Salinity effect on the corona onset for a 765 kV AC substation connector

Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects.Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects.Postprint (published version

Salinity effect on the corona onset for a 765 kV AC substation connector

Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects.Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects

Salinity effect on the corona onset for a 765 kV AC substation connector

Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects.Outdoor substations placed in coastal areas are affected by saline environments. In the technical literature it is found extensive information regarding insulations problems in presence of saline environments [1]. The accumulation of salts and other contaminants promotes the onset of partial discharges on the devices subjected to very high voltages. Insulators are also affected by this phenomenon. While rainfall has a cleaning effect on the insulator surface, humidity enhances the corrosion effect and degrades the performance of insulation [2], favouring onset conditions for partial discharge. Corrosion due to saline environments or dirt increases the roughness of the insulator surface, thus facilitating the appearance of partial discharges [3]. It is well known that the air pollution has a great impact on metals corrosion. Chloride ions are common in coastal environments, because seawater acts as a source of air mineralization. Deposition of chloride ions on metal surfaces intensifies metallic corrosion, thus degrading the conductor surface [4]. In this work the behaviour of a 765 kVRMS AC (line-to-line voltage) outdoor substation connector is analyzed when operating under both dry conditions and under wet saline environments by means of three-dimensional finite elements simulations (3D-FEM). FEM simulations show that the electric field strength in the connector surroundings does not exceed the electric breakdown strength for air under clean and dry atmospheric conditions when energized at its rated voltage, 765 kVRMS AC (line-to-line). These results are corroborated by means of experimental measurements carried out in a high-voltage laboratory. Both, the laboratory tests and the 3D-FEM simulations performed in this study concluded that the corona onset voltage is approximately 980 kVRMS AC (line-to-line voltage). Additionally, 3D-FEM simulations allow detecting the connector weakest points regarding to electrical stress. Hence, this software allows redesigning the connector geometry to optimize its performance, thus minimizing the corona occurrence risk and their associated unwanted effects. Additionally, FEM simulations performed under a saline atmosphere were carried out by including a thin conductive saline moisture layer acting as a wetting film on the connector surface. Results revealed that saline environments worsen the connector behaviour, thus favouring corona onset conditions and their related effects

Aggressiveness-related behavioural types in the pearly razorfish

Behavioural types (i.e., personalities or temperament) are defined as among individual differences in behavioural traits that are consistent over time and ecological contexts. Behavioural types are widespread in nature and play a relevant role in many ecological and evolutionary processes. In this work, we studied for the first time the consistency of individual aggressiveness in the pearly razorfish, Xyrichtys novacula, using a mirror test: a classic method to define aggressive behavioural types. The experiments were carried out in semi-natural behavioural arenas and monitored through a novel Raspberry Pi-based recording system. The experimental set up allowed us to obtain repeated measures of individual aggressivity scores during four consecutive days. The decomposition of the phenotypic variance revealed a significant repeatability score (R) of 0.57 [0.44–0.60], suggesting high predictability of individual behavioural variation and the existence of different behavioural types. Aggressive behavioural types emerged irrespective of body size, sex and the internal condition of the individual. Razorfishes are a ubiquitous group of fish species that occupy sedimentary habitats in most shallow waters of temperate and tropical seas. These species are known for forming strong social structures and playing a relevant role in ecosystem functioning. Therefore, our work provides novel insight into an individual behavioural component that may play a role in poorly known ecological and evolutionary processes occurring in this species.This work was carried out as part of the research project Cronofish (AAEE 101/2017) funded by Balearic Islands Government. In addition, this project also received financing from the CLOCKS project from the Spanish Government (PID2019-104940GA-I00). Martina Martorell-Barceló was supported by an FPI predoctoral fellowship (ref. FPI/2167/2018) from the Balearic Islands Government General Direction of Innovation and Research. Josep Alós was supported by a Ramon y Cajal Grant (grant no. RYC2018-024488-I) and the intramural research project JSATS (grant no. PIE 202030E002) funded by the Spanish Ministry of Science and Innovation, and the Spanish National Research Council

Measuring inter-individual differences in behavioural types of gilthead seabreams in the laboratory using deep learning

