2025
Can Sustainable Policies Drive TOD Effectively? Insights from Multi-Scenario Simulations
Weiyao Yang,Sunan Tian,Mingyu Zhai*,Fupeng Li,Da Huo,Suoao Wang, Sijie Liu,Zenghui Liu.
Journal of Environmental Management 2025
This paper examines the impact of sustainable policies in the Tokyo Metropolitan Area on Transit-Oriented Development (TOD), using the Den-en-toshi Line as an example. It evaluates the sustainability of 27 stations using the Node-Place-Ecology (NPE) model. The findings indicate varying adaptability of stations to policy changes. The study also discusses how policy implementation affects station sustainability and offers specific recommendations for different stations to enhance their sustainability.
Can Sustainable Policies Drive TOD Effectively? Insights from Multi-Scenario Simulations
Weiyao Yang,Sunan Tian,Mingyu Zhai*,Fupeng Li,Da Huo,Suoao Wang, Sijie Liu,Zenghui Liu.
Journal of Environmental Management 2025
This paper examines the impact of sustainable policies in the Tokyo Metropolitan Area on Transit-Oriented Development (TOD), using the Den-en-toshi Line as an example. It evaluates the sustainability of 27 stations using the Node-Place-Ecology (NPE) model. The findings indicate varying adaptability of stations to policy changes. The study also discusses how policy implementation affects station sustainability and offers specific recommendations for different stations to enhance their sustainability.
Advancing just transition: The role of biomass co-firing in emission reductions and employment for coal regions
Mingyu Zhai,Xuelin Tian,Zenghui Liu ,Yincheng Zhao,Yating Deng,Weiyao Yang*.
Sustainable Energy Technologies and Assessments 2025
This study examines the role of biomass co-firing retrofitting in coal plants as part of the low-carbon transition, focusing on its employment effects, carbon emissions, and social benefits. Using an integrated model, the research finds that when the biomass blend rate exceeds 90%, job creation shifts, but the overall impact is negative, suggesting biomass co-firing is ineffective for achieving a just transition during coal phase-out and is less competitive than renewable energy. Additionally, generation efficiency decreases linearly with higher blend rates, while carbon emission intensity and job intensity are positively correlated. The study concludes that biomass co-firing is insufficient for a just transition and recommends regionally adaptive blend ratios for optimal performance.
Advancing just transition: The role of biomass co-firing in emission reductions and employment for coal regions
Mingyu Zhai,Xuelin Tian,Zenghui Liu ,Yincheng Zhao,Yating Deng,Weiyao Yang*.
Sustainable Energy Technologies and Assessments 2025
This study examines the role of biomass co-firing retrofitting in coal plants as part of the low-carbon transition, focusing on its employment effects, carbon emissions, and social benefits. Using an integrated model, the research finds that when the biomass blend rate exceeds 90%, job creation shifts, but the overall impact is negative, suggesting biomass co-firing is ineffective for achieving a just transition during coal phase-out and is less competitive than renewable energy. Additionally, generation efficiency decreases linearly with higher blend rates, while carbon emission intensity and job intensity are positively correlated. The study concludes that biomass co-firing is insufficient for a just transition and recommends regionally adaptive blend ratios for optimal performance.
2024
Dual-agent intelligent fire detection method for large commercial spaces based on numerical databases and artificial intelligence
GANG Liu#,Zenghui Liu#,Guanhua Qu*,Lei Ren*.
Process Safety and Environmental Protection 2024
This study combines distributed fiber optic temperature sensing systems with deep learning algorithms to develop a dual-agent intelligent fire detection method for rapidly and accurately predicting key fire information in large commercial spaces, including the location of the fire source, the intensity of fire development, and the distribution of carbon monoxide on critical planes. This work not only improves the accuracy and response speed of fire alarms but also provides data support for emergency evacuation and rescue operations, reducing casualties and property loss caused by fires, and has significant practical importance for the safety protection systems of modern commercial buildings.
Dual-agent intelligent fire detection method for large commercial spaces based on numerical databases and artificial intelligence
GANG Liu#,Zenghui Liu#,Guanhua Qu*,Lei Ren*.
Process Safety and Environmental Protection 2024
This study combines distributed fiber optic temperature sensing systems with deep learning algorithms to develop a dual-agent intelligent fire detection method for rapidly and accurately predicting key fire information in large commercial spaces, including the location of the fire source, the intensity of fire development, and the distribution of carbon monoxide on critical planes. This work not only improves the accuracy and response speed of fire alarms but also provides data support for emergency evacuation and rescue operations, reducing casualties and property loss caused by fires, and has significant practical importance for the safety protection systems of modern commercial buildings.
The passive optimization mechanism of winter thermal performance in commercial complex based on coupled multi-spatial parameters
Lei Ren#,Guanhau Qu#* ,Gang Liu*,Zenghui Liu.
Journal of Building Engineering 2024
The innovation of this study is to reveal the passive optimization potential of commercial complex thermal performance in winter through coupling analysis of multi-spatial parameters. The research results not only provide a scientific basis for architectural design, but also provide a new idea for realizing low energy consumption and high efficiency architectural design. The thermal performance of commercial complexes can be significantly improved by optimizing the spatial parameters, thus reducing the dependence on active heating systems and reducing operating costs and carbon emissions.
