Universitat Politecnica De Catalunya Research Articles

Full scope scaling analysis and recommendations for PWR SGTR scenarios

Scaling studies were conducted in the field of nuclear thermal-hydraulics to analyze the scaling distortions in a Steam Generator Tube Rupture (SGTR) scenario. Test 4 of the NEA/OECD/ROSA-2 Large-Scale Test Facility (LSTF) was chosen as the basis for the analysis of scaling distortions. Firstly, a post test calculation of the experiment was performed with the RELAP5 system code along with a phenomenological assessment. This model was then scaled over a wide range of sizes to investigate the possible scaling distortions by means of the Power-to-Volume Scaling Tool (PVST) which is an in-house tool developed and validated by the Universitat Politècnica de Catalunya (UPC) for scaling nodalizations. The paper demonstrates that the main scaling distortion observed in Test 4 is attributed to the lack of preservation of the L/D ratio in the SGTR assembly nozzle. This rationale is quite important in the design of break units in experimental facilities to preserve the friction and the mass flows of the reference (prototype) plant and scenario. Subsequently, the paper presents a series of guidelines for minimizing scaling distortions and reports the results obtained by applying them, the proportional scaling distortion was reduced by more than tenfold. Additionally, the paper analyzes the RELAP5 models involved in the conservation of momentum equation for the SGTR assembly nozzle, and their potential scaling distortions.

Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sun photometer, and in situ observations over 17 years at Universitat Politècnica de Catalunya (UPC) Barcelona

Abstract. Aerosols are one of the most important pollutants in the atmosphere and have been monitored for the past few decades by remote sensing and in situ observation platforms to assess the effectiveness of government-managed reduction emission policies and assess their impact on the radiative budget of the Earth's atmosphere. In fact, aerosols can directly modulate incoming short-wave solar radiation and outgoing long-wave radiation and indirectly influence cloud formation, lifetime, and precipitation. In this study, we quantitatively evaluated long-term temporal trends and seasonal variability from a climatological point of view of the optical and microphysical properties of atmospheric particulate matter at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, over the past 17 years, through a synergy of lidar, sun photometer, and in situ concentration measurements. Interannual temporal changes in aerosol optical and microphysical properties are evaluated through the seasonal Mann–Kendall test. Long-term trends in the optical depth of the recovered aerosol; the Ångström exponent (AE); and the concentrations of PM10, PM2.5, and PM1 reveal that emission reduction policies implemented in the past decades were effective in improving air quality, with consistent drops in PM concentrations and optical depth of aerosols. The seasonal analysis of the 17-year average vertically resolved aerosol profiles obtained from lidar observations shows that during summer the aerosol layer can be found up to an altitude of 5 km, after a sharp decay in the first kilometer. In contrast, during the other seasons, the backscatter profiles fit a pronounced exponential decay well with a well-defined scale height. Long-range transport, especially dust outbreaks from the Sahara, is likely to occur throughout the year. During winter, the dust aerosol layers are floating above the boundary layer, while during the other seasons they can penetrate the layer. The analysis also revealed that intense, short-duration pollution events during winter, associated with dust outbreaks, have become more frequent and intense since 2016. This study sheds some light on the meteorological processes and conditions that can lead to the formation of haze and helps decision makers adopt mitigation strategies to preserve large metropolitan areas in the Mediterranean basin.

Ionospheric Weather at Two Starlink Launches during Two-Phase Geomagnetic Storms.

