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Record W2809422173 · doi:10.1061/9780784481677.012

Simple Approaches for the Application of the Mechanics of Unsaturated Soils into Conventional Geotechnical Engineering Practice

2018· article· en· W2809422173 on OpenAlexaff
Sai K. Vanapalli, Zhong Han

Bibliographic record

VenuePanAm Unsaturated Soils 2017 · 2018
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGeotechnical engineeringSimple (philosophy)Soil mechanicsSoil waterGeologyEngineeringSoil science

Abstract

fetched live from OpenAlex

Comprehensive understanding of the mechanical behavior of unsaturated soils is required for the rational analysis and design of geotechnical infrastructure placed in or constructed with unsaturated soils. The mechanical properties of unsaturated soils are sensitive to changes in soil suction and water content. These properties have to be determined from cumbersome experimental studies that require highly trained personnel and are also time-consuming to perform. This paper summarizes a series of experimental studies related to the mechanical properties of a compacted glacial till and their influence on the load-settlement behavior and bearing capacity of a footing and a single friction pile installed in compacted glacial till. A simple unified model was used to predict the mechanical properties of compacted glacial till taking account of the influence of water content and suction. The predictions were further used to model the measured behavior of the model footing and model friction pile from numerical analysis using the conventional Mohr-Coulomb constitutive model. The simple approaches used in this study require only limited experimental data and soil properties information for interpreting the complex behavior of a compacted unsaturated soil. The study presented in this paper is of interest to the geotechnical engineers for extending the mechanics of unsaturated soils into conventional practice.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.797
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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