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马远力
2024-04-30 14:10     (点击次数:)

马远力


建筑系讲师,博士研究生学历,博士学位,1996年9月出生。


CIBSE 英国皇家注册设备工程师协会会员。参与多项科研项目,发表多篇权威期刊论文,参编《国内外既有居住建筑改造典型案例》《既有居住建筑宜居改造功能提升标准概要》。曾担任Solar Energy等国际权威期刊审稿人。主要研究方向:建筑类型学、建筑低碳与可持续发展、超低能耗建筑设计、结合AI的建筑设计等。


电子邮箱:[email protected]

专业方向:建筑与建筑环境



 




个人教育和工作经历

2014.09—2016.07  宁波诺丁汉大学 建筑环境与能源应用工程专业 学士学位

2016.09—2017.07  诺丁汉大学(英国) 建筑环境与能源应用工程专业 交换生

2017.09—2018.07  宁波诺丁汉大学 建筑环境与能源应用工程专业 学士学位

2018.09—2023.07  诺丁汉大学 建筑与建筑环境专业 博士学位

2023.09—至今  宁波大学 讲师



主要成果

一、主持项目

1. 2019-2021宁波市科技计划项目:适用于宁波的被动式超低能耗建筑体系研究

2. 2019-2021慈溪市科技计划项目:以节能为导向的民用建筑分类技术及相关节能措施在慈溪应用示范研究

3. 2021-2023宁波市科技计划项目:基于类型学的建筑分类方法在办公建筑节能改造设计中的应用

4. 2021-2023宁波市东部新城明湖南区绿色建筑发展策略与应用研究

5. 2022宁波市建设科研计划项目:宁波农村超低能耗建筑技术方案及图集应用


二、论文著作

1. Ma, Y., Deng, W., Xie, J., Heath, T., Xiang, Y., & Hong, Y. (2022). Generating prototypical residential building geometry models using a new hybrid approach. Building Simulation (Vol. 15, No. 1, pp. 17-28). Tsinghua University Press. (IF: 5.5, JCR Q1,中科院1区)

2. 马远力,叶东杰,陈易,邓武,谢晶,叶一航 王靖雯.(2023).居住建筑原型建立及被动式技术节能影响探究.建筑节能(中英文)(01),10-16+25. (建筑科学领域高质量科技期刊T3,中文核心)

3. Ma, Y., Deng, W., Xie, J., Heath, T., Ezeh, C. I., Hong, Y. & Zhang, H. A macro-scale optimisation of zero-energy design schemes for residential buildings based on building archetypes. Solar Energy, 257, 196-209. (IF: 6.7, JCR Q2,中科院2区top)

4. Hong, Y., Ezeh, C. I., Deng, W., Hong, S. H., Ma, Y., Tang, Y., & Jin, Y. (2021). Coordinated energy-environmental-economic optimisation of building retrofits for optimal energy performance on a macro-scale: A life-cycle cost-based evaluation. Energy Conversion and Management, 243, 114327. (IF: 10.4, JCR Q1,中科院1区top)

5. Deng, W., Cheshmehzangi, A., Ma, Y., & Peng, Z. (2021). Promoting sustainability through governance of eco-city indicators: a multi-spatial perspective. International Journal of Low-Carbon Technologies, 16(1), 61-72. (IF: 2.455, JCR Q2)

6. Peng, Z., Zhao, S., Shen, L., Ma, Y., Zhang, Q., & Deng, W. (2021). Retrofit or rebuild? The future of old residential buildings in urban areas of China based on the analysis of environmental benefits. International Journal of Low-Carbon Technologies. 2021, 00, 1–13. (IF: 2.455, JCR Q2)

7. Hong Y, Ezeh C I, Deng W, Lu J, Ma Y, Jin Y. Climate adaptation of design scheme for energy-conserving high-rise buildings—Comparative study of achieving building sustainability in different climate scenarios[J]. Energy Reports, 2022, 8: 13735-13752. (IF: 4.937, JCR Q2)

8. Ma, Y., Shen, L., Ye, D., & Deng, W. (2021, June). Passive House in China’s Hot Summer Cold Winter Zone. In IOP Conference Series: Earth and Environmental Science (Vol. 798, No. 1, p. 012002). IOP Publishing. (EI Compendex, Scopus)

9. Ma, Y., Ye, D., Ma, S., Zhang, Q., Hong, Y., Xie, J. & Deng, W. (2022) Passive Energy-Saving Technologies for Low-Rise Residential Buildings Based on Building Prototyping: Cixi City as a Case. In: Mendonça P., Cortiços N.D. (eds) Proceedings of the 7th International Conference on Architecture, Materials and Construction. ICAMC 2021. Lecture Notes in Civil Engineering, vol 226. Springer, Cham. //doi.org/10.1007/978-3-030-94514-5_39. (EI Compendex, Scopus)

10. Ma S., Ma Y., Zhang Q., Deng W., Lu J., Zhou T. (2022) Thermal Comfort and Energy Consumption in Healthcare Buildings – A Review. In: Mendonça P., Cortiços N.D. (eds) Proceedings of the 7th International Conference on Architecture, Materials and Construction. ICAMC 2021. Lecture Notes in Civil Engineering, vol 226. Springer, Cham. //doi.org/10.1007/978-3-030-94514-5_38 (EI Compendex, Scopus).

11. Hong Y., Ezeh C.I., Ma Y., Hong SH., Deng W. (2022) Certifying Buildings in China Using Energy, Environmental, Engineering and Economic Factors: Assessing the Suitability of BREEAM, LEED and Green Star. In: Mendonça P., Cortiços N.D. (eds) Proceedings of the 7th International Conference on Architecture, Materials and Construction. ICAMC 2021. Lecture Notes in Civil Engineering, vol 226. Springer, Cham. //doi.org/10.1007/978-3-030-94514-5_42. (EI Compendex, Scopus)




三、获奖

1. 2021年第七届环境与可再生能源国际会议最佳报告

2. 宁波城市科学研究会2023年度优秀论文一等奖。



对研究生要求

具有一定统计学和编程基础,思维活跃,诚实,态度认真。











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