Open AccessA multiple Linear Regression Model to predict indoor temperature trend in historic buildings for book conservation: the case study of “Sala del Dottorato” in Palazzo Murena, Italy
Author(s) -
Elisa Moretti,
Maria Giulia Proietti,
Ettore Stamponi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2069/1/012142
Subject(s) - microclimate , environmental science , relative humidity , cultural heritage , architectural engineering , linear regression , inertia , meteorology , thermal inertia , computer science , geography , engineering , statistics , mathematics , archaeology , physics , classical mechanics , thermal
The indoor climate of historic buildings is governed by the desire to preserve them, their interiors and to ensure human comfort. For preservation of cultural heritage and libraries, relative humidity and temperature are very important parameters, including their amplitudes and changes rate in time. In the present study an experimental campaign of thermo-hygrometric parameters inside of “Sala del Dottorato”, located in Palazzo Murena (Perugia), is carried out. In this room a great number of rare and ancient books are preserved. The paper deals with the study and the evaluation of the correlation between outdoor and indoor microclimate conditions in the room, to ensure the proper conservation of the books; it is aimed at understanding how the two parameters follow outdoor variations and how the hygrothermal inertia of the building can mitigate these variations. This is done, specifically for temperature, which is the most critical aspect. Thanks to a continuous monitoring system for indoor and outdoor thermo-hygrometric parameters, a Multiple Linear Regression model is developed in order to predict and analyse the indoor temperature trend. This model allows to estimate a future forecast of this parameter and to predict in advance critical conditions for correct conservation.