Mingxuan Luo

Ms. Mingxuan Luo


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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14 October 2024 in Buildings
Verified
Journal Article
Open access
PDF file
Fei GuoFei Guo
Fei Guo
MLMingxuan Luo
Mingxuan Luo
CZChenxi Zhang
Chenxi Zhang
JCJun Cai
Jun Cai
XZXiang Zhang
Xiang Zhang
JDJing Dong
Jing Dong
The influence of street spatial form on thermal comfort from urban morphology and human-centered perspectives has been underexplored. This study, utilizing multi-source data and focusing on urban central districts, establishes a refined index system for street spatial form and a thermal comfort prediction model based on extreme gradient boosting (XGBoost) and Shapley additive explanations (SHAP). The results reveal the following: (1) Thermal comfort levels display spatial heterogeneity, with areas of thermal discomfort concentrated in commercial zones and plaza spaces. (2) Compared to the human-centered perspective, urban morphology indicators correlate strongly with thermal comfort. (3) The key factors influencing thermal comfort, in descending order of importance, are distance from green and blue infrastructure (GBI), tree visibility factor (TVF), street aspect ratio (H/W), orientation, functional diversity indices, and sky view factor. All but the TVF negatively correlates with thermal comfort. (4) In local analyses, the primary factors affecting thermal comfort vary across streets with different heat-risk levels. In high heat-risk streets, thermal comfort is mainly influenced by distance from GBI, H/W, and orientation, whereas in low heat-risk streets, vegetation-related factors dominate. These findings provide a new methodological approach for optimizing urban thermal environments from both urban and human perspectives, offering theoretical insights for creating more comfortable cities.

27 December 2024 in Energies
Verified
Journal Article
Open access
PDF file
Fei GuoFei Guo
Fei Guo
SMShiyu Miao
Shiyu Miao
SXSheng Xu
Sheng Xu
MLMingxuan Luo
Mingxuan Luo
JDJing Dong
Jing Dong
HZHongchi Zhang
Hongchi Zhang
Performance parameters and generative design applications have redefined the human–machine collaborative relationship, challenging traditional architectural design paradigms and guiding the architectural design process toward a performance-based design transformation. This study proposes a multi-objective optimization (MOO) design approach based on performance simulation, utilizing the Grasshopper-EvoMass multi-objective optimization platform. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to coordinate two performance metrics—outdoor thermal comfort and building energy loads—for the multi-objective optimization of architectural design. The results indicate that (1) a performance-based multi-objective optimization design workflow is established. Compared to the baseline design, the optimized building form shows a significant improvement in performance. The Pareto optimal solutions, under 2022 meteorological conditions, demonstrate an annual energy efficiency improvement of 16.55%, and the outdoor thermal neutrality ratio increases by 1.11%. These results suggest that the optimization approach effectively balances building energy loads and outdoor thermal comfort. (2) A total of 1500 building form solutions were generated, from which 16 optimal solutions were selected through the Pareto front method. The resulting Pareto optimal building layouts provide multiple feasible form configurations for the early-stage design phase.

5 November 2024 in Buildings
Verified
Journal Article
Open access
PDF file
Fei GuoFei Guo
Fei Guo
MLMingxuan Luo
Mingxuan Luo
HZHui Zhao
Hui Zhao
ZDZekun Du
Zekun Du
ZZZhen Zhang
Zhen Zhang
DZDongxu Zhang
Dongxu Zhang
The indoor environment is widely acknowledged as a non-pharmacological tool for regulating residents’ mental health. In dormitory environments with relatively high residential density, the mental health of university students requires particular attention. This study surveyed 445 students from a northern Chinese university and used structural equation modeling (SEM) to analyze the impact of perceived indoor environmental quality (IEQ)—including thermal, lighting, acoustics, indoor air quality, and overcrowding—on self-reported anxiety symptoms. The results indicated the following: (1) students’ perceptions of dormitory IEQ significantly affected anxiety symptoms, explaining 40% of the variance; (2) anxiety symptoms associated with the IEQ were mainly characterized by anxiety and panic (r = 0.91, p < 0.001); (3) subjective perceptions of the acoustic environment (r = −0.55, p < 0.001) and indoor air quality (r = −0.15, p < 0.05) were key predictors of anxiety, while thermal environment, lighting environment, and overcrowding were not significant. The findings enrich the IEQ system and provide directions for optimizing the dormitory indoor environment from the perspective of student mental health, with implications for other types of residential buildings.