Mija FrossardPhD Student

MINES ParisTech

Mija Frossard is an engineer and doctoral student at the CES (Centre for Energy Efficiency of Systems). His PhD thesis focuses on the development of decision support tools that integrate consideration of prospective uncertainties in eco-design of buildings. His skill set covers DES (dynamic energy simulation), LCA (life-cycle assessment), multicriteria genetic optimisation, decision support under uncertainties and the Python and Matlab programming languages. The environmental resilience of buildings and territories is a subject that he tackles with a complex system transdisciplinary approach.

Ecodistrict in Paris
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Life-cycle assessment is a method to assess the environmental impacts of buildings and infrastructures throughout their life cycle, from the extraction of raw materials through to their end-of-lifetime handling.
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Office building with solar panels
Buildings can be designed and operated to radically improve their energy efficiency and reduce their environmental impact.
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Scientific publications
Conference papers
Mija Frossard, Bruno Peuportier, Patrick Schalbart Optimisation multicritère et analyse de cycle de vie de bâtiments zéro-énergie
IBPSA France: Conférence Francophone de l'International Building Performance, May 2018, Bordeaux, France
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Conference papers
Bruno Peuportier, Mija Frossard Le projet européen A-ZEB, Affordable zero energy buildings (bâtiments zéro énergie à coût abordable)
PASSIBAT 2018, Mar 2018, Paris, France
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An optimisation procedure will be used to complete the environmental assessment of a block of buildings while reducing economic costs and the overall impact on the environment.
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This software program for life cycle assessment of neighbourhood projects is used to measure the environmental impacts from the manufacture of materials to the end of their life.
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This dynamic thermal simulation model of buildings anticipates energy consumption and the risk of discomfort in all seasons. Thanks to the Amapola module, this software program makes it possible to identify the least
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