Objective: The operational safety resilience of urban lifeline systems refers to their ability to maintain critical functions and recover swiftly when faced with multiple disruptive events during their operational period. This resilience is crucial for ensuring the safe and uninterrupted operation of these critical systems. However, existing resilience evaluation methods often risk inaccuracies under multi-event scenarios, making it challenging to accurately assess the systems' overall resilience. To address this issue, this paper proposes a comprehensive resilience evaluation model and methodology tailored for urban lifeline systems during their operational phase. The approach considers multi-event contexts and is built on a detailed analysis of resilience mechanisms. It incorporates key factors such as resistance, recovery, and adaptability. Methods: This study presents an evaluation method for assessing the operational safety resilience of urban lifeline systems under multi-event scenarios. The methodology is structured around three main steps: analyzing resilience mechanisms, constructing a resilience evaluation model for multi-event contexts, and applying the method in a case study. First, using resilience curve theory, scenario assumptions and theoretical deductions were used to analyze the specific roles and effects of resistance, recovery, and adaptability during operational performance loss and recovery under both single and multiple disruptive event scenarios. This analysis facilitated a systematic understanding of the resilience mechanisms governing urban lifeline systems. Second, building on existing resilience metrics, the study identified misjudgment risks and limitations in current resilience evaluation models. This led to the development of an enhanced model that integrates the advantages of existing methods. The improved model accounts for resilience mechanisms, computational efficiency, and reasonable distribution. An exponential function was utilized to establish an evaluation model for urban lifeline system resilience during the operational period. Key components, including system performance indicator settings, performance calculations, the resilience evaluation model, and a comprehensive resilience judgment matrix, were incorporated to form a "four-step" evaluation process tailored to multi-event scenarios. Finally, the methodology was validated through a case study on the Hong Kong (China) MTR East Rail Line from 2005 to 2009. Service performance indicators for the metro system were identified, and the causes of annual changes in comprehensive resilience levels were calculated and analyzed. The results demonstrated the feasibility and effectiveness of the proposed evaluation method. Results: The research results revealed the following insights: (1) During the operational period, the resilience mechanisms of urban lifeline systems differ significantly between single and multiple disruptive events. In single-event scenarios, the system primarily relies on resistance to mitigate or eliminate disruptions and uses recovery to restore functionality. In contrast, in multiple-event scenarios, the system leverages adaptability, continuously optimizing resistance and post-event recovery. This enhances its capacity to respond to regular, extreme, or unknown events. (2) The proposed evaluation model, incorporating key resilience factors like resistance, recovery, and adaptability, assesses the comprehensive resilience level of the system throughout its operational period. It also measures the average resilience in single-event scenarios and cumulative resilience under multiple events. (3) Practical application demonstrates that a high average resilience in single-event scenarios does not necessarily correlate with high cumulative or comprehensive resilience. Enhancing comprehensive resilience is a long-term, dynamic process that relies on adaptability to repeatedly refine system resistance and recovery. This approach minimizes the impact of disruptive events and accelerates recovery. These findings validate the feasibility and effectiveness of the proposed evaluation method. Conclusions: This method enhances the safe operation of urban lifeline systems and serves as a valuable methodological reference for future research on resilience enhancement strategies. It also holds significant potential for application in the resilience analysis of complex coupled systems.

[Objective] Recently, extreme precipitation has increased globally. Waterlogging disasters caused by rainfall have endangered people's lives and caused property losses. As the cell of the city, the community is the fundamental unit to resiliently withstand disasters. However, stress testing in the community resilience field is still in its infancy, and little research exists on relevant theoretical and technical frameworks. Therefore, this paper uses a rainstorm waterlogging disaster as an example to study the community resilience stress test method and provides application cases. [Methods] The community resilience stress test stimulates and assesses community resilience in response to various emergency events. Herein, the resilience curve method is used to calculate community resilience. This paper presents a specific community resilience stress test method for rainstorm waterlogging disasters. First, using the historical rainstorm disaster data and rainstorm intensity formula, 12 extreme rainfall scenarios were designed according to the 2 dimensions of hourly rain intensity and rainfall duration, covering 30-200 mm hourly rain intensity. Second, based on InfoWorks Integrated Catchment Modeling, this paper constructs a community rainstorm waterlogging hydrodynamic model. This study conducted the community rainstorm waterlogging measurement experiment in the rainy season. The monitoring data obtained are used for parameter calibration and validation of the hydrodynamic model. Then, this paper presented a resilience evaluation method focusing on engineering resilience. The system performance of community rainstorm waterlogging is defined by the proportion of inundated areas. The system performance of a drainage network is defined by the fullness of the drainage network. Community waterlogging resilience was calculated using these two types of system performance. Resilience is expressed using the area of the concave portion of the system performance curve of community rainstorm waterlogging. The termination time of the integral is calculated as the time when the system performance of the drainage network returns to 1. [Results] Using the community J in Beijing as an example, this paper conducted a stress test on the community's waterlogging resilience under 12 different extreme rainfall scenarios, based on the results of hydrodynamic simulation. The results show that community resilience is less affected by rainfall duration and positively correlated with hourly rainfall intensity under rainstorm waterlogging disasters. Under the extreme rainfall scenario of 200 mm/h, about 44% of the community was flooded, and the maximum water depth was nearly 1 m. About 95% of drainage pipes are overloaded. It takes 5.7 hours to fully restore the drainage capacity of the network. Waterlogging spots of varying severity in this community are observed. This paper provides targeted suggestions on how to improve community resilience under rainstorm waterlogging disasters for five main waterlogging-prone spots. [Conclusions] This paper proposes a stress test method for community resilience to waterlogging and analyzes the evolution process of resilience and risk tolerance of community J from two perspectives: drainage capacity of pipe network and inundated area of the community. This method provides a quantitative assessment of community resilience. The test results can be used for monitoring and investigating rainstorm waterlogging risk in community institutions and government departments. These results are conducive to preventing and resolving disaster risks in advance.

