Deep Learning-Based Fault Detection and Isolation in Solar Plants for Highly Dynamic Days

ICCAD'22: 2022- 6th International Conference on Control, Automation and Diagnosis, Lisbon, Portugal, July 13-15, 2022Solar plants are exposed to numerous agents that degrade and damage their components. Due to their large size and constant operation, it is not easy to access them constantly to analyze possible failures on-site. It is, therefore, necessary to use techniques that automatically detect faults. In addition, it is crucial to detect the fault and know its location to deal with it as quickly and effectively as possible. This work applies a fault detection and isolation method to parabolic trough collector plants. A characteristic of solar plants is that they are highly dependent on the sun and the existence of clouds throughout the day, so it is not easy to achieve methods that work well when disturbances are too variable and difficult to predict. This work proposes dynamic artificial neural networks (ANNs) that take into account past information and are not so sensitive to the variations of the plant at each moment. With this, three types of failures are distinguished: failures in the optical efficiency of the mirrors, flow rate, and thermal losses in the pipes. Different ANNs have been proposed and compared with a simple feedforward ANN, obtaining an accuracy of 73.35%.European Research Council 10.13039/50110000078

A deep learning-based strategy for fault detection and isolation in parabolic-trough collectors

Solar plants are exposed to the appearance of faults in some of their components, as they are vulnerable to the action of external agents (wind, rain, dust, birds …) and internal defects. However, it is necessary to ensure a satisfactory operation when these factors affect the plant. Fault detection and diagnosis methods are essential to detecting and locating the faults, maintaining efficiency and safety in the plant. This work proposes a methodology for detecting and isolating faults in parabolic-trough plants. It is based on a three-layer methodology composed of a neural network to obtain a preliminary detection and classification between three types of fault, a second stage analyzing the flow rate dynamics, and a third stage defocusing the first collector to analyze thermal losses. The methodology has been applied by simulation to a model of the ACUREX plant, which was located at the Plataforma Solar de Almería. The confusion matrices have been obtained, with accuracies over 80% when using the three layers in a hierarchical structure. By forcing all the three layers, the accuracies exceed 90%.Unión Europea - Horizonte 2020 No 789 05

Electron and ion stagnation at the collision front between two laser produced plasmas

We report results from a combined optical interferometric and spectrally resolved imaging study on colliding laser produced aluminium plasmas. A Nomarski interferometer was used to probe the spatio-temporal distribution of electron densities at the collision front. Analysis of the resulting interferograms reveals the formation and evolution of a localized electron density feature with a well-defined profile reminiscent of a stagnation layer. Electron stagnation begins at a time delay of 10 ns after the peak of the plasma generating laser pulse. The peak electron density was found to exceed 10^19 cm^−3 and the layer remained well defined up to a time delay of ca 100 ns. Temporally and spectrally resolved optical imaging was also undertaken, to compare the Al^+ ion distribution with that of the 2D electron density profile. This revealed nascent stagnation of singly charged ions at a delay time of 20 ns. We attribute these results to the effects of space charge separation in the seed plasma plumes

Prevalence of metabolic syndrome in scholars from Bucaramanga, Colombia: a population-based study

Background: Obesity and metabolic syndrome are strongly associated with type 2 diabetes mellitus and cardiovascular diseases, thus the increasing trend in their prevalence among children and adolescents from developing countries requires a further understanding of their epidemiology and determinants. Methods and design: A cross-sectional study was designed to determine the prevalence of metabolic syndrome among 6–10 year-old children from Bucaramanga, Colombia. A two-stage random-cluster (neighborhoods, houses) sampling process was performed based on local city maps and local statistics. The study involves a domiciliary survey; including a comprehensive sociodemographic, nutritional and physical activity characterization of the children that participated in the study, followed by a complete clinical examination; including blood pressure, anthropometry, lipid profile determination, fasting glucose and insulin levels. The prevalence of metabolic syndrome will be determined using definitions and specific percentile cut-off points for this population. Finally, the association between components of metabolic syndrome and higher degrees of insulin resistance will be analyzed through a multivariable logistic regression model. This study protocol was designed in compliance with the Helsinki declaration and approved by the local ethics board. Consent was obtained from the children and their parents/guardians. Discussion: A complete description of the environmental and non-environmental factors underlying the burden of metabolic syndrome in children from a developing country like Colombia will provide policy makers, health care providers and educators from similar settings with an opportunity to guide primary and secondary preventive initiatives at both individual and community levels. Moreover, this description may give an insight into the pathophysiological mechanisms mediating the development of cardio-metabolic diseases early in life

