Uncertainty and sensitivity analysis applied to hygrothermal simulation of a brick building in a hot and humid climate

Abstract

This paper presents a statistical approach for uncertainty and sensitivity analyses applied to 14 inputs whose 10 properties associated with brick material, using the four different EnergyPlus wall models. The variability of inputs has been extracted from several characterization works presented in IEA Annexes 14, 24 and 55, being coherent to the lack of knowledge in the early design stage. Besides the methodology, this paper presents the moisture effects on cooling energy demand and indoor air conditions, using a simple building geometry and the humid climate of Singapore. Results are presented in terms of uncertainty quantification, most uncertain parameters and sensitivity indices for all models, illustrating the impact of moisture and the importance of the need to well define moisture-dependent functions. The methodology is well adapted for use in complex interactive models with a low-cost simulation and can be used to reduce uncertainties in the design stage and promote reliability of retrofitting assessment.

Keywords:

• uncertainty and sensitivity analysis
• reliability assessment
• hygrothermal performance
• moisture effects on building performance
• brick properties
• enegyplus ou EnergyPlus

Nomenclature

;	=	material specific heat capacity; water specific heat capacity (J/kg  K)
	=	EMPD active layer depth (m)
	=	liquid transport coefficient (m2/s)
	=	total enthalpy (J/m3)
	=	evaporation enthalpy of water (J/kg)
	=	number of harmonics (–)
	=	number of simulation (–)
	=	saturation vapour pressure (Pa)
RH	=	relative humidity (–)
	=	sensitivity index of ith input (–)
	=	time (s)
	=	temperature (°C)
	=	moisture content by mass (kg_moisture/ kg_dry)
	=	output total variance
	=	output partial variance associated with the ith input;
	=	moisture content by volume; humidity ratio (kg/m3)
	=	length (thickness) (m)
	=	ith input value
	=	output value
Greek symbols	=
;	=	vapour permeability in air; vapour permeability in material (vapour diffusion coefficient) (kg/m s Pa)
;	=	constant thermal conductivity at 60% RH; thermal conductivity of the moist material (W/m K)
	=	vapour diffusion resistance factor (–)
	=	bulk density (kg/m3)
	=	time period (s)
	=	relative humidity (–)
	=	angular frequency (rad/s)
Upper scripts	=
	=	estimated value
	=	surface value

Additional information

Funding

The authors are very grateful for the strong support for the research carried out at the Laboratory of Thermal Systems of PUCPR, by means of CNPq of the Ministry of Science, Technology and Innovation and CAPES of the Ministry of Education for the post-doctoral scholarships.