MétaCan
Menu
Back to cohort
Record W2482666757 · doi:10.1680/jgeen.15.00187

Application of deformation adjustors in piled raft foundations

2016· article· en· W2482666757 on OpenAlexaff
Feng Zhou, Cheng Lin, Xudong Wang, Jianyang Chen

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Geotechnical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsCoast Mountain College
Fundersnot available
KeywordsRaftSettlement (finance)Geotechnical engineeringDeformation (meteorology)PileBearing (navigation)StiffnessFoundation (evidence)Bearing capacityEngineeringGeologyCivil engineeringStructural engineeringComputer scienceMaterials scienceLaw

Abstract

fetched live from OpenAlex

This paper introduces a new device called a deformation adjustor to improve the performance of piled raft foundations in supporting high-rise buildings. The deformation adjustors are placed between pile head and raft to optimise the stiffness distribution in the piled raft system so that the differential settlement can be minimised and the potential bearing capacity of subsoils can be effectively utilised. They are particularly promising for piled raft foundations in complicated loading, construction and subsurface conditions. This paper first describes the development of the deformation adjustors and the installation procedures in piled rafts, followed by their potential applications to piled raft foundations in different challenging conditions. The possible challenging applications include piled rafts with end-bearing piles, reuse of old piles as a part of the piled rafts and piled rafts in complicated geological conditions. The preliminary design procedures for each application are also discussed. At the end of this paper, a case history is documented to show the potential of using deformation adjustors to improve the performance of piled rafts.

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 score0.695
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.183
Teacher spread0.179 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Geotechnical EngineeringSame topicGeotechnical Engineering and AnalysisFrench-language works237,207