Energy transition potential in peri-urban dwellings: Assessment of theoretical scenarios in the Swiss context
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Europe is currently transitioning from fossil energy sources to renewable generation of electric power. Although fundamental to reach net-zero targets, intermittent renewables are disrupting conventional methods used in operational planning and design of p ...
Building sector decarbonisation involves large scale integration of renewable energy sources within the energy mix commonly used to fulfil the heat demand. For this, to combine several energy sources and to control conversion systems based on a systemic ap ...
HEPIA Geneva University of Applied Sciences and Arts Western Switzerland2021
Industrial process integration based on mixed integer linear programming has been used for decades to design and improve industrial processes. The technique has later been extended to solve multi-period and multi-scale problems for the design of urban ener ...
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For compact, isometrically embedded Riemannian manifolds N -> R-L, we introduce a fourth-order version of the wave maps equation. By energy estimates, we prove an a priori estimate for smooth local solutions in the energy subcritical dimension n = 1, 2. Th ...
CISBAT 2021 took place from 8 to 10 September 2021 online and at the Swiss Tech Convention Center on the campus of the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland under the heading "Carbon Neutral Buildings - Energy Efficiency & Renewabl ...
We performed the first large-scale investigation of indoor air quality (IAQ), energy and occupant behavior and satisfaction, in 650 energy-efficient dwellings in western Switzerland. The investigation included comparative assessment of 217 green-certified ...
Tomorrow's cities are already largely built, as much of the existing building stock – with a low level of energy performance – will still be standing in 2050. Urban renewal processes therefore play an essential role towards the sustainable transition of Eu ...
ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...
Inferences using Convolutional Neural Networks (CNNs) are resource and energy intensive. Therefore, their execution on highly constrained edge devices demands the careful co-optimization of algorithms and hardware. Addressing this challenge, in this paper ...