Egress Time Research Articles

Numerical analysis on the hazards of open stairwell doors in high-rise residential buildings

High-rise buildings have unique risks associated with fire as egress is often limited to stairwells. Protecting these vertical paths from the infiltration of smoke is essential for safe evacuation. Passive fire safety strategies have addressed this by using fire-rated compartmentation. Fire-rated stairwell doors are commonly compromised in residential buildings, as observations have found them propped open or failing to close correctly. Many recent fire tragedies have demonstrated the spread of smoke into the stairwell can render egress paths untenable and carry smoke throughout the building. The consequence of stairwell door openings on smoke spread in high-rise multi-unit residential buildings is evaluated in this study. The smoke spread is predicted within a 10-storey multi-unit residential building using computational fluid dynamics. Tenability predictions in the stairwells determine available safe egress time for an array of leakage and door parameters. This illustrates the relative hazard to egress where stairwell doors are not properly closed.

Coupling transport and electricity: How can vehicle-to-grid boost the attractiveness of carsharing?

Combining carsharing and vehicle-to-grid could result in synergies for decarbonizing transport and electricity systems. For carsharing operators, often experiencing financial difficulties, vehicle-to-grid service provision could generate additional revenues while supporting the integration of renewable energy. However, extant research has not yet studied customers’ interest in vehicle-to-grid carsharing. We therefore investigate whether and how vehicle-to-grid could improve the attractiveness of carsharing. Based on a stated-choice experiment in Germany and Switzerland, we compare the attractiveness of vehicle-to-grid, electric and conventional carsharing. We find that customers choose vehicle-to-grid over electric carsharing in 56.1% and over conventional carsharing in 74.2% of the choices. By estimating a multinomial, a mixed-logit, and a willingness-to-pay-space model, we find that costs show the highest relative importance for customers’ utilities despite the early adopter sample. Access and egress times as the second most important service characteristics, combined with free-floating as the preferred scheme, highlight the relevance of charging infrastructure. • Stated-choice experiment with vehicle-to-grid, electric, and conventional carsharing. • Vehicle-to-grid carsharing is more attractive to customers than current carsharing. • Costs, access and egress times are most important service attributes. • Operators and regulators need to thoroughly plan charging infrastructure.

Egress Safety Criteria for Nursing Hospitals

Nursing hospitals have a high probability of casualties during a fire disaster because they have many patients with impaired mobility. In this study, fire and egress simulations were conducted to evaluate the egress safety of a typical nursing hospital. The available safe egress time (ASET) of the prototype nursing hospital was calculated using Fire Dynamics Simulator, and the required safe egress time (RSET) was estimated by Pathfinder, reflecting characteristics of the occupants. The egress safety of the nursing hospital was then evaluated by comparing the ASET and RSET, considering the number of egress guides and delay time. According to the simulation results, the RSET increased as the egress delay time increased and the number of egress guides decreased. In addition, it is estimated that at least 20 workers (egress guides) should be on duty in the prototype nursing hospital, even during shiftwork and night duty. Based on the simulation results, egress safety criteria have been proposed in terms of normalized numbers of egress guides and egress delay time. The proposed criteria can be very easily applied to evaluate the egress safety of a typical nursing hospital in operation.

A Study on the Improvement of Evacuation Routes according to the Quantitative Evaluation of Fire Disaster Vulnerable Facilities

In this study, the available safe egress time of occupants in elderly nursing hospitals was calculated from the ignition time using Fire Dynamics Simulator by considering the evacuation characteristics of the vulnerable. The required safe egress time for each evacuation condition was also calculated using Pathfinder to determine the evacuation time. Finally, the calculated results were used to assess evacuation efficiency according to the performance of the selected evacuation route. FED-based quantitative death prediction indicated that the efficiency of single and distributed evacuation caused minimization of casualties in the event of a disaster. The results collectively justify the need for a ramp in disaster-prone facilities and highlight the importance of managing fire hazards.

