Matching Items (12)
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
With the desire of high standards of comfort, huge amount of energy is being consumed to maintain the indoor environment. In US building consumes 40% of the total primary energy while residential buildings consume about 21%. A large proportion of this consumption is due to cooling of buildings. Deteriorating environmental conditions due to excessive energy use suggest that we should look at passive designs and renewable energy opportunities to supply the required comfort. Phoenix gets about 300 days of clear sky every year. It also witnesses large temperature variations from night and day. The humidity ratio almost always stays below the 50% mark. With more than six months having outside temperatures more than 75 oF, night sky radiative cooling promise to be an attractive means to cool the buildings during summer. This technique can be useful for small commercial facilities or residential buildings. The roof ponds can be made more effective by covering them with Band Filters. These band filters block the solar heat gain and allow the water to cool down to lower temperatures. It also reduces the convection heat gain. This helps rood ponds maintain lower temperatures and provide more cooling then an exposed pond. 50 μm Polyethylene band filter is used in this study. Using this band filter, roof ponds can be made up to 10% more effective. About 45% of the energy required to cool a typical residential building in summer can be saved.
ContributorsSiddiqui, Mohd. Aqdus (Author) / Bryan, Harvey (Thesis advisor) / Reddy, T Agami (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The need for alternative energy efficient building heating and cooling technologies has given rise to the development and widespread use of Ground Coupled Heat Pump (GCHP) systems. This dissertation looks at the feasibility of using GCHP systems as a viable economic alternative to traditional air source cooling systems (ASHP) for conditioning buildings in the hot, semi-arid climate of Phoenix, Arizona. Despite high initial costs, GCHPs are gaining a foothold in northern climates where heating dominates, in large part due to government incentives. However, due to issues associated with low ground heat exchanger (GHE) efficiency and thermally-induced soil deformations, GCHPs are typically not considered a viable option in hot climates with deep groundwater and low permeability soil. To evaluate the energy performance and technical feasibility of GCHPs in Phoenix, the DOE 5,500 sq.ft small office, commercial building prototype was simulated in EnergyPlus to determine the cooling and heating loads. Next, a commercial software program, Ground Loop Design (GLD), was used to design and simulate the annual energy performance of both vertical (V-GCHPs) and horizontal GCHPs (H-GCHPs). Life cycle costs (LCC) were evaluated using realistic market costs both under dry, as well as fully saturated soil conditions (meant as an upper performance limit achievable by ground modification techniques). This analysis included performing several sensitivity analyses and also investigating the effect of financial rebates. The range of annual energy savings from the GCHP system for space cooling and heating was around 38-40% compared to ASHPs for dry soil. Saturated soil condition significantly affects the length of the GHE. For V-GCHPs, there was about 26% decrease in the length of GHE, thereby reducing the initial cost by 18-19% and decreasing the payback period by 24-25%. Likewise, for H-GCHPs, the length of GHE was reduced by 25% resulting in 22% and 39-42 % reduction in the initial cost and payback period respectively. With federal incentives, H-GCHPs under saturated soil conditions have the least LCC and a good payback periods of 2.3-4.7 years. V-GCHPs systems were been found to have payback periods of over 25 years, making them unfeasible for Phoenix, AZ, for the type of building investigated.
ContributorsTambe, Vaibhavi Parmanand (Author) / Reddy, T Agami (Thesis advisor) / Kavanzanjian, Edward (Thesis advisor) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2014
Description
The objective of this thesis is to investigate the various types of energy end-uses to be expected in future high efficiency single family residences. For this purpose, this study has analyzed monitored data from 14 houses in the 2013 Solar Decathlon competition, and segregates the energy consumption patterns in various residential end-uses (such as lights, refrigerators, washing machines, ...). The analysis was not straight-forward since these homes were operated according to schedules previously determined by the contest rules. The analysis approach allowed the isolation of the comfort energy use by the Heating, Venting and Cooling (HVAC) systems. HVAC are the biggest contributors to energy consumption during operation of a building, and therefore are a prime concern for energy performance during the building design and the operation. Both steady state and dynamic models of comfort energy use which take into account variations in indoor and outdoor temperatures, solar radiation and thermal mass of the building were explicitly considered. Steady State Inverse Models are frequently used for thermal analysis to evaluate HVAC energy performance. These are fast, accurate, offer great flexibility for mathematical modifications and can be applied to a variety of buildings. The results are presented as a horizontal study that compares energy consumption across homes to arrive at a generic rather than unique model - to be used in future discussions in the context of ultra efficient homes. It is suggested that similar analyses of the energy-use data that compare the performance of variety of ultra efficient technologies be conducted to provide more accurate indications of the consumption by end use for future single family residences. These can be used alongside the Residential Energy Consumption Survey (RECS) and the Leading Indicator for Remodeling Activity (LIRA) indices to assist in planning and policy making related to residential energy sector.