The launch of a series of Starlink internet satellites on 3 February 2022 (S-36), and 7 July 2022 (S-49), coincided with the development of two-phase geomagnetic storms. The first launch S-36 took place in the middle of the moderate two-phase space weather storm, which induced significant technological consequences. After liftoff on 3 February at 18:13 UT, all Starlink satellites reached an initial altitude of 350 km in perigee and had to reach an altitude of ~550 km after the maneuver. However, 38 of 49 launched spacecrafts did not reach the planned altitude, left orbit due to increased drag and reentered the atmosphere on 8 February. A geomagnetic storm on 3-4 February 2022 has increased the density of the neutral atmosphere up to 50%, increasing drag of the satellites and dooming most of them. The second launch of S-49 at 13:11 UT on 7 July 2022 was successful at the peak of the two-phase geomagnetic storm. The global ionospheric maps of the total electron content (GIM-TEC) have been used to produce the ionospheric weather GIM-W index maps and Global Electron Content (GEC). We observed a GEC increment from 10 to 24% for the storm peak after the Starlink launch at both storms, accompanying the neutral density increase identified earlier. GIM-TEC maps are available with a lag (delay) of 1-2 days (real-time GIMs have a lag less than 15 min), so the GIMs forecast is required by the time of the launch. Comparisons of different GIMs forecast techniques are provided including the Center for Orbit Determination in Europe (CODE), Beijing (BADG and CASG) and IZMIRAN (JPRG) 1- and 2-day forecasts, and the Universitat Politecnica de Catalunya (UPC-ionSAT) forecast for 6, 12, 18, 24 and 48 h in advance. We present the results of the analysis of evolution of the ionospheric parameters during both events. The poor correspondence between observed and predicted GIM-TEC and GEC confirms an urgent need for the industry-science awareness of now-casting/forecasting/accessibility of GIM-TECs during the space weather events.

12th EASN International Conference

The 12th EASN International Conference on Innovation in Aviation & Space was successfully held in Barcelona - Spain, from October 18th to October 21st, 2022. It was the first EASN in-person gathering after the COVID-19 pandemic outbreak in March 2020.The EASN Association and the Universitat Politecnica de Catalunya – Barcelona Tech (UPC) would like to cordially thank all the participants of the 12th EASN International Conference. Many thanks are also due to the Keynote Speakers, Session Chairs, Authors and Presenters, the International Scientific Committee, and the local Organizing Committee for making this Conference a big success.The event included 8 Keynote Speeches, more than 400 technical presentations and feedback slots distributed in 75 sessions and workshops. Moreover, 85 Aviation & Space Projects disseminated their latest research results as well as the future trends in the respective technological fields. In total, more than 470 participants from 39 countries joined the 12th EASN International Conference, making this year’s gathering the most successful in the EASN Conference series so far.List of The EASN Conference Co-Chairmen, International Scientific Committee of the 12th EASN International Conference and Logos are available in this pdf.

Performance and Consistency of Final Global Ionospheric Maps from Different IGS Analysis Centers

Ionospheric delay is one of the most problematic errors in satellite-based positioning data processing. The Global Ionospheric Map (GIM), which is publicly available daily in various analysis centers, is thus vitally important for positioning users. There are variations in the accuracy and consistency of GIMs issued by Ionosphere Associate Analysis Centers (IAACs) due to the differences in ionospheric modeling methods and selected tracking stations. In this study on the International GNSS Service’s (IGS) final GIM, the ionospheric total electron content (TEC) (from 243 global navigation satellite system (GNSS) monitoring stations around the world) and the ionospheric TEC (from the Jason-3 altimeter satellite) are selected as reference. By using these three references, we evaluate the performance and consistency of final GIM products from seven IGS IAACs, including the Chinese Academy of Sciences (CAS), the Center for Orbit Determination in Europe (CODE), Natural Resources Canada (EMR), the European Space Agency (ESA), the Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU) in the mid-solar activity year (2022) and the low-solar activity year (2020). Firstly, the comparison with the IGS final GIM shows that the consistency of each GIMs is basically the same, with the mean value ranging from −0.3 TECu (total electron content unit) to 1.4 TECu. Secondly, the validation with Jason-3 altimeter satellite shows that the accuracy of several GIMs is almost the same, except for the JPL with the worst accuracy and an overall mean deviation (BIAS) between 2 and 6 TECu. Thirdly, the comparison with VTEC extracted from GNSS monitor stations shows that the CAS has the best accuracy in different latitude bands with a root mean square (RMS) of about 2.2–4.7 TECu. In addition, it is found that the accuracy in areas with more stations for ionospheric modelling is better than those with less stations in different latitude bands; meanwhile, the accuracy is closely related to the modeling methods of different GIMs.

