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Adaptive, predictive, uncertainty quantified models of dynamic building envelope technologies will be developed in Modelica and Python and connected through the FMI standard to link with other common practice software, specifically EnergyPlus (and possibly Grasshopper) for our studies.   The envelope model developed thus far is referred to as a dynamic network model with medium-fidelity. Network of volumes, connected through conservations laws.  The capture and transformation of natural climatic energy flows at the building envelope is a vastly complex, interconnected physical problem of heat, mass, electromagnetic, and momentum transport.   To explore the exchange of energy between the building exterior and interior, through a dynamic envelope, a multiscale modeling approach will be designed.   The proposed modeling strategy spans micro (microns to mm), meso (mm to m) and macro (m to km) scales.  
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The co-simulation of next-generation adaptive building envelopes within whole building simulations enables fundamental modeling of transport phenomena that is otherwise under represented or that would not be achievable in EnergyPlus alone.   Using advanced modeling methods of uncertainty quantification and pervasive adaptivity, critical knowledge gaps in the building sciences can be explored and leveraged to better improve our understanding, provide the best approximation, and project the impact of adaptive building envelopes.  Additionally, the improved results inform current and future energy modeling practices through co-simulation and the growing functional mock-up interface standard, with software like EnergyPlus and MatLab already functional.