Evacuation Distance Research Articles

Estimating Evacuation Distance, Time, and Range to Shelters Through Network Analysis

This study employed the QGIS spatial information analysis tool to conduct network analyses through the O-D Matrix and ISO-Area methods. These network analyses calculated travel distances and evacuation times from flooded residential buildings (evacuation start points) to shelters (evacuation end points) in the event of a reservoir collapse. Feasibility of evacuation from each residential building was assessed by comparing the evacuation time with the initial flood wave arrival and peak flood level occurrence times. Walking speeds were set based on population characteristics: 1 m/s for children and the elderly and 2 m/s for adults (fast walking). Using a walking speed of 1 m/s, evacuation zones were established at 300-meter intervals, representing a 5-minute walking distance for each shelter. The resident population per building was estimated to determine the number of evacuees, and shelter capacity was calculated based on the required space per person.

The Collection and Compilation of Small Group Data for Scenario Setting of Simulations and Experiments

The influence of small groups in evacuation cannot be ignored. However, the current simulations and experimental studies have oversimplified the settings of small groups and evacuation scenarios. A significant disparity exists between the findings of existing studies and real-world scenarios. This paper compiled data on the number and size of small groups and the location of small group members in built environments. Subsequently, a scenario with intricate functions and shapes was established, and finally, these data was employed in agent-based simulations. The data encompassed 50 small groups comprising a total of 111 members. These groups, ranging from 2 to 4 members each, exhibited spatial separations between members spanning from 1 m to 23 m. Simulation outcomes indicated a detrimental effect of small groups on overall evacuation. A significant and positive correlation was observed between the distance separating small group members and the escalation in evacuation time, total jam time, and evacuation distance. The data provides a foundation for configuring initial scenarios in small group evacuation experiments and simulations. The simulation results can provide a basis for hospital safety evacuation management.

Multi-Objective Evcuation Planning Model Considering Post-Earthquake Fire Spread: A Tokyo Case Study

As an integral part of the 2030 Agenda for Sustainable Development, Disaster Risk Reduction (DRR) is essential for human safety and city sustainability. In recent years, natural disasters, which have had a tremendous negative impact on economic and social development, have frequently occurred in cities. As one of these devastating disasters, earthquakes can severely damage the achievements of urban development and impact the sustainable development of cities. To prepare for potential large earthquakes in the future, efficient evacuation plans need to be developed to enhance evacuation efficiency and minimize casualties. Most previous research focuses on minimization of distance or cost while ignoring risk factors. We propose a multi-objective optimization model with the goal of reducing the risk during the evacuation process, which is called the risk reduction model (RRM). Problem-specific indicators for screening optimal solutions are introduced. The research selects the Ogu area in Tokyo as a case study, where there is a relatively high density of wooden structures, increasing the risks of building collapse and fire spread after an earthquake, and is based on a two-phase evacuation flow that considers secondary evacuation for fire response. The results indicate that, in this case, RRM can, in most situations, reduce the risk level during the evacuation process and improve evacuation efficiency and success rate without significantly increasing the total evacuation distance. It proves to be superior to the traditional distance minimization model (DMM), which prioritizes minimizing the total distance as the objective function.

Integrated assessment of bioaerosol dispersion patterns and infection risk in a typical urban environment: Implications for urban biosecurity management

Exposure to bioaerosols in high-density urban environments will pose a severe threat to human life and health and present significant challenges to the sustainability and resilience of cities. In this study, the aerodynamic dispersion patterns of bioaerosols at two release locations (open and dense areas) under both thermal conditions in Zhongguancun, Beijing, are investigated. By coupling a dose-response model and an improved cellular automaton, the infection risk within exposed populations was assessed, and emergency evacuation strategies for distinct populations in high-risk areas were devised. This study reveals that bioaerosol distribution is notably influenced by factors such as thermal conditions, release locations and pedestrian height. Bioaerosol concentration above the release source decreases with increasing pedestrian height at two release locations. Under the same exposure time, the infection probability of different groups in this area declines with pedestrian height increases, with adult males having the highest and elderly females having the lowest probability. Thermal conditions and building layout near the release source were second only to exposure time in influencing infection probability and evacuation path. Proximity to the release source indicates a high infection probability but a short evacuation distance to safe areas, while downstream areas exhibit lower infection probability but require longer evacuation distances. The layout of buildings near the release source has the most significant effect on evacuation time. Evacuation for high-risk populations should be prioritized upstream or either side of the mainstream. This study aims to mitigate potential biological threats, address challenges in enhancing urban biosecurity management, and enable sustainable urban development.