Study of Ionosphere Irregularities over the Iberian Peninsula during Two Moderate Geomagnetic Storms Using GNSS and Ionosonde Observations

Studies on the irregularities of the ionosphere during disturbed geomagnetic conditions are fundamental to understanding the complex dynamics taking place in the upper atmosphere. In this work, different data sources are used to study the ionosphere effects of two moderate geomagnetic storms, 26–27 February 2014 and 17–18 September 2021, over the Iberian Peninsula. Data are obtained from digital ionosondes in Spain, Italy and Greece; the Global Navigation Satellite System (GNSS) derived Total Electron Content (TEC) and Rate Of TEC Index (ROTI) from several receiver stations in Spain, Portugal and Morocco; and the UPC Quarter-of-an-hour time resolution Rapid GIM (UQRG), vertical TEC global ionosphere maps (GIMs), produced at 15 min intervals by the Universitat Politecnica de Catalunya (UPC, Spain). This analysis showed that, during the two moderate storms, spread-F and high values of ROTI, indicating the presence of irregularities, are found in a very localized area (Southern Iberian Peninsula and northwest Africa) and local times (night-time). However, no irregularities are found eastwards and northwards of the location indicated. We propose some possible explanations for these observations for both the storms, one of them related to the position of the Equatorial Ionosphere Anomaly (EIA) and the other one attributed to the Perkins’ instabilities.

A Formal Verification and Validation of a Low Magnetic Reynolds Number MHD Code for Fusion Applications

As the nuclear fusion research advances, researchers and engineers focus more on the design of the required systems that complement the nuclear fusion reaction in the plasma of a Tokamak. Some proposals for breeding blankets as well as plasma-facing components’ protection systems are based in liquid metal flows under the Tokamak intense magnetic fields. This creates the situation where induced magnetic field can be neglected and the low magnetic Reynolds number (Re) electric potential formulation can be used to close the magnetohydrodynamic (MHD) system of equations. In the last few years, many different laboratories have developed their own MHD codes to study the liquid metal flow. A formal verification and validation of such codes is necessary to enhance the reliability of the numerical results and to make sure that design decisions are based on safe grounds. The fusion community has made the effort of proposing standardized benchmark cases through which any MHD code should demonstrate its reliability. This work contains the formal validation and verification activities of the MHD code developed some years ago in the Universitat Politecnica de Catalunya (UPC) and currently candidate to contribute to the research done at the Princeton Plasma Phyisics Laboratory (PPPL). The code is implemented over OpenFOAM which makes it easily modifiable. Among these benchmark cases, there are high Hartmann number (Ha), 3-D flows, and magneto-convective interaction cases.

Deep RNN-based network traffic classification scheme in edge computing system

This paper proposes a deep recurrent neural network (RNN)-based traffic classification scheme (deep RNN-TCS) for classifying applications from traffic patterns in a hybrid edge computing and cloud computing architecture.We can also classify traffic from a cloud server, but there will be a time delay when packets transfer to the server. Therefore, the traffic classification is possible almost in realtime when it performed on edge computing nodes. However, training takes a lot of time and needs a lot of computing resources to learn traffic patterns. Therefore, it is efficient to perform training on cloud server and to perform serving on edge computing node. Here, a cloud server collects and stores output labels corresponding to the application packets. Then, it trains those data and generates inferred functions. An edge computation node receives the inferred functions and executes classification. Compared to deep packet inspection (DPI), which requires the periodic verification of existing signatures and updated application information (e.g., versions adding new features), the proposed scheme can classify the applications in an automated manner. Also, deep learning can automatically make classifiers for traffic classification when there is enough data. Specifically, input features and output labels are defined for classification as traffic packets and target applications, respectively, which are created as two-dimensional images. As our training data, traffic packets measured at Universitat Politecnica de Catalunya Barcelonatech were utilized. Accordingly, the proposed deep RNN-TCS is implemented using a deep long short-term memory system. Through extensive simulation-based experiments, it is verified that the proposed deep RNN-TCS achieves almost 5% improvement in accuracy (96% accuracy) while operating 500 times faster (elapsed time) compared to the conventional scheme.

