esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Such synergies underscore the ambition to harness advanced analytics for holistic energy system planning in pursuit of Europe's climate targets, which include installing over 600 GW of renewable capacity by 2030 and reaching climate neutrality by 2050 [15]. Despite this momentum, significant challenges remain on the path to a fully functional digital twin of the European electricity grid. Regulatory fragmentation and data governance rules must be harmonized to facilitate cross-border data sharing [4]. Technologically, achieving real-time observability and interoperability across millions of distributed assets requires standardized interfaces, robust cybersecurity measures, and scalable computing infrastructures [5]. Economically, stakeholders need clear incentives and funding mechanisms to invest in digital twin solutions that promise long-term system benefits but require substantial upfront outlays [16]. While several reviews have discussed various technical aspects of digital twins in the context of smart grids or energy systems [12; 17; 18; 19; 20; 21; 22], this review provides a novel contribution by focusing specifically on the European electricity grid through the lens of regulatory, technological, and economic barriers. It synthesizes not only academic and technical literature but also integrates EU policy frameworks, legislative instruments, and flagship projects such as TwinEU. Unlike previous work that treats digital twin development as a predominantly technical endeavor, this review offers a structured, transdisciplinary synthesis that connects regulatory misalignments, infrastructure readiness, and investment rationales, providing a policy-relevant roadmap for realizing a federated EU-wide grid digital twin. This article provides a comprehensive review of these challenges and opportunities, drawing upon policy documents, academic research, and recent industry projects such as TwinEU. The discussion focuses on the EU-27 context and assesses how to align regulations, technology, and economics to realize the vision of a continent-wide digital twin. Section 2 presents the methodology and details the scoping review framework, search strategy, inclusion criteria, and data extraction process, following PRISMA-ScR guidelines. Section 3 examines the regulatory and policy barriers, which include issues such as data-sharing frameworks and standards harmonization. Section 4 explores the technological state of the art and the remaining gaps, including modeling complexities, interoperability challenges, and cybersecurity. Section 5 discusses the economic rationale for digital twin investments and reviews cost-benefit analyses, market innovations, and potential funding strategies. Section 6 concludes with an outlook on how Europe's ambitious digital twin initiatives will contribute to a more resilient, efficient, and decarbonized electricity system.
# Valorization of Waste Tires by Pyrolysis and Activation Processes
## 4 Conclusions  
In the present study, the effect of the chemical and physical activations on the characteristics of derived pyrolytic products was analyzed. As the solid fraction utilization can be responsible for the profitability of the pyrolysis process, a higher solid yield is desired, which was observed in the presence of chemical activation prior to pyrolysis. The properties of the solid fraction varied with the type of activation; while CO\({}_{2}\) activation increased surface area, chemical activation decreased pore size. We observed a correlation between small pore size and high conductivity values. In this manner, the solid fraction from acid-treated tires presented the best electrical conductivity, higher than that of biomass-based electrode materials. Liquid fraction was highly influenced by the chemical activation; liquids derived from nonactivated waste tires presented limonene as the main compound, while liquids from acid-treated presented a higher percentage of aromatic compounds, suggesting that, during chemical activation, a significant percentage of volatiles that generate the liquid fraction was eliminated and aromatization reactions were favored because of the high pyrolysis temperature. The chemical activation also resulted in a greater concentration of gases, such as H\({}_{2}\) and CH\({}_{4}\), leading to a higher heating value. The enhanced properties of the pyrolytic products derived from acid-treated waste tires demonstrate the possibility of recovering valuable products, including a solid product for energy storage applications.  
Figure 10: Gas fraction composition on a nitrogen-free basis of pyrolysis of waste tire powder without chemical activation (average of G1 and G3) and pyrolysis of chemically activated waste tire powder (average of G2 and G4). Note: Gas produced during physical activation was not considered.  
**Author Contributions:** Methodology, R.B.G.-G. and A.M.; investigation, R.B.G.-G., N.R.-G. and M.V.-P.; writing--original draft preparation, R.B.G.-G.; writing--review, A.M., G.G., S.O.M.-C. and P.C.; supervision, A.M.; funding acquisition, A.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Tecnologico de Monterrey and the Energy and Climate Change Research Group (Internal Grant 0020209115).  
Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available because the study was funded with institutional resources.  
R.B.G.-G. acknowledges the support received by Mexico's National Council for Science and Technology (CONACYT) through its scholarship program.  
The authors declare no conflict of interest.
# Improved Durability of Wood Strand-Based Panels Using Guayule
## 2 Materials and Methodology
### Treatment Process
#### 2.3.2 Brushing/Spraying  
Figure 2 shows uniform brushing (the image on the left), using a 2.54 cm wide paint brush, and uniform spraying (the image on the right), using a gravity feed air spray gun with guayule-acetone solution to treat WSB panels. Brushing or spraying guayule-acetone solution on control specimens is referred to as brushing or spraying treatment, respectively. Termite and fungus test specimens had an average length and width of 2.54 cm (an average standard deviation (S.D.) of 0.01 cm) and average thickness of 1.27 cm (an average standard deviation (S.D.) of 0.04 cm), which was the target thickness of the fabricated panels, and were sprayed or brushed only one time on all six sides with an even uniform coating of guayule-acetone solution to better emulate industrial practices and procedures. One uniform coating, with an average application of 1.36 g of guayule solution, was used to brush each termite and fungus specimen on all six sides. Likewise, one uniform coating, with an average application of 3.76 g of guayule solution, was used to treat fungus and termite specimens on all six sides using the spraying technique. Overall, the spraying methodology was a faster procedure, but it used approximately 2.76 times more guayule solution compared to the brushing technique. After the specimens were brushed or sprayed, they were left under a fume hood to off-gas the acetone and then were conditioned for at least 14 days before conducting termite and fungus tests according to American Wood Protection Association (AWPA) E1-23 and AWPA E10-22 protocol standards [31; 32].  
Figure 2: Brushing (left image), using a 2.54 cm wide paint brush, versus spraying (right image), using a gravity feed air spray gun, techniques with a uniform guayule–acetone solution to treat wood strand-based (WSB) panel specimens prior to testing.
## 3 The Proposed Method and Simulation Verification
### Modal Training and Results  
The response data with different SNRs are trained to test the proposed method's anti-noise ability. The response data without SNR accounts for 40%, and others are 20%, respectively. The proposed method first trains the dataset and then tests the first beam. As shown in Figure 5a, 11 beams with different SNRs are trained. When iterating to step 5, four loss function curves are close to the optimal and reach the optimal in step 10, and these loss function curves are smooth, indicating that the model training effect is good. Then,  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer** & **Parameters** & **Activation Function** \\ \hline \multirow{3}{*}{Conv1 (C1)} & kernel size = 64; stride = 1; \\  & padding = 2; input channels = 1; \\  & output channels = 16 & \\ \hline Max pooling1 (P1) & data kernel size = 2; stride = 2 & - \\ \hline GRU (G2) & hidden size = 256; layers = 2 & tanh \\ \hline \multirow{2}{*}{Fully connected layer3 (FC3)} & Inputdim = Size(\(Y_{G}\)); \\  & Outputdim = Size (Output) & PReLU \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the hybrid neural network.
## 3 Lamb Wave Measurement Using 3D Laser Vibrometry  
One of the earliest set of studies to use scanning laser vibrometry to sense Lamb waves and their interaction with damage was presented in [30; 31; 32]. In these studies, 1D scanning laser vibrometry was used to measure the out-of-plane velocities of A\({}_{0}\) Lamb wave propagation through aluminium plates with various defects. The Vibrometry data recorded was validated using the responses of piezoelectric transducers bonded to the surface. Numerical simulations were also found using the local interaction simulation analysis (LISA). This set of studies demonstrated the potential of using scanning laser vibrometry for investigating Lamb wave propagation and interaction with damage.  
Out-of-plane scanning laser Doppler vibrometry has been previously used to successfully detect damage in a stiffened panel [33]. Experimental work was carried out to detect the voids left by the absence of rivets used to attach a t-shaped aluminium stiffener to a flat aluminium plate. The plate was excited by a lead zirconate titanate (PZT) transducer with a 5-cycle sine wave multiplied by a Hann-window at frequencies of 5 kHz, 35 kHz, 100 kHz and random noise. By calculating the route mean square of the signal received at each measurement point it was possible to generate a visualisation that clearly showed the absence of the rivets. The best visualisations were found to be obtained from results taken at higher frequencies.  
