## 2 Materials and Methods
### T-H-O-Risk Framework  
The PRA-based T-H-O-Risk methodology includes a set of sequentially linked tools and techniques. These are used to estimate probabilities and consequences for several fire scenarios and provide output in the form of both individual and societal risk. The process is described concisely here while the complete methodology can be found in our earlier papers [27; 28; 29]. Appendix A provides more details on the T-H-O-Risk methodology that incorporates ETA, FTA, Bayesian networks, system dynamics, and fire and evacuation modelling to determine available safe egress time (ASET) and required safe egress time (RSET). Briefly, the model involves the following steps:  
1. Calculation of the frequency of ignition: the calculation is based on [32]. The resulting value is then multiplied by the probability of a fire located in a sole occupancy unit (SOU), in other words an apartment fire, or in the corridor (corridor fire). 2. Deployment of the accident scenarios and calculation of the associated probability using ETA: starting from the initiating event, the possible scenarios are derived by assuming a set of events that could or could not happen. The events are related to the effectiveness of the safety countermeasures (detection, notification, sprinkler, smoke management system) hat is linked to the type of fire (flaming or smouldering). FTA, a top-down failure analysis tool, is used to estimate the effectiveness of the safety measures. 3. Calculation of the consequences for each scenario using ASET/RSET analysis: as described elsewhere, consequences are estimated by comparison of the ASET and the RSET. The first parameter is obtained from the B-Risk fire modelling simulation by determination of the time available before untenable conditions occur; the second is obtained as the sum of the time to complete different evacuation phases (detection, notification, pre-movement, and movement). Those times are derived partly from analytical calculations (hydraulic model), and partly via B-Risk simulation. 4. Introduction of HOEs through a BN: a static evaluation of the effects of human and organisational failures is performed through a BN. The ET structure of the model is converted into the more flexible BN which allows the description of multiple relationships between variables. 5. Calculation of the individual and societal risk for different contexts (level of organization): the impact on the risk of a good or bad safety organisation is investigated using two different indicators. The first indicator is a single risk value, the Expected Risk to Life (ERL), which expresses the risk in deaths/year\"building; the second risk indicator, the SR is represented using the Frequency--Consequences (F-N) curves. F-N curves allow a comparison of the different solutions on Societal Risk which reflects average risk, in terms of death that a whole group of occupants is exposed to a fire scenario instead of looking at individual occupant. This second indicator is helpful in the decision-making process, introducing the possibility of adopting human-related countermeasures. 6. Dynamic modelling of risk variations in the system using SD: to include future changes of the various components of a complex system, the evolution along its entire life cycle should be investigated. The analysis incorporating changes over time is performed with SD: each parameter of the system is checked along a period of ten years and hypotheses are made on the evolution of their values in relationships with all other parameters. A'societal' loop is created which enables the modelling of HOEs in response to changes in the perception of the risk in the system. 7. Calculation of the time--risk curve for the entire lifecycle of the building. 8. Sensitivity and uncertainty analyses using a Monte Carlo approach. Uncertainties in point estimates of ERL values are propagated through probability distributions with Monte Carlo simulations while a family of F-N curves and confidence intervals propagate epistemic uncertainty on SRs.