PI-MVS: MATHEMATICAL MODEL FOR UNCERTAINTY EVALUATION OF VIRTUAL INSTRUMENTS IN FLARE SYSTEMS AND AUDITABLE REPORTING TO THE NATIONAL PLATFORM «ECOSYSTEMA»

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Autore principale: Andrii Syrotenko
Natura: Recurso digital
Pubblicazione: Zenodo 2022
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author Andrii Syrotenko
author_facet Andrii Syrotenko
contents Abstract. This paper presents the PI-MVS (Physics-Informed Methane Verification System) methodology for continuous monitoring of industrial flare systems aimed at reducing the risk of unburned methane emissions and ensuring an auditable digital chain "measurement → interpretation → reporting". The approach is motivated by increasing pressure for climate verification and the diminishing "invisibility" of methane emissions due to satellite and remote sensing technologies, as well as by the operational gap between measured gas throughput and actual flare plume composition under wind-driven flame lift-off, over-steaming, and unstable low-flow regimes. The method integrates multispectral optical and thermal data, meteorological inputs, and process parameters, applies physically constrained combustion-regime reconstruction, and calculates DRE_calc as an estimate of methane destruction efficiency over a defined time interval. A dedicated data-quality loop assigns VALID/INVALID/ALARM statuses with reason codes to prevent erroneous decisions under degraded input conditions. The methodology incorporates a Decision Engine with event tagging (e.g., CH4_risk_event, soot_event, flameout_event) and generates a machine-readable Eco-Report with a qualified electronic signature and cryptographic hash references to locally stored video fragments, ensuring audit integrity without external video transfer. Alignment with national automated emission-monitoring logic positions PI-MVS as a "trust layer" for integration into the «Ecosystema» platform.
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publishDate 2022
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spellingShingle PI-MVS: MATHEMATICAL MODEL FOR UNCERTAINTY EVALUATION OF VIRTUAL INSTRUMENTS IN FLARE SYSTEMS AND AUDITABLE REPORTING TO THE NATIONAL PLATFORM «ECOSYSTEMA»
Andrii Syrotenko
flare system; methane; methane destruction efficiency; uncertainty evaluation; virtual measuring instrument; multispectral monitoring; sensor fusion; computer vision; environmental compliance; qualified e-signature; Ecosystema
Abstract. This paper presents the PI-MVS (Physics-Informed Methane Verification System) methodology for continuous monitoring of industrial flare systems aimed at reducing the risk of unburned methane emissions and ensuring an auditable digital chain "measurement → interpretation → reporting". The approach is motivated by increasing pressure for climate verification and the diminishing "invisibility" of methane emissions due to satellite and remote sensing technologies, as well as by the operational gap between measured gas throughput and actual flare plume composition under wind-driven flame lift-off, over-steaming, and unstable low-flow regimes. The method integrates multispectral optical and thermal data, meteorological inputs, and process parameters, applies physically constrained combustion-regime reconstruction, and calculates DRE_calc as an estimate of methane destruction efficiency over a defined time interval. A dedicated data-quality loop assigns VALID/INVALID/ALARM statuses with reason codes to prevent erroneous decisions under degraded input conditions. The methodology incorporates a Decision Engine with event tagging (e.g., CH4_risk_event, soot_event, flameout_event) and generates a machine-readable Eco-Report with a qualified electronic signature and cryptographic hash references to locally stored video fragments, ensuring audit integrity without external video transfer. Alignment with national automated emission-monitoring logic positions PI-MVS as a "trust layer" for integration into the «Ecosystema» platform.
title PI-MVS: MATHEMATICAL MODEL FOR UNCERTAINTY EVALUATION OF VIRTUAL INSTRUMENTS IN FLARE SYSTEMS AND AUDITABLE REPORTING TO THE NATIONAL PLATFORM «ECOSYSTEMA»
topic flare system; methane; methane destruction efficiency; uncertainty evaluation; virtual measuring instrument; multispectral monitoring; sensor fusion; computer vision; environmental compliance; qualified e-signature; Ecosystema
url https://doi.org/10.5281/zenodo.18877576