Zhengdao Fang

Mr. Zhengdao Fang

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 November 2025 in Buildings
Verified
Journal Article
Open access
PDF file
ZFZhengdao Fang
Zhengdao Fang
ショウ トウショウ トウ
ショウ トウ
Zhenjiang ShenZhenjiang Shen
Zhenjiang Shen
DYDi Yang
Di Yang
XLXinyue Lin
Xinyue Lin
In smart home projects, building data management at the design stage increasingly relies on digital-twin assets delivered via game engines. Without a clear governance workflow, however, these practices tend to generate non-standard building data on the consumption side, causing broken data chains and increasing construction and management risks. To address this problem, this study proposes a traceability-oriented governance workflow that strengthens IfcGUID compliance and automatically detects and converts inconsistent digital-twin assets into IFC-compliant, auditable data, thereby reducing data chain breakage and improving cross-system traceability in building data management. The workflow uses IfcGUID as a cross-system primary key and is evaluated in a virtual smart home project through a pre-test–repair–post-test experiment at the design stage. We examine four indicators of IfcGUID quality—completeness, validity, uniqueness, and stability—together with a bridge recognition rate that reflects game engine interoperability on the consumption side. The results show that all four IfcGUID indicators converge towards 1 after applying the workflow, and the bridge recognition rate approaches 100%, indicating that the risk of data chain breakage, measured on an IFC basis, is substantially reduced. Within existing toolchains, this workflow provides design teams, visualization teams, clients, and auditors with a low-cost and reproducible path for standardizing design-stage digital-twin assets and establishing a traceable, auditable baseline for cross-system interoperability and lifecycle building data management and data reuse.

1 October 2025 in Preprints.org
Verified
Preprint
Open access
PDF file
ZFZhengdao Fang
Zhengdao Fang
ショウ トウショウ トウ
ショウ トウ
Zhenjiang ShenZhenjiang Shen
Zhenjiang Shen
DYDi Yang
Di Yang
XLXinyue Lin
Xinyue Lin
This study addresses non-standard data that emerge on the consumption side when digital-twin assets are introduced during the design stage of a smart home. We present a traceability-oriented governance workflow that standardizes non-standard assets into compliant, auditable data streams for cross-system reconciliation in building data management. The workflow front-loads control, measurement, and evidence: the export/consumption pipeline is frozen; Industry Foundation Classes Globally Unique Identifier (IfcGUID) compliance is enforced by adopting the Industry Foundation Classes (IFC) Globally Unique Identifier (IfcGUID-22) as the minimal cross-system object key; containers and objects are registered in a controlled Common Data Environment (CDE); and Unity unique identifiers are bridged to IfcGUID-22 via a template-based mapping with read-only minimal repairs to restore traceability and game engine interoperability. Effectiveness is validated in a virtual testbed using a pre-test → bridging/minimal-repair → post-test design under a fixed denominator, interpreter, and configuration. Four IfcGUID metrics—completeness, validity, uniqueness, and stability—are computed together with an Ifc-side stability control; interoperability is summarized by Bridge Recognition Rate (BRR) and Disconnect Rate (DR). Results show BRR = 0.9987 with 1/778 broken pairs and 18 stable scene recognitions; completeness, validity, and stability reach 1.00, and uniqueness improves to 0.976744. The findings demonstrate a verifiable, low-cost, and transferable path that reduces breakage risks from non-standard data and restores cross-system traceability for Building Information Modeling (BIM) managers, CDE managers, visualization/engine teams, and owners.