Evacuation information methodology that combined a flooded environment and pedestrian behavioral model

Disaster information influences decision-making. Wireless internet and location-based services, aided by recent technological advances, have laid the foundation for providing personalized disaster information. Despite the provision of simple disaster forecasts and warnings, provision of specific evacuation actions (“where” and “how,” i.e., location and reachability of safe areas) and location-based personalized information that consider real-time disaster situations are a pressing priority. Thus, this study proposed and developed a three-step methodology for providing disaster information during floods that combined a flooded environment and pedestrian behavioral model, namely, 1) prediction of the flooded environment, 2) analysis of evacuation routes based on the movement time of evacuees according to the flood depth, and 3) provision of evacuation information by selecting the optimal evacuation route. This model was demonstrated in the Gangnam Station area in Seoul, Korea. Flooded environment prediction modeling of the target area was performed by applying the 100-year rainfall design to the Storm Water Management Model. The optimal evacuation route, according to the flood depth, was selected by applying the behavioral model (movement time calculation formula) for each evacuee derived through an evacuation behavior experiment. The pre- and post-flooding age- and gender-wise total evacuation distance and time were compared and analyzed. Post-flooding, the evacuation distance and time increased by 168.3% (381.34 m) and 172.3% (3.16 min) on average, respectively, indicating that evacuees must travel farther and longer. The analysis of post-flooding evacuation route change types revealed changes in evacuation distance and time in cases where shelters and evacuation routes and time were significantly different depending on evacuee characteristics (age and gender). This indicated that specific and visual disaster information can be provided according to evacuees’ age and gender using the proposed methodology. This study can serve as the basis for designing an advanced and personalized disaster information system that can provide specific evacuation actions to aid fast evacuation decision-making during floods.

Development on risk assessment model of urban ventilation based on COVID-19 pollution——A case study of an innovation base in Chongqing

Numbers of constructions have emerged due to the continuous urbanization process and the diversity of building clusters. Meanwhile, frequent global epidemics, such as COVID-19, have raised higher requirements for efficient urban ventilation. Traditional building design is insufficient to quantitatively consider the rationality of urban ventilation and corresponding risk assessments. This study carries out urban safety ventilation research and provides risk assessment models by using simulation and mathematical induction based on on-site measurement data, to realize accurate evaluation of disturbance of building clusters in urban environment, taking an Innovation Base in Chongqing as an example. The Amplification Coefficients on Urban Disturbance (ACUD) of the Innovation Base are respectively σ1 = 0.047 representing safe evacuation distance for ventilation of new buildings downstream, σ2 = 0.403 representing origin airflow disturbance retreat of new buildings, σ3 = 1.261 representing the control range of skyline design, and σ4 = 4.381 representing urban canopy ventilation boundary. The Comprehensive Risk Coefficient (CRC) of the Innovation Base in the horizontal & vertical direction of CRCh = 17.88 and CRCv = 102.97 is obtained indicating the infection risk of residents in the vertical direction is 5.76 times greater than that in the horizontal direction. The Comprehensive Pollution Disturbance (CPD) is 1.70692*10−19 kg/m3 which can be regarded as the quantitative risk assessment index of the Innovation Base under large public health safety events. This study contributes to effective support of architectural and urban design facing safe ventilation, providing theoretical support for the risk assessments, the resident control and anti-epidemic policies for both governments and residents during the worldwide epidemic situation.

