A large scale artificial dataset to evaluate the impact of on-board monitoring set-ups on the Heat Transfer Coefficient assessment

Ritoša, Katia; Sælens, Dirk; Roels, Staf

doi:10.1016/j.enbuild.2023.113061

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…The simulated large-scale dataset used in this work was generated according to the procedure described in [12] and it represented a sample of 1012 real-life single-family Flemish houses. The envelope properties were allocated from surveys conducted on newly built houses, after 2006, thus reflecting well-insulated and heavy-weight typology.…”

Section: Methodsmentioning

confidence: 99%

How reliable is the co-heating test?

Ritosa,

Saelens,

Roels

2023

J. Phys.: Conf. Ser.

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The predicted or designed envelope’s energy performance often differs from the in-reality achieved one and this phenomenon, known as the building fabric performance gap, is usually caused by poor workmanship or material properties differing from ones specified in the design phase. To bridge this gap, and quantify the achieved envelope’s thermal characteristics, different methodologies based on dedicated on-site monitoring campaigns are applied. One of the recognized methods for evaluating the building’s Heat Loss Coefficient (HLC) is the co-heating test, during which a vacated house is submitted to elevated temperatures while the delivered heat and the indoor and outdoor environments are precisely monitored. In recent years, researchers are turning towards non-intrusive methods and to validate them the co-heating test is often recognized as the benchmark. However, the validity of this approach is hard to prove since the reference is undefined, therefore, the aim of this work is to evaluate the reliability of the HLC estimation by the co-heating test. Since in this investigation actual reference values are required, such an assessment was performed by applying the co-heating testing procedure and established statistical models to artificially generated data which resemble ideal monitoring campaigns. In this work, the prescribed co-heating testing procedure and statistical models are applied to a simulated sample size of single-family dwellings characteristic of Flanders. The main aim here is to assess the trends in the results when different estimation approaches are applied to the same ideal monitoring dataset. Moreover, the analysis can be performed on a large sample size and, since indoor conditions are prescribed, outdoor conditions can be manipulated in a way to isolate the effect of different weather parameters on the estimation.

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Section: Methodsmentioning

confidence: 99%

How reliable is the co-heating test?

Ritosa,

Saelens,

Roels

2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…The selected sample of houses reflects a high-performing building stock built after 2006, geometries originate from detailed scans of a real neighbourhood while the material properties are chosen considering distributions generated based on EPB reports for Flanders. A comprehensive explanation of the allocation of geometries and material properties is given in Ritosa et al [39]. A total of 1012 houses were simulated as one or two-zone buildings, depending on the number of floors which ranged from one to three floors, while the house types were detached, semi-detached or terraced and not exceeding a total useful floor area of 200 m 2 .…”

Section: Artificial Datasetmentioning

confidence: 99%

“…Since bypassing measurement deviations is only possible with simulated data, this study focuses on a largescale artificial dataset where monitoring campaigns were generated using white-box simulated models representing 1012 high-performing single-family houses for a typical Flemish neighbourhood [39]. The generated data served as a basis for the application of the prescribed co-heating testing procedure and statistical models and it provides a singular opportunity for investigating the impact of different parameters and the validity of the HLC estimated by co-heating tests.…”

Section: Introductionmentioning

confidence: 99%