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ContributorsWasbotten, Leia (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
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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

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
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Description
Libby Larsen is one of the most performed and acclaimed composers today. She is a spirited, compelling, and sensitive composer whose music enhances the poetry of America's most prominent authors. Notable among her works are song cycles for soprano based on the poetry of female writers, among them novelist and

Libby Larsen is one of the most performed and acclaimed composers today. She is a spirited, compelling, and sensitive composer whose music enhances the poetry of America's most prominent authors. Notable among her works are song cycles for soprano based on the poetry of female writers, among them novelist and poet Willa Cather (1873-1947). Larsen has produced two song cycles on works from Cather's substantial output of fiction: one based on Cather's short story, "Eric Hermannson's Soul," titled Margaret Songs: Three Songs from Willa Cather (1996); and later, My Antonia (2000), based on Cather's novel of the same title. In Margaret Songs, Cather's poetry and short stories--specifically the character of Margaret Elliot--combine with Larsen's unique compositional style to create a surprising collaboration. This study explores how Larsen in these songs delves into the emotional and psychological depths of Margaret's character, not fully formed by Cather. It is only through Larsen's music and Cather's poetry that Margaret's journey through self-discovery and love become fully realized. This song cycle is a glimpse through the eyes of two prominent female artists on the societal pressures placed upon Margaret's character, many of which still resonate with women in today's culture. This study examines the work Margaret Songs by discussing Willa Cather, her musical influences, and the conditions surrounding the writing of "Eric Hermannson's Soul." It looks also into Cather's influence on Libby Larsen and the commission leading to Margaret Songs. Finally, a description of the musical, dramatic, and textual content of the songs completes this interpretation of the interactions of Willa Cather, Libby Larsen, and the character of Margaret Elliot.
ContributorsMcLain, Christi Marie (Author) / FitzPatrick, Carole (Thesis advisor) / Dreyfoos, Dale (Committee member) / Holbrook, Amy (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Puerto Rico has produced many important composers who have contributed to the musical culture of the nation during the last 200 years. However, a considerable amount of their music has proven to be difficult to access and may contain numerous errors. This research project intends to contribute to the accessibility

Puerto Rico has produced many important composers who have contributed to the musical culture of the nation during the last 200 years. However, a considerable amount of their music has proven to be difficult to access and may contain numerous errors. This research project intends to contribute to the accessibility of such music and to encourage similar studies of Puerto Rican music. This study focuses on the music of Héctor Campos Parsi (1922-1998), one of the most prominent composers of the 20th century in Puerto Rico. After an overview of the historical background of music on the island and the biography of the composer, four works from his art song repertoire are given for detailed examination. A product of this study is the first corrected edition of his cycles Canciones de Cielo y Agua, Tres Poemas de Corretjer, Los Paréntesis, and the song Majestad Negra. These compositions date from 1947 to 1959, and reflect both the European and nationalistic writing styles of the composer during this time. Data for these corrections have been obtained from the composer's manuscripts, published and unpublished editions, and published recordings. The corrected scores are ready for publication and a compact disc of this repertoire, performed by soprano Melliangee Pérez and the author, has been recorded to bring to life these revisions. Despite the best intentions of the author, the various copyright issues have yet to be resolved. It is hoped that this document will provide the foundation for a resolution and that these important works will be available for public performance and study in the near future.
ContributorsRodríguez Morales, Luis F., 1980- (Author) / Campbell, Andrew (Thesis advisor) / Buck, Elizabeth (Committee member) / Holbrook, Amy (Committee member) / Kopta, Anne (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsYi, Joyce (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-22
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Description
The green building movement has been an effective catalyst in reducing energy demands of buildings and a large number of `green' certified buildings have been in operation for several years. Whether these buildings are actually performing as intended, and if not, identifying specific causes for this discrepancy falls into the

The green building movement has been an effective catalyst in reducing energy demands of buildings and a large number of `green' certified buildings have been in operation for several years. Whether these buildings are actually performing as intended, and if not, identifying specific causes for this discrepancy falls into the general realm of post-occupancy evaluation (POE). POE involves evaluating building performance in terms of energy-use, indoor environmental quality, acoustics and water-use; the first aspect i.e. energy-use is addressed in this thesis. Normally, a full year or more of energy-use and weather data is required to determine the actual post-occupancy energy-use of buildings. In many cases, either measured building performance data is not available or the time and cost implications may not make it feasible to invest in monitoring the building for a whole year. Knowledge about the minimum amount of measured data needed to accurately capture the behavior of the building over the entire year can be immensely beneficial. This research identifies simple modeling techniques to determine best time of the year to begin in-situ monitoring of building energy-use, and the least amount of data required for generating acceptable long-term predictions. Four analysis procedures are studied. The short-term monitoring for long-term prediction (SMLP) approach and dry-bulb temperature analysis (DBTA) approach allow determining the best time and duration of the year for in-situ monitoring to be performed based only on the ambient temperature data of the location. Multivariate change-point (MCP) modeling uses simulated/monitored data to determine best monitoring period of the year. This is also used to validate the SMLP and DBTA approaches. The hybrid inverse modeling method-1 predicts energy-use by combining a short dataset of monitored internal loads with a year of utility-bills, and hybrid inverse method-2 predicts long term building performance using utility-bills only. The results obtained show that often less than three to four months of monitored data is adequate for estimating the annual building energy use, provided that the monitoring is initiated at the right time, and the seasonal as well as daily variations are adequately captured by the short dataset. The predictive accuracy of the short data-sets is found to be strongly influenced by the closeness of the dataset's mean temperature to the annual average temperature. The analysis methods studied would be very useful for energy professionals involved in POE.
ContributorsSingh, Vipul (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Buildings (approximately half commercial and half residential) consume over 70% of the electricity among all the consumption units in the United States. Buildings are also responsible for approximately 40% of CO2 emissions, which is more than any other industry sectors. As a result, the initiative smart building which aims to

