The Inclusion of End-of-Life Modeling in the Life Cycle Energy Optimization Methodology
Author(s) -
Hamza Bouchouireb,
Merle-Hendrikje Jank,
Ciarán J. O’Reilly,
Peter Göransson,
JosefPeter Schöggl,
Rupert J. Baumgartner,
José Potting
Publication year - 2020
Publication title -
journal of mechanical design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.911
H-Index - 120
eISSN - 1528-9001
pISSN - 1050-0472
DOI - 10.1115/1.4048447
Subject(s) - energy (signal processing) , incineration , engineering , energy recovery , phase (matter) , optimal design , reliability engineering , automotive engineering , computer science , waste management , statistics , chemistry , mathematics , organic chemistry , machine learning
In this study, an end-of-life (EOL) model is included in the life cycle energy optimization (LCEO) methodology to account for the energy burdens and credits stemming from a vehicle’s EOL processing phase and balance them against the vehicle’s functional requirements and production and use-phase energies. The substitution with a correction factor allocation method is used to model the contribution of recycling to the EOL phase’s energy. The methodology is illustrated through the optimization of the design of a simplified vehicle subsystem. For the latter, multiple recycling scenarios with varying levels of assumed recycling induced material property degradation were built, and their impact on the vehicle subsystem’s optimal solutions was compared to that of scenarios based on landfilling and incineration with energy recovery. The results show that the vehicle subsystem’s optimal designs are significantly dependent on the EOL scenario considered. In particular, the optimal designs associated with the recycling scenarios are on average substantially heavier, and less life cycle energy demanding, than their landfilling or incineration with energy recovery-related counterparts, thus demonstrating how the inclusion of EOL modeling in the LCEO methodology can significantly alter material use patterns, thereby effecting the very mechanisms enabling the embodiment of the resulting life cycle energy optimal designs.
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