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%To create a parametric modeling framework that allows for pervasive adaptivity in the analysis and design process, we propose to control error and manage uncertainty in our simulations through adaptivity of all components. Much like the building systems adapt to changing climatic conditions, so must the models adapt to varying inputs and user defined parameters. An adaptive model must have the following criteria to achieve confident results: (a) a mechanism to achieve higher-fidelity solutions, (b) error indicators/estimators, and (c) an adaptive strategy. A framework will be set up that allows parametric adaptation of the models while maintaining accurate results and minimal run-times. When adaptivity is applied to our meso- and macro-scale numerical methods, higher-fidelity solutions are constructed through grid refinement in space, time and probability domains. In a particle-based simulation they are typically obtained through increasing the sample size in space and/or time. In both cases error estimators will be used to measure the difference between an exact solution to the underlying mathematical problem and its numerical approximation. The adaptive strategy utilizes these indicators to adapt the mesh (for meso- and macro-scale simulations) or to increase the sampling domain (micro-scale simulations).   The co-simulation of next-generation adaptive building envelopes adaptive, medium-fidelity system models  withinwhole  building simulations energy modeling (BEM)  enables fundamental modeling of transport phenomena that isotherwise  under represented or that would otherwise  notbe  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, themodeling  framework in development today will produce models that are relevant to today's BEM practices and future simulation methods through the use of the FMI standard, allowing the  simulations to apply to future software  that streamlined also adapt the standard, already including EnergyPlus and Matlab.   %streamlined  the workflow and provide confidence in results for current and future BEM practitioners through co-simulation and the growing functional mock-up interface standard, with software like EnergyPlus and MatLab already functional.      
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