esa-sceva/satcom-chunk-collection huggingface dataset:
# Digitally Chirped Multilayer Quantum Dot Lasers with Dual-Wavelength Lasing Emissions
## 3 Theoretical Simulations
\begin{table}
\begin{tabular}{c l l l} \hline \hline
**Symbol** & **Description** & **Value** & **Reference** \\ \hline \(\Delta E\) & energy resolution & 1 meV & \\ \(E_{1},E_{2}\) & lasing energy peaks & 0.98, 1.016 eV & \\ \(D_{g},D_{e}\) & GS, ES degeneracy (with spin) & \(2,4\) & [17] \\ \(N_{s}\) & QD surface density & \(4\times 10^{10}\) cm\({}^{-2}\) & \\ \(W,L\) & waveguide width, cavity length & \(10,2500\) μm & \\ \(g_{0}\) & differential gain coefficient & \(10^{-15}\) cm\({}^{2}\) & \\ \(V_{t}\) & total QD volume & \(10^{-9}\) cm\({}^{3}\) & \\ \(\Gamma_{inh}\) & inhomogeneous broadening factor & 30 meV & \\ \(\Gamma_{hom}\) & homogeneous broadening factor & 13 meV & \\ \(n_{tr}\) & refraction index & 3.47 & \\ \(\beta\) & spontaneous emission factor & \(10^{-5}\) & [14] \\ \(\Gamma_{a1},\Gamma_{a2}\) & optical confinement factor & 0.023, 0.047 & \\ \(\tau_{p}\) & photon lifetime & 15 ps & \\ \(\tau_{\text{zw}_{1}},\tau_{\text{e}_{1}w}\) & QW \(\leftrightarrow\) ES1 transition time & \(2,10\) ps & [17] \\ \(\tau_{\text{zw}_{2}},\tau_{\text{zw}_{2}w}\) & QW \(\leftrightarrow\) ES2 transition time & \(3,10\) ps & \\ \(\tau_{\text{e}_{1}g_{1}},\tau_{\text{g}_{1}e1}\) & ES1 \(\leftrightarrow\) GS1 transition time & \(8,18\) ps & [17] \\ \(\tau_{\text{zg}_{2}},\tau_{\text{g}_{2}e2}\) & ES2 \(\leftrightarrow\) GS2 transition time & \(8,18\) ps & \\ \(\tau_{\text{zw}}\) & QW spontaneous lifetime & 5000 ps & [17] \\ \(\tau_{\text{e}_{1}},\tau_{\text{g}_{1}}\) & ES1, GS1 spontaneous lifetime & 500, 2000 ps & [17] \\ \(\tau_{\text{e}_{2}},\tau_{\text{g}_{2}}\) & ES2, GS2 spontaneous lifetime & 200, 1000 ps & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Device parameters for digitally chirped multilayer quantum-dot (DC-MQD) lasers. where the homogeneous broadening factor (\(\Gamma_{hom}\)) is its FWHM. The spontaneous emitted photons associated with ES1 and ES2 are not considered in gain calculation because they are well below respective transparent population in our investigated range of injection current.
## 3 Application  
### The Isolated Bridge Geometry and Finite Element Model  
The study object of this article is a six-span reinforced concrete continuous girder bridge with a total length of 120 m. The bridge arrangement is shown in Figure 2. The bridge superstructure is a 6 \(\times\) 20 m cast-in-place C40 concrete box girder with a beam height of 1.3 m. The lower part of the structure is an RC circular pier column of C30 concrete. No. 1 and No. 5 piers are double-column piers 1.3 m in diameter and 8 m in height; No. 2, 3, and 4 piers are variable cross-section one-column circular bridge piers with a height of 8 m and diameter of 1.5 m. The main girder and the pier top are connected to an LRB500 isolation bearing by setting expansion joints on both sides of the stage. The bridge pier foundation material is C30 concrete. The seismic fortification intensity is 8 degrees in the area, and the site class is II.  
Figure 1: The technical route of the research process.  
