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Record W4253608594 · doi:10.1109/wsc.2012.6465087

DEVS-based Building Information Modeling and simulation for emergency evacuation

2012· article· en· W4253608594 on OpenAlex
Sixuan Wang, Michael Van Schyndel, Gabriel Wainer, Vinu Subashini Rajus, Robert Woodbury

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.

Bibliographic record

VenueProceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC) · 2012
Typearticle
Languageen
FieldEngineering
TopicEvacuation and Crowd Dynamics
Canadian institutionsSimon Fraser UniversityCarleton University
Fundersnot available
KeywordsDEVSComputer scienceSystems engineeringModeling and simulationSimulationEngineering

Abstract

fetched live from OpenAlex

Nowadays, numerous Computer-aided Design (CAD) software packages support Building Information Modeling (BIM). BIM software can benefit of advanced simulation in the pre-design phase of construction projects. In this case, we show focus on models of the emergency evacuation regarding the security and safety. We analyze the evacuation simulation of a model based on DEVS (Discrete Event systems Specification) for BIM authoring tools. The idea is to automate to extraction of building information that can be subsequently used in a simulation. Our case study uses a Cell-DEVS model of the evacuation of a multi-floor building. We also show how to obtain a 3D visualization by transforming the simulation results, facilitating the work of architects, contractors and fabricators. This kind of application could be used to analyze bottlenecks and the maximum occupation for determining an optical evacuation plan.

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)0.000
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 score0.507
Threshold uncertainty score0.554

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 communication0.0000.002
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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