Crowd behaviour in Canadian football stadia — Part 1: Data collection

Large crowd sizes at stadia events require an in-depth consideration of human behaviour, since the reliability of egress models in design depends on the confidence of the input data. However, there is little contemporary public data surrounding crowd behaviour, and its implementation into pedestrian movement models, particularly focused on Canadian demographics in stadia. A novel data collection (Part 1) and subsequent egress validation modelling of a Canadian stadium were completed to examine the variability of simulations with behavioural inputs (Part 2). The demographic distribution, pedestrian speed, exit and route choice, and areas of congestion were quantified using high resolution cameras. Behaviourally, pedestrians exited the stadium where they entered which created high levels of cross flow. It was observed that contemporary walking speed profiles for stadia will differentiate from classical profiles especially with reflection of demographic distribution by as much as 31%. Individual walking speeds, while highly variable, impacted overall egress time. Crowd density also being a factor that further reduced their speed.

Crowd behaviour in Canadian football stadia — Part 2: Modelling

In Part 1, a novel data collection exercise of a Canadian Stadium was conducted. Demographic distribution, pedestrian speed, exit and route choice, and areas of congestion were quantified using high resolution cameras. Herein, a numerical model space is built to simulate these observations in conventional software while exemplifying proper techniques. The simulations showed that using real-world behavioural data can significantly improve the accuracy of the model. When using lowest cost inputs rather than behavioural inputs, the maximum percent difference between the model and the observed egress was 15% higher. Parametric simulations showed that individual walking speeds impact overall egress time. This is in addition to crowd density also being a factor that further reduced speed. In simulations with only the fastest and slowest demographics, the maximum percent difference was 9%. Further parametric simulations increased the amount of two directional flow by 10%, which (non-linearly) increased the total egress time.

Experimental Study on the Effect of Using Smartphones on Pedestrian Flow in Straight Corridors

With the development of science and technology, smartphones are widely used in people’s daily lives. An interesting phenomenon is that many pedestrians use smartphones while walking in the public places, which not only harm and even kill in some cases, but also affect the pedestrian traffic safety. At present, most studies focus on the pedestrians in the normal state that they don’t use phones while walking. Few research has been done on the pedestrian flow when they use phones. Therefore, the experiment that the pedestrians use phones while walking in straight corridor was conducted to study the movement characteristics and compared with the normal one. From the trajectories, the lane formation can be found in all experiments and the trajectories when they use phones are more chaotic. When pedestrians distract themselves by using phones, they walk more slowly and the flow is lower, leading to the longer egress time to pass the corridor. The distance from the boundary is defined as the shortest distance between the pedestrians and the wall. When they use phones, they try to avoid collision with the wall and walk away from the wall, so the distance is further than the normal one. The nearest pedestrian distance is defined as the nearest distance among all pedestrians. When they use phones, they distract themselves and don’t have enough time to avoid collision with others, so the nearest pedestrians distance is closer than the normal one. Our findings maybe a new insight for pedestrian flow when they distract themselves by using the phones, talking with others and thinking deeply, which can enrich empirical data and contribute to the simulation model.

Exploring for Route Preferences of Subway Passengers Using Smart Card and Train Log Data

As the mode share of the subway in Seoul has increased, the estimation of passenger travel routes has become a crucial issue to identify the congestion sections in the subway network. This paper aims to estimate the travel train of subway passengers in Seoul. The alternative routes are generated based on the train log data. The travel route is then estimated by the empirical cumulative distribution functions (ECDFs) of access time, egress time, and transfer time. The train choice probability is estimated for alternative train combinations and the train combination with the highest probability is assigned to the subway passenger. The estimated result is validated using the transfer gate data which are recorded on private subway lines. The result showed that the accuracy of the estimated travel train is shown to be 95.6%. The choice ratios for no-transfer, one-transfer, two-transfer, three-transfer, and four-transfer trips are estimated to be 53.9%, 37.7%, 6.5%, 1.5%, and 0.4%, respectively. Regarding the practical application, the passenger kilometers by lines are estimated with the travel route estimation of the whole network. As results of the passenger kilometer calculation, the passenger kilometer of the proposed algorithm is estimated to be 88,314 million passenger kilometer. The proposed algorithm estimates the passenger kilometer about 13% higher than the shortest path algorithm. This result implies that the passengers do not always prefer the shortest path and detour about 13% for their convenience.