The finite element dynamic analysis model of the isolated bridge structure was established using OpenSees software [32], and the seismic response of the structure was measured by only the longitudinal seismic motion. The superstructure was modeled with elastic beam-column elements because they remain undamaged and in an elastic state in earthquakes. The damping was simulated with Rayleigh damping [23]. The bearings were modeled using zero-length elements [33], and the shear force-deformation relationship was assumed to be perfect elastic-plastic [34]. Regarding the pier, it often enters the plastic stage, and the plastic hinge appears. Therefore, in the time history analysis, the piers were simulated by nonlinear beam-column elements. The cross section of the element was defined by fibers with the corresponding material stress-strain relationship. The concrete behavior was modeled with Concrete01 in OpenSees. This material was defined with the Kent-Scott-Park model [35]. The reinforcing steel was modeled with Steel 01 in OpenSees, and the constitutive model is shown in Figure 1. The expansion joint between the main beam and the abutment was modeled with a nonlinear contact Gap unit, as shown in Figure 3. It is worth noting that when solving the contact collision problem, it is required that the two components in the collision should not have initial penetration, otherwise the wrong calculation results will be obtained. Therefore, when establishing the model, the spatial clearance at the contact should be maintained as far as possible, so as to conform to the actual spatial position of the bridge [36]. Therefore, this paper assumed that the value of the relative displacement of the abutment and the girder was set, and the collision would occur when the open value was reached.
## 5 Applications and Discussions
### Waste Heat Utilizing System Modeling  
#### 5.3.1 System Description  
An application of modeling the 11 kW waste heat utilizing system is studied in this section, and the conceptual diagram of the power generate process is shown in Figure 4. In the system, R123 whose critical properties listed in Table 6 is selected as the working fluid. The energy of the waste heat source is transferred to the working fluid in the evaporator, and then the vaporized R123 enters the turbine and drives it to generate power. The working fluid vapor from the expander is next used to preheat the cold working fluid in a regenerator before it enters the evaporator. The vapor from the regenerator is then condensed back into liquid state in a water-cooled condenser. The liquid stored in a receiver then is pumped into the regenerator again.  
The physical model of the waste heat utilizing system can be drawn from the partial differential equations of the mass balance and the energy balance, while there are many strong nonlinear components in the circle, such as evaporator, condenser and some electrical valves. The system evolved by physical modeling and traditional identification modeling strategy usually cannot match the needs of the control system when the work condition varies; therefore, the agent based fuzzy identification method for waste  
Figure 3: Comparison of the ABFT-SM identification results with heater system outputs. (**a**,**b**) are corresponding to the working condition 1 and 2 respectively; (**c**) is the varied condition situation.  
heat utilizing system is investigated in this paper. In general, the nonlinear expression of this process is as follows:  
\[y_{k}=f(y_{k-1},...,y_{(}k-n_{A}),u_{k},u_{k-1},...,u_{k-n_{B}},\xi_{k}) \tag{26}\]  
where, \(y_{k}\) is the output of the system, \(u_{k}\) is the input, and \(\xi_{k}\) is the random disturb.