ContributorsGarkhail, Rahul (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Passive cooling designs & technologies offer great promise to lower energy use in buildings. Though the working principles of these designs and technologies are well understood, simplified tools to quantitatively evaluate their performance are lacking. Cooling by night ventilation, which is the topic of this research, is one of the well known passive cooling technologies. The building's thermal mass can be cooled at night by ventilating the inside of the space with the relatively lower outdoor air temperatures, thereby maintaining lower indoor temperatures during the warmer daytime period. Numerous studies, both experimental and theoretical, have been performed and have shown the effectiveness of the method to significantly reduce air conditioning loads or improve comfort levels in those climates where the night time ambient air temperature drops below that of the indoor air. The impact of widespread adoption of night ventilation cooling can be substantial, given the large fraction of energy consumed by air conditioning of buildings (about 12-13% of the total electricity use in U.S. buildings). Night ventilation is relatively easy to implement with minimal design changes to existing buildings. Contemporary mathematical models to evaluate the performance of night ventilation are embedded in detailed whole building simulation tools which require a certain amount of expertise and is a time consuming approach. This research proposes a methodology incorporating two models, Heat Transfer model and Thermal Network model, to evaluate the effectiveness of night ventilation. This methodology is easier to use and the run time to evaluate the results is faster. Both these models are approximations of thermal coupling between thermal mass and night ventilation in buildings. These models are modifications of existing approaches meant to model dynamic thermal response in buildings subject to natural ventilation. Effectiveness of night ventilation was quantified by a parameter called the Discomfort Reduction Factor (DRF) which is the index of reduction of occupant discomfort levels during the day time from night ventilation. Daily and Monthly DRFs are calculated for two climate zones and three building heat capacities. It is verified that night ventilation is effective in seasons and regions when day temperatures are between 30 oC and 36 oC and night temperatures are below 20 oC. The accuracy of these models may be lower than using a detailed simulation program but the loss in accuracy in using these tools more than compensates for the insights provided and better transparency in the analysis approach and results obtained.
ContributorsEndurthy, Akhilesh Reddy (Author) / Reddy, T Agami (Thesis advisor) / Phelan, Patrick (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
Description
A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed.
ContributorsKhanolkar, Amruta (Author) / Reddy, T Agami (Thesis advisor) / Addison, Marlin (Committee member) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2012
Description
Among the various end-use sectors, the commercial sector is expected to have the second-largest increase in total primary energy consump¬tion from 2009 to 2035 (5.8 quadrillion Btu) with a growth rate of 1.1% per year, it is the fastest growing end-use sectors. In order to make major gains in reducing U.S. building energy use commercial sector buildings must be improved. Energy benchmarking of buildings gives the facility manager or the building owner a quick evaluation of energy use and the potential for energy savings. It is the process of comparing the energy performance of a building to standards and codes, to a set target performance or to a range of energy performance values of similar buildings in order to help assess opportunities for improvement. Commissioning of buildings is the process of ensuring that systems are designed, installed, functionally tested and capable of being operated and maintained according to the owner's operational needs. It is the first stage in the building upgrade process after it has been assessed using benchmarking tools. The staged approach accounts for the interactions among all the energy flows in a building and produces a systematic method for planning upgrades that increase energy savings. This research compares and analyzes selected benchmarking and retrocommissioning tools to validate their accuracy such that they could be used in the initial audit process of a building. The benchmarking study analyzes the Energy Use Intensities (EUIs) and Ratings assigned by Portfolio Manager and Oak Ridge National Laboratory (ORNL) Spreadsheets. The 90.1 Prototype models and Commercial Reference Building model for Large Office building type were used for this comparative analysis. A case-study building from the DOE - funded Energize Phoenix program was also benchmarked for its EUI and rating. The retrocommissioning study was conducted by modeling these prototype models and the case-study building in the Facility Energy Decision System (FEDS) tool to simulate their energy consumption and analyze the retrofits suggested by the tool. The results of the benchmarking study proved that a benchmarking tool could be used as a first step in the audit process, encouraging the building owner to conduct an energy audit and realize the energy savings potential. The retrocommissioning study established the validity of FEDS as an accurate tool to simulate a building for its energy performance using basic inputs and to accurately predict the energy savings achieved by the retrofits recommended on the basis of maximum LCC savings.