Maximizing access in transit network design

This study adopts an Access-Oriented Design (AOD) framework for optimizing transit network design. We present and demonstrate a method to evaluate the best combination of local and express alternative transit system designs through the novel concept of ‘iso-access lines’. Two bus network system designs were explored for a greenfield development in suburban Sydney: through-routed transit lines (T-ways) with higher speeds and more direct service, but longer access and egress times, and local routes that provide additional spatial coverage. We developed scenarios with T-ways only, local routes only, and both, and computed transit access to jobs as a cumulative-opportunities measure for each scenario. Local routes offer greater overall access, while T-ways provide greater access-per-unit-cost. The optimal combination of the two was established by generating ‘iso-access’ lines and determining access-maximizing combinations for a given cost by applying production-theory principles. For 15-min access, the optimal combinations had T-way service frequency equivalent to 0.48 times that of local routes. This ratio increased to 1.45, 2.05 and 2.63 for 30-min, 45- min and 60-min access respectively. In practice, the method can be applied to determine optimal transit combinations for any given budget and desired access level.

Risk Assessment through Fire and Evacuation Simulation in the Main Control Room of a Domestic Thermal Power Plant

A fire in the main control room of a thermal power plant is a significant threat to the entire power plant by incapacitating the concept of performance design to secure the safety of the power plant. In this study, using the PyroSim and Pathfinder programs to evaluate fire and evacuation risk of the main control room, the appropriate time and fire shape for evacuating people calmly were confirmed when the available safe egress time and required safe egress time of the main control room were compared. In the case of a cable fire, the simulation results indicate the heat generation rate to be more serious than the actual experimental results showed. This is because heat generation was lower in the experiment as the polymer material constituting the cable fell to the floor during combustion and no loger burns. The fire dynamics simulator results indicate that the power plant facility is safe because even these points are not considered.

A sensitivity matrix method to understand the building fire egress performance gap

A building performance gap may exist in each building area. While performance monitoring tools are available and widely applied in energy efficiency and structural health, there are currently no available performance monitoring tools in the area of fire safety. Although a fire accident is an acute phenomenon that is rare and unpredictable and makes observing a building's fire performance very difficult, the evolution of underlying factors that determine the building fire performance in a future fire is in fact a chronic phenomenon that is observable and predictable. This article proposes a sensitivity matrix method (SMM) based on Taylor series expansion to better understand the building fire egress performance gap by analyzing changes in chronic influencing factors. Uncertainty of this method is investigated against FDS simulations in an exemplar 3-story apartment building and described by two parameters: the system bias and the relative standard deviation. Combining the available safe egress time (ASET) with the required safe egress time (RSET), the resulting Egress Safety Ratio (ESR) is chosen as the key building fire egress performance indicator in case studies, and a prototype fire performance monitoring tool based on the SMM is developed, indicating its potential of tracking and closing the building fire egress performance gap.

Statistical estimation in passenger‐to‐train assignment models based on automated data

AbstractWith the rapid development of metro systems, it has become increasingly important to study phenomena such as passenger flow distribution and passenger boarding behavior. It is difficult for existing methods to accurately describe actual situations and to extend to the whole metro system due to the limitations from parameter uncertainties in their mathematical models. In this article, we propose a passenger‐to‐train assignment model to evaluate the probabilities of individual passengers boarding each feasible train for both no‐transfer and one‐transfer situations. This model can be used to understand passenger flows and crowdedness. The input parameters of the model include the probabilities that the passengers take each train and the probability distribution of egress time, which is the time to walk to the tap‐out fare gate after alighting from the train. We present the likelihood method to estimate these parameters based on data from the automatic fare collection and automatic vehicle location systems. This method can construct several nonparametric density estimates without assuming the parametric form of the distribution of egress time. The EM algorithm is used to compute the maximum likelihood estimates. Simulation results indicate that the proposed estimates perform well. By applying our method to real data in Beijing metro system, we can identify different passenger flow patterns between peak and off‐peak hours.