Ionospheric Storm Scale Index Based on High Time Resolution UPC‐IonSAT Global Ionospheric Maps (IsUG)

AbstractThe ionospheric storms have adverse effects on the radio communications, satellite communications and also the Global Navigation Satellite Systems (GNSS) application. A new Ionospheric storm Scale from Universitat Politècnica de Catalunya (UPC) Global Ionosphere Map (GIM), IsUG, is introduced for characterizing the ionospheric state on a global scale. The IsUG is based on the Vertical Total Electron Content (VTEC) derived from the continuously computed UPC Quarter‐of‐an‐hour time resolution Rapid GIM (UQRG), taking as reference the ones during the period 1997 to 2014. It is similar to the I‐scale index previously introduced, although it was over Japan and based on raw GNSS data. The dependence of the VTEC on season, local time and geographical location at each grid point of UQRG is removed by normalizing (i.e., by substracting the mean and dividing by the corresponding standard deviation) the percentage deviation of hourly median VTEC. After validating IsUG versus I‐scale, the IsUG distribution is presented and analyzed at global scale during a severe geomagnetic storm from 7 to 10 November 2004 as an example of the potentialities of the new index. The results suggest that the IsUG global map has a great potential for the scientific study of ionospheric storms from a global perspective and also for space weather warning considering the accuracy of the recently developed real‐time GIMs.

Numerical and Experimental Approaches to Estimate Discharge Coefficients and Energy Loss Coefficients in Pressurized Grated Inlets

Numerical models concerning inlet systems are run to assess the hydraulic performance of existing or new systems and estimate the flow interchanges between the surface overland and sewer flows. In most programs, these interactions are modelled using the orifice equation, with estimated discharge coefficients around 0.6. In this paper, discharge values and energy loss coefficients for several pressurized grated inlets were obtained by experimental and numerical approaches and compared. To achieve these goals, a numerical model replicating several experimental tests carried out at the hydraulic laboratory of Universitat Politècnica de Catalunya (UPC) was produced using a CFD model (Flow 3D). This numerical model was found to be highly sensitive to the mesh size used; however, it was able to accurately simulate the experimental processes. The comparison considered different combinations of pressurized flow though the grate, between 10 to 50 l/s, and different longitudinal gradients. The experimental discharge coefficient was found to increase with surcharging flowrate (ranging from 0.14 and 0.41), whereas the longitudinal gradient was found to have no effect. The discharge coefficients obtained in this study show that the standard 0.6 value commonly used by practitioners should be revised to a range between 0.14 to 0.41, depending on circulating flow and inlet type. In addition, the loss coefficient values range from 0.25 to 3.41.

The cooperative IGS RT-GIMs: a reliable estimation of the global ionospheric electron content distribution in real time

Abstract. The Real-Time Working Group (RTWG) of the International GNSS Service (IGS) is dedicated to providing high-quality data and high-accuracy products for Global Navigation Satellite System (GNSS) positioning, navigation, timing and Earth observations. As one part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) has been generated by the real-time weighting of the RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d'Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC) and Wuhan University (WHU). The performance of global vertical total electron content (VTEC) representation in all of the RT-GIMs has been assessed by VTEC from Jason-3 altimeter for 3 months over oceans and dSTEC-GPS technique with 2 d observations over continental regions. According to the Jason-3 VTEC and dSTEC-GPS assessment, the real-time weighting technique is sensitive to the accuracy of RT-GIMs. Compared with the performance of post-processed rapid global ionosphere maps (GIMs) and IGS combined final GIM (igsg) during the testing period, the accuracy of UPC RT-GIM (after the improvement of the interpolation technique) and IGS combined RT-GIM (IRTG) is equivalent to the rapid GIMs and reaches around 2.7 and 3.0 TECU (TEC unit, 1016 el m−2) over oceans and continental regions, respectively. The accuracy of CAS RT-GIM and CNES RT-GIM is slightly worse than the rapid GIMs, while WHU RT-GIM requires a further upgrade to obtain similar performance. In addition, a strong response to the recent geomagnetic storms has been found in the global electron content (GEC) of IGS RT-GIMs (especially UPC RT-GIM and IGS combined RT-GIM). The IGS RT-GIMs turn out to be reliable sources of real-time global VTEC information and have great potential for real-time applications including range error correction for transionospheric radio signals, the monitoring of space weather, and detection of natural hazards on a global scale. All the IGS combined RT-GIMs generated and analyzed during the testing period are available at https://doi.org/10.5281/zenodo.5042622 (Liu et al., 2021b).

