hydraulic Component Design  
According to the aims of the research, the design of the hydraulic circuit was carried out in a way that is very similar to the standard spraying system installed on commercial sprayers. For this reason, a 70-liter plastic tank and a diaphragm pump (AR 30, Annovi Reverberi, Reggio Emilia, Italy, able to ensure pressure values up to at least 3 MPa) were chosen. The pump is driven by a single phase 230 V AC, 2.2 kW induction motor with a gearbox. As the pump capacity is much higher than the flow rate of the nozzle under test, the surplus was recirculated to the main tank by means of a pressure regulator as it is in the sprayers to ensure continuous mixing of the liquid.  
In addition, to take into account the different working pressure ranges of the nozzles under test, the circuit was designed with two pressure lines (Figure 1): a low (up to 0.6 MPa) and a high pressure line (up to 3 MPa). According to the needs, the required working pressure was established by manually selecting the proper line by acting on the appropriate ball valves and then by acting on the corresponding pressure regulator.  
Due to the effect of the spray pressure and nozzle flow rate on the drop pulverization, the design of the hydraulic circuit also provided the sensors to measure in real time both quantities. Fluid pressure at the nozzle was measured by means of a piezoresistive pressure transmitter (Series 22 S model from Keller Italy SrI, Milano, Italy) and flow rate by means of a turbine flow sensor (SF800-6 model from  
Figure 1: Scheme of the hydraulic circuit (blue: low pressure line; red: high pressure line; S: electro valve; FS: flux sensor; PT: pressure transmitter).  
Swissflow BV-Fazantlaan 4 6026 SN Maarheeze, The Netherlands). The pressure transmitter (3.0 MPa full-scale) has a standard 4-20 mA analog output, while the flow sensor has a digital pulse output with a nominal coefficient of 6000 pulse/L, a flow rate limit between 0.5 and 20 L/min, and a maximum operating pressure of 25 MPa.
## 2 Literature Review
### IoT Sensors for Fine Dust Management at Construction Sites  
As measuring fine dust and preparing reports are performed by humans, data falsification and manipulation are possible. In addition, the time consumption and human resources required to visit construction sites for fine dust measurements and writing and submitting a report are considerable. Therefore, many studies using the IoT to minimize human intervention, remotely measure the concentration of fine dust at construction sites in real time, and establish advanced monitoring systems have been conducted.  
[PERSON] et al. suggested real-time air dust monitoring that can be deployed ubiquitously at a construction site and integrated as part of a daily construction management system [19].  
[PERSON] et al. developed a wireless pervasive and real-time dust concentration monitoring system to maintain admissible concentration values defined by national legislation in place [20].  
[PERSON] et al. employed two low-cost dust sensors (Sharp GP2Y1014 AU0F and Alpha sense OPC-N2) without implementing control measures to explicitly evaluate, compare, and gauge them for construction activities. Latin hypercube sampling was used to analyze the measurement results and predict the exposure concentrations [21].  
Real-time monitoring of fine dust at construction sites using IoT has been studied from various perspectives. Many studies focus on the accuracy of the fine dust measurement of IoT sensors for construction sites. However, few studies exist on the accessibility and reliability of information collected through these fine dust-monitoring systems.
# Adaptive QoS-Aware Multi-Metrics Gateway Selection Scheme for Heterogenous Vehicular Network +
## 3 Adaptive QoS-Aware Multi-Metrics Gateway Selection Scheme
### Gateway Discovery Process
#### 3.3.2 Gateway Available Capacity ( AVC\({}_{\text{NV}}\))  
In the gateway selection process, the selected MGW can serve several vehicles more than its actual capability. This may result in an overloading problem on the selected MGW. If this condition occurs, the traffic transmitted to the LTE-eNB via the MGW will experience higher delay, and packets will be dropped due to the congestion. Figure 3 shows the overloading scenario of the MGW. The MGW G2 is connected to many vehicles, S, compared with the G1 and G3 gateways. This might happen if the MGW is the perfect gateway for many vehicles in its coverage area. If this happens, the G2 will be overloaded, and this can affect the overall network performance. To overcome this problem, the IV also needs to check the \(AVC_{NV}\) of each potential MGW candidate (i.e., NV) and include this as one of the metrics involved in the gateway selection process.  
During the gateway discovery process, when the NV receives the GWreq message, it computes its \(AVC_{NV}\), and inserts it in the GWrep message before its relay to the IV.  
