Numerical Simulation of Dual Phase Vacuum Extraction for the Removal of Nonaqueous Phase Liquids in Subsurface: A Canadian Case Study
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".