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Enregistrement W6963093609 · doi:10.17635/lancaster/thesis/2077

Use of Geoelectrical Techniques with Numerical Modelling for Surveying and Monitoring of Engineered Water Retaining Structures

2023· article· en· W6963093609 sur OpenAlexaboutno aff

Notice bibliographique

RevueLancaster EPrints (Lancaster University) · 2023
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueGeophysical and Geoelectrical Methods
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésElectrical resistivity tomographyLeveeEmbankment damNumerical modelingNumerical modelsWork (physics)GroundwaterGround-penetrating radarElectrical resistivity and conductivity

Résumé

récupéré en direct d'OpenAlex

Water retaining structures are societally and economically important barriers which degrade through various erosional processes over time. Walkover surveys and geotechnical investigations are traditionally used to examine such structures but are limited by a lack of knowledge of internal structure. Near-surface geophysics can provide comprehensive information about the internal structure of embankments, and several techniques exist which can survey and monitor water retaining structures. One such technique is electrical resistivity tomography (ERT), where the resistivity profile of the ground can be linked to moisture content, porosity, and composition, making it a useful tool for use in detecting defects and changes in ground conditions within water retaining structures. However, several uncertainties exist with ERT for use on embankments. A key problem is whether results will be impacted by a 3D effect, where off-line features influence resistivities in the inversion.Such features may be the water body itself, or complex engineering structures within the barrier. This thesis explores the impact of a 3D effect arising from the water body and structural geometry. The work was undertaken using synthetic numerical modelling of an embankment in a tidal setting and a fluctuating water level and resistivity, which was then compared to realERT data. Further synthetic numerical modelling of the Mactaquac dam, Canada, was used as a case study assessing the influence of a large concrete structure within the dam on ERT data. The study also examined the effect of resistivity variation in the headpond of the dam through time. Comparisons between 2D and 3D inversions were also assessed to determine the possibility of 3D inversions mitigating any 3D effects. This was undertaken for sites at Bartley Dam, Birmingham, UK and Paull Holme Strays, Yorkshire, UK. The Bartley Dam case study utilised time-lapse ERT to determine the value of 3D inversions over 2D inversions in a monitoring scheme and to identify whether 3D or 2D inversions could adequately identify water seepage present with changes in ground conditions. The Paull Holme Strays case study focussed on use of crosslines in a 3D inversion for a tidal embankment and compared outcomes to a 2D inversion without use of crosslines. The results of the research shows that 3D effects are likely to be significant when undertaking ERT surveys of a water retaining structure, e.g. artefacts induced by a river with changing water level and resistivity, in addition to the impact of engineering structures that may be present in the embankment. Analysis of time-lapse ERT data at the at Mactaquac Dam site has revealed that changing headpond resistivity can create compensatory effects in an ERT data inversion. No seepage pathways could be reliably identified in time-lapse analysis of Bartley Dam with 2D inversions, likely because of 3D effects and sensitivity issues, whereas 3D inversions had more reliable evidence of seepage pathways. However, analysis of Paull Holme Strays showed that when a large proportion of the measurements have been filtered, there might be artefacts induced by another electrode array along the crest. However, use of crosslines enhanced the ability for a 3D inversion to reduce 3D effects at Paull Holme Strays. This research has shown that 3D effects can be detrimental to ERT surveys, particularly in 2D inversions. However, 3D inversions can mitigate the effect where differences in data filtering between lines are minimal. For further reduction in the impact of the 3D effect it is recommended that smaller crosslines are used between the major electrode lines. Also, results should be compared with geological, geotechnical and hydrological information for understanding the reliability of the inversion. There is a need for further exploration of the impacts of 3D effects on ERT in other water retaining structures and environments, as well as undertaking more comprehensive studies into dynamic changes within embankments and how they impact the 3D effect. By incorporating dynamic change into a synthetic model, a greater understanding of how 3D effects can impact ERT surveys of water retaining structures can be made, especially for timelapse ERT.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,161
Score d'incertitude au seuil0,431

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,061
Tête enseignante GPT0,226
Écart entre enseignants0,165 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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