Numerical Simulation of Dual Phase Vacuum Extraction for the Removal of Nonaqueous Phase Liquids in Subsurface: A Canadian Case Study
Notice bibliographique
Résumé
Abstract Dual-phase vacuum extraction (DPVE) is a popular cost-effective emerging technology to enhance remediation efficiency by recovering petroleum hydrocarbon from the subsurface. In order to improve the remediation efficiency, the complex processes and phase/component interactions in the remediation system should be clearly understood, and then the DPVE system can be properly designed and operated. In this paper, a numerical finite element simulation approach is proposed for analyzing and predicting the complex DPVE remediation system behavior. The developed simulator is applied to a petroleum-contaminated site in western Canada that is undergoing DPVE remediation, and the proposed approach can provide effective tools for evaluating remediation system performances and help to make decisions of site remediation and management actions. Introduction Leakage and spill of petroleum products from underground storage tanks and pipelines may result in many environmental concerns (1), and the hydrocarbon pollutants from this kind of leakage and spill have posed significant threats to groundwater resources across many petroleum-related sites in North America. The petroleum hydrocarbons that are light non-aqueous phase liquids (LNAPL) will travel downward under the force of gravity and capillarity upon leaking to the subsurface, and they may partition into one or more phases that include(2, 3):vapor phase within which the hydrocarbon exists in gaseous state or as volatile organic compounds (VOC) and this occurs primarily in the unsaturated zone;residual phase where the hydrocarbon is adsorbed to soil particles and trapped in the soil pores in unsaturated and saturated zones;aqueous phase where the hydrocarbon is dissolved in groundwater and soil moisture, andliquid phase where the hydrocarbon exists as free product that spreads over the water table. If enough volume of hydrocarbons is leaked, the above four phases are usually present, and the hydrocarbons may eventually accumulate on the groundwater table and then migrate along the natural hydraulic gradient until saturation and permeability become relatively small(4,5). Because of high toxicity of the hydrocarbon constituents, the industrial sites associated with subsurface LNAPLs contamination have evolved into greater concerns to governments, communities, and polluters themselves (6). Therefore, cleanup of these contaminated sites is necessary for protecting the groundwater resources and reducing risks to the communities, and all of the contaminants in their various phases should be essentially removed to meet the desired standards (7). During the past decades, much attention has been paid to the development and implementation of remediation technologies for contaminated soil and groundwater, and numerous technologies are available nowadays (8,9). Among various remediation measures for cleaning up such contaminations, dual-phase vacuum extraction (DPVE) is a popular cost-effective emerging technology to enhance remediation efficiency by recovering petroleum hydrocarbon from the subsurface (10). This technology applies a high vacuum system to remove various combinations of contaminated groundwater, free product, and hydrocarbon vapor from the subsurface, and the extracted liquids and vapor are collected and then treated above ground.
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Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».