A systematic review and meta-analysis on the effect social groups have on the egress times of pedestrian crowds

Conflicting results in the literature raise the question of how reliable findings from single experiments on pedestrian crowd movements are. An important example is the effect social groups have on crowd egress times from confined spaces where both increases and decreases were reported. We identify only six comparable studies and conduct the first analysis on this topic that integrates evidence from multiple studies quantitatively, accounting for different sample sizes. The aggregated findings suggest social groups increase average egress times but there is insufficient evidence to reject the null hypothesis of no effect. The conflicting results across published studies are thus likely to have arisen by chance, as experiments are statistically underpowered for determining a small effect. We find no evidence for publication bias in terms of findings or statistical power. Our work presents a quantitative basis for discussing the statistical reliability of experiments considering the high context-dependency of pedestrian dynamics.

Comparison of sensitivity matrix method, power function-based response surface method, and artificial neural network in the analysis of building fire egress performance

Unlike the areas of building energy and structural health, performance monitoring tools are currently absent in the area of building fire protection. Computational Fluid Dynamics (CFD) models like Fire Dynamics Simulator (FDS) are widely applied in building fire performance design, which can be equally used to predict changes of building fire performance. However, due to its time-consuming nature, it is not realistic to apply FDS frequently. The sensitivity matrix method (SMM) has been discussed as a quick method to predict changes of building fire egress performance. However, this approach can have significant uncertainties when being applied to datasets with many input parameters due to its inherent incapability of predicting accurately system responses if input data are considerably far away from the baseline points around which a SMM is developed. Response surface methods (RSM) are commonly used to characterize the relationships between input variables and output quantities for complicated problems. Different from conventional RSMs, a novel two phase power function fitting process is proposed to develop substitute algebraic models of the available safe egress time (ASET) from FDS numerical experiments based on a theorem which states that an output variable is proportional to the product of input parameters to their respective powers if the output variable is proportional to each input parameter to some power and the input parameters are independent of each other. An artificial neural network (ANN) is a universal method to approximate any arbitrary complicated, nonlinear system response with limited number of discontinuities without deep understanding of how the system works. This paper employs MATLAB's feedforward neural networks with error backpropagating algorithm to approximate the FDS response. Applicability in terms of uncertainties including system bias and relative standard deviation (RSD) or percentage of predictions falling in a preset acceptable error range are compared among RSMs developed from various datasets, ANNs with various hidden layer sizes and dataset sizes, and SMMs which use the same fire scenarios in a small three-story apartment building. The result shows that it is possible for ANNs to have lowest model uncertainties and highest percentage of predictions within the preset 20% error scope as far as the specific fire egress safety problem discussed in this paper is concerned, but the cost of developing a SMM, namely the number of data cases, is the lowest. Due to the different aspects of RSMs, ANNs, and SMMs, to better understand the building fire performance gap continuously, a hybrid strategy of starting with SMMs followed by RSMs and/or ANNs is recommended in a fire performance monitoring tool. • A novel Response Surface Method is proposed based on two-phase power function fitting. • MATLAB's feedforward NN with error backpropagating algorithm is employed to approximate the FDS simulation results. • The applicability of Sensitivity Matrix Method, Response Surface Method, and Artificial Neural Network is compared. • A hybrid strategy of starting with SMM followed by RSM and/or ANN is recommended in a fire performance monitoring tool.

What drives the utility of shared transport services for urban travellers? A stated preference survey in German cities

The supply of shared mobility solutions has been increasing during the last years, so has the popularity of Mobility-as-a-Service. Both promise an easy access to and usage of shared vehicles or shared rides. Nevertheless, usage of these services remains low in German cities. Hence, the question arises: what determines the utility of travellers regarding shared modes and how is this different to conventional modes? To answer this, we conduct a stated preference experiment amongst 1,445 respondents (8,670 observations). The sample is drawn from residents of the 83 largest cities in Germany. We consider four shared (e-scooter-, bike-, carsharing, and ridepooling) and three conventional modes (walking, private car, and public transport). We estimate a mixed logit model and calculate the respective value of travel time (VoT) as well as the value of access, egress, and parking search time. The importance of the individual attributes is analysed drawing on a part-worth analysis. Further, we calculate average treatment effects to show simulated mode-choice probability changes. We find that costs are more important than travel time for carsharing and ridepooling whilst they are equally important for the remaining modes. For shared services, access is more important than egress. Moreover, among the shared services, e-scootersharing shows the highest VoT (23.73 EUR/h), followed by bikesharing (18.53 EUR/h). Finally, cost changes to private cars and public transport show the highest simulated shifting potential with carsharing profiting most from cost increases in these two modes.