Damage mitigation method studies through simulation modeling of chemical accidents

AbstractIn the chemical industry, when a fire occurs, a significant amount of energy is generated due to combustion, impacting other facilities within the plant and potentially leading to severe consequences through a domino effect. For decades, thermal radiation caused by flames has been calculated and predicted through simplified fire modeling. However, with advancements in computing technology, numerical model‐based calculations have greatly improved, allowing for a more realistic implementation that considers actual phenomena. In this study, accident data and 3D modeling information were utilized to conduct fire modeling and simulation based on actual incidents in chemical plants. Through the analysis of simulation results, the initial emergency evacuation distance was provided to minimize the damage caused by thermal radiation, and the final evacuation distance was presented using the probit function. In addition, the study evaluated the impact of generated thermal radiation and overpressure on structures and equipment, providing evidence regarding the potential for secondary incidents. Moreover, the research revealed that the impact of thermal radiation and overpressure decreases due to obstacles, offering insights into the selection of emergency evacuation routes. This study can contribute to supporting effective emergency evacuation strategies in chemical facilities.

Modelling and interpreting evacuation time and exit choice for large-scale ancient architectural complex using machine learning

The intricate spatial structures of large-scale ancient architectural complexes, combined with their complex crowd compositions, hinder evacuation efficiency. However, research on the evacuation of such complexes is limited. Moreover, among the existing evacuation studies, most solely rely on either simulation models or machine learning techniques. Few integrate the strengths of simulation modeling in capturing otherwise inaccessible evacuation data with the advantages of machine learning in addressing complex problems. This study aims to utilize random forest algorithm, based on Pathfinder simulation evacuation data, to model the evacuation time and exit choice of occupants within such complexes. Additionally, we employ tools to interpret the random forest models, analyzing the influence of various factors on evacuation time and exit choice. Specifically, this methodology was applied to examine evacuation time and exit choice of 4800 occupants, comprising both tourists and residents, within the Xidi ancient architecture complex that spans nearly 130,000 square meters. The reliability of the random forest evacuation models is validated using real experimental data. The results indicate that the impact of environmental factors on evacuation time is often nonlinear. Compared to environmental factors, individual factors tend to have a lesser influence on evacuation time. For exit choice, the influence of environmental factors varies in significance at different scales. Individual factors have a notably higher influence on exit choice than on evacuation time. We also discern that evacuation distance affects the degree to which other factors influence exit choice. Overall, this research contributes to a deeper understanding of evacuation time and exit choice in such complexes, offering decision-makers more comprehensive evacuation strategies.

Sequentially modeling household accommodation, destination, and departure time choices

During evacuations, households make a number of important, related choices including accommodation type, destination, and departure time. They may make trade-offs among these choices where one decision affects the others. The analysis models the linkages among these three aforementioned choices using data from a household behavioral intention survey conducted in 2017 in the Hampton Roads, VA area. Statistical tests and a theoretical basis show that the approach that best fits the dataset was to estimate the three choices in a sequence, where the first decision serves as an independent variable in the next choice process. To model the sequence, we began by modeling accommodation choice using a multinomial logit (MNL) model. Next, the accommodation choice decisions were used with other control variables to estimate destination choice in a second MNL model. Last, evacuation distance (related to destination decisions) was used in a Cox proportional-hazards model to estimate departure time choices. The models that provide the best estimates included the following control variables that help explain the sequence of decisions residents in the Hampton Roads area expect to make: (1) a variable expressing residential stability helps explain accommodation choice; (2) prior evacuation experience, the geographic location of a household, and the duration of living in the area help predict the destination choice; and (3) distance to the chosen destination helps predict departure time. Findings from this study provide evidence that the decisions associated with these three choices influence each other and help emergency managers identify additional actions that potentially can improve the evacuation experiences of local residents.

