## 5 Conclusions  
_Summary:_ The current study demonstrates how T-H-O-Risk methodology enhances current FSVMs by incorporating HOEs in a PRA for a more inclusive view of risk in high-rise residential buildings. The limitations of existing deterministic methods and how they are overcome using the T-H-O-risk methodology is elaborated in this paper. While the T-H-O-risk approach enables an integrated analysis of HOE factors and their nonlinear interactions and feedbacks, it generally results in a higher level of uncertainty, hence, detailed sensitivity and uncertainty analyses were performed to assess the model robustness and reliability of model outputs. _Influence of HOEs:_ The study identifies the most important HOE variables and the extent they contribute to the fire risk in high-rise buildings. Uncertainties in point estimate of ERL values are propagated through appropriate probability distributions with Monte Carlo simulations while a family of F-N curves propagate epistemic uncertainty in societal risks of the case studies. Four case studies were used for the study including the reference case from the ABCB FSVM Handbook. For each case, a performance solution, a performance solution incorporating HOEs and a DTS solution were compared using risk values that assess the level of safety. The analysis finds that the level of risk as measured by the ERL of the performance solution is lower than the DTS solution however when HOEs are considered, their influence is significant for all cases. _Sensitivity and uncertainty analyses_--A sensitivity analysis using a Monte Carlo approach found that the most influential HOE variables were 'not complying with instruc  
Figure 28: SD sensitivity analysis of ‘not comply with instructions’ and ‘inefficient timely control’ variables. tions', 'deficient training' and 'inefficient emergency plan'. An uncertainty analysis of the ERL indicates that the most influencing HOE factors determine important variations in the ERL value of the system by up to 30% of the reference value. The minimum amount of variation associated with these HOEs is approximately 3-5% indicating that HOEs impact global risk levels; the F-N curves for all cases and scenarios with HOEs shift upwards indicating risk is underestimated when HOEs are ignored. Indeed, as system complexity increases, so does the influence of HOEs on risk primarily due to increasing numbers of fire safety measures and maintenance regimes. Sensitivity and uncertainty analyses in SD risk modelling indicate that risk thresholds oscillate or spike at year seven over the 10-year cycle. Risk variation over time analysis indicates that maintenance of an active safety system is required within five to seven years due to the degrading influence of HOEs on the reliability of the system. _Advantages of T-H-O-Risk_--The research demonstrates how fire safety verification methods can be improved with the incorporation of human and organizational risks in PRA, where uncertainties in point estimates of individual risk are propagated with probability distributions while uncertainties in societal risks and risk variations over time due to human and organizational risks are propagated with confidence-interval-based societal risk curves. It is important to determine the significance of uncertainty in the PRA process, to produce effective fire safety measures for high-rise residential buildings. _State-of-the-art PRA_--Although there are instances of using HOEs for modelling in other applications and industries, this is the first state-of-the-art methodology where HOEs have been incorporated in the fire risk analysis for high-rise buildings in a comprehensive manner, where technical systems such as sprinklers and smoke detection systems are integrated with HOEs. When HOEs are ignored in a PRA, overall risk levels are likely to be underestimated given that some DTS or performance-based designs that were initially assessed as within an ALARP region may fail the tolerability limit when HOEs are included.