Buildings (approximately half commercial and half residential) consume over 70% of the electricity among all the consumption units in the United States. Buildings are also responsible for approximately 40% of CO2 emissions, which is more than any other industry sectors. As a result, the initiative smart building which aims to not only manage electrical consumption in an efficient way but also reduce the damaging effect of greenhouse gases on the environment has been launched. Another important technology being promoted by government agencies is the smart grid which manages energy usage across a wide range of buildings in an effort to reduce cost and increase reliability and transparency. As a great amount of efforts have been devoted to these two initiatives by either exploring the smart grid designs or developing technologies for smart buildings, the research studying how the smart buildings and smart grid coordinate thus more efficiently use the energy is currently lacking. In this dissertation, a "system-of-system" approach is employed to develop an integrated building model which consists a number of buildings (building cluster) interacting with smart grid. The buildings can function as both energy consumption unit as well as energy generation/storage unit. Memetic Algorithm (MA) and Particle Swarm Optimization (PSO) based decision framework are developed for building operation decisions. In addition, Particle Filter (PF) is explored as a mean for fusing online sensor and meter data so adaptive decision could be made in responding to dynamic environment. The dissertation is divided into three inter-connected research components. First, an integrated building energy model including building consumption, storage, generation sub-systems for the building cluster is developed. Then a bi-level Memetic Algorithm (MA) based decentralized decision framework is developed to identify the Pareto optimal operation strategies for the building cluster. The Pareto solutions not only enable multiple dimensional tradeoff analysis, but also provide valuable insight for determining pricing mechanisms and power grid capacity. Secondly, a multi-objective PSO based decision framework is developed to reduce the computational effort of the MA based decision framework without scarifying accuracy. With the improved performance, the decision time scale could be refined to make it capable for hourly operation decisions. Finally, by integrating the multi-objective PSO based decision framework with PF, an adaptive framework is developed for adaptive operation decisions for smart building cluster. The adaptive framework not only enables me to develop a high fidelity decision model but also enables the building cluster to respond to the dynamics and uncertainties inherent in the system.
ContributorsHu, Mengqi (Author) / Wu, Teresa (Thesis advisor) / Weir, Jeffery (Thesis advisor) / Wen, Jin (Committee member) / Fowler, John (Committee member) / Shunk, Dan (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The Urban Heat Island (UHI) has been known to have been around from as long as people have been urbanizing. The growth and conglomeration of cities in the past century has caused an increase in the intensity and impact of Urban Heat Island, causing significant changes to the micro-climate and

The Urban Heat Island (UHI) has been known to have been around from as long as people have been urbanizing. The growth and conglomeration of cities in the past century has caused an increase in the intensity and impact of Urban Heat Island, causing significant changes to the micro-climate and causing imbalances in the temperature patterns of cities. The urban heat island (UHI) is a well established phenomenon and it has been attributed to the reduced heating loads and increased cooling loads, impacting the total energy consumption of affected buildings in all climatic regions. This thesis endeavors to understand the impact of the urban heat island on the typical buildings in the Phoenix Metropolitan region through an annual energy simulation process spanning through the years 1950 to 2005. Phoenix, as a representative city for the hot-arid cooling-dominated region, would be an interesting example to see how the reduction in heating energy consumption offsets the increased demand for cooling energy in the building. The commercial reference building models from the Department of Energy have been used to simulate commercial building stock, while for the residential stock a representative residential model prescribing to IECC 2006 standards will be used. The multiyear simulation process will bring forth the energy consumptions of various building typologies, thus highlighting differing impacts on the various building typologies. A vigorous analysis is performed to see the impact on the cooling loads annually, specifically during summer and summer nights, when the impact of the 'atmospheric canopy layer' - urban heat island (UHI) causes an increase in the summer night time minimum and night time average temperatures. This study also shows the disparity in results of annual simulations run utilizing a typical meteorological year (TMY) weather file, to that of the current recorded weather data. The under prediction due to the use of TMY would translate to higher or lower predicted energy savings in the future years, for changes made to the efficiencies of the cooling or heating systems and thermal performance of the built-forms. The change in energy usage patterns caused by higher cooling energy and lesser heating energy consumptions could influence future policies and energy conservation standards. This study could also be utilized to understand the impacts of the equipment sizing protocols currently adopted, equipment use and longevity and fuel swapping as heating cooling ratios change.
ContributorsDoddaballapur, Sandeep (Author) / Bryan, Harvey (Thesis advisor) / Reddy, Agami T (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
ContributorsCummiskey, Hannah (Performer) / Kim, Olga (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-23
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Description
Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by

Lighting systems and air-conditioning systems are two of the largest energy consuming end-uses in buildings. Lighting control in smart buildings and homes can be automated by having computer controlled lights and window blinds along with illumination sensors that are distributed in the building, while temperature control can be automated by having computer controlled air-conditioning systems. However, programming actuators in a large-scale environment for buildings and homes can be time consuming and expensive. This dissertation presents an approach that algorithmically sets up the control system that can automate any building without requiring custom programming. This is achieved by imbibing the system self calibrating and self learning abilities.

For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting.

For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control.

The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
ContributorsWang, Yuan (Author) / Dasgupta, Partha (Thesis advisor) / Davulcu, Hasan (Committee member) / Huang, Dijiang (Committee member) / Reddy, T. Agami (Committee member) / Arizona State University (Publisher)
Created2015