A Methodology to Study the University’s Online Teaching Activity from Virtual Platform Indicators: The Effect of the Covid-19 Pandemic at Universitat Politècnica de Catalunya

The Covid-19 pandemic led Catalan universities to do all teaching and evaluation online from 11 March 2020 until the end of term on 30 July. Conventional universities made the transition to online teaching in just a few days and suddenly virtual platforms become the centre of interaction between lecturers and students. Data that were obtained from the virtual platforms gave extremely valuable information about what was being done in class. This paper analyses data taken from Atenea, the Moodle virtual platform at the Universitat Politècnica de Catalunya (UPC), during quarantine. The key indicators and a data analysis design for Moodle have been proposed, which reveal teaching developments at various levels (overall and at the centre and subject level). This is applied to study data from the UPC Moodle and the results are discussed. The methodology can be extrapolated to other universities with Moodle platforms because the UPC is a set of small campuses and centres.

On the validation of BEPU methodologies through the simulation of integral experiments: Application to the PKL test facility

Validation is a key step in the field of thermal hydraulics and has played a crucial role in the implementation of system codes. These codes are then included in licensing methodologies being those either best estimate plus uncertainties (BEPU) or conservative approaches. However, only a small amount of efforts has been done on the validation of the methodologies as a whole. Such validation would imply the comparison of the bounding limits and the experimental data. Due to the lack of actual data of accidental situations, such validation should be carried out with data from integral test facility (ITF) experiments.The OECD/NEA PKL-4 test programme is investigating safety issues relevant for current pressurized water reactor (PWR) plants as well as for new PWR design concepts focusing on complex heat transfer mechanisms under two-phase flow. Within the project, a blind benchmark activity has been launched where an IBLOCA experiment has been simulated by 12 different organizations. The Universitat Politècnica de Catalunya (UPC) participated in the activity with a blind BEPU approach with the main objective of assessing the validity of the methodology as a whole.At first, the scalars that characterize the phenomenology of the particular scenario have been considered. Secondly, in order to broaden the extent of the validation, the results of the different participants have been interpreted as if they were blind experiments as well. Finally, different output parameters have been considered providing a matrix of results that is used to evaluate the validity of the methodology.

Performance evaluation of GIMs released by different IGS ionosphere associate analysis centers in ionospheric constrained single-frequency precise point positioning

Single-frequency precise point positioning (PPP) is widely used with the advantage of cost-efficient, while its further development and application are limited by the difficulty of ionospheric delay correction and the long-time convergence, especially for real-time positioning. And the development of high-accuracy ionospheric models plays an important role for the correction of ionospheric delay in single-frequency PPP. In this paper, the final and rapid global ionospheric map (GIM) products released by Chinese Academy of Science (CAS), Center for Orbit Determination in Europe (CODE), European Space Agency (ESA), Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), Wuhan University (WHU) and International GNSS Service (IGS) were used as external constraints in static, simulation kinematic and kinematic single-frequency PPP respectively. The performance and practicality of each product were analyzed by using IGS station observation data (September 2017 and January 2018, with different ionospheric activity levels) and a kinematic experiment. The results indicate that GIM products may improve convergence time in most areas of middle and high latitudes of the globe. However, the improvement of convergence time of some regions in low latitudes or near the equator with dense and uniform distributed IGS stations show even better performance than the regions in middle and high latitudes. Comparing with standard PPP (S-PPP), the convergence time of static PPP is reduced about 14–42% and 13–29% with GIM final and rapid products respectively. In simulation kinematic PPP, the convergence time improves 10–43% and 12–25% for final and rapid products respectively. In the kinematic positioning, the addition of external ionospheric constraints may speed up the convergence in the early stage of positioning and improve the accuracy to a certain extent. Among all GIM products, the final products show better performance than that of the rapid products obviously. The GIM products from CAS and CODE and UQRG from UPC express the best performance are recommended to process ionospheric delay in the high-accuracy positioning.

