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- All Subjects: Buildings--Energy conservation.
- All Subjects: energy
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
Dwindling energy resources and associated environmental costs have resulted in a serious need to design and construct energy efficient buildings. One of the strategies to develop energy efficient structural materials is through the incorporation of phase change materials (PCM) in the host matrix. This research work presents details of a finite element-based framework that is used to study the thermal performance of structural precast concrete wall elements with and without a layer of phase change material. The simulation platform developed can be implemented for a wide variety of input parameters. In this study, two different locations in the continental United States, representing different ambient temperature conditions (corresponding to hot, cold and typical days of the year) are studied. Two different types of concrete - normal weight and lightweight, different PCM types, gypsum wallboard's with varying PCM percentages and different PCM layer thicknesses are also considered with an aim of understanding the energy flow across the wall member. Effect of changing PCM location and prolonged thermal loading are also studied. The temperature of the inside face of the wall and energy flow through the inside face of the wall, which determines the indoor HVAC energy consumption are used as the defining parameters. An ad-hoc optimization scheme is also implemented where the PCM thickness is fixed but its location and properties are varied. Numerical results show that energy savings are possible with small changes in baseline values, facilitating appropriate material design for desired characteristics.
ContributorsHembade, Lavannya Babanrao (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2012
Description
ABSTRACT Leadership in Energy and Environmental Design (LEED) is a non-governmental organization of U.S. Green Building Council (USGBC) which promotes a sustainable built environment with its rating systems. One of the building segments which it considers is healthcare, where it is a challenge to identify the most cost-effective variety of complex equipments, to meet the demand for 24/7 health care and diagnosis, and implement various energy efficient strategies in inpatient hospitals. According to their “End Use Monitoring” study, Hospital Energy Alliances (HEA), an initiative of U.S. Department of Energy (DOE), reducing plug load reduces hospital energy consumption. The aim of this thesis is to investigate the extent to which realistic changes to the building envelope, together with HVAC and operation schedules would allow LEED credits to be earned in the DOE–hospital prototype. The scope of this research is to specifically investigate the inpatient block where patient stays longer. However, to obtain LEED credits the percentage cost saving should be considered along with the end use monitoring. Several steps have been taken to identify the optimal set of the end use results by adopting the Whole Building Energy Simulation option of the LEED Energy & Atmosphere (EA) pre– requisite 2: Minimum Energy Performance. The initial step includes evaluating certain LEED criteria consistent with ASHRAE Standard 90.1–2007 with the constraint that hospital prototype is to be upgraded from Standard 2004 to Standard 2007. The simulation method stipulates energy conservation measures as well as utility costing to enhance the LEED credits. A series of simulations with different values of Light Power Density, Sizing Factors, Chiller Coefficient of Performance, Boiler Efficiency, Plug Loads and utility cost were run for a variety of end uses with the extreme climatic condition of Phoenix. These assessments are then compared and used as a framework for a proposed interactive design decision approach. As a result, a total of 19.4% energy savings and 20% utility cost savings were achieved by the building simulation tool, which refer to 5 and 7 LEED credits respectively. The study develops a proper framework for future evaluations intended to achieve more LEED points.
ContributorsHaque, Sadia Khandaker (Author) / Reddy, T A (Thesis advisor) / Bryan, Harvey J. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2012
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