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Record W4411430462 · doi:10.1007/s40515-025-00617-5

Improved Wave Equation Analysis and Economic Impact Studies for Driven Steel Piles in Rock-Based Intermediate Geomaterials

2025· article· en· W4411430462 on OpenAlexaff
Harish K. Kalauni, Nafis Bin Masud, Kam Ng, Shaun S. Wulff

Bibliographic record

VenueTransportation Infrastructure Geotechnology · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsIntertek (Canada)
FundersKansas Department of TransportationIowa Department of TransportationIdaho Transportation DepartmentWyoming Department of TransportationColorado Department of TransportationMontana Department of TransportationUniversity of WyomingNorth Dakota Department of TransportationU.S. Department of Transportation
KeywordsPileGeotechnical engineeringDynamic load testingReliability (semiconductor)Structural engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Assigning static and dynamic properties to rock-based Intermediate Geomaterials (R-IGMs) remains a challenge in the Wave Equation Analysis Program (WEAP) to accurately predict the pile performance during construction. This was partly attributed to the absence of reliable methods to determine pile resistances in R-IGMs. Furthermore, the recommended Smith parameters are developed based on pile load test data in soils, but not IGMs. Using 95 dynamic load test results of steel H and pipe piles from five state DOTs, improved WEAP and Load and Resistance Factor Design (LRFD) procedures are recommended for piles driven in R-IGMs. The proposed WEAP procedures are based on newly developed static analysis methods and back-calculated dynamic parameters for R-IGMs. Sixteen independent test pile data are collected to validate the recommendations. Compared to the default WEAP procedure, the proposed WEAP procedure reduces the underprediction of pile resistances by 12%, improves reliability by 5%, and yields a higher calibrated resistance factor of 0.70. Our economic impact assessment on 116 test pile data found that the proposed WEAP method yields, on average, a smaller difference in steel weight during construction based on pile types and bearing IGM types.

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 score0.206
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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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