Uncertainty

Notarianni, Kathy A.; Parry, Gareth

doi:10.1007/978-1-4939-2565-0_76

Cited by 8 publications

(5 citation statements)

References 46 publications

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“…These uncertainties are related to the occupant's behaviours, the life-cycle use and safety of buildings, the occupant's risk perceptions and values, and so on. 37,38 All these uncertainty factors in the real world will have a great impact on evacuation route selection. With all these uncertainty factors considered, the route selected in the real world may have the shortest evacuation time and the lowest risk.…”

Section: Discussionmentioning

confidence: 99%

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

Song

Niu

Liu

et al. 2021

Indoor and Built Environment

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A safe and effective evacuation route is important for reducing casualties during building fires, and this topic has been a long-term focus of emergency management. Indoor space is a space within one or multiple buildings consisting of architectural components and is the basis of indoor route analyses. Based on indoor space, an indoor network model is designed that considers fire protection design, spatial matching between fire information and the indoor space, and the passability of the indoor space during a fire. Then, an evacuation route selection algorithm that considers hazard and time is proposed. The key features of the route selection algorithm, which include assessing the fire hazards, evacuation time in each indoor space and parallel computing in the route selection algorithm, are subsequently presented. Finally, taking a gymnasium as an example, case modelling and fire information integration are performed to investigate two fire scenarios and the optimal evacuation routes over time are identified in each scenario.

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Section: Discussionmentioning

confidence: 99%

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

Song

Niu

Liu

et al. 2021

Indoor and Built Environment

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show abstract

“…The Monte Carlo method involves the repeated sampling of inputs from mathematical distributions with the aim to generate a desired output distribution. 32…”

Section: Modelling Methodologymentioning

confidence: 99%

Numerical simulations of concealed residential sprinkler head activation time in a standard thermal response room test

Hopkin

Spearpoint²

2020

Building Services Engineering Research and Technology

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It is common for sprinkler heads in residential buildings to be of the concealed type. Key parameters for the thermal sensitivity of sprinkler heads are the response time index (m½s½) and conductivity factor (C factor, m½s−½). BS 9252:2011 and BS EN 12259-14:2020 outline test methods to determine whether sprinkler heads achieve adequate thermal sensitivity, stipulating that a room test be undertaken for concealed heads. In carrying out this test, neither the response time index nor C factor is defined. This paper uses computational modelling tools Fire Dynamics Simulator and B-RISK to simulate the room test. In running these simulations, maximum values for the ‘effective’ response time index and C factor needed to pass the room test can be estimated, assuming concealed heads can be represented as equivalent pendent heads. Initial deterministic simulations are used to calibrate results between Fire Dynamics Simulator and B-RISK. Monte Carlo modelling is then utilised within B-RISK, with variable parameters for the response time index and C factor (C), to estimate the relationship between the two parameters necessary to pass the room test. As a result, it is proposed that this relationship can be represented using a simple, empirical power law equation of response time index = 100 (5.4–C)2/3, where C < 5.4. Practical application: The results indicate that the minimum RTI and C factor values needed to pass the room test are greater than those needed to pass wind tunnel testing methods. In observing that equivalency is not demonstrated by the room test, and by defining the RTI/C factor relationship needed to pass the test, this paper provides fire safety engineers with amended values for concealed heads to be adopted in future assessments. In the absence of any detailed specification for sprinkler heads, it is recommended that an RTI of 290 m½s½ and a C factor of 0.5 m½s−½ may be applied.

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“…In general, different sources of uncertainty associate the problem identification and risk analysis phases in the risk assessment methodology. These uncertainties might be related to the system variability and randomness, the presence of errors, either in the measurements, or modeling and analysis, scenarios or data insignificance, and lack of knowledge, indeterminacy, judgment, and linguistic imprecision in decision making [17][18][19][20][21][22][23][24][25]. Some of these uncertainties could be reduced and others are irreducible.…”

Section: Uncertainty Classificationmentioning

confidence: 99%

“…Two uncertainty classification systems are used; the first is based on the ability to reduce these uncertainties and the second is based on their sources [18][19][20][21][22][23][24]. The first consists of two classes, i.e.…”

Section: Uncertainty Classificationmentioning

confidence: 99%

Introductory Chapter: Uncertainty Management to Support Pollution Prevention and Control Decisions

Rahman¹,

Hung²

2022

Engineering Problems - Uncertainties, Constraints and Optimization Techniques

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Uncertainty

Cited by 8 publications

References 46 publications

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

Fire hazard assessment with indoor spaces for evacuation route selection in building fire scenarios

Numerical simulations of concealed residential sprinkler head activation time in a standard thermal response room test

Introductory Chapter: Uncertainty Management to Support Pollution Prevention and Control Decisions

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