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Record W4391624430 · doi:10.2749/newdelhi.2023.0172

Case study using Non-Linear Finite Element Analysis for Assessment of Slutchers Lane bridge

2023· article· en· W4391624430 on OpenAlex
Jithu G. Francis, Sreejith Parayil, Abani Kumar Satapathy

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReport · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsFinite element methodStructural engineeringBridge (graph theory)Nonlinear systemLimit state designBucklingSensitivity (control systems)EngineeringBeam (structure)Limit (mathematics)Computer scienceMathematics

Abstract

fetched live from OpenAlex

<p>200 years of British railway infrastructure is now owned, managed, and developed by Network Rail. Safe and effective management of the rail network needs to have up-to-date information regarding the capacities of these ageing assets. Slutchers Lane bridge (Warrington, UK) is a structure designed to carry rail loads over a public road. According to the 2010 NBSI assessment and the archive drawings, bridge widening took place circa 1907.</p> <p>The previous assessment of this bridge was carried out using simple statics with an idealised line beam approach, the results obtained were inadequate to serve the current load requirements of Network Rail. To get a more accurate theoretical capacity, a more refined analysis was required, incorporating recent site inspection data representing the current condition of the bridge. Performing a nonlinear finite element analysis was found to be suitable for this requirement.</p> <p>For the study, the entire structure was modelled in LUSAS software using shell elements and analysed for various potential failure mechanisms. The finite element model was able to capture all the deteriorations identified during the recent site investigation. A mesh sensitivity study was carried out for the selection of an appropriate mesh size. In the analysis, material nonlinearity is considered along with geometric nonlinearity. The initial geometric imperfection is assigned based on the critical buckling mode identified in the linear Eigenvalue buckling analysis with appropriate scale factor. To determine the results at both ultimate limit state and service limit state, the following outputs were captured, Von Mises stresses, the extent of material yielding, and the propensity for buckling. Recommendations were made based on standard guidance and engineering judgement.</p> <p>From the nonlinear finite element study, it was established that the structure in its current condition is adequate for the current Network rail requirement, which is an improvement on the results of the previous assessment.</p>

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.080
GPT teacher head0.366
Teacher spread0.286 · 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