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Record W1920168922 · doi:10.1108/09699981011074574

Dynamic modeling of construction and demolition waste management processes

2010· article· en· W1920168922 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 · 2010
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsToronto Metropolitan University
FundersU.S. Environmental Protection Agency
KeywordsDemolition wasteDemolitionMainland ChinaReuseConstruction wasteConstruct (python library)EngineeringChinaComputer scienceCivil engineeringWaste managementGeography

Abstract

fetched live from OpenAlex

Purpose The aim of this paper is to develop a model based on system dynamics (SD) approach, which integrates three subsystems for simulating construction and demolition (C&D) waste management in Shenzhen, Mainland China. Design/methodology/approach SD approach was first used to construct the model for C&D waste management in Shenzhen. The model was then converted for running on computer through the software package “iThink”, which was specifically designed for SD modeling. The data required for model simulation was derived through various ways, including literature review, examination of official reports and yearbooks, and questionnaires. After all the parameters in the model were determined, simulation was carried out. Findings The model proposed in this research can provide an experimental simulation platform to investigate the complexity and interdependencies of factors in managing C&D waste in Shenzhen, Mainland China. The simulation results show that the pressing situation of C&D waste management in Shenzhen would aggravate if no effective measures were taken to address it during the simulation period. Participants' active participation and cost consideration are the two major factors affecting C&D waste reduction. Furthermore, new landfills should be planned to properly handle the C&D waste accumulated in Shenzhen over the past few years. Originality/value Although some studies have been conducted under the topic of C&D waste management during the past few years in Shenzhen – how to effectively and efficiently handle the waste is still unsolved. Factors affecting the effectiveness of C&D waste management have separately been examined in the previous studies, without considering their interrelations. The SD‐based model is developed in this research to investigate the complex and interdependent relationships among these factors. The model can deepen participants' understandings about C&D waste management and help explore the major factors affecting the effectiveness of management activities. The measures, which are proposed based on the simulation results, can serve as a valuable reference for planning C&D waste management in Shenzhen.

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 categoriesMeta-epidemiology (narrow)
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 score0.192
Threshold uncertainty score1.000

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 head0.003
GPT teacher head0.170
Teacher spread0.167 · 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