Matching Items (3)
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- All Subjects: Building
- Creators: Reddy, T. Agami
- Creators: Bhate, Dhruv
Description
Through manipulation of adaptable opportunities available within a given environment, individuals become active participants in managing personal comfort requirements, by exercising control over their comfort without the assistance of mechanical heating and cooling systems. Similarly, continuous manipulation of a building skin's form, insulation, porosity, and transmissivity qualities exerts control over the energy exchanged between indoor and outdoor environments. This research uses four adaptive response variables in a modified software algorithm to explore an adaptive building skin's potential in reacting to environmental stimuli with the purpose of minimizing energy use without sacrificing occupant comfort. Results illustrate that significant energy savings can be realized with adaptive envelopes over static building envelopes even under extreme summer and winter climate conditions; that the magnitude of these savings are dependent on climate and orientation; and that occupant thermal comfort can be improved consistently over comfort levels achieved by optimized static building envelopes. The resulting adaptive envelope's unique climate-specific behavior could inform designers in creating an intelligent kinetic aesthetic that helps facilitate adaptability and resiliency in architecture.
ContributorsErickson, James (Author) / Bryan, Harvey (Thesis advisor) / Addison, Marlin (Committee member) / Kroelinger, Michael D. (Committee member) / Reddy, T. Agami (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research is aimed at studying the impact of building design parameters in terms of their importance and mutual interaction, and how these aspects vary across climates and HVAC system types. A methodology is proposed for such a study, by examining the feasibility and use of two different statistical methods to derive all realistic ‘near-optimum’ solutions which might be lost using a simple optimization technique.
DOE prototype medium office building compliant with ASHRAE 90.1-2010 was selected for the analysis and four different HVAC systems in three US climates were simulated.
The interaction between building design parameters related to envelope characteristics and geometry (total of seven variables) has been studied using two different statistical methods, namely the ‘Morris method’ and ‘Predictive Learning via Rule Ensembles’.
Subsequently, a simple graphical tool based on sensitivity analysis has been developed and demonstrated to present the results from parametric simulations. This tool would be useful to better inform design decisions since it allows imposition of constraints on various parameters and visualize their interaction with other parameters.
It was observed that the Radiant system performed best in all three climates, followed by displacement ventilation system. However, it should be noted that this study did not deal with performance optimization of HVAC systems while there have been several studies which concluded that a VAV system with better controls can perform better than some of the newer HVAC technologies. In terms of building design parameters, it was observed that ‘Ceiling Height’, ‘Window-Wall Ratio’ and ‘Window Properties’ showed highest importance as well as interaction as compared to other parameters considered in this study, for all HVAC systems and climates.
Based on the results of this study, it is suggested to extend such analysis using statistical methods such as the ‘Morris method’, which require much fewer simulations to categorize parameters based on their importance and interaction strength. Usage of statistical methods like ‘Rule Ensembles’ or other simple visual tools to analyze simulation results for all combinations of parameters that show interaction would allow designers to make informed and superior design decisions while benefiting from large reduction in computational time.
DOE prototype medium office building compliant with ASHRAE 90.1-2010 was selected for the analysis and four different HVAC systems in three US climates were simulated.
The interaction between building design parameters related to envelope characteristics and geometry (total of seven variables) has been studied using two different statistical methods, namely the ‘Morris method’ and ‘Predictive Learning via Rule Ensembles’.
Subsequently, a simple graphical tool based on sensitivity analysis has been developed and demonstrated to present the results from parametric simulations. This tool would be useful to better inform design decisions since it allows imposition of constraints on various parameters and visualize their interaction with other parameters.
It was observed that the Radiant system performed best in all three climates, followed by displacement ventilation system. However, it should be noted that this study did not deal with performance optimization of HVAC systems while there have been several studies which concluded that a VAV system with better controls can perform better than some of the newer HVAC technologies. In terms of building design parameters, it was observed that ‘Ceiling Height’, ‘Window-Wall Ratio’ and ‘Window Properties’ showed highest importance as well as interaction as compared to other parameters considered in this study, for all HVAC systems and climates.
Based on the results of this study, it is suggested to extend such analysis using statistical methods such as the ‘Morris method’, which require much fewer simulations to categorize parameters based on their importance and interaction strength. Usage of statistical methods like ‘Rule Ensembles’ or other simple visual tools to analyze simulation results for all combinations of parameters that show interaction would allow designers to make informed and superior design decisions while benefiting from large reduction in computational time.
ContributorsDidwania, Srijan Kumar (Author) / Reddy, T. Agami (Thesis advisor) / Addison, Marlin S. (Thesis advisor) / Bryan, Harvey J. (Committee member) / Arizona State University (Publisher)
Created2015
Description
The presence of huge amounts of waste heat and the constant demand for electric energy makes this an appreciable research topic, yet at present there is no commercially viable technology to harness the inherent energy resource provided by the temperature differential between the inside and outside of buildings. In a newly developed technology, electricity is generated from the temperature gradient between building walls through a Seebeck effect. A 3D-printed triply periodic minimal surface (TPMS) structure is sandwiched in copper electrodes with copper (I) sulphate (Cu2SO4) electrolyte to mimic a thermogalvanic cell. Previous studies mainly concentrated on mechanical properties and the electric power generation ability of these structures; however, the goal of this study is to estimate the thermal resistance of the 3D-printed TPMS experimentally. This investigation elucidates their thermal resistances which in turn helps to appreciate the power output associated in the thermogalvanic structure. Schwarz P, Gyroid, IWP, and Split P geometries were considered for the experiment with electrolyte in the thermogalvanic brick. Among these TPMS structures, Split P was found more thermally resistive than the others with a thermal resistance of 0.012 m2 K W-1. The thermal resistances of Schwarz D and Gyroid structures were also assessed experimentally without electrolyte and the results are compared to numerical predictions in a previous Mater's thesis.
ContributorsDasinor, Emmanuel (Author) / Phelan, Patrick (Thesis advisor) / Milcarek, Ryan (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2020