Matching Items (36)
Description
Learning from the anatomy of leaves, a new approach to bio-inspired passive evaporative cooling is presented that utilizes the temperature-responsive properties of PNIPAm hydrogels. Specifically, an experimental evaporation rate from the polymer, PNIPAm, is determined within an environmental chamber, which is programmed to simulate temperature and humidity conditions common in Phoenix, Arizona in the summer. This evaporation rate is then used to determine the theoretical heat transfer through a layer of PNIPAm that is attached to an exterior wall of a building within a ventilated cavity in Phoenix. The evaporation of water to the air gap from the polymer layer absorbs heat that could otherwise be conducted to the interior space of the building and then dispels it as a vapor away from the building. The results indicate that the addition of the PNIPAm layer removes all heat radiated from the exterior cladding, indicating that it could significantly reduce the demand for air conditioning at the interior side of the wall to which it is attached.
ContributorsBradford, Katherine (Author) / Reddy, T A (Thesis advisor) / Bryan, Harvey (Thesis advisor) / Ramalingam, Muthu (Committee member) / Arizona State University (Publisher)
Created2018
Description
The following document addresses two grand challenges posed to engineers: to make solar energy economically viable and to restore and improve urban infrastructure. Design solutions to these problems consist of the preliminary designs of two energy systems: a Packaged Photovoltaic (PPV) energy system and a natural gas based Modular Micro Combined Cycle (MMCC) with 3D renderings. Defining requirements and problem-solving approach methodology for generating complex design solutions required iterative design and a thorough understanding of industry practices and market trends. This paper briefly discusses design specifics; however, the major emphasis is on aspects pertaining to economical manufacture, deployment, and subsequent suitability to address the aforementioned challenges. The selection of these systems is based on the steady reduction of PV installation costs in recent years (average among utility, commercial, and residential down 27% from Q4 2012 to Q4 2013) and the dramatic decline in natural gas prices to $5.61 per thousand cubic feet. In addition, a large number of utility scale coal-based power plants will be retired in 2014, many due to progressive emission criteria, creating a demand for additional power systems to offset the capacity loss and to increase generating capacity in order to facilitate the ever-expanding world population. The proposed energy systems are not designed to provide power to the masses through a central location. Rather, they are intended to provide economical, reliable, and high quality power to remote locations and decentralized power to community-based grids. These energy systems are designed as a means of transforming and supporting the current infrastructure through distributed electricity generation.
ContributorsSandoval, Benjamin Mark (Author) / Bryan, Harvey (Thesis director) / Fonseca, Ernesto (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
Hospitals constitute 9 percent of commercial energy consumption in the U.S. annually, though they only make up 2 percent of the U.S. commercial floor space. Consuming an average of 259,000 Btu per square foot, U.S. hospitals spend about 8.3 billion dollars on energy every year. Utilizing collaborative delivery method for hospital construction can effectively save healthcare business owners thousands of dollars while reducing construction time and resulting in a better product: a building that has fewer operational deficiencies and requires less maintenance. Healthcare systems are integrated by nature, and are rich in technical complexity to meet the needs of their various patients. In addition to being technologically and energy intensive, hospitals must meet health regulations while maintaining human comfort. The interdisciplinary nature of hospitals suggests that multiple perspectives would be valuable in optimizing the building design. Integrated project delivery provides a means to reaching the optimal design by emphasizing group collaboration and expertise of the architect, engineer, owner, builder, and hospital staff. In previous studies, IPD has proven to be particularly beneficial when it comes to highly complex projects, such as hospitals. To assess the effects of a high level of team collaboration in the delivery of a hospital, case studies were prepared on several hospitals that have been built in the past decade. The case studies each utilized some form of a collaborative delivery method, and each were successful in saving and/or redirecting time and money to other building components, achieving various certifications, recognitions, and awards, and satisfying the client. The purpose of this research is to determine key strategies in the construction of healthcare facilities that allow for quicker construction, greater monetary savings, and improved operational efficiency. This research aims to communicate the value of both "green building" and a high level of team collaboration in the hospital-building process.
