Neural network modeling of Moroccan weather conditions effect on solar reflectors degradation

Guerguer, Mohamed; Naamane, Sanae; Raccurt, Olivier; Bouaouine, Hassan

doi:10.1063/5.0028933

Cited by 2 publications

(4 citation statements)

References 19 publications

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“…For example, in ISO 12944, "Coatings and varnishes-corrosion protection of steel structures by protective coating systems" [53], different environments were classified into three types of exposure: immersion, atmospheric and splash zone. Meteorological data are a common input that are needed for the development of models that aim to estimate coating performance and lifetime in-service condition [41][42][43]. In [50], a further subclassification was proposed (see Figure 1).…”

Section: Organic Coating Generalitiesmentioning

confidence: 99%

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A Review of In-Service Coating Health Monitoring Technologies: Towards “Smart” Neural-Like Networks for Condition-Based Preventive Maintenance

et al. 2022

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In line with the recent industrial trends of hyperconnectivity, 5G technology deployment, the Internet of Things (IoT) and Industry 4.0, the ultimate goal of corrosion prevention is the invention of smart coatings that are able to assess their own condition, predict the onset of corrosion and alert users just before it happens. It is of particular interest to tackle corrosion that occurs in non-accessible areas where human inspectors or handheld devices are useless. To accomplish this, a variety of technologies that are embedded or could potentially be embedded into the coatings are being developed to monitor coating condition, which are based, for instance, on the evolution of electrochemical or mechanical properties over time. For these technologies to be fully embedded into the coatings and work remotely, solutions are needed for connectivity and power supply. A paradigm shift from routine prescheduled maintenance to condition-based preventive maintenance could then become a reality. In this work, the technologies that enable the in-service monitoring of organic anticorrosion coatings were compiled. Soon, some of them could be integrated into the sensing elements of autonomous, connected neural-like networks that are capable of remotely assessing the condition of the anticorrosion protection of future infrastructures.

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Section: Organic Coating Generalitiesmentioning

confidence: 99%

“…This is known as atmospheric corrosion monitoring (ACM). Environmental parameters are the main inputs for these models and are often sensed using neural networks [41][42][43][44]. The majority of these models focus on the behaviour of metals and few target the modelling of coating degradation and lifetime expectancy [45,46].…”

Section: Introductionmentioning

confidence: 99%

A Review of In-Service Coating Health Monitoring Technologies: Towards “Smart” Neural-Like Networks for Condition-Based Preventive Maintenance

et al. 2022

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“…Spain, 4 weeks Presentation of a new device to measure soiling rates of a parabolic trough's tube receivers. Guerguer et al [72] Morocco, 3 years Neural network modeling can be trained to predict with high precision the reflectance loss. High wind speed and humidity are causes of high soiling rates.…”

Section: Wolfertstetter Et Al [71]mentioning

confidence: 99%

“…Intense, rare soiling events cause much more important reflectivity drops than the frequent, moderate dust deposition [49,62]. Many authors developed innovative methods to measure soiling rates [71][72][73][74][75]115]. Soiling of pyrheliometers causes erroneous evaluation of DNI in potential CSP sites [119].…”

Section: Figmentioning

confidence: 99%

Dust impact on concentrated solar power: A review

Zereg

Gama

Aksas³

et al. 2021

Environmental Engineering Research

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Many sites with high solar radiation face high dust loads that reduce energy generation by concentrated solar power plants. This review presents the attenuative impacts of atmospheric aerosols, as well as reflectivity losses due to soiling of solar reflectors, by covering both experimental investigations and numerical studies; along with presenting the theoretical background. The chemical nature of aerosols, and the physics of soiling and atmospheric extinction phenomena (scattering and absorption) are also reviewed. Suspended particles like aerosols result in atmospheric extinction of the solar radiation that reaches the concentrators, and the deposition of these particles on the solar reflectors provokes decreases up to 80% in their reflectivity, and thus enhances the cumulus of optical losses and the reduction of energy production. Even though dust affects both CSP and photovoltaics, CSP technologies suffer more losses. The impact of dust should be particularly considered during the planning phase of solar thermal plants, since its consequent reduction in energy output can be severe. While there have been multiple papers to review dust-related problems for PV, the present paper is the first literature review dedicated to the impact of soiling on concentrated solar power.

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Neural network modeling of Moroccan weather conditions effect on solar reflectors degradation

Cited by 2 publications

References 19 publications

A Review of In-Service Coating Health Monitoring Technologies: Towards “Smart” Neural-Like Networks for Condition-Based Preventive Maintenance

A Review of In-Service Coating Health Monitoring Technologies: Towards “Smart” Neural-Like Networks for Condition-Based Preventive Maintenance

Dust impact on concentrated solar power: A review

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