PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 23, 2024Journal of Building Engineering14 citationsOpen Access

A validated multi-physic model for the optimization of an innovative Trombe Wall for winter use

View Full Paper
PBPiero BevilacquaRBRoberto BrunoSGS. Gallo

Key Points

Key points are not available for this paper at this time.

Abstract

Trombe walls are passive systems integrated into the building envelopes that contribute to limiting heating demands. Usually, to rationally use the absorbed solar radiation, traditional configurations are not equipped with an insulating layer in the massive structure, and this feature could be in contrast with rules that impose the achievement of limited thermal transmittances. Alternative modifications such as the Thermo-Diode Trombe Wall, partially transparent and with appreciable insulation properties can overcome this issue. This study validates a multi-physics model of such an innovative solution through data provided by an experimental set-up properly monitored. A parametric study was then conducted to investigate how important geometrical and physical properties affect the thermal performances of the proposed solution. Results confirm that air temperatures over 35 °C can be achieved in the upper part of the solar space maintaining air velocity below 0.2 m/s and allowing for transferring significant thermal loads to the adjacent room. Simulations identified 24 cm as the optimum solar space thickness, whereas insulation layers over 12 cm do not improve thermal performances significantly but increase the system encumbrance. If the thermal conductivity of the separating wall is doubled, a percentage increase of 24% of the transferred peak heating load was detected reaching a value of 28 W/m2. Results confirm the proposed system as a feasible solution to meet energy-saving purposes and regulation constraints in the building design.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bevilacqua et al. (2024) studied this question.

synapsesocial.com/papers/68e77c94b6db6435876f0ffchttps://doi.org/10.1016/j.jobe.2024.108915
Ask AI
Helpful
Bookmark
Share
View Full Paper