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\section{Methods}  This research will review and outline the methods and results of best practice building energy modeling (BEM)simulations and  tools used for the modeling simulation  of advanced built environment technologies. Each modeling method will be evaluated on criteria of adaptivity, repeatability, and accuracy to valuation of systems for building design iteration  and impact to design. economic valuation.  Previous simulations done by CASE and myself of pre- and post-processing Integrated Concentrating Solar and Electroactive Dynamic Daylighting System, respectively, will be used to discuss limitations of current methods. Additionally, existing best practice projects that use methods such as, computational fluid dynamics, raytracing, and moisture modeling, will be discussed and outlined for their precedence and limitations. From current research and projections, future simulations will be dominated by co-simulation need to possess a level  of specialized abstraction able to adapt and easily model new built environment technologies but accurate enough to have confidence in the results.   Because of this  models coupled together through are often created within coding languages that the developer feels comfortable using to model the system, isolated from  the building context.   The  Functional Mock-up Mock-Up  Interface (FMI) Standard.\footnote{"FMI Standard provides an structure for built environment system models to develop code which, through the standard, can effortless connect and exchange data between simulation time steps, also known as co-simulation.\footnote{"FMI  for Model Exchange and Co-Simulation." FMI-Standard.org. Modelica Association, 25 July 2014. Web.} Research by LBNL's Simulation Research Group is leveraging Modelica, a language used for modeling complex, dynamic systems, and functional mock-up units (FMUs), a standard for packaging models, for use in co-simulation of complex building systems into common practice building simulation software, such as EnergyPlus.\footnote{Nouidui, Thierry Stephane, Michael Wetter, and Wangda Zuo. "Functional Mock-Up Unit Import in EnergyPlus For Co-Simulation." In Proceedings of BS2013: 13th Conference of, 2013. http://btus.lbl.gov/sites/all/files/lbnl-6413e.pdf.}  This method of creating models and linking to common practice energy simulation software (FMU co-simulation) has exciting but not yet explored potential in the modeling and validation of next-generation adaptive envelope technology.  Adaptive, predictive, uncertainty quantified models of dynamic building envelope technology technologies  will be developed in Modelica and exported as an FMU Python and connected through the FMI standard  to link with other common practice software, specifically EnergyPlus (and possibly Grasshopper)  for our studies. 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.  
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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.