ContributorsAgnihotri, Shreya Prabodhkumar (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to the lack of understanding of soil thermal behavior, rules-of-thumb and generalized procedures are typically used to guide building professionals in the design of ground coupled heat pump systems. This is especially true when sizing the ground heat exchanger (GHE) loop. Unfortunately, these generalized procedures often encourage building engineers to adopt a conservative design approach resulting in the gross over-sizing of the GHE, thus drastically increasing their installation cost. This conservative design approach is particularly prevalent for buildings located in hot and arid climates, where the soils are often granular and where the water table tends to exist deep below the soil surface. These adverse soil conditions reduce the heat dissipation efficiency of the GHE and have hindered the adoption of ground coupled heat pump systems in such climates. During cooling mode operation, heat is extracted from the building and rejected into the ground via the GHE. Prolonged heat dissipation into the ground can result in a coupled flow of both heat and moisture, causing the moisture to migrate away from the GHE piping. This coupled flow phenomenon causes the soil near the GHE to dry out and results in the degradation of the GHE heat dissipation capacity. Although relatively simple techniques of backfilling the GHE have been used in practice to mitigate such coupled effects, methods of improving the thermal behavior of the backfill region around the GHE, especially in horizontal systems, have not been extensively studied. This thesis presents an experimental study of heat dissipation from a horizontal GHE, buried in two backfill materials: (1) dry sand, and (2) wax-sand composite mixture. The HYDRUS software was then used to numerically model the temperature profiles associated with the aforementioned backfill conditions, and the influence of the contact resistance at the GHE-backfill interface was studied. The modeling strategy developed in HYDRUS was proven to be adequate in predicting the thermal performance of GHE buried in dry sand. However, when predicting the GHE heat dissipation in the wax-sand backfill, significant discrepancies between model prediction and experimental results still exist even after calibrating the model by including a term for the contact resistance. Overall, the thermal properties of the backfill were determined to be a key determinant of the GHE heat dissipation capacity. In particular, the wax-sand backfill was estimated to dissipate 50-60% more heat than dry sand backfill.
ContributorsDAngelo, Kurtis (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Kavazanjian, Edward (Committee member) / Arizona State University (Publisher)
Created2012
Description
Passive cooling techniques, specifically passive downdraft cooling (PDC), have proven to be a solution that can address issues associated with air conditioning (AC). Globally, over 100 buildings have integrated PDC in its different forms, most of which use direct evaporative cooling. Even though all surveyed buildings were energy efficient and cost-effective and most surveyed buildings were thermally comfortable, application of PDC remains limited. This study aims to advance performance of the single stage passive downdraft evaporative cooling tower (PDECT), and expand its applicability beyond the hot dry conditions where it is typically used, by designing and testing a multi-stage passive and hybrid downdraft cooling tower (PHDCT). Experimental evaluation on half-scale prototypes of these towers was conducted in Tempe, Arizona, during the hot dry and hot humid days of Summer, 2017. Ambient air dry-bulb temperatures ranged between 73.0°F with 82.9 percent coincident relative humidity, and 123.4°F with 7.8 percent coincident relative humidity. Cooling systems in both towers were operated simultaneously to evaluate performance under identical conditions.
Results indicated that the hybrid tower outperformed the single stage tower under all ambient conditions and that towers site water consumption was at least 2 times lower than source water required by electric powered AC. Under hot dry conditions, the single stage tower produced average temperature drops of 35°F (5°F higher than what was reported in the literature), average air velocities of 200 fpm, and average cooling capacities of 4 tons. Furthermore, the hybrid tower produced average temperature drops of 45°F (50°F in certain operation modes), average air velocities of 160 fpm, and average cooling capacities exceeding 4 tons. Under hot humid conditions, temperature drops from the single stage tower were limited to the ambient air wet-bulb temperatures whereas drops continued beyond the wet-bulb in the hybrid tower, resulting in 60 percent decline in the former’s cooling capacity while maintaining the capacity of the latter. The outcomes from this study will act as an incentive for designers to consider incorporating PDC into their designs as a viable replacement/supplement to AC; thus, reducing the impact of the built environment on the natural environment.
Results indicated that the hybrid tower outperformed the single stage tower under all ambient conditions and that towers site water consumption was at least 2 times lower than source water required by electric powered AC. Under hot dry conditions, the single stage tower produced average temperature drops of 35°F (5°F higher than what was reported in the literature), average air velocities of 200 fpm, and average cooling capacities of 4 tons. Furthermore, the hybrid tower produced average temperature drops of 45°F (50°F in certain operation modes), average air velocities of 160 fpm, and average cooling capacities exceeding 4 tons. Under hot humid conditions, temperature drops from the single stage tower were limited to the ambient air wet-bulb temperatures whereas drops continued beyond the wet-bulb in the hybrid tower, resulting in 60 percent decline in the former’s cooling capacity while maintaining the capacity of the latter. The outcomes from this study will act as an incentive for designers to consider incorporating PDC into their designs as a viable replacement/supplement to AC; thus, reducing the impact of the built environment on the natural environment.
ContributorsAl-Hassawi, Omar Dhia Sadulah (Author) / Bryan, Harvey (Thesis advisor) / Reddy, T Agami (Committee member) / Chalfoun, Nader (Committee member) / Arizona State University (Publisher)
Created2017
Description
City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study.
The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation.
Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models.
The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits.
From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction.
The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation.
Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models.
The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits.
From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction.
ContributorsPathak, Maharshi P. (Author) / Reddy, T Agami (Thesis advisor) / Addison, Marlin (Committee member) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2017