Figure 3: An overloaded gateway vehicle condition.  
The available capacity \(AVC_{NV}\) of the v (in megabits per second) is computed using Equation (5) [46].  
\[AVC_{NV}=C_{vmax}-\lambda_{v}-c_{v} \tag{5}\]  
where \(C_{vmax}\) is the maximum traffic that can be served by NV, \(\lambda_{v}\) is the current traffic served by the NV (computed using Equation (6)), and \(c_{v}\) is the constant value that prevents the gateway from being congested.  
\[\lambda_{v}=\sum_{v=1}^{n}Pr_{v}Ps_{v} \tag{6}\]  
where \(Pr_{v}\) and \(Ps_{v}\) denote the average packet arrival rate and the average packet size of the traffic from vehicle v to the NV, respectively.
# Coded-GFDM for Reliable Communication in Underwater Acoustic Channels
## 5 Discussion  
It is evident that using BCH encoding, improves the error performance of GFDM manifolds with BCH (31,6) giving the best performance. Moreover, the performance with a zero-forcing equalizer is marginally better than the matched filter receiver. This is because a zero-forcing scheme assumes perfect channel estimates and hence can compensate for channel impairments better than the matched filter. It is also noted that even at 2.5 km, the BCH (31,6) code gives an acceptable performance at a relatively high Signal to Noise  
Figure 5: Convolutionally encoded 4 QAM-GFDM schemes. (**a**) Comparison of selected convolutional codes with MF equalizer. (**b**) Comparison of selected convolutional codes with ZF equalizer. (**c**) Error performance as a function of Tx-Rx distance for rate 1/4, constraint length 5 scheme with MF equalizer. (**d**) Error performance as a function of Tx-Rx distance for rate 1/4, constraint length 5 scheme with ZF equalizer.  
Ratio (SNR). The performance of both matched filter and zero-forcing is quite similar and it is hard to distinguish the two plots. When using RS encoding, the error performance of GFDM improves manifolds with RS (15,3) giving the best performance. However, the difference between the error performances of the three RS schemes is relatively less than what was observed in the case of BCH encoding. Moreover, the performance with the zero-forcing equalizer is quite similar to that of the matched filter receiver and it is difficult to distinguish the two plots. Moreover, it is also observed that the use of convolutional encoding improves the error performance of GFDM but not as much as shown in the case of BCH and RS encoding. Furthermore, for both equalizers, it is hard to distinguish the performances of the three codes of rate 1/4 as they are quite similar. It is observed that at 2.5 km, high SNR is required to achieve acceptable error performance.
## 5 Conclusions  
In this paper, n-heptane, n-dodecane, tetralin and decalin are blended with diesel in the volume ratios of 20% and 50% to study the effects of hydrocarbon components on China VI diesel engine power, fuel economy, combustion and emission characteristics. The main conclusions are summarized as follows.  
1. The blending of hydrocarbons into diesel linearly changes the fuel's density, viscosity, LHV and CN in the range of blending rates, but there is a significant change in distillation temperatures which changes the engine combustion and emission characteristics deeply;
2. Due to the lower boiling temperature, the addition of heptane will improve spray atomization and thus enhance the combustion process. The hydrocarbons of heptane and dodecane with higher CN can reduce fuel consumption. The addition of decalin will promote engine power because of its higher energy. Polyaromatic hydrocarbons like tetralin have a weak effect on power but worsen fuel economy to some extent;
3. For the China VI heavy-duty diesel test engine with two-stage injection, the addition of hydrocarbons has confused effects on the combustion of pre-injected fuel but limited effects on the main injection and combustion. The differences in in-cylinder pressure and HRR of the different fuels are less than 2% under the same conditions, which indicates that the fuel hydrocarbons are not so sensitive to the main combustion phase;
4. The addition of heptane and tetralin will increase the emissions of HC, CO and NOx, because of the higher volatility of heptane and the molecular specialty of tetralin.  