One-Way Coupling of Fire and Egress Modeling for Realistic Evaluation of Evacuation Process

In the discipline of fire engineering, computational simulation tools are used to evaluate the available safe egress time (ASET) and required safe egress time (RSET) of a building fire. ASET and RSET are often analyzed separately, using computational fluid dynamics (CFD) and crowd dynamics, respectively. Although there are advantages to coupling the ASET and RSET analysis to quantify tenability conditions and reevaluate evacuation time within a building, the coupling process is computationally complex, requiring multiple steps. The coupling setup can be time-consuming, particularly when the results are limited to the modeled scenario. In addition, the procedure is not uniform throughout the industry. This paper presents the successful one-way coupling of CFD and crowd dynamics modeling through a new simplified methodology that captures the impact of fractional effective dose (FED) and reduced visibility from smoke on the individual evacuee’s movement and the human interaction. The simulation tools used were Fire Dynamics Simulator (FDS) and Oasys MassMotion for crowd dynamics. The coupling was carried out with the help of the software development kit of Oasys MassMotion in two different example geometries: an open-plan room and a floor with six rooms and a corridor. The results presented in this paper show that, when comparing an uncoupled and a coupled simulation, the effects of the smoke lead to different crowd density profiles, particularly closer to the exit, which elongates the overall evacuation time. This coupling method can be applied to any geometry because of its flexible and modular framework.

BIM-Based Co-Simulation of Fire and Occupants’ Behavior for Safe Construction Rehabilitation Planning

Construction renovation projects increase the risk of structural fire, mostly due to the accumulation of combustible construction materials and waste. In particular, when the building remains operational during such projects, the redistribution of occupants and interruptions with access corridors/exit egress can exponentially increase the risk for the occupants. Most construction projects are, however, planned and scheduled merely based on the time and budget criteria. While safety is considered paramount and is meant to be applied as a hard constraint in the scheduling stage, in practice, safe evacuation considerations are reduced to rules of thumb and general code guidelines. In this paper, we propose simulation as a tool to introduce safety under structural fire, as a decision criterion, to be mixed with time and budget for selecting the best construction schedule alternative. We have used the BIM (building information model) to extract the building’s spatial and physical properties; and have applied co-simulation of fire, through computational fluid dynamics (CFD), and occupants’ evacuation behavior, through agent-based modeling (ABM) to estimate the average and maximum required safe egress time for various construction sequencing alternatives. This parameter is then used as a third decision criterion, combined with the project’s cost and duration, to evaluate construction schedule alternatives. We applied our method to a three-floor fire zone in a high-rise educational building in Montreal, and our results show that considering the fire safety criterion can make a difference in the final construction schedule. Our proposed method suggests an additional metric for evaluating renovation projects’ construction plans, particularly in congested buildings which need to remain fully or partially operational during the renovation. Thus, this method can be employed by safety officers and facility managers, as well as construction project planners to guide accounting for fire incidents while planning for these types of projects.

Evaluation of fire smoke control in underground space

The main goal of the fire management strategy is to avoid people interaction with fire hazards, therefore several studies are carried out for optimal escape route planning as well as smoke management and mechanical ventilation design. Underground spaces are a special case of study due to their technical characteristics that create different fire spread conditions compared to conventional buildings. In this paper, a comparative study on the fire smoke propagation is carried out taking into account the use and performance of smoke mitigation techniques. The Underground Hazardous Waste Management Repository of Lavrion Technological and Cultural Park in Greece, is selected as a case study to achieve the paper objectives. A Computer Fluid Dynamic software is used to simulate various fire scenarios based on the specific characteristics of the underground space. Parameters that have significant impact on evacuation procedure and human health such as visibility and carbon monoxide concentration are monitored. Finally, the results are presented and an evaluation method is proposed based on evacuation simulation results, in order to predict the impact of the smoke control design on the conditions inside the underground space. The results reveal that the ventilation shaft (passive system) offers an effective smoke control without any other combined control system and that the installation of smoke curtains, which are activated on time, offers significant improvement on smoke spread control extending the available egress time (ASET) in case of fire.

