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Record W6996230783

Risk to buried gas pipelines in landslide areas

2016· dissertation· en· W6996230783 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline transportServiceability (structure)LandslidePipeline (software)Instrumentation (computer programming)PipingNatural gas
DOInot available

Abstract

fetched live from OpenAlex

Natural Hazards are a risk to buried gas pipeline infrastructure, but these risks are difficult to assess and quantify. This can often lead to the risks not being properly identified by pipeline owners. The risk to pipelines within landslide areas are particularly difficult to assess given the complex nature of landslide movements and the soil-pipeline interaction mechanisms imposing loads on a pipeline. This thesis research examines the relationship between ground movements and strains/stresses in buried pipelines through field measured ground movements and in-situ measured pipe strains/stresses. The pipe stresses and strains are then used to estimate probability of pipeline failure and risk based on RBDA limit states approaches. Within Manitoba Hydro’s pipeline network, three at-risk landslide areas (riverbank and deep river valleys) were selected for detailed studies. A field investigation and monitoring program was undertaken to assess possible sources of load and stresses on pipelines. Soil, ground, and pipe instrumentation were installed at the sites and monitored over a four year period. Monitoring results identified soil near the pipeline does not freeze, and ground movements at valley sites are slow moving (<50 mm/year) landslides. The monitoring results also showed pipe stresses and behaviour were affected by backfilling, changes in river levels, thermal affects, soil-pipe relaxation, and ground movements. Pipe push tests were conducted in conjunction with FEM modelling to examine pipe adhesion and to possible explain the pipe behaviour observed. Several ultimate and serviceability limit states pipe failure modes were assessed using the measured pipe stresses. Statistical analysis was undertaken to calculate the probability of pipeline failure for the various limit states failure modes and compared against limit states targets for several scenarios (backfill loads, initial stress-state of the pipeline, other pipelines within Manitoba Hydro network). Overall, the probability of failure estimates were generally insignificant or low due to a postulated soil-pipe relaxation mechanism which is causing a repeated release in longitudinal pipe stresses as the landslide continues to accumulate ongoing ground movements. Three mechanisms are presented and discussed. The statistical analysis indicate pipelines within Manitoba Hydro’s network may exceed limit states targets for yielding and local buckling depending on the loading scenario and the class of the pipeline within the landslide area. The outcome of the research was used to develop a risk managements system to examine geotechnical hazards within Manitoba Hydro’s pipeline network. Specifically, risks associated with ground movements along natural slopes and at river crossings are examined within the system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.177
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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