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Record W2153126112 · doi:10.1139/l00-082

Structural performance of scrap tire culverts

2001· article· en· W2153126112 on OpenAlexvenueno aff
Shiping Yang, Bruce H. Kjartanson, Robert A. Lohnes

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersIowa Department of Natural ResourcesUniversity of Northern Iowa
KeywordsCulvertTruckStiffnessScrapEngineeringGeotechnical engineeringStructural engineeringAutomotive engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Culverts constructed of whole truck tires are a cost-effective alternative for draining water from small drainage basins with areas up to several hectares. Truck tire culvert design involves both hydraulic and structural performance considerations. This paper focuses on the structural considerations. Structural performance of truck tire culverts depends on the strength and stiffness of the truck tires and on their interaction with the surrounding backfill soil. The strength and stiffness properties of truck tires were determined by parallel plate testing. Field tests were conducted to evaluate the soil-structure interaction of buried truck tire culverts under a relatively shallow backfill. Responses with well-compacted and uncompacted (dumped) glacial till backfill soil were compared. Drawing on the results of the parallel plate tests and using the buried conduit test results for calibration, the Culvert Analysis and Design (CANDE) program was used to assess the load response of a truck tire culvert for a variety of backfill soils and to develop structural performance-based design guidelines.Key words: scrap tires, culvert, parallel plate test, field testing, CANDE.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.721

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 head0.165
Teacher spread0.159 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations19
Published2001
Admission routes1
Has abstractyes

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