In traditional disaster prevention and mitigation analyses, risk assessments for waterlogging disasters usually only consider the infrastructure resilience and natural conditions such as weather and terrain. However, with the development of resilience theory, risk assessment and countermeasures should also include flood prevention and control, emergency responses and post-disaster recovery by the government and residents. This paper presents a set of indicators for evaluating the ability of cities to deal with waterlogging disasters, including 41 basic indicators covering 13 aspects incorporated into a resilience assessment model. The resilience assessment model is then applied to Kunshan, a low lying city in Jiangsu Province, China. The results show that the Kunshan High-Tech Zone has the best resilience and the strongest ability to deal with waterlogging disasters. The index system and model evaluation results are used to develop a targeted improvement strategy for areas with poor resilience to waterlogging disasters.

The seismic resilience of buildings has attracted increasing research attention for earthquake prevention and damage mitigation. However, there have been few studies using economic analyses. This study minimized the building life-cycle costs with two models used to quantify the household willingness to pay (WTP) for improved residential building seismic resilience based on two subjective utility models using expected utility theory and prospect theory. Then, the household WTP for residential building seismic resilience was calculated and compared with the corresponding incremental costs using parameters from the Standard for Seismic Resilience Assessment of Buildings for selected new residential buildings in Beijing in 2017 as an example. The results show that improving the residential building seismic resilience to the 1 or 2 star levels is financially feasible. However, further development to the 3 star level still relies on government subsidies or other support. This study also provides some policy implications to increase the household WTP for building seismic resilience.

A safety resilience analysis of Chinese earthquake emergency response characteristics was used to develop a training program to improve the abilities of professional rescuers regarding rapid disaster assessment, survivor search and rescue, action planning and emergency medical treatment. Simulations were used to analyze building damage triggering mechanisms and damage characteristics in strong earthquakes for various working conditions. The finite element simulations of common earthquake disaster scenes show the potential distribution of survivors in the field. The simulations provide theoretical support and a quantitative basis for designing training functions such as structural support training, search and rescue training, vertical transfer training, inclined staircase training, high altitude rescue training and temporary camp construction training for emergency rescue training for earthquakes.

Leakage from underground medium pressure gas pipelines can easily lead to major fires and explosions. A physical model was developed to model accidents in real underground building structures. CFD simulations were then used to predict the gas diffusion and explosion characteristics for leaks from medium pressure pipelines. The safety characteristics of the underground space were analyzed along with the impact of the accident on the resilience of the underground space. The study concluded that 2 s and 210 s are two important critical leak times for the given leakage and space characteristics. The gas concentration in a cooked food portion of a kitchen with gas leakage reached the lower explosion limit at 2 s, while the gas concentration in the hall outside the kitchen reached the lower flammability limit at 210 s. The gas explosion overpressure in the kitchen was about 12 kPa. The explosion overpressure for a 1 m thick gas layer along the top of the hallway was approximately 24 kPa. The shock wave from the kitchen explosion had little influence on the structural stability of the building, while that from the hallway explosion damaged the building structure but did not lead to complete failure of the structure. Thus, poor fire resistance in the underground space can lead to accidents and significantly impact the safety resilience. Gas explosions can affect the bearing capacity, absorption capacity and resilience of the underground space. An accident characterization curve was then developed to show the safety resilience of underground spaces with the resilience a function of the gas leakage length. The key point when the accident transitions from the formation of a dangerous condition to an explosion and deflagration is the relative location of the ignition source. More serious accidents have longer recovery times and higher costs but with better designs after the accident. The key measures to improve the spatial resilience are to promptly close the leakage source, improve ventilation to avoid the formation of a flammable cloud, control ignition sources, increase pressure relief areas, and improve space fire performance.

Crowd evacuation simulations were used to evaluate evacuation capabilities and disaster response strategies for mountainous neighborhoods. The results were used to develop evacuation plans based on the building layout, road networks, exit distribution and greenery morphology. The simulations used an agent based model for the crowd evacuation simulations with control groups based on potential paths, spatial enclosure degree and green space layout. The simulations give the overall evacuation time, best paths, congestion characteristics and changes in the number of people in various sections. The results also show how the structure affects the crowd evacuation behavior and the overall safety to support mountainous neighborhood safety evacuation planning and disaster response planning in southwest China.