663 QUANTITATIVE PERFUSION ASSESSMENT TO PREDICT ANASTOMOTIC LEAK AFTER ESOPHAGECTOMY

Abstract Impaired gastric conduit perfusion is a risk factor for anastomotic leak after esophagectomy. Most studies evaluating conduit perfusion have been qualitative with limited impact on post-operative care. The aim of this study is to evaluate the feasibility of intraoperative quantitative assessment of gastric conduit perfusion with indocyanine green (ICG) fluorescence angiography as a predictor for cervical esophagogastric anastomotic (CEGA) leak after esophagectomy. Methods ICG fluorescence angiography using the SPY elite® (Stryker, MI, USA) system was performed in patients who had undergone a transhiatal or McKeown esophagectomy CEGA from July 2015 through December 2020. Fluorescence angiography assessed Ingress (dye uptake) and Egress (dye exit). Ingress Index, Ingress Time, Egress Index, and Egress Time at two anatomic landmarks (tip of the conduit, and 5 cm from tip) were calculated from the measured curve of fluorescence (Figure). The collected data between the leak (L) group and the no-leak (NL) group were compared by both univariate and multivariable analyses to analyze risk factors potentially associated with CEGA leak. Results 304 patients were evaluated. There was no significant difference in patients' demographic and post-operative complications between the groups (L n = 73; NL n = 231), except for anastomotic stricture (42.5 vs 9.1%, p < 0.01). 5 cm and Tip Ingress Index were significantly lower in L (35.0 vs 45.1% and 17.4 vs 25.7%, p < 0.01). 5 cm Ingress Time was significantly higher in L (70.6 vs 56.8 sec, p < 0.01). On multivariable analysis, these variables retained statistical significance, suggesting that these three variables can be used to predict future leak. Conclusion This study revealed that gastric conduit perfusion correlates with the incidence of CEGA leak. Intraoperative measurement of gastric conduit perfusion may be predictive for CEGA leak following esophagectomy. These variables can be easily collected intraoperatively with the SPY study and used to make clinical decisions which may avert CEGA leak.

Pedestrian lane formation and its influence on egress efficiency in the presence of an obstacle

Due to the inevitability of placing obstacles when designing walking facilities, it is important to understand the influence of the obstacle during pedestrian egress to build a safer and more efficient walking environment. However, previous experimental studies on the influence of the obstacle during egress tend to be controversial: some suggest improving egress efficiency, whereas others do not. This controversy is probably due to the diversified obstacle layouts and pedestrian pushing degree, making the influencing mechanism of the obstacle layout alone dubious. In this paper, we focus on the obstacle layout and explore its influencing mechanism on pedestrian egress efficiency under conditions without intentional physical pushing. Controlled experiments were conducted under various obstacle layouts in terms of obstacle size and obstacle-exit distance. The preliminary analysis revealed that the obstacle layout affected egress efficiency, which we hypothesized was due to the pedestrian lane formation, i.e., the single-files of self-organized pedestrians directed toward the exit. For a quantitative validation, we proposed a novel two-layer k-means clustering method to recognize the pedestrian lanes that are nearly parallel. Accordingly, the deviation parameter, which represented the deviation of pedestrians from the established lane, was proposed to evaluate the lane-formation status. We also found a positive correlation between the deviation parameter and the egress time, suggesting that worse lane-formation status could lead to lower egress efficiency. Moreover, the deterioration of the lane-formation status was mainly caused by the lane-changing behavior, which indicated pedestrian movements from one lane to another. Further analysis showed that the lane-changing behavior was presumably motivated by the tendency of pedestrians to pursue better egress direction before the exit. Results indicated that the obstacle can be used to adjust the pedestrian lane-formation status, thus controlling the egress efficiency. We would also suggest the possibility of stabilizing the egress efficiency through restraining the pedestrian lane-changing behavior. We expect this paper to contribute to the reasonable placement of obstacles in actual walking facilities with diversified obstacle layouts and pedestrian characteristics.