Software Endorse 1.0

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F22%3A00010998" target="_blank" >RIV/46747885:24220/22:00010998 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68145535:_____/22:00577993

Výsledek na webu

<a href="https://github.com/GeoMop/endorse" target="_blank" >https://github.com/GeoMop/endorse</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Software Endorse 1.0

Popis výsledku v původním jazyce

The package provides stochastic simulation tools for the characterization of the safety of the excavation damage zone of a deep geological repository of radioactive waste. The safety is described by the safety indicator – the maximum of a simulated concentration on the boundary of the computational domain. The Darcy flow and transport of the contaminant are calculated by the [Flow123d](https://flow123d.github.io/) simulator. The simulator uses the discrete fracture-matrix (DFM) approach that combines a network of (random) fractures and a 3D continuum. The safety indicator is considered a random variable dependent on the random fracture network and uncertainties in other parameters of the model. The stochastic properties (mean, variance, …) of the safety indicator are estimated using the Multilevel Monte Carlo (MLMC) method. The whole stochastic calculation is executed through the endorse-mlmc script. The hydraulic conductivity and porosity on the excavation disturbed zone (EDZ) are the key parameters affecting the safety indicator. These parameters are substantially increased in the vicinity of the tunnels of the repository compared to the intact rock, partly due to damage attributed directly to the excavation method and partly due to deformations caused by changes in the stress field. However, the response to the stress changes is not immediate due to the presence of water. The continuous measurement of the pore pressure close to the excavated tunnel is used to determine the parameters of a poroelastic problem describing the relaxation of the EDZ. The Bayes inversion is used to obtain modified fields of hydraulic conductivity and porosity on the EDZ as the set of random samples. These can later be used as the input to the stochastic prediction of the safety indicator. The Bayes inversion is realized through the endorse-bayes script.

Název v anglickém jazyce

Software Endorse 1.0

Popis výsledku anglicky

The package provides stochastic simulation tools for the characterization of the safety of the excavation damage zone of a deep geological repository of radioactive waste. The safety is described by the safety indicator – the maximum of a simulated concentration on the boundary of the computational domain. The Darcy flow and transport of the contaminant are calculated by the [Flow123d](https://flow123d.github.io/) simulator. The simulator uses the discrete fracture-matrix (DFM) approach that combines a network of (random) fractures and a 3D continuum. The safety indicator is considered a random variable dependent on the random fracture network and uncertainties in other parameters of the model. The stochastic properties (mean, variance, …) of the safety indicator are estimated using the Multilevel Monte Carlo (MLMC) method. The whole stochastic calculation is executed through the endorse-mlmc script. The hydraulic conductivity and porosity on the excavation disturbed zone (EDZ) are the key parameters affecting the safety indicator. These parameters are substantially increased in the vicinity of the tunnels of the repository compared to the intact rock, partly due to damage attributed directly to the excavation method and partly due to deformations caused by changes in the stress field. However, the response to the stress changes is not immediate due to the presence of water. The continuous measurement of the pore pressure close to the excavated tunnel is used to determine the parameters of a poroelastic problem describing the relaxation of the EDZ. The Bayes inversion is used to obtain modified fields of hydraulic conductivity and porosity on the EDZ as the set of random samples. These can later be used as the input to the stochastic prediction of the safety indicator. The Bayes inversion is realized through the endorse-bayes script.

Druh

R - Software

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/TK02010118" target="_blank" >TK02010118: Predikce vlastností EDZ s vlivem na bezpečnost a spolehlivost hlubinného úložiště radioaktivního odpadu.</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Interní identifikační kód produktu

Endorse

Technické parametry

See documantation at https://github.com/GeoMop/endorse.

Ekonomické parametry

cost savings resulting from modeling capabilities.

IČO vlastníka výsledku

46747885

Název vlastníka

Technická univerzita v Liberci