Allowable Drill Rig Wheel Loads on Frozen Muskeg
Bibliographic record
Abstract
Abstract Considerable expanses of Alaska, Canada and Russia have unfrozen muskeg terrain. A broad study was undertaken to determine the seasonally frozen thickness of muskeg required to support heavy drill vehicle loads. The study included field testing and collection of frozen muskeg samples for laboratory testing to assess the engineering properties of the frozen muskeg, insitu testing of the muskeg and underlying mineral soils, and numerical modeling of a frozen muskeg layer subject to loading by heavy drilling equipment. This paper reports on the numerical modeling to assess the wheel load capacity of relatively thin frozen layers overlying a weak (non-zero strength) unfrozen stratum. The wheel load capacity of the frozen muskeg was assessed considering several failure mechanisms. For the shear failure mode a finite element model was used to predict soil and muskeg deformation and assess the factor of safety against failure. For a punching shear failure, the factor of safety against failure was estimated by a closed-form solution. The results are presented as a series of graphs of factor of safety versus frozen layer thickness for a number of average frozen layer strengths. A single loading scenario was considered, consisting of a loaded drill rig with a gross weight of 62,000kg. Introduction Large drilling and support vehicles can often exceed 50,000 kg in gross vehicle weight and require special permits to travel over some roads during parts of the year. In many areas the travel surface to drilling or well sites consists of soft and weak soils or organic layers that restrict access by all vehicle travel to winter periods when the ground is frozen. The capacity of the soil or organic layer to support vehicles is notionally a function of the thickness and strength of the surface layer and the mass of the vehicle. If the access requirements to this terrain can be addressed in a rational manner then operators can undertake better planning and allocation of equipment and resources. This paper documents a study to determine the required seasonally frozen thickness of muskeg required to support heavy drill vehicle loads. The broader study included field testing and collection of frozen muskeg samples for laboratory testing to assess the engineering properties of the frozen muskeg, insitu testing of the muskeg and underlying mineral soils, and numerical modeling of a frozen muskeg layer subject to loading by heavy vehicles. The goal of the overall study was to develop a field assessment method to determine the potential load carrying capacity of frozen organic soils such as muskegs. The study assumed that the frozen muskeg was underlain by a material with some low, but non-zero, shear strength.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
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; both teacher heads agree on what is shown here.
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".