Abstract
The U values assumptions for construction components represent a significant source of uncertainty when estimating the energy performance of buildings. This uncertainty affects decision-making processes in multiple ways, from policy making to design of new and refurbished buildings. The correct estimation of both static (e.g. thermal transmittance) and dynamic thermal properties is crucial for quality assurance in building performance assessment. Further, while today many sophisticated simulators are available for building performance modelling, lumped parameter models can help reducing computational time for parametric simulation or optimization and enable inverse estimation of lumped thermal characteristics. A lumped parameter approach for construction components is proposed, for example, by the ISO 52016-1:2017 norm, introducing simplifications that are intrinsically dependent on component’s stratigraphy. This approach complements ISO 13786:2017 norm method, which is limited to steady-state periodic temperature and heat flux boundary conditions. In this research we consider these two different approaches, detailed and lumped modelling, comparing them first in idealized conditions and then in experimental conditions to analyse the robustness of methods.
Highlights
The U values assumptions for construction components represent a significant source of uncertainty when estimating the energy performance of buildings [1]
Considering the present necessity of linking calculation methodologies that are applied for performance assessment in different phases of building life cycle, we report in this paper preliminary results from a test facility, following an experimental campaign on different pre-fabricated opaque construction components for high-efficiency and low-cost development in the Mediterranean area
In this case study we conducted our analysis on a pre-fabricated opaque construction component, which is part of a test facility
Summary
The U values assumptions for construction components represent a significant source of uncertainty when estimating the energy performance of buildings [1]. This uncertainty affects decision making processes in multiple ways, from policy making to design of new and refurbished buildings [2], including aspect such as indoor environmental quality [3], technical systems sizing [4] and critical issues such as long-term preservation of historical heritage buildings [5].
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