Matching Items (4)

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Obtaining LEED credits directed towards healthy inpatient block

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

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.

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Created

Date Created
  • 2012

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Statistical and graphical methods to determine importance and interaction of building design parameters to inform and support design decisions

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

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.

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Date Created
  • 2015

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A visual analytics based decision support methodology for evaluating low energy building design alternatives

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

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.

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Created

Date Created
  • 2013

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Investigation of CO2 tracer gas-based calibration of multi-zone airflow models

Description

The modeling and simulation of airflow dynamics in buildings has many applications including indoor air quality and ventilation analysis, contaminant dispersion prediction, and the calculation of personal occupant exposure. Multi-zone

The modeling and simulation of airflow dynamics in buildings has many applications including indoor air quality and ventilation analysis, contaminant dispersion prediction, and the calculation of personal occupant exposure. Multi-zone airflow model software programs provide such capabilities in a manner that is practical for whole building analysis. This research addresses the need for calibration methodologies to improve the prediction accuracy of multi-zone software programs. Of particular interest is accurate modeling of airflow dynamics in response to extraordinary events, i.e. chemical and biological attacks. This research developed and explored a candidate calibration methodology which utilizes tracer gas (e.g., CO2) data. A key concept behind this research was that calibration of airflow models is a highly over-parameterized problem and that some form of model reduction is imperative. Model reduction was achieved by proposing the concept of macro-zones, i.e. groups of rooms that can be combined into one zone for the purposes of predicting or studying dynamic airflow behavior under different types of stimuli. The proposed calibration methodology consists of five steps: (i) develop a "somewhat" realistic or partially calibrated multi-zone model of a building so that the subsequent steps yield meaningful results, (ii) perform an airflow-based sensitivity analysis to determine influential system drivers, (iii) perform a tracer gas-based sensitivity analysis to identify macro-zones for model reduction, (iv) release CO2 in the building and measure tracer gas concentrations in at least one room within each macro-zone (some replication in other rooms is highly desirable) and use these measurements to further calibrate aggregate flow parameters of macro-zone flow elements so as to improve the model fit, and (v) evaluate model adequacy of the updated model based on some metric. The proposed methodology was first evaluated with a synthetic building and subsequently refined using actual measured airflows and CO2 concentrations for a real building. The airflow dynamics of the buildings analyzed were found to be dominated by the HVAC system. In such buildings, rectifying differences between measured and predicted tracer gas behavior should focus on factors impacting room air change rates first and flow parameter assumptions between zones second.

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Agent

Created

Date Created
  • 2011