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Record W2091875401 · doi:10.1139/l02-110

Integrated three-dimensional computer-aided design and discrete-event simulation models

2003· article· en· W2091875401 on OpenAlexvenueno aff
Jianfei Xu, Simaan AbouRizk, Cam Fraser

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCADComputer Aided DesignComponent (thermodynamics)Context (archaeology)Computer scienceKey (lock)Engineering drawingSoftwareSystems engineeringEngineering

Abstract

fetched live from OpenAlex

Three-dimensional computer-aided design (3D-CAD) systems that integrate critical path method (CPM) algorithms, commonly referred to as four-dimensional computer-aided design (4D-CAD), have received a high level of interest over the past few years due to the insight they offer into constructability and feasibility analysis. This paper outlines an approach that facilitates this modeling method through integration between a commercial 3D-CAD software package and a discrete-event simulation tool. This approach employs a product-based modeling method that integrates simulation models with CAD drawings to provide real-time analysis and improved model accuracy in modeling construction operations. By integrating with 3D-CAD drawings, the models require much less data entry and provide a much higher degree of accuracy. Additionally, during the course of a project, resource and time consumption data can be collected and used to continually update the model, minimizing the use of assumptions and generalized data. This paper provides a short background and literature review to contextualize the problem statement, describes the product atomic component (PAC) used to integrate 3D-CAD and the simulation model, outlines some of the implementation issues in a simulation context, and presents a prototype system with an example application for an earthmoving project.Key words: 4D-CAD, CPM, product atomic component, simulation modeling, integration, earthmoving.

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 score0.954
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.185
Teacher spread0.172 · 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

Citations15
Published2003
Admission routes1
Has abstractyes

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