Human decision change in crowd evacuation: A virtual reality-based study

In complex building evacuations, continuous decision-making is unavoidable to make a sequence of route choices at intersections. Evacuees can change their initial decisions with the environmental context changes to deal with the uncertainties of the evacuation. However, this decision-changing phenomenon in evacuation wayfinding has not been well explained. Therefore, this study investigates the decision-changing behavior in crowd evacuation. The influence of two typical crowd flow modes (i.e., symmetric split and asymmetric split crowd flow) on human decision changes in evacuation wayfinding is explored. The results show that evacuees are likely to change their initial route choice decision under the influence of crowd flows, and asymmetric crowd flow significantly reinforces this trend. Moreover, crowd flow modes significantly affected participants' wayfinding performance, including evacuation time, distance, and speed. This study provides behavioral observations and empirical evidence of the persistent effects of crowd flows on evacuees' wayfinding decisions changing and performance during the evacuation.

Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm.

Shelter allocation is one of the most important measures in urban disaster prevention and mitigation planning. Meanwhile, it is essentially a comprehensive planning problem combining resource allocation and traffic routing. A reasonable allocation scheme can avoid congestion, improve evacuation efficiency, and reduce the casualty rate. Owing to the large region and large evacuation population demand, quickly solving the complex allocation problem is somewhat challenging, and thus, the optimal results are difficult to obtain with the increase of evacuation scale by traditional allocation methods. This article aims to establish a shelter allocation model for large-scale evacuation, which employs an improved quantum genetic algorithm (IQGA) based on spreading operation and considering the total evacuation distance, the capacity constraint of evacuation sites, and the dispersion of allocation results, and compare allocation schemes of the spreading model with those of models that consider different constraints. Results show that the allocation model with the spreading operation has better allocation results than that without the spreading operation. For the allocation model with spreading operation, the spreading model with different spreading speeds is more reasonable than that with the same spreading speed, and the allocation results are closer to the ideal results with the increase of constraints. In addition, according to the allocation results, the evacuation route map and the evacuation heat map are drawn to intuitively understand the distribution scheme of each shelter.

Optimal junction localization minimizing maximum miners’ evacuation distance in underground mining network

ABSTRACT Safety is a primary consideration in underground mining operations. Accidents could cause fatalities, injuries, and permanent disability of labourers, as well as irreparable financial and reputational losses. As an underground mine consists of many workspaces distributed in various zones, the selection of a junction location will be significant for timely evacuation of miners from different areas. This paper aims to determine the optimal location of the junction point for emergency evacuation in the underground network. The location problem is formulated as a MiniMax problem. Three methods are presented: Elzinga–Hearn algorithm, a three-dimensional extension of the Elzinga–Hearn algorithm, and the Welzl algorithm. The proposed methods are fully implemented in Python, and their functionality is demonstrated by conducting various case studies in 2D and 3D. The case studies showed that the proposed approaches could be used to determine junction point(s) in an underground network to serve as an evacuation location.

Which Mode Will Be Effective in a Massive Evacuation?

The earthquake which struck Eastern Japan in 2011 caused many casualties. The ratio of the mode of evacuation in areas damaged by the earthquake varied depending on geographical conditions, but cars were the primary mode in many areas. Although the Japanese government has provided guidelines to assist evacuation during a natural disaster, the disaster in 2011 demonstrated that the behavior of refugees did not adhere to these guidelines. This study analyzes refugees’ behavior during evacuations using a dataset gathered through surveys of refugees in 2011. By analyzing their evacuation speed and distance based on their geographical conditions, the necessary distance and available distance for their evacuation are calculated in this study, following which an optimized distance for evacuation is derived. Analyzing various modes of evacuation, such as walking, bicycling, and car travel, this study identifies thresholds for an efficient mode of evacuation based on evacuation distance. In conclusion, this study finds that a walking-based evacuation plan is necessary in most areas, whereas vehicles are required in areas where it is impossible to evacuate by walking.