# Additive Manufacturing and Chemical Engineering: Looking for Synergies from a Bibliometric Study
###### Abstract  
Additive manufacturing must be highlighted as an innovative technology with the capacity to produce objects with complex and customized geometries using a diverse range of raw materials. Despite its significant potential, research compiling and evaluating the specific contributions of additive manufacturing in the field of chemical engineering was scarce in both quantitative and qualitative terms. Similarly, the application of chemical engineering tools to additive manufacturing has not been specifically reviewed. Therefore, this work conducted a comprehensive review of the scientific literature covering these issues using bibliometric analysis. The search encompassed the entirety of the scientific literature up to the year 2023, yielding 3761 documents in the Scopus database. The principal findings of this bibliometric analysis indicated an exponential growth in the number of publications, which suggests a rising scientific interest in this field. The analysis revealed that English was the dominant language in the documents, and articles constituted the most common document type, indicating the quality and maturity of the research. The thematic distribution proved to be multidisciplinary, with a primary focus on engineering and materials science, as well as basic sciences. The United States was the foremost contributor to scientific production, followed by China and Germany. Keyword analysis and scrutiny of the most cited documents enabled the identification of the main topics, which were found to include biofabrication and biomedical applications. Moreover, bibliometric network analysis using the software SciMAT (v 1.1.06) yielded the corresponding strategic diagrams, evolution maps, and thematic networks, which provided a comprehensive overview of trends and research gaps. The considerable interest in the application of additive manufacturing to biofabrication and other biomedical purposes has overshadowed the specific applications within the chemical engineering field, while the potential contributions that chemical engineering could make to the field of additive manufacturing have been eclipsed too. On the one hand, applications focused on process intensification in chemical engineering could benefit from additive manufacturing to design advanced microreactors and other miniaturized devices or to produce more efficient heat exchangers, catalysts, and adsorbents with complex geometries and separation membranes with innovative materials and structures. On the other hand, life cycle assessment and optimization are established chemical engineering tools that should be more extensively employed in the context of additive manufacturing to ensure a more sustainable outcome.  
additive manufacturing; chemical engineering; 3D printing; biofabrication; bibliometric analysis +
Footnote †: journal: Applied sciences
## 4 Discussion
### Limitations and Prospects  
Although the XGB-based GPP estimation model demonstrates promising performance, several aspects could be further enhanced to optimize the model performance. Firstly, sampling sites are regional. While the flux tower data for Chinese forest types used in the study are representative, the sites are mainly concentrated in southern regions. This bias  
Figure 14: Temporal variation in GPP estimates from multiple products across four Chinese provinces (2008–2016). Time series comparison of gross primary productivity (GPP) derived from four products (FLUXCOM, GOSIF, GLASS, and XGBoost) for (**a**) Guangdong, (**b**) Yunnan, (**c**) Jilin, and (**d**) Jiangxi provinces from 2008 to 2016.  
may limit accuracy improvements in northern regions with lower GPP values. Secondly, sampling interval differences exist. Remote sensing data such as EVI, NDVI, and LAI are obtained at a 16-day frequency, and the model uses daily data derived through Cubic Spline interpolation, potentially introducing additional uncertainty. Thirdly, there is spatial resolution difference among the data. The variables in the study come from sources with different spatial resolutions. Although downscaling or upscaling was applied using the resampling method in ArcGIS to standardize the spatial resolution, uncertainties may still exist in variable extraction.  
Future research should focus on the following aspects: First, to improve the spatiotemporal resolution of GPP estimates for forest ecosystems, it is essential to develop a high-resolution and representative large-scale training dataset. This approach aims to enhance data quality [72; 73], thereby increasing the accuracy of GPP estimation. Second, to further boost the performance of the RGSA hyperparameter optimization algorithm, integrating swarm intelligence algorithms such as the Whale Optimization Algorithm (WOA) [74] and Particle Swarm Optimization (PSO) [75] is recommended. This integration could improve hyperparameter tuning accuracy and reduce computation time. Third, optimizing the variable combinations used for estimating GPP should be considered. In addition to the variables used in this study, other variables highly correlated with GPP, such as precipitation, wind speed, and terrain data, should be included. Fourth, using additional characteristic variables related to GPP products, and combining this strategy with few-shot learning methods in transfer learning [76; 77], could help address the challenge of accurately estimating GPP in remote areas where measured GPP data are scarce or costly to obtain [78].
# Evaluation of Measurement Strategy for Track Side Monitoring of Railway Wheels
## 3 Methodology
### Wayside Measurements  
Wayside measurements of the wheel profile parameters were performed using a commercial laser-based automatic wheel profile measurement system developed by Beena Vision, USA. The automatic monitoring system is located at the track section situated in the southernmost part of the Iron Ore Line in Sweden. The automatic wheel profile measurement system is depicted in Figure 3, and the system consists of two main units. The first wheel triggers a sensor when a train passes the boxes housing the measurement units and the protective cover opens. The laser beams activate and project laser lines onto the surface of the passing wheels, and the camera captures pictures of this. Each unit consists of two cameras (depicted in Figure 3) and three lasers that produce two images, one for  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Wheelset ID** & **Age (km)** & **Measurements** \\ \hline HP8628 & 0 & 35 \\ HP9270 & 0 & 35 \\ HP8507 & 237,832 & 35 \\ HP7480 & 315,740 & 35 \\ HP6448 & 317,125 & 35 \\ HP9264 & 409,522 & 35 \\ HP9709 & 409,522 & 35 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Wheel profiles and their relative age with respect to distance, used for manual measurements.  
