Digital Twin–driven construction of low-carbon communities in traditional villages:The Case Study Of Yuxiao Village At East Qing Tombs

Authors

  • Liang Pan North China University of Science and Technology, Tangshan, China
  • Xiaolin Li North China University of Science and Technology, Tangshan, China
  • Xuan Ding North China University of Science and Technology, Tangshan, China

DOI:

https://doi.org/10.62051/ajmse.v1n1.04

Keywords:

Digital Twin, Traditional Villages, Low-carbon Community, Space Syntax, Energy Simulation

Abstract

Old villages are facing the problem of disassembled broken information, and it is hard to make much numerical help convert to reduce less carbon dioxide. The update with digital twins (DT) will be offered Taking Yuxiao village which belongs to the Northern area of East Qing tombs as an example we construct Meso – spatial pattern and Micro – building performance evaluation system. By using the space syntax method, we conduct the spatial analysis on the yuxiaovillage and carry out simulation study about dynamic energy consumption through DeST-H software. According to the result, by using meso-scale ventilation structure improvement and also improve micro-level envelope performance at the same time so that we can save up from 35 - 40% operational building energy use. This is a road that can prove the scientific correctness and usefulness of Digital Twin helping rural area make low-carbon decision-making.

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References

[1] Pomponi, F.; D’Amico, B. Low Energy Architecture and Low Carbon Cities: Exploring Links, Scales, and Environmental Impacts. Sustainability 2020, 12, doi:10.3390/su12219189. DOI: https://doi.org/10.3390/su12219189

[2] Yang, C.; Misni, A. Exploring Comfort and Efficiency: Comparing Vernacular and Modern Dwellings in Rural Handan, Northern China. Sustainability 2026, 18, doi:10.3390/su18031575. DOI: https://doi.org/10.3390/su18031575

[3] Sun, M.; Xue, Y.; Wang, L. Research on Optimized Design of Rural Housing in Cold Regions Based on Parametrization and Machine Learning. Sustainability 2024, 16, doi:10.3390/su16020667. DOI: https://doi.org/10.3390/su16020667

[4] Yu, Z.; Guo, Z.; Ling, Z.; Chen, Y. Research on Low-Carbon Building Design Strategies for Folk Dwellings in Hanzhong Based on Single Objective Optimization. Buildings 2024, 14, doi:10.3390/buildings14072154. DOI: https://doi.org/10.3390/buildings14072154

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Published

16-04-2026

Issue

Section

Articles

How to Cite

Pan, L., Li, X., & Ding, X. (2026). Digital Twin–driven construction of low-carbon communities in traditional villages:The Case Study Of Yuxiao Village At East Qing Tombs. Academic Journal of Management Science and Engineering, 1(1), 28-31. https://doi.org/10.62051/ajmse.v1n1.04