ContributorsHansen, Hannah Elizabeth (Author) / Parrish, Kristen (Thesis director) / Bryan, Harvey (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Improving the conditions of schools in many parts of the world is gradually acquiring importance. The Green School movement is an integral part of this effort since it aims at improving indoor environmental conditions. This would in turn, enhance student- learning while minimizing adverse environmental impact through energy efficiency of comfort-related HVAC and lighting systems. This research, which is a part of a larger research project, aims at evaluating different school building designs in Albania in terms of energy use and indoor thermal comfort, and identify energy efficient options of existing schools. We start by identifying three different climate zones in Albania; Coastal (Durres), Hill/Pre-mountainous (Tirana), mountainous (Korca). Next, two prototypical school building designs are identified from the existing stock. Numerous scenarios are then identified for analysis which consists of combinations of climate zone, building type, building orientation, building upgrade levels, presence of renewable energy systems (solar photovoltaic and solar water heater). The existing building layouts, initially outlined in CAD software and then imported into a detailed building energy software program (eQuest) to perform annual simulations for all scenarios. The research also predicted indoor thermal comfort conditions of the various scenarios on the premise that windows could be opened to provide natural ventilation cooling when appropriate. This study also estimated the energy generated from solar photovoltaic systems and solar water heater systems when placed on the available roof area to determine the extent to which they are able to meet the required electric loads (plug and lights) and building heating loads respectively.
The results showed that there is adequate indoor comfort without the need for mechanical cooling for the three climate zones, and that only heating is needed during the winter months.
The results showed that there is adequate indoor comfort without the need for mechanical cooling for the three climate zones, and that only heating is needed during the winter months.
ContributorsDalvi, Ambalika Rajendra (Author) / Reddy, Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2015
Description
The building sector is one of the main energy consumers within the USA. Energy demand by this sector continues to increase because new buildings are being constructed faster than older ones are retired. Increase in energy demand, in addition to a number of other factors such as the finite nature of fossil fuels, population growth, building impact on global climate change, and energy insecurity and independence has led to the increase in awareness towards conservation through the design of energy efficient buildings. Net Zero Energy Building (NZEB), a highly efficient building that produces as much renewable energy as it consumes annually, provides an effective solution to this global concern. The intent of this thesis is to investigate the relationship of an important factor that has a direct impact on NZEB: Floor / Area Ratio (FAR). Investigating this relationship will help to answer a very important question in establishing NZEB in hot-arid climates such as Phoenix, Arizona. The question this thesis presents is: “How big can a building be and still be Net Zero?” When does this concept start to flip and buildings become unable to generate the required renewable energy to achieve energy balance? The investigation process starts with the analysis of a local NZEB, DPR Construction Office, to evaluate the potential increase in building footprint and FAR with respect to the current annual Energy Use Intensity (EUI). Through the detailed analysis of the local NZEB, in addition to the knowledge gained through research, this thesis will offer an FAR calculator tool that can be used by design teams to help assess the net zero potential of their project. The tool analyzes a number of elements within the project such as total building footprint, available surface area for photovoltaic (PV) installation, outdoor circulation and landscape area, parking area and potential parking spots, potential building area in regards to FAR, number of floors based on the building footprint, FAR, required area for photovoltaic installation, photovoltaic system size, and annual energy production, in addition to the maximum potential FAR their project can reach and still be Net Zero.
