A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Hybrid uncertainty quantification method of internal disturbance parameters for reliability assessment of building air-conditioning design load
Highlights An improved internal disturbance uncertainty quantification method is proposed. Possibility theory is used to reflect epistemic uncertainty in internal disturbances. The application effect of this improved method in reliability assessment is analyzed.
Abstract Internal disturbances are uncertain factors that significantly affect the reliability assessment of building air-conditioning design loads. The parameters related to these disturbances have both the aleatory and epistemic uncertainties, which have been quantified using probabilistic methods in previous studies. However, the probabilistic methods for describing the epistemic uncertainty often involve subjective assumptions that can lead to unreliable assessment outcomes. To address these limitations, a hybrid possibilistic-probabilistic stochastic model of interior disturbance parameters (referred to simply as the HPS model) is proposed to reasonably reflect the different uncertainties. In this model, the epistemic and aleatory uncertainties of the internal disturbance parameters were characterized using the possibility distribution and probabilistic models, respectively, and these two uncertainties were combined using the -cut method. By comparing the HPS model with the traditional model, the results showed that using the probability theory to describe the epistemic uncertainty of internal disturbance parameters may result in an overestimation of the reliability of the design load. Moreover, the extent of the overestimation increases as the value of the design load decreases. Therefore, using the possibility theory to describe the epistemic uncertainty of the internal disturbance parameters is recommended under insufficient information to obtain a more comprehensive reliability assessment result.
Hybrid uncertainty quantification method of internal disturbance parameters for reliability assessment of building air-conditioning design load
Highlights An improved internal disturbance uncertainty quantification method is proposed. Possibility theory is used to reflect epistemic uncertainty in internal disturbances. The application effect of this improved method in reliability assessment is analyzed.
Abstract Internal disturbances are uncertain factors that significantly affect the reliability assessment of building air-conditioning design loads. The parameters related to these disturbances have both the aleatory and epistemic uncertainties, which have been quantified using probabilistic methods in previous studies. However, the probabilistic methods for describing the epistemic uncertainty often involve subjective assumptions that can lead to unreliable assessment outcomes. To address these limitations, a hybrid possibilistic-probabilistic stochastic model of interior disturbance parameters (referred to simply as the HPS model) is proposed to reasonably reflect the different uncertainties. In this model, the epistemic and aleatory uncertainties of the internal disturbance parameters were characterized using the possibility distribution and probabilistic models, respectively, and these two uncertainties were combined using the -cut method. By comparing the HPS model with the traditional model, the results showed that using the probability theory to describe the epistemic uncertainty of internal disturbance parameters may result in an overestimation of the reliability of the design load. Moreover, the extent of the overestimation increases as the value of the design load decreases. Therefore, using the possibility theory to describe the epistemic uncertainty of the internal disturbance parameters is recommended under insufficient information to obtain a more comprehensive reliability assessment result.
Hybrid uncertainty quantification method of internal disturbance parameters for reliability assessment of building air-conditioning design load
Wu, Xia (author) / Tian, Zhe (author) / Niu, Jide (author) / Li, Xiaoyuan (author)
Energy and Buildings ; 299
2023-09-28
Article (Journal)
Electronic Resource
English
Reliability Analysis of High Rise Building Considering Wind Load Uncertainty
| BASE | 2018
Reliability Analysis of High Rise Building Considering Wind Load Uncertainty
| BASE | 2018
Quantification of Model Uncertainty in Structural Reliability
| Springer Verlag | 1997
Control Parameters and Quantification for System Reliability Design
| British Library Online Contents | 2009