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PRODID:-//PHD in Industrial Engineering - ECPv6.15.20//NONSGML v1.0//EN
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X-WR-CALNAME:PHD in Industrial Engineering
X-ORIGINAL-URL:https://academics.dii.unipd.it/phd
X-WR-CALDESC:Events for PHD in Industrial Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
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TZID:UTC
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TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260921T080000
DTEND;TZID=UTC:20260922T170000
DTSTAMP:20260419T112144
CREATED:20260413T151830Z
LAST-MODIFIED:20260413T151858Z
UID:3268-1789977600-1790096400@academics.dii.unipd.it
SUMMARY:Python for numerical heat transfer modeling and building physics
DESCRIPTION:Course unit contentsDespite the rapid rise of data-driven methodologies\, physics-based modeling remains a crucial\, flexible\, and adaptable tool for engineering research. This course provides a practical introduction to transient heat transfer and building physics modeling\, leveraging the Python programming language to bridge theoretical foundations with computational implementation. \nThe programme begins with a brief introduction to Python\, covering data structures\, control loops\, essential libraries\, and data visualization. Students will then progress to developing their first models\, specifically investigating 1D heat transfer through solid elements and the dynamics of radiant panels. The course extends into more complex architectural modeling\, including the development of Resistance-Capacitance (RC) networks for whole-building simulations and an introduction to model calibration techniques. The course concludes with a project discussion\, where students present and refine their simulations of real-world scenarios—such as radiant floor heat flux and transient building behavior—ensuring a deep understanding of the practical guidelines required for high-fidelity physical modeling. \nLearning goalsParticipants will master the basic principles of establishing and solving physics-based systems using both implicit and explicit numerical solution schemes. A primary objective is to develop proficiency in Python for scientific applications\, enabling PhD students to translate physical laws into robust simulation models for transient thermal phenomena. \nSuggested readings\nTransition from MATLAB to Python. https://www.enthought.com/wp-content/uploads/2019/08/Enthought-MATLAB-to-Python-White-Paper_.pdf\nThink Python. https://greenteapress.com/wp/think-python-2e/Physics modeling\nASHRAE Fundamentals. Incropera F.\, De Witt D. Fundamentals of Heat Transfer\, John Wiley&Sons. 1981 or other edition.\nBuilding Physics – Applications in Python. https://www.researchgate.net/publication/353514722_Building_Physics_-_Applications_in_Python\nSolving inverse problems in building physics: an overview of guidelines for a careful and optimal use of data. https://srouchier.github.io/files/2018-enb-review.pdf
URL:https://academics.dii.unipd.it/phd/event/python-for-numerical-heat-transfer-modeling-and-building-physics/
LOCATION:Sede-V\, via Venezia 1\, Padova\, Padova\, 35131\, Italy
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://academics.dii.unipd.it/phd/wp-content/uploads/sites/58/2026/04/CDII_python-scaled.jpeg
ORGANIZER;CN="PhD Course in Industrial Engineering":MAILTO:dottorato.dii@unipd.it
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