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Enregistrement W2296480936

A Numerical Interpretation Model for the Dipole Flow and Reactive Tracer Test

2007· dissertation· en· W2296480936 sur OpenAlexaboutno aff
Blythe Reiha

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2007
Typedissertation
Langueen
DomaineEngineering
ThématiqueNuclear Engineering Thermal-Hydraulics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTRACERInterpretation (philosophy)Test (biology)Flow (mathematics)MechanicsComputer scienceGeologyPhysicsNuclear physicsProgramming language
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In order to protect public health and the natural environment, regulatory agencies such as the U.S. Environmental Protection Agency (USEPA) and the Ontario Ministry of the Environment (MOE) have developed a variety of clean-up programs to remediate contaminated sites. Before a remedial strategy can be implemented, physical, chemical and biological information of the site must be characterized so that an appropriate remedial approach can be selected. Problems exist with common characterization applications such as non-representative sample collection, time-consuming and costly testing, and loss of sample integrity due to transport. The success of the dipole flow test (DFT) and dipole flow tracer test (DFTT) indicate the potential for identifying a wide range of physical aquifer characteristics through in situ techniques; this has led to the development of the dipole flow reactive tracer test (DFRTT), which can be used to identify sorption and degradation characteristics in addition to those characteristics already identifiable by the DFT and DFTT. The DFRTT contains numerous advantages including the ability to inject a variety of reactive tracers using pulse or continuous injection, it can be used at multiple locations and depths across a site, and it is cost-effective. \n \nThe focus of this thesis was to develop and validate an efficient numerical framework for the reactive-transport component of the DFRTT interpretation model so that it could be used to simulate a variety of reactive tracers. The model will then be calibrated to match the resulting DFRTT field breakthrough curves (BTCs) so that certain aquifer property values can be obtained. \n \nThe comprehensive-reactive transport model (CRTM) was developed to solve the advective-dispersive-reactive equation (ADRE) using a streamline-oriented control volume (CV) mesh, to minimize the introduction of numerical dispersion (due to the dipole’s rapidly converging and diverging flow field). In order to reduce computational effort, the ADRE was decoupled using operator-splitting techniques (OS) and the resulting partial differential equation for the transport component was solved using a finite volume approach, while the fourth-order form of Runge-Kutta was used to solve the resulting ordinary differential equation of the reactive component. Four OS techniques were implemented to decouple the ADRE; two of the techniques were iterative, while the other two were non-iterative. The use of iterative OS techniques enabled the introduction of a flux corrected transport (FCT) scheme (in addition to the commonly used central differencing scheme (CDS) and upwind differencing scheme (UDS)), for solving the transport portion of the ADRE. \n \nThe CRTM was validated against a current “off-the-shelf” model, MODFLOW/MT3DMS. The resulting simulations indicated that the CRTM and MODFLOW/MT3DMS BTCs compared well for a conservative, decaying (first-order), and sorbing (linear sorption isotherm) tracer under specific conditions. However, MODFLOW/MT3DMS illustrated signs of failure when a large flow rate or a small longitudinal dispersivity coefficient was employed. It was concluded that MODFLOW/MT3DMS was unable to handle the rapidly converging and diverging dipole flow field, and that it was necessary to develop/utilize a dipole specific model for modelling the DFRTT application. \n \nAnalysis of the three advective schemes indicated that CDS was an inappropriate method for the dipole configuration used in the investigation (due its non-monotone solutions), and that the UDS, although unconditionally monotone, produced excessive numerical dispersion. The FCT scheme had the benefits of both CDS and UDS; however, it was computationally slower than the UDS due to its iterative nature. \n \nExamination of the OS techniques indicated that in most cases there were no significant differences between any of the OS methods; however if a prominent sink term was utilized, the iterative techniques were deemed superior over the non-iterative techniques because of their ability to correct mass depletion. It was also determined that because of FCTs second-order accuracy, the OS techniques employing FCT had lower errors than those which did not. \n \nThe CRTM was used to design a DFRTT biodegradation experiment under Canadian Forces Base (CFB) Borden conditions. Dipole parameters were altered so that a dipole configuration could be recommended for field testing. It was determined that a decent zone of influence aquifer volume (~ 65 m3) with a detectable BTC tail occuring between 2 and 3 days required a dipole length = 0.8 m, and a half-chamber length = 0.15 to 0.30 m. The oxidation of toluene by aerobic bacteria present within the Borden aquifer was also simulated. The purpose of these simulations was to obtain a detectable substrate BTC so that experimental parameters could be recommended for conducting a field experiment. To achieve a detectable substrate BTC the following recommendations were made: (i) sampling events should occur once every 1 to 2 hours (if possible) so that the changes in effluent concentration can be documented accurately; (ii) dipole parameters from Section 5.1 with a standard 2” well should be employed; (iii) a large substrate concentration should be utilized (> 4.0 mg/L); (iv) a flow rate of 1x10-4 m3/s should be used; and (v) an injection duration of 2 hours should be applied. As long as the field substrate BTC is measurable then Monod kinetics parameters can be estimated after a field and CRTM BTC comparison; this enables us to understand the aquifer’s biodegradation potential (for remedial design purposes).

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil0,049

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0020,001
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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 Opus0,006
Tête enseignante GPT0,195
Écart entre enseignants0,189 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
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

Citations9
Publié2007
Routes d'admission1
Résumé présentoui

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