GIMLi: Global Ionospheric total electron content model based on machine learning

EXtreme Gradient Boosting over Decision Trees (XGBoost or XGBDT) is a powerful tool to model a wide range of processes. We propose a new approach to create a global total electron content model, using machine-learning-based techniques, in particular, gradient boosting. The model is based on the Global Ionospheric Maps computed by Universitat Politecnica de Catalunya with a tomographic-kriging combined technique (UQRG). To reduce the problem complexity, we used empirical orthogonal functions (EOFs). The created model involves the first 16 spatial EOFs. For training and validation we used the 1998–2016 data sets, and the 2017 data as a test data set. To drive the model, we used the following features: (1) geomagnetic activity indexes (Kp, Ap, AE, AU, AL) and solar activity indexes (R, F10.7); (2) derivative values from these indexes such as the mean value and standard deviations within the last 12 h, last 11 days, and last 40 days; (3) day of the year (DOY); (4) averaged EOFs for given Kp and UT, and those for a given DOY and UT. The validation data set revealed the following hyperparameters for XGBoost learning: number of trees is 100, tree depth is 6, and learning rate is 0.1. Comparisons with the NeQuick2, Klobuchar, and GEMTEC models show that machine learning achieves higher accuracy for the 2017 test data set. The global averaged root-mean-square errors and mean absolute percentage errors were about 2.5 TECU and 19% for the nonlinear GIMLi-XGBDT model, about 4 TECU and 30–40% for NeQuick2, GEMTEC, and the linear model GIMLi-LM, and about 5.2 TECU and 73% for the Klobuchar model. A 4-fully-connected-layer artificial neural network provided a higher error (3.28 TECU and 27.7%) as compared to GIMLi-XGBDT. For all models mentioned, the error peaked in the equatorial anomaly region. The solar activity increase does not affect the error of the nonlinear GIMLi-XGBDT model. However, an increase in geomagnetic activity strongly affects that model.

Deep Neural Networks for Earthquake Detection and Source Region Estimation in North-Central Venezuela

ABSTRACTReliable earthquake detection algorithms are necessary to properly analyze and catalog the continuously growing seismic records. We report the results of applying a deep convolutional neural network, called UPC-UCV (Universitat Politecnica de Catalunya - Universidad Central de Venezuela), over single-station three-channel signal windows for P-wave earthquake detection and source region estimation in north-central Venezuela. The analysis is performed on a new dataset of handpicked arrivals of P waves from local events, named CARABOBO, built and made public for reproducibility and benchmarking purposes. The CARABOBO dataset consists of three-channel continuous data recorded by the broadband stations of the Venezuelan Foundation for Seismological Research in the region of 9.5°–11.5°N and 67.0°–69.0°W during the time period from April 2018 to April 2019. During this period, 949 earthquakes were recorded in that area, corresponding to earthquakes with magnitudes in the range from Mw 1.1 to 5.2. To estimate the epicentral source region of a detected event, the proposed network employs geographical distribution of the CARABOBO dataset into K clusters as a basis. This geographical partitioning is automatically performed by the k-means algorithm, and the optimality of the K-values for our dataset has been assessed using the elbow (K=5) and silhouette (K=3) methods. For target seismicity, the proposed network achieves 95.27% detection accuracy and 93.36% source region estimation accuracy, when using K=5 geographic clusters. The location accuracy slightly increases to 95.68% in the case of K=3 geographic partitions. The detection capability of this network has also been tested on the OKLAHOMA dataset, which compiles more than 2000 local earthquakes that occurred in this U.S. state. Without any modification, the proposed network yields excellent detection results when trained and evaluated on that dataset (98.21% accuracy; ConvNetQuake, fine-tuned for this dataset, achieves a 97.32% accuracy), corresponding to a totally different geographical region.

Assessment of Centre National d'Études Spatiales Real-Time Ionosphere Maps in Instantaneous Precise Real-Time Kinematic Positioning over Medium and Long Baselines.

