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Record W2615170682 · doi:10.1139/cjce-2016-0413

BIM-based model for quantifying the design change time ripple effect

2017· article· en· W2615170682 on OpenAlex
Valeh Moayeri, Osama Moselhi, Zhenhua Zhu

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsConcordia University
Fundersnot available
KeywordsRippleScheduleDuration (music)Computer scienceComponent (thermodynamics)Reliability engineeringEngineering

Abstract

fetched live from OpenAlex

Design changes by owners are common to many construction projects and can cause severe delays if owners do not consider that a change in one part of the project may cause a series of changes in other parts of that project. The impact of a changed component on other unchanged components is known as the “change ripple effect”. To efficiently manage design changes, the ripple effect should be quantified and impact evaluated. This paper presents a building information modeling (BIM)-based quantification model to quantify the ripple effect of owner-requested design changes. The developed model calculates the impact of design changes and their ripple effect on a project’s total duration. After analyzing the ripple effect over time, the model updates the project schedule accordingly. To demonstrate its usefulness and illustrate its essential features, the model is applied to a case study.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.978
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.221
GPT teacher head0.341
Teacher spread0.120 · 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