Out of plane measurements were taken by [PERSON] _et al._[34] using a 1D scanning laser vibrometer to measure Lamb wave interaction with delaminations in a composite plate after impact as well as Lamb wave interaction with a disbond of a composite spar. In this work, frequency-wavenumber domain and Laplacian image filters were placed over the wave field images to enhance imaging of the defect. This successfully located the presence of the damage and highlighted the potential for image-based techniques for use in SHM applications.  
3D scanning laser vibrometry has served as a successful method for validating results from finite element analysis models by [PERSON] _et al._[35]. This study demonstrated the capability of 3D scanning laser vibrometry to measure accurately in-plane and out-of-plane Lamb modes in thin plates for SHM applications. The advantages of using 3D scanning laser vibrometer over a 1D system were demonstrated by using the data of the in-plane modes to qualitatively and quantitatively more accurately validate finite element models.
# LDS Realization of High-Q SIW Millimeter Wave Filters with Cyclo-Olefin Polymers
###### Abstract  
In this paper, we present narrow-band substrate integrated waveguide (SIW) millimeter wave band-pass filters, designed using cyclo-olefin polymers (COP). The structures were molded, drilled, and metalized with a laser direct structuring (LDS) process. COP are a type of thermoplastic with low dielectric losses in the millimeter waveband, typically 7.5 \(\times\) 10\({}^{-4}\) at 40 GHz for the COP RS420-LDS from Zeon(r). The body of the filter was realized using a molding process that facilitates the combination of thin 50 \(\Omega\) microstrip access lines with high thickness microwave cavities through 3D transitions, thus making high quality factors attainable. The simulations and experimental results are presented and discussed.  
Keywords:substrate integrated waveguide (SIW) filter; cyclo-olefin polymers (COP); LDS metallization; molding process +
Footnote †: journal: Applied Sciences
## 3 Results
Figure 5: Water cost (excl. geothermal). For small seawater RO desalination systems, it does not make any sense not to use energy recovery. * The most cost-effective solution overall is the combination of a grid-connected system with a net-metering PV plant. The current cost of electricity is USD 0.17/kWh in Greece, but it is expected to increase in the future, so this combination will only become more attractive. * Autonomous systems can be of comparable cost to systems consuming grid electricity, as shown in Figure 5.
* Hybrid systems (PV and wind) are the most cost-effective solutions for autonomous systems. * Even considering double sized desalination plants as is the case for the 100 m\({}^{3}\)/day system, it makes sense to utilize the intermittent (ON/OFF) operation rather than getting a unit that runs constantly for autonomous systems. This is due to the fact that the energy storage in an autonomous system costs overall much more to ensure a continuous operation throughout the year than getting a larger plant and operating it for less hours. As the systems become larger, increased size desalination plants are still more economically favorable for autonomous systems. * Water tanks make sense, but up to a specific capacity for any given configuration. This is clearly observed in case studies 19 and 22 where the extra water tank is in reality not needed for the given configurations and as such the system with the 3-day tank presents a slightly increased water cost. If the tank already exists, of course the bigger it is, the better. * Even though batteries' cost is decreasing considerably in the last years due to electro-mobility, optimizations still favor minimizing their size. * Low enthalpy geothermal sources can decrease the cost of the autonomous RE system considerably. If such a source is available, investigation of the use possibility is strongly recommended and this expands also to the location of the geothermal well in relation to the desalination plant location, since most wells are not on the seashore and the cost for deploying the grid for connecting the desalination plant to the geothermal unit might be prohibitive.
# Seismic Performance of Corroded Reinforced Concrete Columns Strengthened with Basalt Fiber Sheets
## 3 Test Results and Analysis
### Ductility and Bearing Capacity  
\(P_{u}\) is the ultimate load of the specimen, and the failure load was taken as 0.85\(P_{u}\). \(\Delta_{u}\) is the ultimate displacement of the specimen; \(\Delta_{y}\) is the yield displacement; u = \(\Delta_{u}/\Delta_{y}\), is the displacement ductility ratio. The values of load and displacement at each stage were listed in Table 5.  
