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Record W2743208638 · doi:10.1061/9780784480885.001

Sinkhole Locating and Corrosion Quantification with Pipe Penetrating Radar

2017· article· en· W2743208638 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePipelines 2017 · 2017
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGround-penetrating radarRebarWater pipeTrenchRadarSinkholeGeologyCorrosionStructural engineeringGeotechnical engineeringEngineeringMaterials scienceLayer (electronics)Mechanical engineeringComposite material

Abstract

fetched live from OpenAlex

Pipe penetrating radar (PPR) is the underground in-pipe application of ground penetrating radar (GPR), a non-destructive testing method that can detect defects and cavities within non-ferrous (reinforced concrete, vitrified clay, PVC, HDPE, etc.) pipes. The key advantage of PPR is the unique ability to map pipe wall thickness and deterioration including voids outside the pipe, enabling accurate predictability of needed rehabilitation or the timing of replacement. This paper presents recent advancement of PPR inspection technology together with selected case studies. The century old Broadway sewer main in Everett, WA, is a combination of a 30” reinforced concrete (RC) pipe and a 36” brick pipe. Little information is known about the condition of these pipes and the owners needed structural information beyond the usual closed circuit television (CCTV) in order to plan long term management of these critical assets. Over 16,000 ft of high resolution PPR line data were collected via robotic inspection. Due to the highly complex nature of the geophysical data, data processing and interpretation was a critical component of this project. The PPR results revealed that there are variations in the rebar cover in segments of the RC pipe. Although the average minimum rebar cover (depth of the first layer of rebar measured from the inner surface of the pipe wall) in almost every pipe segment appears to be sufficient (more than 0.75"), local anomalies occur along the pipe. No voids were detected outside the concrete pipe. In the second case study PPR was used for the condition assessment of asbestos cement (AC) pipes. AC pipes form a significant component of the water distribution and sewer collection systems in many cities. A majority of these pipes appear to be approaching the end of their useful life. The ability to accurately and cost-effectively assess the wall thickness of asbestos cement pipe has become a critically important issue for pipe owners. A new, high resolution PPR system, the SewerVUE AC Pipe Scanner (ACPS) was developed and successfully deployed in a live 10” AC pipe in Surrey, BC, Canada. Using new, high frequency antennae, the PPR inspection accurately mapped the remaining wall thickness.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.361

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 head0.034
GPT teacher head0.288
Teacher spread0.254 · 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