Research on the Influence of Narrow and Long Obstacles with Regular Configuration on Crowd Evacuation Efficiency Based on Tri-14 Model with an Example of Supermarket

Regular shelves configuration forms unique characteristics of internal obstacles in a supermarket. It is crucial to study the crowd evacuation affected by obstacles during accidents or disasters in supermarkets as assembly occupancies. Based on the Tri-14 model, this paper studied the influence of safety exit designs and shelves’ configuration on the crowd evacuation efficiency with different densities in a supermarket through parameters and images. The results mainly indicate that: (1) The evacuation distance of farthest grid (Dfg) is the key factor to determine the total evacuation time of a low-density crowd. (2) For a high-density crowd, the closer the proportion ratio of the number of evacuees choosing each exit is to that of designed strand numbers of crowd flow at each exit, the higher the evacuation efficiency and average utilization efficiency of exits get; the scattered arrangement of exits will not necessarily lead to improving evacuation efficiency. Shelves’ configuration could lead to the extension of Dfg, but the change may reduce evacuation time instead, especially when forming effective advanced-gathering zones. (3) Under appropriate conditions, the impact of shelves’ configuration on evacuation efficiency can be negligible. This study has certain guiding significance for obstacle configuration and architectural design in large public gathering places.

A two-stage hierarchical model for spatial location and evacuation allocation problem of urban earthquake shelters: a case study in Central urban area of Yangbi county, Yunnan province, China

The scientific planning of urban shelters can greatly reduce property losses and casualties, and can improve the efficiency and safety of post-disaster evacuation. Based on the hierarchical characteristics of shelters and the shortcomings of previous studies on evacuation demands and blocked roads, this study proposes a two-stage multi-hierarchy planning method for shelters. In the first stage, the construction cost of shelters is taken as the objective function to complete the spatial configuration of shelters. In the second stage, the evacuation allocation model for refugees is established, which minimizes the total evacuation distance. The planning method also establishes the calculation method for dynamic high-precision refuge demands, and considers the blockage of evacuation roads caused by damaged buildings. The traditional genetic algorithm is improved and hierarchical 0-1 coding is adopted to solve the spatial configuration model of hierarchical shelters. An “exchange” heuristic algorithm is proposed to solve the hierarchical evacuation allocation model. Finally, Yangbi County in Yunnan Province, China, is taken as an empirical case to verify the applicability and accuracy of the proposed method. When the algorithm iterates to 150 rounds, the fitness function value converges to 3040675, indicating that 61 new shelters should be constructed to satisfy the refuge demands, and the minimum construction cost of these shelters is 3,040,675 RMB. The minimum evacuation distances in the first, second, and third evacuation stages are determined to be 51645192, 17351731, and 16136090 m, respectively.

Electrocautery smoke exposure and smoke evacuation in thoracic surgery: A prospective randomized study

Abstract Objective Worldwide, health care professionals working in operating rooms (ORs) are exposed to electrocautery smoke on a daily basis. Aims of this study were to determine the composition and concentrations of electrocautery smoke in the OR using mass spectrometry and investigate whether smoke evacuation systems, operative technique and distance to the cautery source are effective in reducing exposure. Methods Single-center study at our thoracic surgical unit including 122 surgical procedures. Besides room air measurements away from the operating table (n=35) and direct breath analysis (n=3), 84 minimally invasive and open procedures were in each group 1:1 computer randomized to smoke evacuation system (SES) versus no SES use and hazardous compounds were measured at the height of the operating surgeons respiratory tract. Results Irritating, toxic, carcinogenic and mutagenic volaticle organic compounds (VOCs) were observed in OR air, with some exceeding permissible exposure limits (OSHA/NIOSH). Mean total concentration of harmful compounds at surgeon height without SES was 273ppb (±189ppb) with a maximum total concentration of harmful substances of 8991ppb . Maximum total VOC concentrations were 1.6±1.2 ppm (minimally-invasive surgery) and 2.1±1.5 ppm (open surgery), and total maximum VOC concentrations were 1.8±1.3 ppm at the OR table and 1.4±1.0 ppm in OR air in general. Neither difference was statistically significant. In open surgery, SES significantly reduced maximum concentrations of specific VOCs at surgeon height, including aromatics and aldehydes. Conclusion Our data indicate relevant exposure of health care professionals to volatile organic compounds in the OR. Surgical technique and distance to cautery devices did not significantly reduce exposure. SES reduced exposure to specific harmful VOC's during open surgery.

Can Homecare Chronic Respiratory Disease Patients with Home Oxygen Treatment (HOT) in Southern Okinawa, Japan Be Evacuated Ahead of the Next Anticipated Tsunami?