The results of specimens Z1 and Z2 were compared as shown in Table 5. Compared with the intact specimen Z1, the bearing capacity and ductility of Z2 with a corrosion rate of 8% decreased by 10.1% and 14.8%, respectively. Therefore, the steel bars with severe corrosion (>8%) will lead to a significant decrease in the bearing capacity and ductility of the specimens. The ductility of the corroded specimen decreased more obviously than the bearing capacity.  
The bearing capacity of the strengthened specimens Z3 and Z4 with a corrosion rate of 8% was increased by 4.1% and 13.99%, respectively, and the ductility was increased by 6.58% and 10.95%, respectively, compared with the intact specimen Z1. The bearing capacity of the strengthened specimens Z3 and Z4 with corrosion rate of 8% was increased by 16.1% and 20.6%, respectively, and the ductility was increased by 24.14% and 30.27%, respectively, compared with the specimen Z2 with a corrosion rate of 8%. It can be seen  
Figure 15: Backbone curve of specimens.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Specimens** & \(P_{u}\) **(kN)** & \(\Delta_{y}\) **(mm)** & \(\Delta_{u}\) **(mm)** & **u** & **0.85\(P_{u}\) **(kN)** \\ \hline Z1 & 109.58 & 14.43 & 54.27 & 3.76 & 93.14 \\ Z2 & 98.5 & 12.51 & 46.22 & 3.69 & 83.73 \\ Z3 & 114.04 & 14.52 & 57.84 & 3.98 & 96.93 \\ Z4 & 124.9 & 15.09 & 60.21 & 3.99 & 106.17 \\ \hline \end{tabular}
\end{table}
Table 5: Characteristic loads and ductility of specimens.  
that the bearing capacity and ductility of the specimen was greatly improved due to the wrapping of basalt fiber sheet. With the increase of reinforcement layers, the restraint effect of basalt fiber sheet on the specimen also increased, and the improvement effect on the bearing capacity and ductility of reinforced specimens was also more obvious.  
This indicates that utilizing a BFRP sheet can rehabilitate the ductility and bearing capacity of corroded to the level of the uncorroded specimen, and similar results can also be found in [22; 23].
## 2 Materials and Methods
### Infrared Emission Thermography System  
This system was developed as a low-cost portable device, which meets the needs of the clinical field to function as one of the first pieces of front-end equipment for diabetes mellitus complications. The device was developed with a Raspberry Pi card as an embedded system, a touch screen and a Lepton Flir sensor as an IR (Infrared) sensor. The codes were established in SPI and I\({}^{2}\)C communications between the computer and the sensor [21]. The system was programmed in C++ with Qt, designing also a database to store the collected information. The system provides as a result three files per patient: the thermographic image, the data matrix obtained from the sensor and a color map, which gives us the information about the temperature in degrees Celsius. The IR sensor was characterized to measure the surface of the sole of the feet radiometrically; the characteristic equation allows non-ionizing imaging studies related to temperature changes characteristic of diabetic foot complications. These data obtained allow the user to visually analyze and perform image processing in order to determine the condition of each patient as we obtain qualitative information, in order to support the physician's information and diagnosis.  
The system has a thermographic image acquisition protocol, with accessories that facilitate repeatability in image acquisition, as we can see in Figure 3a, in which the user is lying supine on the examination table with a system that limits the visual noise for the thermography sensor, as well as the base of the device with height, distance and angulation adjustments for the acquisition of thermographic images. To comply with the creation of  
Figure 2: (**a**) The patient takes their place with both feet inside the box and the camera will cover X and Y axis; this improves the panorama of all macules that patient has; (**b**) Region selected for the study (skin); (**c**) Selection of atrophic, traumatic and vascular macules.  
a useful database, quantitative data were chosen to support the thermographic images obtained. Each patient has information of vital signs, glycated hemoglobin, glucose, weight and height, as well as the writing of a medical note in which the responsible physician describes the observations at the time of the study to obtain a comparative record of the patient's evolution [21].  
In Figure 3b, we can see a photograph captured with this system of a patient in follow-up of a diabetic foot injury. In each zone, the temperature was taken and an average of each of the zones (1, 2 and 3) was made. Once the average temperature of each of the zones of both feet was obtained, a temperature comparison of each evaluated zone was made to know the degrees of difference between each of the zones of the diabetic foot.