Figure 2: Wheel profiles plotted along the circumference of the wheel using the different measurement positions for the wheel id HP6448.  
each flange and tread side of the wheel. The two images are merged to form one image of the wheel profile, from which the wheel profile parameters are estimated (refer Figure 1).  
During the wayside measurement, eight different wheels were measured, and the wheel profile parameters were estimated for each reading. To reduce the effect of wheel wear influencing the study, the wheels were measured during a time span of ten days. During this period, each wheel passed the measurement system ten times, resulting in a set of ten measures for each wheel. Between each measurement, the travel distance of the wheel was approximately 800 km. Depending on the direction of the train, the right or left system was used to measure the wheel profile parameters. Due to measurement errors for some wheels, some measurements had to be discarded. The measurement error involved those sequences where the camera failed to capture and save the images of the wheel. Table 2 depicts the number of measurements recorded for each individual wheel.
## 4 Financial and Environmental Analysis
### Environmental Viability  
Incorporating PCMs into building envelopes, particularly BioPCMs, has the potential to mitigate temperature fluctuations, enhancing thermal comfort and contributing to sustainability goals by reducing energy consumption and carbon emissions. BioPCMs are environmentally friendly materials derived from renewable biomass sources, exhibiting non-toxic and recyclable properties. Unlike conventional insulation materials, BioPCMs do not generate emissions during manufacturing. To assess the energy-related environmental impact, the greenhouse gas (GHG) emissions equivalent to a kilowatt-hour (kWh) of electricity in Jordan (435 g of CO\({}_{2}\)e) are considered [59]. The emissions factor is based on the current electricity generation mix, primarily comprising natural gas and oil, with growing prospects for renewable sources like solar and wind power. The reduction in GHG emissions resulting from energy savings can be estimated using the formula: GHG reduced emissions (kg CO\({}_{2}\)e) = kWh of electricity saved \(\times\) 0.435 kg CO\({}_{2}\)e per kWh. For Amman,with an annual energy saving of 5476.58 kWh/year, this corresponds to an estimated reduction of 2382.31 kg of equivalent carbon dioxide emissions per year (kgCO\({}_{2}\)e/year).
# Modelling, Analysis and Performance of a Low Inertia AC-DC Microgrid
## 3 Stability Analysis
### Impact of Cdc Variation  
Figure 6 shows the system's eigenvalues while varying the DC link capacitance from 0.2 to 2 of the nominal value. The eigenvalues show the stability effect added to the system and the reduced frequency oscillations by increasing the capacitance, as the capacitance works as the inertia storage for the proposed virtual inertia controller.
## 1 Introduction
In summary, we propose a survivable RBMSA algorithm in C+L-EONs, which considers the fragmentation and ISRS issues comprehensively. The following are the main points of this article:  
First, the band partitioning method is adopted, which allocates the primary path resource in the L band and backup path resource in the C band. The method reduces the ISRS impact by ensuring that the lightpaths do not establish in the C band before network failures. Second, a path weight metric that considers the idle fragmentation within a link is proposed in the primary path selection phase, while a path weight metric that jointly considers the idle fragmentation and the shareable fragmentation within a link is proposed in the alternate path selection phase. The proposed path weight metric can select less fragmented paths for requests as much as possible in order to maximize the use of the spectrum resources of each link and thus successfully establish optical paths for more requests. Third, in the spectrum allocation phase, two fragmentation metrics are proposed, one focusing on idle fragments within the primary path and the other jointly considering idle and shareable fragments within the alternate path. Among them, the fragmentation metric that jointly considers idle fragments and shareable fragments in the alternate path extends the scope of the spectrum fragmentation metric, which can reserve more consecutively available FSs for subsequent requests; further reduces the ISRS impact of the requests in the C band on the requests in the L band during the occurrence of faults; and guarantees the QoT of the requests. The following parts of the study are structured as follows. In Section 2, we provide a comprehensive review of the pertinent paper pertaining to C+L-EONs. Section 3 introduces the system model and quality of transmission (QoT) estimation framework for the C+L bands. Subsequently, in Section 4, we expound upon the fundamental principles underlying the proposed algorithm. Section 5 offers a comprehensive evaluation and in-depth analysis of the performance characteristics of the proposed algorithmic approach. Subsequently, Section 6 consolidates the key conclusions derived from this investigative study.