An earthquake with a magnitude of 8 or 9 is predicted to occur near the Ryukyu Islands in Japan, for which the Okinawa Prefecture is preparing countermeasures. Evacuating people to a safe shelter within the tsunami arrival time is a crucial countermeasure. This study aims to understand the vulnerabilities of patients with chronic respiratory diseases in southern parts of Okinawa during a tsunami evacuation, thereby calculating evacuation distance of vulnerable patients and creating individual evacuation plans. Data for chronic respiratory patients obtained in July 2021 from the hospitals in Okinawa Prefecture include age, gender, diagnosis, residence, nearest tsunami shelter, oxygen flow at rest and walking, and maximum walking distance for 6 min based on a 6-min walk test. A quantum geographic information system was used for mapping the data. The survival potential of patients with chronic respiratory disease was evaluated by using a tsunami inundation depth of one meter and the distance within which an evacuation can be performed until the first tsunami wave reaches the nearest evacuation shelter. Results revealed a low survival potential for respiratory disease patients under the current tsunami evacuation plan. The study suggests creating an individual evacuation plan for vulnerable patients involving families and medical staff and then conducting a drill for improving the plan.

A Hybrid Decision Support Model for Deploying Humanitarian Operations to Respond to Earthquakes

This paper addresses the four essential humanitarian operations: location of emergency facilities, prepositioning of supplies, evacuation, and relief distribution by proposing a hybrid method that combines fuzzy set theory, analytic hierarchy process (AHP), a technique for order preference by similarity to an ideal solution (TOPSIS), and multi-objective programming. The objectives of the proposition are to minimize the evacuation distance, the cost of humanitarian operations, and the suitability of facilities based on qualitative factors while considering the demand, capacity, budget, and utilization constraints. Engineering managers can benefit from the collective expertise of multiple decision-makers, using their knowledge to automatically determine emergency facility location and allocation processes by running the proposed model. The model attempts to achieve a compromise solution for multiple objectives in various humanitarian operations. Finally, the real case study of the Wenchuan earthquake in China is taken to validate the model.

Simulation and Optimization of Emergency Evacuation of Huoshenshan Hospital Based on BIM and Pathfinder

After the outbreak of the Covid-19 epidemic, Huoshenshan Hospital, as the main place for patient isolation, is characterized by large floor space and high staff density, and its evacuation time is directly related to the safety of patients and medical care. In this article, we use BIM and Pathfinder software to establish an emergency evacuation simulation model, setting 2400 patients of different ages and degrees to participate in the simulation, and carry out the simulation in Steering behavior mode to study the influence of evacuation mode, exit size and initial distribution of personnel on the evacuation time and evacuation distance of Huoshenshan Hospital respectively. The simulation results provide a theoretical basis for the standardized management of Huoshenshan Hospital and have certain reference significance.

Study of Flood Disaster Mitigation Analysis for Transportation Routes in Panakukkang District, Makassar City

This study conducted an analysis study of flood disaster mitigation for transportation routes in the Panakukkang district of Makassar City. By using ArcGis software, the results of the simulation of safe and vulnerable zone levels based on color indicators are known. There are 5 villages in Panakukkang District which are flood safe zones, with the number of evacuation sites, namely 21 buildings. Then there are 4 villages which are flood alert zones with 2 evacuation sites, 2 buildings. On the first evacuation route there are 8 reference points namely Reference Point C with the distance to the nearest evacuation site 3.22 km and a travel time of 64.3 minutes. Then the reference point A with a distance to the nearest evacuation site is 2.85 km and a travel time of 57 minutes. While the reference point F is the closest point to the nearest evacuation distance 0.71 km and the travel time is 14.2 minutes. All these reference points require travel speeds of 3 km / h on foot. On the second evacuation route there are 6 Reference Points namely reference point A with distance to the nearest evacuation point 1.94 km and travel time 38.8 minutes, reference point E with distance to nearest evacuation location 1.23 km and travel time 24.6 minutes. Then at the reference point C is the closest point to the nearest evacuation distance 0.72 km and the travel time is 14.4 minutes.