Feasibility modeling of passive soil vapor extraction
Bibliographic record
Abstract
Passive soil vapor extraction (PSVE) is a soil remediation process that uses ambient meteorological conditions to accomplish gas well pumping. Passive soil vapor extraction wells use simple unpowered wellheads in place of vacuum pumps or blowers. They can be used for extraction or injection pumping and can reduce the complexity and cost of either. The innate "pulse-pumping" pattern of PSVE may also help overcome mass transfer resistances within the soil. However, the meteorological conditions that drive PSVE are strongly random in magnitude and duration and produce flows that are lower than pumped soil vapor extraction (SVE). Although PSVE had been successfully field demonstrated, uncertainty about well yields and design procedures has hindered application. This manuscript presents the results of PSVE feasibility modeling. Analysis is presented to illustrate that, under appropriate conditions, PSVE can yield useful well flows. Transient gas flow analysis is required to account for meteorological boundary conditions that impact the domain on relatively fine time scales. Analysis is also presented to illustrate the impacts that non-steady flow conditions can have on contaminant mass transport. Results show that under appropriate conditions PSVE could be competitive with conventional pumped vapor extraction. Extraction rates will be lower, but may be achieved at significantly lower cost. Key words: vapor extraction, remediation, passive pumping, mass transport modeling, transient boundary conditions, feasibility analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".