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Record W4410209598 · doi:10.1201/9781003559047-325

Durability and sustainability in design and construction of Ontario Line South tunnels

2025· book-chapter· en· W4410209598 on OpenAlexaboutno aff
Mehdi Bakhshi, Verya Nasri, Ishtiaq Hassan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityDurabilityEngineeringLine (geometry)Civil engineeringConstruction engineeringComputer scienceMathematicsEcologyDatabase

Abstract

fetched live from OpenAlex

The Ontario Line South (OLS) is a critical component of Toronto’s expanding rapid transit network, connecting the Ontario Science Centre to Exhibition/Ontario Place. This 5.9 km underground segment includes twin-bored tunnels and seven stations, six of which are below ground. The station construction employs temporary support systems including shotcrete and rock bolts, while permanent structures include reinforced concrete linings and sheet waterproofing membranes. Twin-bored tunnels, constructed using tunnel boring machines (TBMs), feature fiber-reinforced concrete (FRC) precast segments, with waterproofing ensured by segmental gaskets. This paper presents a comprehensive durability evaluation of the OLS underground structures over their 100-year design life, focusing on the impact of ground and groundwater exposure. Durability design follows the Canadian CSA A23.1 (2019) standard and incorporates supplementary full probabilistic service life modeling based on fib Bulletin No. 34 (2006) to validate the prescriptive measures. Using CSA C-1 class concrete with 40% cement replaced by ground granulated blast-furnace slag (GGBS) as a supplementary cementitious material (SCM), the OLS meets its durability and embodied carbon reduction targets, aligning with sustainable infrastructure goals. Monte Carlo simulations show that the final concrete linings achieve a reliability index exceeding the target of 1.3 for up to 150 years, 1.5 times the required service life.

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: none
Teacher disagreement score0.904
Threshold uncertainty score0.779

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 head0.007
GPT teacher head0.178
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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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