Deep learning allows us to automatize the acquisition of large amounts of behavioural animal data with applications for fisheries and aquaculture. In this work, we have trained an image-based deep learning algorithm, the Faster R-CNN (Faster region-based convolutional neural network), to automatically detect and track the gilthead seabream, Sparus aurata, to search for individual differences in behaviour. We collected videos using a novel Raspberry Pi high throughput recording system attached to individual experimental behavioural arenas. From the continuous recording during behavioural assays, we acquired and labelled a total of 14,000 images and used them, along with data augmentation techniques, to train the network. Then, we evaluated the performance of our network at different training levels, increasing the number of images and applying data augmentation. For every validation step, we processed more than 52,000 images, with and without the presence of the gilthead seabream, in normal and altered (i.e., after the introduction of a non-familiar object to test for explorative behaviour) behavioural arenas. The final and best version of the neural network, trained with all the images and with data augmentation, reached an accuracy of 92,79% ± 6.78% [89.24–96.34] of correct classification and 10.25 ± 61.59 pixels [6.59-13.91] of fish positioning error. Our recording system based on a Raspberry Pi and a trained convolutional neural network provides a valuable non-invasive tool to automatically track fish movements in experimental arenas and, using the trajectories obtained during behavioural tests, to assay behavioural types.This project was funded by the research project FISHOBES (grant no. CTM2017-91490-EXP) funded by the Spanish Ministry of Science and Innovation (MICINN). Marco Signaroli was suppoerted by a “Ayudas para contratos predoctorales” (grant no. PRE2020-095580) funded by MCIN/AEI /10.13039/501100011033 and the FSE “invierte en tu futuro”. Josep Alós received funding from a Ramon y Cajal Grant (grant no. RYC2018-024488-I), the CLOCKS I+D+I project (grant no. PID2019-104940GA-I00) and JSATS PIE project (grant no. PIE202030E002) funded by MCIN/AEI/10.13039/501100011033 and the FSE “invierte en tu futuro”

Aggressiveness-related behavioural types in the pearly razorfish [dataset]

Los datos fueron generados manualmente a través de la visualización de videos de los experimentos. Fueron introducidos en RStudio Team (2020), donde se analizaron para la obtención de los resultados.-- este conjunto de datos es original de este trabajo. No se ha usado datos de estudios preliminares.-- Datos recogidos en experimentos realizados en el Laboratorio de Investigaciones Marinas y Acuicultura (LIMIA) en Mallorca. Los individuos experimentales fueron capturados en la Bahía de Palma, Mallorca.This data set is supplementary material for the article "Types of behaviour related to aggressiveness in pearlescent fish". Animal personality has a very relevant implication in a multitude of eco-evolutionary processes. It is a topic very approached in freshwater fish, not so in marine species, because its captivity is a challenge to reproduce its natural habitat. this is the first evidence of behavioural traits in the pearly razorfish. For this, we designed experiments in the laboratory, where the experimental individuals were subjected to the mirror test—a widely used test to determine each individual's aggressiveness. By not recognizing their reflection in the mirror, fish perceive their reflection as the intrusion of another individual into their territory. Thanks to these experiments, we were able to determine each individual's aggressiveness score, finding significant differences between individuals. Differences found regardless of height, sex or individual condition. These findings suggest that this species' aggressiveness may have a genetic origin, as has been demonstrated in other species.Este trabajo ha recibido financiación del Proyecto CLOCKS I + D + i (subvención no. PID2019-104940GA-I00) financiado por el MICINN y la Agencia Estatal de Investigación, y del proyecto de investigación intramuros JSATS (subvención no. PIE202030E002) financiado por la MICINN y Consejo Nacional de Investigaciones Científicas (CSIC). Martina Martorell-Barceló contó con una beca pre doctoral FPI (ref. FPI / 2167/2018) de la Dirección General de Innovación e Investigación del Gobierno de las Illes Balears. Josep Alós ha recibido una Beca Ramón y Cajal (beca nº. RYC2018-024488-I) financiada por el Ministerio de Ciencia e Innovación (MICINN). Margarida Barcelo-Serra fue apoyada por una MSCA-IF (subvención núm. WildFishGenes-891404).N

Disparate behavioral types in wild and reared juveniles of gilthead seabream

[Methods used for collection/generation of data] Standardized behavioral tests with continuous recording was provided by a camera attached to each arena controlled by a Raspberry Pi 3 system. All the behavioral tests were analyzed using a trained deep learning algorithm.[Methods for processing the data] Deep learning algorithm and R-Studio.The tests started with wild individuals on March 11th, 2019 and ended on April 23rd, 2019. Reared individuals were tested starting on July 19th, 2019 and ending on August 22nd, 2019.Project funded by the research project FISHOBES (grant no. CTM2017-91490-EXP) funded by the Spanish Ministry of Science and Innovation (MICINN). Marco Signaroli was supported by a “Ayudas para contratos predoctorales” (grant no. PRE2020-095580) funded by MCIN/AEI /10.13039/501100011033 and the FSE “invierte en tu futuro”. Aina Pons was supported by an FPI predoctoral fellowship (ref. FPI/2269/2019) from the Balearic Islands Government General Direction of Innovation and Research. Josep Alós received funding from the CLOCKS I+D+I project (grant no. PID2019-104940GA-I00) and the JSATS PIE project (grant no. PIE202030E002) funded by MCIN/AEI/10.13039/501100011033 and the FSE “invierte en tu futuro”.Peer reviewe

OCEANS OF BIG DATA AND ARTIFICIAL INTELLIGENCE

International audienceThe ocean is a fundamental element for the Earth and for the wellbeing of human societies. It influences weather and climate, impacting sectors such as marine ecosystems, economy, tourism, and human health. Urgent actions are demanded to help in understanding and managing the ocean in a multidisciplinary and integrated way. Here we present the major ocean research challenges for the next decades, CSIC leadership and resources needed. In this context, this chapter specifically addresses big data and AI