MétaCan
Menu
Back to cohort
Record W3037746521 · doi:10.1108/ecam-06-2019-0314

Exploring and verifying BIM-based energy simulation for building operations

2020· article· en· W3037746521 on OpenAlex

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

VenueEngineering Construction & Architectural Management · 2020
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInteroperabilityBuilding information modelingEnergy consumptionUnavailabilitySimulation softwareComputer scienceProcess (computing)Systems engineeringScheduleBuilding energy simulationEnergy modelingSoftwareReliability engineeringSimulationEngineeringEnergy performanceOperating system

Abstract

fetched live from OpenAlex

Purpose The operational phase of a building's lifecycle is receiving increasing attention, as it consumes an enormous amount of energy and results in tremendous detrimental impacts on the environment. While energy simulation can be applied as a tool to evaluate the energy performance of a building in operation, the emergence of Building Information Modeling (BIM) technology is expected to facilitate the evaluation process with predefined and enriched building information. However, such an approach has been confronted by the challenge of interoperability issues among the related application software, including the BIM tools and energy simulation tools, and the results of simulation have been seldom verified due to the unavailability of corresponding experimental data. This study aims to explore the interoperability between the commonly used energy simulation and BIM tools and verifies the simulation approach by undertaking a case study. Design/methodology/approach With Autodesk Revit and EnergyPlus selected as the commonly used BIM and energy simulation tools, respectively, a valid technical framework of transferring building information between two tools is proposed, and the interoperability issues that occur during the data transfer are studied. The proposed framework is then employed to simulate the energy consumption of a single-family house, and sensitivity analysis and analysis on such parameters as schedule are conducted for building operations to showcase its applicability. Findings The simulation results are compared with monitored data and the results from another simulation tool, HOT2000; the comparison reveals that EnergyPlus and HOT2000 predict the total energy consumption with a difference from the monitoring data of 8.0 and 7.1%, respectively. Practical implications This research shows how to efficiently use BIM to support building energy simulation. Relevant stakeholders can learn from this research to avoid data loss during BIM model transformation. Originality/value This research explores the application of BIM for building energy simulation, compares the simulation results among different tools and validates simulation results using monitored data.

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 score0.727
Threshold uncertainty score0.860

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 head0.037
GPT teacher head0.211
Teacher spread0.174 · 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