ContributorsBen Salamah, Fahad (Author) / Bryan, Harvey (Thesis advisor) / Reddy, T. Agami (Committee member) / Ramalingam, Muthukumar (Committee member) / Arizona State University (Publisher)
Created2016
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
Description
The poor energy efficiency of buildings is a major barrier to alleviating the energy dilemma. Historically, monthly utility billing data was widely available and analytical methods for identifying building energy efficiency improvements, performing building Monitoring and Verification (M&V;) and continuous commissioning (CCx) were based on them. Although robust, these methods were not sensitive enough to detect a number of common causes for increased energy use. In recent years, prevalence of short-term building energy consumption data, also known as Energy Interval Data (EID), made available through the Smart Meters, along with data mining techniques presents the potential of knowledge discovery inherent in this data. This allows more sophisticated analytical tools to be developed resulting in greater sensitivities due to higher prediction accuracies; leading to deep energy savings and highly efficient building system operations. The research explores enhancements to Inverse Statistical Modeling techniques due to the availability of EID. Inverse statistical modeling is the process of identification of prediction model structure and estimates of model parameters. The methodology is based on several common statistical and data mining techniques: cluster analysis for day typing, outlier detection and removal, and generation of building scheduling. Inverse methods are simpler to develop and require fewer inputs for model identification. They can model changes in energy consumption based on changes in climatic variables and up to a certain extent, occupancy. This makes them easy-to-use and appealing to building managers for evaluating any general retrofits, building condition monitoring, continuous commissioning and short-term load forecasting (STLF). After evaluating several model structures, an elegant model form was derived which can be used to model daily energy consumption; which can be extended to model energy consumption for any specific hour by adding corrective terms. Additionally, adding AR terms to this model makes it usable for STLF. Two different buildings, one synthetic (ASHRAE medium-office prototype) building and another, an actual office building, were modeled using these techniques. The methodologies proposed have several novel features compared to the manner in which these models have been described earlier. Finally, this thesis investigates characteristic fault signature identification from detailed simulation models and subsequent inverse analysis.
ContributorsJalori, Saurabh (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the increasing interest in energy efficient building design, whole building energy simulation programs are increasingly employed in the design process to help architects and engineers determine which design alternatives save energy and are cost effective. DOE-2 is one of the most popular programs used by the building energy simulation community. eQUEST is a powerful graphic user interface for the DOE-2 engine. EnergyPlus is the newest generation simulation program under development by the U.S. Department of Energy which adds new modeling features beyond the DOE-2's capability. The new modeling capabilities of EnergyPlus make it possible to model new and complex building technologies which cannot be modeled by other whole building energy simulation programs. On the other hand, EnergyPlus models, especially with a large number of zones, run much slower than those of eQUEST. Both eQUEST and EnergyPlus offer their own set of advantages and disadvantages. The choice of which building simulation program should be used might vary in each case. The purpose of this thesis is to investigate the potential of both the programs to do the whole building energy analysis and compare the results with the actual building energy performance. For this purpose the energy simulation of a fully functional building is done in eQUEST and EnergyPlus and the results were compared with utility data of the building to identify the degree of closeness with which simulation results match with the actual heat and energy flows in building. It was observed in this study that eQUEST is easy to use and quick in producing results that would especially help in the taking critical decisions during the design phase. On the other hand EnergyPlus aids in modeling complex systems, producing more accurate results, but consumes more time. The choice of simulation program might change depending on the usability and applicability of the program to our need in different phases of a building's lifecycle. Therefore, it makes sense if a common front end is designed for both these simulation programs thereby allowing the user to select either the DOE-2.2 engine or the EnergyPlus engine based upon the need in each particular case.
ContributorsRallapalli, Hema Sree (Author) / Bryan, Harvey (Thesis advisor) / Addison, Marlin (Committee member) / Reddy, Agami (Committee member) / Arizona State University (Publisher)
Created2010
Description
The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial viability of the system installations as well as the purchase price. The research was conducted using PPAs and historical solar power production data from the ASU's Energy Information System (EIS). The results indicate that most PPAs slightly underestimate the annual energy yield. However, the modeled power output from PVsyst indicates that higher energy outputs are possible with better system monitoring.
ContributorsVulic, Natasa (Author) / Bowden, Stuart (Thesis director) / Bryan, Harvey (Committee member) / Sharma, Vivek (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
Description
Original exhibit panel text and an associated interview with ASU faculty Charles Backus and Harvey Bryan for the exhibit presented at the Luhrs Gallery, Hayden Library, Fall, 2013.
ContributorsSpindler, Rob (Curator) / Backus, Charles (Interviewee) / Bryan, Harvey (Interviewee)
Created2013-07-01