Zhaoyin Zhou

Prof. Zhaoyin Zhou


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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19 October 2021 in Sustainability
Verified
Journal Article
Open access
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YWYuanping Wang
Yuanping Wang
GJGao Jingxin
Gao Jingxin
GJGao Jingxin
Gao Jingxin
ZZZhaoyin Zhou
Zhaoyin Zhou
The accelerated flow of resources and the population has resulted in the coexistence of the expansion and shrinkage of cities. The shrinking city is not a new thing, but it is a new problem that needs to be solved urgently in China. Urban resources reveal the direct cause of the shrinking city: attraction, which reflects the competition for external resources and the endowment of the intrinsic resources of cities. Therefore, this paper established the Urban Resource Degree (URD) model to measure the urban resource degree of the shrinking city. Factors were then selected to analyze the ways in which they influence the shrinking cities. Given the spillover effect and heterogeneity of the influencing factors, a Spatial Durbin Model (SDM) and a Spatiotemporal Geographically Weighted Regression Model (GTWR) were used to conduct a spatial spillover (SSA) and spatial heterogeneity (SHA) analysis of the URD of the shrinking cities in Northeast China. The results show that the ability gap to compete for and control resources between prefecture-level shrinking cities and county-level shrinking cities is narrowed. From the SSA and SHA perspectives, the influence factors can be categorized into three types: “High West–Low East and Negative–Positive Spillover”, “Low West and High East Positive–Negative Spillover”, “Low Northwest and High Southeast Negative Spillover”. Finally, policy implications are proposed to provide support for policy-making.

8 October 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
YLYu Luo
Yu Luo
YLYiminxuan Liu
Yiminxuan Liu
XLXiaofeng Liao
Xiaofeng Liao
CCChangSaar Chai
ChangSaar Chai
Heap-Yih ChongHeap-Yih Chong
Heap-Yih Chong
ZZZhaoyin Zhou
Zhaoyin Zhou
Steel reinforcement is one of the most important materials used in the construction industry. This research optimizes reinforcement bar fabrication by integrating Building Information Modeling (BIM) with visual programming in Dynamo. On-site rebar cutting and bending generate significant material waste, increasing costs and environmental impact. To address this, an intelligent Dynamo script was developed to extract detailed 3D rebar and 4D scheduling data from BIM models. The script optimizes material usage by specifying cut-off lengths to improve reuse and minimize waste. Validation through two real-world case studies demonstrated the method’s significant potential. Effectiveness was assessed using benchmarks comparing the number of bars saved, waste reduced, and overall cost savings. The study confirms that optimized fabrication significantly cuts waste and cost. Its effectiveness, however, varies with rebar type and structural component, with the most significant gains observed in medium-length bars and pile caps. By offering a novel tool for sustainable construction, this research advances BIM-enabled reinforcement design and material optimization.