The passive optimization mechanism of winter thermal performance in commercial complex based on coupled multi-spatial parameters
Lei Ren#,Guanhau Qu#* ,Gang Liu*,Zenghui Liu.
Journal of Building Engineering 2024
The innovation of this study is to reveal the passive optimization potential of commercial complex thermal performance in winter through coupling analysis of multi-spatial parameters. The research results not only provide a scientific basis for architectural design, but also provide a new idea for realizing low energy consumption and high efficiency architectural design. The thermal performance of commercial complexes can be significantly improved by optimizing the spatial parameters, thus reducing the dependence on active heating systems and reducing operating costs and carbon emissions.
Intelligent generation method of infection risk map and management system in hospital waiting room for respiratory infectious diseases
Guanhua Qu#,Zenghui Liu#,Lei Ren*,Gang Liu*.
Journal of Building Engineering 2024
The innovation of this study is to generate infection risk map by intelligent method and manage the system, so as to achieve accurate control of airborne infection risk in waiting room. The results of this study not only help to select hospital design scheme, but also optimize the operation control strategy of ventilation system, so as to strengthen the control of infectious diseases and reduce the threat of cross-infection of respiratory infectious diseases to public health safety during peak periods in hospitals..
Intelligent generation method of infection risk map and management system in hospital waiting room for respiratory infectious diseases
Guanhua Qu#,Zenghui Liu#,Lei Ren*,Gang Liu*.
Journal of Building Engineering 2024
The innovation of this study is to generate infection risk map by intelligent method and manage the system, so as to achieve accurate control of airborne infection risk in waiting room. The results of this study not only help to select hospital design scheme, but also optimize the operation control strategy of ventilation system, so as to strengthen the control of infectious diseases and reduce the threat of cross-infection of respiratory infectious diseases to public health safety during peak periods in hospitals..
Combinatorial machine learning approaches for high-rise building cost prediction and their interpretability analysis
Zenghui Liu,Jing Lin*.
Journal of Asian Architecture and Building Engineering 2024
The innovation of this study is the combination of combinatorial machine learning methods with explanatory analysis, which not only improves the accuracy of cost predictions, but also enhances the transparency of the model. By analyzing the interaction between features, the researchers found that there is a negative correlation between the "expected project duration" and the "building structure", while the "expected project duration" and the "interior decoration" may cancel each other out. This research result is of great significance to construction management. It not only helps investors assess the profitability of projects more accurately, but also improves the efficiency and quality of investment decisions.
Combinatorial machine learning approaches for high-rise building cost prediction and their interpretability analysis
Zenghui Liu,Jing Lin*.
Journal of Asian Architecture and Building Engineering 2024
The innovation of this study is the combination of combinatorial machine learning methods with explanatory analysis, which not only improves the accuracy of cost predictions, but also enhances the transparency of the model. By analyzing the interaction between features, the researchers found that there is a negative correlation between the "expected project duration" and the "building structure", while the "expected project duration" and the "interior decoration" may cancel each other out. This research result is of great significance to construction management. It not only helps investors assess the profitability of projects more accurately, but also improves the efficiency and quality of investment decisions.
An investigation using resampling techniques and explainable machine learning to minimize fire losses in residential buildings
Zenghui Liu*,Yingnan Zhuang.
Journal of Building Engineering 2024
This study not only improves the emergency response strategies for urban residential fires, but also provides customized fire safety policies for different urban environments, effectively reducing fire risk. Through the introduction of resampler technology and interpretable machine learning, this study not only improves the prediction accuracy of the model, but also enhances the transparency and interpretability of the model, providing a more scientific and reliable tool for fire risk management..
An investigation using resampling techniques and explainable machine learning to minimize fire losses in residential buildings
Zenghui Liu*,Yingnan Zhuang.
Journal of Building Engineering 2024
This study not only improves the emergency response strategies for urban residential fires, but also provides customized fire safety policies for different urban environments, effectively reducing fire risk. Through the introduction of resampler technology and interpretable machine learning, this study not only improves the prediction accuracy of the model, but also enhances the transparency and interpretability of the model, providing a more scientific and reliable tool for fire risk management..
Cross-physical field prediction method for smoke field distribution in commercial building fire based on distributed optical fiber sensor
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Journal of Building Engineering 2024
This study uses a single fiber optic sensor to achieve dynamic prediction of different physical fields, and expands the application range of fiber optic sensors to monitor gas and visibility fields in commercial building fires. This not only improves the level of fire monitoring, but also effectively reduces the cost of equipment. It provides effective data support for planning individual evacuation routes and firefighter rescue arrangements, further ensuring personnel safety.
Cross-physical field prediction method for smoke field distribution in commercial building fire based on distributed optical fiber sensor
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Journal of Building Engineering 2024
This study uses a single fiber optic sensor to achieve dynamic prediction of different physical fields, and expands the application range of fiber optic sensors to monitor gas and visibility fields in commercial building fires. This not only improves the level of fire monitoring, but also effectively reduces the cost of equipment. It provides effective data support for planning individual evacuation routes and firefighter rescue arrangements, further ensuring personnel safety.