A novel model for uncertainty propagation analysis applied for human thermal comfort evaluation

Andrea Manuello Bertetto, Luigi Antonio Besalduch, Edmondo Minisci, Martin Kubicek, Roberto Ricciu

Research output: Contribution to journalArticle

39 Downloads (Pure)

Abstract

The comfort sensation is mainly affected by six variables: air temperature, mean radiant temperature, air velocity, relative humidity, personal metabolism and clothing insulation. These are characterized by different mean values and distributions. To analyze the uncertainty propagation three numerical models are used: the Fully Monte Carlo Simulation MCSs, the Monte Carlo Simulation Trials MCSt, and a novel model named "Adaptive Derivative based High Dimensional Model Representation" (AD-HDMR). In the paper these three different methods are applied to the thermal comfort evaluation, through the PMV Index, they are analyzed and their efficiency was verified in terms of computational time. To allow a revision of this index, the effect of the different variables was then analyzed.
Original languageEnglish
Article number27
Pages (from-to)246-255
Number of pages10
JournalWSEAS Transactions on Environment and Development
Volume11
Publication statusPublished - 1 Nov 2015

Keywords

  • mathematical models
  • statistical analysis
  • thermal comfort
  • engineering physics

Fingerprint Dive into the research topics of 'A novel model for uncertainty propagation analysis applied for human thermal comfort evaluation'. Together they form a unique fingerprint.

  • Research Output

    Uncertainty based optimal planning of residential building stocks retrofits

    Ricciu, R., Besalduch, A. L., Minisci, E. & Manuello Bertetto, A., 10 Jun 2019, (Accepted/In press) In : International Journal of Mechanics and Control. 20, 1, 6 p.

    Research output: Contribution to journalArticle

    Open Access
    File
  • Cite this