## 5 CFD Modeling
### Governing Equations  
The fluid (air) was assumed to be incompressible with density and dynamic viscosity values 1.206 kg/m\({}^{3}\) and 1.83 \(\times\) 10\({}^{-5}\) Pa-s, respectively, at an ambient temperature of 20 \({}^{\circ}\)C. The numerical simulations to reproduce physical phenomena were performed using the following governing equation [41]:  
Mass conservation equation  
\[\frac{\partial u_{i}}{\partial x_{i}}=0 \tag{1}\]  
where \(u_{i}\) is the flow velocity in m/s in \(x_{i}\) direction.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{**Cross-Section No.**} & \multicolumn{6}{c}{**Velocity (m/s)**} \\ \cline{2-10}  & \multicolumn{3}{c}{**0\%**} & \multicolumn{3}{c}{**50\%**} & \multicolumn{3}{c}{**100\%**} \\  & \multicolumn{3}{c}{**Scrubber Capacity**} & \multicolumn{3}{c}{**Scrubber Capacity**} & \multicolumn{3}{c}{**Scrubber Capacity**} \\ \hline \multirow{2}{*}{1} & 3.29 & 3.35 & 3.19 & 3.51 & 3.37 & 3.31 & 3.57 & 3.37 & 3.30 \\  & 3.43 & 2.97 & 3.06 & 3.44 & 2.93 & 3.16 & 3.50 & 2.69 & 3.01 \\ \hline \multirow{2}{*}{2} & 4.27 & 3.41 & 3.86 & 4.17 & 3.43 & 3.90 & 4.07 & 3.57 & 3.62 \\  & 3.89 & 3.68 & 3.63 & 3.69 & 3.67 & 3.64 & 3.99 & 3.70 & 3.38 \\ \hline \multirow{2}{*}{3} & 3.23 & 3.72 & 3.94 & 4.39 & 4.27 & 3.91 & 5.25 & 4.10 & 3.87 \\  & 3.99 & 3.75 & 3.82 & 4.36 & 3.86 & 3.76 & 5.08 & 3.78 & 3.76 \\ \hline \multirow{2}{*}{4} & 3.31 & 3.64 & 3.97 & 3.12 & 3.38 & 3.22 & 3.13 & 3.76 & 2.98 \\  & 1.89 & 4.11 & 4.11 & 2.76 & 3.78 & 3.75 & 2.33 & 3.33 & 3.65 \\ \hline \end{tabular}
\end{table}
Table 3: Results of air velocity survey showing velocities at six points at each of four cross-sections at different scrubber fan capacities.  
Momentum conservation equation (_i_ direction)  
\[\frac{\partial\rho u_{i}}{\partial t}+\frac{\partial u_{j}\partial u_{i}}{ \partial x_{j}}=-\frac{\partial p}{\partial x_{i}}+\frac{\partial}{\partial x_{ j}}\mu\left(\frac{\partial u_{i}}{\partial x_{j}}+\frac{\partial u_{j}}{ \partial x_{i}}\right)-\rho g_{i}\beta(T-T_{0}) \tag{2}\]  
where \(u_{i}\) is the flow velocity in m/s in \(x_{i}\) direction, \(t\) is the time in second, \(\rho\) is the density in m\({}^{3}\)/s, \(P\) is the fluid pressure in Pa, \(\mu\) is the viscosity in Pa-s, \(g_{i}\) is the gravity in m/s\({}^{2}\), \(\beta\) is the coefficient of volume expansion in K\({}^{-1}\), \(T\) is the fluid temperature in K, and \(T_{0}\) is the reference fluid temperature K.  
Energy conservation equation  
\[\frac{\partial\rho C_{P}T}{\partial t}+\frac{\partial u_{j}\rho C_{P}T}{ \partial x_{j}}=\frac{\partial}{\partial x_{j}}K\frac{\partial T}{\partial x_ {j}}+\dot{q} \tag{3}\]  
where \(\rho\) is the density in m\({}^{3}\)/s, \(P\) is the fluid pressure in Pa, \(T\) is the fluid temperature in K, \(C_{P}\) is the specific heat at constant pressure in J/(kg\(\cdot\)K), \(K\) is the thermal conductivity in W/(m.K), and \(\dot{q}\) is the heat source in W/m\({}^{2}\).