Precise real-time kinematic (RTK) Global Navigation Satellite System (GNSS) positioning requires fixing integer ambiguities after a short initialization time. Originally, it was assumed that it was only possible at a relatively short distance from a reference station (<10 km), because otherwise the atmospheric effects prevent effective ambiguity fixing. Nowadays, through the use of VRS, MAC, or FKP corrections, the distances to the closest reference station have been increased to around 35 km. However, the baselines resolved in real time are not as far as in the case of static positioning. Further extension of the baseline requires the use of an ionosphere-weighted model with ionospheric delay corrections available in real time. This solution is now possible thanks to the Radio Technical Commission for Maritime (RTCM) stream of SSR corrections from, for example, Centre National d’Études Spatiales (CNES), the first analysis center to provide it in the context of the International GNSS Service. Then, ionospheric delays are treated as pseudo-observations that have a priori values from the CLK RTCM stream. Additionally, satellite orbit and clock errors are properly considered using space-state representation (SSR) real-time radial, along-track, and cross-track corrections. The following paper presents the initial results of such RTK positioning. Measurements were performed in various field conditions reflecting realistic scenarios that could have been experienced by actual RTK users. We have shown that the assumed methodology was suitable for single-epoch RTK positioning with up to 82 km baseline in solar minimum (30 March 2019) mid and high latitude (Olsztyn, Poland) conditions. We also confirmed that it is possible to obtain a rover position at the level of a few centimeters of precision. Finally, the possibility of using other newer experimental IGS RT Global Ionospheric Maps (GIMs), from Chinese Academy of Sciences (CAS) and Universitat Politècnica de Catalunya (UPC) among CNES, is discussed in terms of their recent performance in the ionospheric delay domain.

IGS real-time service for global ionospheric total electron content modeling

Benefiting from global multi-frequency and multi-constellation GNSS measurements provided by the experimental International GNSS real-time service (IGS RTS), a predicting-plus-modeling approach employed by Chinese Academy of Sciences (CAS) for the routine generation of real-time global ionospheric maps (RT-GIM) is first reported. Along with RT-GIMs generated by Universitat Politecnica de Catalunya (UPC), the quality of CAS and UPC RT-GIMs in IONEX format is assessed during a low soar activity period from September 2017 to December 2019. The differential slant total electron contents (dSTEC) derived from 50 GPS stations of the IGS and Jason-3 vertical TECs (VTEC) over the ocean are used as references. In comparison with different reference TECs, CAS and UPC RT-GIMs are approximately 1.7–4.9% and 8.6–12.5% worse than the respective post-processed GIMs CASG and UQRG, respectively. Using RTCM ionospheric data streams from CAS, Centre National d’Etudes Spatiales (CNES) and UPC, the first experimental IGS combined RT-GIM is generated and validated in actual real-time conditions. Compared to Jason-3 VTEC measurements available during the period of common availability, from October 2018 to April 2019, RT-GIM discrepancies present similar relative RMS errors, which are 33, 36, 36 and 38% for CNES, combined one, UPC and CAS, respectively. Aside from a better understanding of the influence of working in the original IONEX versus RTCM ionospheric formats, the update to a new experimental adaptation of RT strategy is highlighted by UPC, and the computation of multi-layer RT-GIM is emphasized by CAS in view of the inadequacy of single-layer ionospheric assumption in the presence of large latitudinal gradients.

Neural network based model for global Total Electron Content forecasting

We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

The Open Access Observatory

Open Access seems to have reached a flipping point and become a real option when researchers decide where to publish. However the figures provided when someone gives percentages are not clear because there is a lack of coincidence when defining open access. In this paper we would like to explain the project initiated by two Catalan universities, the Universitat de Barcelona (UB) and the Universitat Politècnica de Catalunya (UPC), which decided to use a common methodology to measure the different levels of open access in their institution. A methodology that can be used by any institution around the world to make visible their evolution and trends in the Open Access movement. Moreover, we also share a methodology to estimate the expenditure on fees to publish open access. In these two research institutions there is not a central system for processing those payments and therefore we need to make estimations in order to know how much we pay each year. Again, we think this methodology can be used worldwide. Both initiatives configure the initial work of what we called the Open Access Observatory, a project that was created aimed at providing and sharing evidences, methodologies and data in relation to open access publications.