Tandem Repeat DNA provides many cytological markers for hybrid zone analysis in two subspecies of the grasshopper chorthippus parallelus

Recent advances in next generation sequencing (NGS) have greatly increased our understanding of non-coding tandem repeat (TR) DNA. Here we show how TR DNA can be useful for the study of hybrid zones (HZ), as it serves as a marker to identify introgression in areas where two biological entities come in contact. We used Illumina libraries to analyse two subspecies of the grasshopper Chorthippus parallelus, which currently form a HZ in the Pyrenees. We retrieved a total of 152 TR sequences, and used fluorescent in situ hybridization (FISH) to map 77 families in purebred individuals from both subspecies. Our analysis revealed 50 TR families that could serve as markers for analysis of this HZ, using FISH. Differential TR bands were unevenly distributed between chromosomes and subspecies. Some of these TR families yielded FISH bands in only one of the subspecies, suggesting the amplification of these TR families after the geographic separation of the subspecies in the Pleistocene. Our cytological analysis of two TR markers along a transect of the Pyrenean hybrid zone showed asymmetrical introgression of one subspecies into the other, consistent with previous findings using other markers. These results demonstrate the reliability of TR-band markers for hybrid zone studie

Behavior of mixed Chlorophyceae cultures under prolonged dark exposure. Respiration rate modeling

[EN] The behavior of three different microalgal cultures, when exposed for a long period (>48 h) to dark conditions, was studied with a methodology based on respirometry. The cultures were transferred to darkness and the oxygen evolution in the reactors was monitored after successive air injections. Several sequential oxygen uptake rates were thus calculated and a respiration constant, assuming a first order decay of a fraction of the biomass, was obtained by calibration. Initial specific oxygen uptake rates were in the range of 0.9 5.1 mg O2 g TSS−1 h−1 and dark respiration constants in the range of 0.005 0.018 h−1.This research work has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO, CTM2011-28595-C02- 01/02) jointly with the European Regional Development Fund (ERDF) which are gratefully acknowledged. This research was also supported by the Spanish Ministry of Science and Innovation via a pre doctoral FPU fellowship to the first author (AP2009-4903). The authors would also like to thank the water management entities of the Generalitat Valenciana (EPSAR).Ruiz Martínez, A.; Serralta Sevilla, J.; Seco Torrecillas, A.; Ferrer, J. (2016). Behavior of mixed Chlorophyceae cultures under prolonged dark exposure. Respiration rate modeling. Ecological Engineering. 91:265-269. https://doi.org/10.1016/j.ecoleng.2016.02.025S2652699

Transposable element landscapes illuminate past evolutionary events in the endangered fern Vandenboschia speciosa

Vandenboschia speciosa is an endangered tetraploid fern species with a large genome (10.5 Gb). Its geographical distribution is characterized by disjoined tertiary flora refuges, with relict populations that survived past climate crises. Here we analyze the transposable elements (TEs) and found that they comprise about 76% of the V. speciosa genome, thus being the most abundant kind of DNA sequences in this gigantic genome. V. speciosa genome is composed of 51% and 5.6% of Class I and Class II elements, respectively. LTR retrotransposons were the most abundant TEs in this species (at least 42% of the genome), followed by non-LTR retrotransposons that constituted at least 8.7% of the genome of this species. We introduce an additional analysis to identify the nature of non-annotated elements (19% of the genome). A BLAST search of the non-annotated contigs against the V. speciosa TE database allowed determining the identity of almost half of them, which were most likely diverged sequence variants of the annotated TEs. In general, TE composition in V. speciosa resembles TE composition in seed plants. In addition, repeat landscapes revealed three episodes of amplification for all TEs, most likely due to demographic changes associated to past climate crises