A Study on the Effectiveness of Climate Adaptation Materials for Urban Heat Islands using Digital Twin and Computational Fluid Dynamics DOI Open Access

Jaekyoung Kim,

Jung Min Lee, Hwandon Jun

et al.

Korean Society of Hazard Mitigation, Journal Year: 2024, Volume and Issue: 24(5), P. 9 - 17

Published: Oct. 29, 2024

This study analyzed the impact of climate adaptation materials on mitigation urban heat islands (UHI) using digital twin visualization and computational fluid dynamics (CFD) technology. The effects UHI due to increased impervious surfaces have become more pronounced, climate-adaptation are gaining attention as potential solutions. In this study, was CFD program STAR-CCM+ based finite volume method (FVM). selected research site Byeoryang-dong, Gwacheon City, four simulation scenarios were created emissivity values asphalt concrete materials. results showed that application decreased surface aboveground (1.5 m) temperatures by 6.3 0.8 °C, respectively. suggests can significantly mitigate UHI.

Language: Английский

Participatory Framework for Urban Pluvial Flood Modeling in the Digital Twin Era DOI
Samuel Park,

Jaekyoung Kim,

Yejin Kim

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 108, P. 105496 - 105496

Published: May 5, 2024

Language: Английский

Citations

22

Exploring the network structure of coupled green-grey infrastructure to enhance urban pluvial flood resilience: A scenario-based approach focusing on ‘centralized’ and ‘decentralized’ structures DOI Creative Commons
Samuel Park,

Jaekyoung Kim,

Hyeryeong Yun

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122344 - 122344

Published: Sept. 8, 2024

Language: Английский

Citations

7

Investigating the Degradation Process of Steel Fiber-Reinforced Concrete under Sulfuric Acid Corrosion by Combining Laboratory Tests and Numerical Modeling DOI
Qihang Xu, Xin Huang,

Wang Hui

et al.

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 111598 - 111598

Published: Jan. 1, 2025

Language: Английский

Citations

0

The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data DOI Creative Commons
Julieber T. Bersabe, Byong-Woon Jun

ISPRS International Journal of Geo-Information, Journal Year: 2025, Volume and Issue: 14(2), P. 57 - 57

Published: Feb. 1, 2025

In the last two decades, South Korea has seen an increase in extreme rainfall coinciding with proliferation of impermeable surfaces due to urban development. When underground drainage systems are overwhelmed, pluvial flooding can occur. Therefore, recognizing as key flood-conditioning factors is vital for identifying flood-prone areas and developing predictive models highly urbanized regions. This study evaluates maps flood susceptibility Seoul, using machine learning techniques such logistic regression (LR), random forest (RF), support vector machines (SVM), integrating traditional conditioning drainage-related data. Together known points from 2010 2022, sixteen were selected, including parameters sewer pipe density (SPD) distance a storm drain (DSD). The RF model performed best (accuracy: 0.837, area under receiver operating characteristic curve (AUC): 0.902), indicated that 32.65% high flooding. accuracy AUC improved by 7.58% 3.80%, respectively, after variables model. research provides valuable insights management, highlighting primary causes Seoul heightened susceptibility, particularly relating infrastructure.

Language: Английский

Citations

0

Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system DOI
Li‐Chiu Chang,

Ming-Ting Yang,

Fi‐John Chang

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 379, P. 124835 - 124835

Published: March 7, 2025

Language: Английский

Citations

0

Flood prediction in urban areas based on machine learning considering the statistical characteristics of rainfall DOI Creative Commons
Sung-Chul Jang,

Jae-Hwan Yoo,

Yeonsu Lee

et al.

Progress in Disaster Science, Journal Year: 2025, Volume and Issue: unknown, P. 100415 - 100415

Published: March 1, 2025

Language: Английский

Citations

0

Enhancing Hydrogen Sulfide Control in Urban Sewer Systems Using Machine Learning Models: Development of a New Predictive Simulation Approach by using Boosting Algorithm DOI
Nguyen Duc Viet,

Miran Seo,

Yue Chen

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 491, P. 137906 - 137906

Published: March 11, 2025

Language: Английский

Citations

0

The Governance and Optimization of Urban Flooding in Dense Urban Areas Utilizing Deep Tunnel Drainage Systems: A Case Study of Guangzhou, China DOI Open Access

Jingyi Sun,

Xuewei Wu, Guanghua Wang

et al.

Water, Journal Year: 2024, Volume and Issue: 16(17), P. 2429 - 2429

Published: Aug. 28, 2024

With urban expansion, traditional drainage systems in densely populated cities face significant challenges, leading to frequent flooding and pollution issues. Deep tunnel emerge as an innovative approach, offering underground storage for excess precipitation alleviating inundation. This research investigates the deployment of a deep system Guangzhou’s core. By integrating with existing networks, this aims curtail over-flow contamination boost sewage-handling capacity. Successful implementation hinges on thorough evaluation synchronization broader development objectives. In Guangzhou, where methods fall short, tunnels present viable option. study explores techniques identifying deficiencies, devising enhancements, refining citywide strategies. Economic analysis indicates that are more cost-effective than conventional upgrades, long-term benefits land conservation efficiency. Following implementation, these markedly enhance sewage management, diminish overflow incidents, improve mitigation. Although initial investments substantial, enduring advantages preservation efficiency significant. Thus, practical flood control solution high-density areas like fostering sustainable metropolitan growth.

Language: Английский

Citations

2

Heuristic approach to urban sewershed delineation for pluvial flood modeling DOI
Samuel Park,

Jaekyoung Kim,

Junsuk Kang

et al.

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 67, P. 106129 - 106129

Published: Sept. 11, 2024

Language: Английский

Citations

2

Hydraulic characteristics of a deep tunnel system under different inflow conditions DOI
Chao Yu, Xiaodong Yu, Jian Zhang

et al.

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(11)

Published: Nov. 1, 2024

Deep tunnel systems are characterized by large burial depths, long distances, and free-surface pressurized flows, operating under complex inflow conditions that can lead to strong pressure oscillations, particularly in the transitions between main shafts. This paper focuses on deep system Shanghai, China. A physical model was established based gravity similarity, a corresponding one-dimensional mathematical for flows established. The entire process of water observed experiment, several conditions, including different discharge schemes, were conducted analyze maximum at junction shaft tunnel, as well along tunnel. deviation degree introduced validate reliability numerical model. impact distribution studied with simulation. results indicated simultaneous from both shafts leads more pronounced phase difference. downstream after stabilization higher than upstream. Simulations variations same scenarios revealed symmetric midpoint front shaft. Asymmetric only creates localized high shaft, producing greater overall. When upslope exceeds downslope inflow, it also reduce within pipeline. difference sides, smaller pressure.

Language: Английский

Citations

1