Conceptualization, Y.-J.W. and S.-H.L.; methodology, Y.-J.W.; software, X.-D.Z.; Z.-Q.Z., Y.-J.Z., X.-Y.S. and X.-L.J.; formal analysis, X.-D.Z.; investigation, Y.-J.W.; resources, Y.-J.W.; data curation, X.-D.Z.; writing--original draft preparation, Y.-J.W.; writing--review and editing, Y.-J.Z.; visualization, X.-D.Z.; supervision, H.-M.G.; project administration, S.-H.L.; funding acquisition, Y.-J.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by [the National Natural Science Foundation of China] grant number [52176128] and [the Shaanxi Provincial Key R&D Program] grant number [2019 ZDLGY15-10].  
The work in Xi'an Jiaotong University was supported by the National Natural Science Foundation of China (Grant Nos. 52176128) and the Shaanxi Provincial Key R&D Program (Grant No. 2019 ZDLGY15-10).  
The authors declare no conflict of interest.
## 2 Materials and Methods  
### Mathematical Formulation  
Taking into account small deformations and negligibly small dissipative heat release, it is possible to separate the boundary value problem of unsteady thermal conductivity and the boundary value problem of thermomechanics on the stress-strain state (SSS), which are unrelated in this formulation. The technology of \"killing\" and subsequent \"aliving\" (Elements Birth and Death technology in ANSYS) of a part of the material that was initially absent in the model and appearing during the deposition process is used to solve them. At the same time, the domain occupied by the finished product is considered as the computational one. The continuous deposition of the material is carried out discretely; at each calculation sub-stage corresponding to the \"aliving\" of the next subdomain of the \"killed\" elements, the boundary value problem of thermal conductivity and thermomechanics is solved, and the result of solving the previous sub-stage serves as the initial conditions for the next one (see Sections 2.3.1 and 2.3.2 for a detailed illustration of the simulation of the material deposition process). Modeled geometry is presented in Figure 1.  
At the _k-th_ sub-stage of the solution, the formulation of the boundary value problem of unsteady thermal conductivity for determining temperature fields \(T(\mathbf{x},t)\) in a domain \(V_{k}\) with a boundary \(S_{1,k}\cup\ S_{2}\), taking into account the accepted hypotheses, includes [29]:  
_heat conductivity equation:_  
\[\rho(\mathbf{x})c(\mathbf{x},T)\frac{\partial T}{\partial t}=\text{div}( \lambda(\mathbf{x},T)grad(T))+\rho(\mathbf{x})\dot{q}(\mathbf{x},t),\ \mathbf{x}\in V_{k}, \tag{1}\]  
where \(c(\mathbf{x},T)\), \(\lambda(\mathbf{x},T)\), and \(\rho(\mathbf{x})\) are the heat capacity, heat conductivity, and density of the material, respectively. \(\dot{q}(\mathbf{x},t)\) is the specific power of an external heat source, which means the energy that is taken by the extruder heater for heating PEEK up to 430 \({}^{\circ}\)C;  
_boundary conditions:_  
\[-\lambda(\mathbf{x},T)\text{grad}(T)\cdot\mathbf{n}=h(T)\cdot(T-T_{c}(t)), \mathbf{x}\in S_{1,k}, \tag{2}\]  
\[T(\mathbf{x},t)=T_{o}(\mathbf{x}),\ \mathbf{x}\in S_{2}, \tag{3}\]  
where the first equation describes convective heat transfer, and the second one describes platform heating; \(h(T)\) is the heat transfer coefficient, \(T_{c}(t)\) is the ambient temperature, \(\mathbf{n}\) is the normal vector to the boundary \(S_{1,k}\) of objects, and \(T_{o}(\mathbf{x})\) is the platform heating temperature;  
_initial conditions:_  
\[T(\mathbf{x},t_{0,k})=T_{k-1}(\mathbf{x}),\ \mathbf{x}\in V_{k}, \tag{4}\]  
where \(T(\mathbf{x},t_{0,k})\) is the initial temperature distribution for the _k-th_ sub-stage and \(T_{k-1}(\mathbf{x})\) is the temperature determined at the end of the previous one. These relations take into account the condition that the research domain \(V_{k}=V_{k}^{live}\cup\ V_{k}^{Kli}\) remains unchanged throughout the sub-stage. Here, \(V_{k}^{live}\) and \(V_{k}^{Kli}\) indicate zones occupied by \"alive\" and \"killed\" elements, respectively.
