(Georgia Institute of Technology, 2024-01)
Zarate Villazon, Angel M.; Peak, Varick J.; Duncan, Scott J.; Fischer, Olivia J. Pinion; Mavris, Dimitri N.
Decarbonizing our activities is one of the most important challenges of our generation. The potential consequences of climate change for all life on Earth make these efforts urgently necessary. While a lot of focus has been put on emissions associated with transportation, the International Panel on Climate Change suggests that up to 40% of the total Greenhouse gas emissions come from buildings. As a result, there is a growing need to understand the impact of the different elements around buildings to propose a truly sustainable infrastructure. This impact, however, to be of value, needs to be assessed across multiple perspectives: policy, technological and financial. To that end, this paper studies buildings and infrastructure from a system-of-systems perspective to provide a financially-optimized combination of energy sources that satisfy a specific demand and assesses it across financial, environmental and performance metrics. More specifically, this paper balances the energy impact of building HVAC systems and the demand of electric vehicle charging against the inclusion of photovoltaic and storage systems. To enable such study, a methodology is proposed that leverages surrogate models to integrate a dynamic, Modelica-based model of a building HVAC system with a techno-economic decision support tool developed by the US National Renewable Energy Laboratory. The resulting capability is an integrated analysis of the green infrastructure that considers the multiple aspects of building energy sourcing through renewable and non-renewable sources for a given consumption pattern as a mean to assess the role that technologies and policies have in helping achieve greener, decarbonized buildings and infrastructure.
(Georgia Institute of Technology, 2024-01)
Lepez Da Silva Duarte, Noe; Fischer, Olivia J. Pinion; Mavris, Dimitri N.
This paper presents an initial exploration into a comprehensive, reusable, and scalable approach to enterprise architecture modeling and simulation, with a significant emphasis on the use of SysML. Through a case study of a large academic research laboratory, the research delineates the application of UAF and SysML models with diverse simulation methodologies, prioritizing the seamless transfer and enhanced visualization of SysML model data. A key contribution of this study is the incorporation of ontologies and graph databases through Neo4j, offering a robust framework for representing and querying complex SysML data. By juxtaposing traditional tools, such as SimPy, with Neo4j, the research underscores the effectiveness of graph databases in presenting a clearer, more intuitive visualization. While the presented simulation serves primarily as a proof-of-concept, it sheds light on the complexities of enterprise dynamics. The potential for richer, more detailed simulations that harness the full capability of these tools beckons further exploration in subsequent research endeavors.