## 3 Precise Orbit Determination Strategy
### Three-Day Solution  
In order to obtain a stable solution, long data arc is needed for POD based on a regional tracking network because of the weak observing geometry. For the BeiDou regional system, GEO satellites have almost no movement with respect to the ground network and IGSOs are restricted within a certain longitude zone. Therefore, long arc estimation is even more important for the current regional BeiDou system. In this study we use three-day data in a batch estimation to obtain a three-day solution, instead of combining three daily solutions on the level of normal equations [9]. The orbit quality is assessed by the orbit consistency of two adjacent three-day solutions over the overlapping time: the orbit of the last day in one three-day solution is compared with that of the middle day in the next, as illustrated in Figure 3. Although the overlapping consistency, measured by the RMS of the orbit differences over the overlapping day, cannot fully represent the true orbit accuracy because two-thirds common data is involved in two adjacent solutions, from the validation using satellite laser range [9,11] it is still an useful orbit quality index for the related study.  
Figure 3: Three-day solution and orbit overlap comparison.  
Figure 2: Daily data availability of the 13 selected tracking stations over the testing period.
## 2 Materials and Methods
### Characterization of La-EPRC Particles for Static Adsorption of Phosphorus Removal
#### 2.3.4 Solution pH Experiments  
The pH of nine 250 mL phosphate solutions (20 mg P/L) was adjusted to 2-12 using 1 mol/L, 0.1 mol/L NaOH, and HCl solutions. Adding 2 g of La-EPRC particles to solutions with different pH levels, the mixtures were placed on a shaking table (25 \(\pm\) 1 \({}^{\circ}\)C, 150 \(\pm\) 5 r/min) for continuous shaking until the adsorption reaction reached equilibrium, typically at 48 h. After reaching equilibrium, the reaction was halted, and supernatant samples were collected to determine and calculate the remaining phosphorus content and adsorbent removal efficiency. This process involved filtering the supernatant through a 0.45 \(\upmu\)m filter and analyzing the impact of solution pH on the adsorption effect.
# Investigation of Aerosol Climatology and Long-Range Transport of Aerosols over Pokhara, Nepal
## 2 Methodology
### Tools Used for Backward Trajectories and Fire Spots  
Four clusters were generated for each season by calculating five days backward air mass trajectories, starting at 500 m over the receptor site Pokhara (28.19\({}^{\circ}\) N, 83.19\({}^{\circ}\) E), for every day at 0:00, 6:00, 12:00, and 18:00 UTC, based on the HYSPLIT model [13]. A free software plugin called TrajStat was used from MeteoInfo for the calculations [36]. Fire spots were obtained from NASA's Fire Information for Resource Management System (FIRMS),which allows visualizing large scale bio-mass burning activities around the region. These active fire data were observed from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and NASA's Visible Infrared Imaging Radiometer Suite (VIIRS),however, these satellite images will not provide the household level of biomass burning. A combination of satellite images of fire spots with air masses back trajectory will be presented to demonstrate a significant picture of aerosol climatology over the region [37; 38; 39].  
In this study, we have used the data of the year 2017 to present a cluster analysis for indicating the seasonal aerosol sources' characterization over the observation site Pokhara.