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Record W3097054013 · doi:10.1155/2020/8834389

Collaboration-Based BIM Model Development Management System for General Contractors in Infrastructure Projects

2020· article· en· W3097054013 on OpenAlexvenueno aff
Yu‐Cheng Lin, Nan-Hai Lo, Hsin-Tzu Hu, Ya-Ting Hsu

Bibliographic record

VenueJournal of Advanced Transportation · 2020
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
FundersMinistry of Science and Technology, Taiwan
KeywordsBuilding information modelingProcess (computing)Construction engineeringConstruction managementProcess managementEngineering managementSystems engineeringInformation modelProject managementFacility managementEngineeringComputer scienceSoftware engineeringOperations managementBusinessCivil engineering

Abstract

fetched live from OpenAlex

For mass rapid transit (MRT) projects, the characteristics of MRT engineering include large scopes, long durations, complex interfaces, significant requirements for management, and complicated coordination and cooperation. Owing to the complexity of these projects, the use of building information modeling (BIM) technology will be necessary and helpful to improve construction management. The increasing application of BIM in the architecture, engineering, and construction (AEC) industries has strengthened the need for effective construction management for general contractors (GC) for BIM implementation during the construction phase. Collaboration-based BIM model development for GCs typically involves relevant participants from different fields during the construction phase of MRT projects. However, collaboration-based BIM model development tasks often create numerous practical problems (e.g., reworks and errors regarding BIM model development). As the BIM manager and engineers for the general contractor who handle BIM model development are located in different departments and different office locations in MRT construction projects, a centralized platform is needed to share the latest real-time BIM model developments for related participants. Effective collaboration-based BIM model development management (CBMDM) is therefore essential for GCs to obtain accurate BIM models before the implementation of BIM-related applications. While the latest information for collaboration-based BIM model development should be updated and tracked effectively for CBMDM for related participants during the development process, in practice, GCs lack systematic approaches and information management platforms for use in CBMDM tasks. Thus, this study proposes a novel approach and develops an information system to manage and track all CBMDM tasks for GCs during the BIM development process. The purpose of this study is to develop a CBMDM system to improve the efficiency of sharing and tracking information for CBMDM activities. The research scope of this study is to propose an approach and system for CBMDM work in large-scale construction and infrastructure projects. The CBMDM system assists users by providing workflow management of CBMDM tasks for BIM engineers and managers so users can manage all BIM model development tasks effectively. The proposed system can also be utilized for other types of large-scale construction projects for CBMDM tasks. Furthermore, to understand its effectiveness, the proposed CBMDM system is applied to a case study of an MRT project in Taiwan. Finally, the major practical advantages, disadvantages, and limitations of the system are identified for infrastructure projects.

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 score0.337
Threshold uncertainty score0.369

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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