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- All Subjects: Urban heat mitigation
Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid rate of urbanization coupled with continued population growth and anthropogenic activities has resulted in a myriad of urban climate related impacts across different cities around the world. Hot-arid cities are more vulnerable to induced urban heat effects due to the intense solar radiation during most of the year, leading to increased ambient air temperature and outdoor/indoor discomfort in Phoenix, Arizona. With the fast growth of the capital city of Arizona, the automobile-dependent planning of the city contributed negatively to the outdoor thermal comfort and to the people's daily social lives. One of the biggest challenges for hot-arid cities is to mitigate against the induced urban heat increase and improve the outdoor thermal. The objective of this study is to propose a pragmatic and useful framework that would improve the outdoor thermal comfort, by being able to evaluate and select minimally invasive urban heat mitigation strategies that could be applied to the existing urban settings in the hot-arid area of Phoenix. The study started with an evaluation of existing microclimate conditions by means of multiple field observations cross a North-South oriented urban block of buildings within Arizona State University’s Downtown campus in Phoenix. The collected data was evaluated and analyzed for a better understanding of the different local climates within the study area, then used to evaluate and partially validate a computational fluid dynamics model, ENVI-Met. Furthermore, three mitigation strategies were analyzed to the Urban Canopy Layer (UCL) level, an increase in the fraction of permeable materials in the ground surface, adding different configurations of high/low Leaf Area Density (LAD) trees, and replacing the trees configurations with fabric shading. All the strategies were compared and analyzed to determine the most impactful and effective mitigation strategies. The evaluated strategies have shown a substantial cooling effect from the High LAD trees scenarios. Also, the fabric shading strategies have shown a higher cooling effect than the Low LAD trees. Integrating the trees scenarios with the fabric shading had close cooling effect results in the High LAD trees scenarios. Finally, how to integrate these successful strategies into practical situations was addressed.
ContributorsAldakheelallah, Abdullah (Author) / Reddy, T Agami (Thesis advisor) / Middel, Ariane (Committee member) / Coseo, Paul (Committee member) / Arizona State University (Publisher)
Created2020