## 1 Introduction
Formulated as an optimization issue under the constraints of transmitting power, maximization of system throughput is studied in [25] to provide a cooperative power allocation method. In [26], the energy harvesting relays are considered and then proposed an algorithm for user association, resource allocation, and power control in the heterogeneous multi-tier network. Also, the resource allocation with more realistic bursty traffic is optimized by a centralized resource allocation method with delay-aware and a power control framework that is based on queuing model [27]. Considering the abovementioned literature, a problem is that the fairness for wireless nodes or users has not been taken into consideration. The links with poor states may lose the ability of communication in the competition with good-state links, such a phenomenon known as'starvation' in communication systems. In this paper, we propose a low complexity and effective spectrum resource allocation mechanism for D2D communication based on the interference-aware method. In the uplink stage, the interference can be sensed by associated D2D receivers, as they are different due to diverse channel gains and transmit power. Therefore, D2D pairs with good uplink states may have priority to share RBs with CUs, which is unfair for poor D2D link. In regard to this problem, we weight the D2D pairs and promote the efficiency of resource allocation. The contributions of this paper are shown as follows:  
* The proposed resource allocation mechanism based on weighted efficiency interference-aware (WE-I-A) can guarantee the Quality-of-Service (QoS) of D2D pairs and CUs. On the premise of distributed power control method, we manage the interference and cluster the D2D pairs in a novel way that each D2D pair can be an intended user of different clusters in terms of the constraint of SINR. As defined in the proposed scheme, each D2D pair should be in the different clusters and each cluster can only remain one D2D pair after resource allocation,
* Due to'starvation' of poor-state D2D link, we attempt to overcome the problem by weighting D2D pairs in the clusters with received SINR for fairness. By this way, each D2D pair competes to be the actual user of the cluster by weight value rather than that D2D pairs with good link states have priority to reuse RBs. The active D2D pairs can be increased while promoting the effectiveness of RBs. As a consequence, the overall performance of system throughput is highly enhanced. The rest of this paper is organized as follows. The system model of the D2D underlaid cellular network, and the expression of the system throughput are presented in Section 2, and the resource allocation mechanism based on weighted efficiency interference-aware is proposed in Section 3. In Section 4, simulation results and relevant analysis of the SINR, throughput, and utility of allocation are depicted and discussed, and finally, concluding remarks, and future directions are presented in Section 5.
## 6 Future Perspectives for the Methodology  
Nevertheless, there remain several avenues for enhancement, as follows:  
* Currently, it addresses optimization problems involving continuous variables; an extension to accommodate discrete variables is necessary;
* The paper presents a sizing approach for power electronics applications. It would be advantageous to extend this methodology to address optimization problems that encompass both sizing and optimal control, such as energy management in regard to microgrids. The integration of optimal control could be incorporated into the dynamic simulations of the proposed methodology;
* Surrogate-based algorithms yield greater precision when gradients are incorporated, thus the methodology should be employed alongside such algorithms to facilitate the sizing of larger systems characterized by state spaces with more dimensions;
* Optimization problems involving a larger number of constraints, and of greater complexity, could, in theory, be addressed using this methodology. However, the limitations regarding the computation of the Jacobian matrix (in relation to the inputs) must be clearly defined;
* The availability of gradients enables the efficient computation of global sensitivity analysis for a model using the DGSM algorithm [51];
* It would be valuable to establish a connection between this methodology and other design environments. Indeed, modeling power electronics applications remains partially manual in nature, as the designer is required to encode the model within Python script. In some instances, this process can be tedious, whereas other environments, such as Matlab/Simulink, provide a more intuitive block-based approach, facilitating ease of use for the designer (especially when incorporating FMU component standards). These aspects could potentially serve as an advanced layer of modeling for NoLOAD. However, it is worth noting that models encapsulated within FMU components become non-differentiable 'black boxes', necessitating the evolution of these standards;
* Hybridized optimization approaches, which merge gradient-based and global methods, such as SQP with differential evolution, could have been employed to address our optimization problem, thereby obviating the need for the'multi-start' procedure.  
Conceptualization, L.G. and B.D.; Methodology, L.A., L.G. and B.D.; Software, L.A., L.G. and B.D.; Investigation, L.A.; Writing--original draft, L.A.; Writing--review & editing, L.G. and B.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The code will be made available through a simple request to the authors.  
The authors declare that there are no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AD & Automatic differentiation \\ FFT & Fast Fourier Transform \\ JIT & Just-In-Time \\ RK & Runge-Kutta \\ SQP & Sequential Quadratic Programming \\ \end{tabular}