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- Creators: ASU Library. Music Library
ContributorsBurton, Charlotte (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-08
ContributorsSong, Yiqian (Performer) / Hankins, Kim (Performer) / Pendleton, Aaron (Performer) / Miller, Isaac (Performer) / Hsu, Gabrielle (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-08
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 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
ContributorsArch, Nathan (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-18
ContributorsLovelady, Alexis (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-08
Description
The intent of this research is to determine if cool roofs lead to increased energy use in the U.S. and if so, in what climates. Directed by the LEED environmental building rating system, cool roofs are increasingly specified in an attempt to mitigate urban heat island effect. A typical single story retail building was simulated using eQUEST energy software across seven different climatic zones in the U.S.. Two roof types are varied, one with a low solar reflectance index of 30 (typical bituminous roof), and a roof with SRI of 90 (high performing membrane roof). The model also varied the perimeter / core fraction, internal loads, and schedule of operations. The data suggests a certain point at which a high SRI roofing finish results in energy penalties over the course of the year in climate zones which are heating driven. Climate zones 5 and above appear to be the flipping point, beyond which the application of a high SRI roof creates sufficient heating penalties to outweigh the cooling energy benefits.
ContributorsLee, John (Author) / Bryan, Harvey (Thesis advisor) / Marlin, Marlin (Committee member) / Ramalingam, Muthukumar (Committee member) / Arizona State University (Publisher)
Created2011
ContributorsLougheed, Julia (Performer) / Novak, Gail (Pianist) (Performer) / Bayer, Elizabeth Kennedy (Performer) / Clifton-Armenta, Tyler (Performer) / Park, Julie (Performer) / Javier de Alba, Francisco (Performer) / Vientos Dulces (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-07
Description
This study examines the applicability of high dynamic range (HDR) imagery as a diagnostic tool for studying lighting quality in interior environments. It originates from the limitations in lighting quality assessments, particularly from the problematic nature of measuring luminance contrast--a significant lighting quality definer. In this research, HDR imaging method is studied systematically and in detail via extensive camera calibration tests considering the effect of lens and light source geometry (i.e. vignetting, point spread and modulation transfer functions), in-camera variables (i.e. spectral response, sensor sensitivity, metering mode,), and environmental variables (i.e. ambient light level, surface color and reflectance, light source spectral power distribution) on the accuracy of HDR-image-derived luminance data. The calibration test findings are used to create camera setup and calibration guidelines for future research, especially to help minimize errors in image extracted lighting data. The findings are also utilized to demonstrate the viability of the tool in a real world setting--an office environment combining vertical and horizontal tasks. Via the quasi-experimental setup, the relationship between line of sight and perceived luminance contrast ratios are studied using HDR images. Future research can benefit from the calibration guidelines to minimize HDR-based luminance estimation errors. The proposed tool can be used and tested in different contexts and tasks with varying user groups for revising the former luminance-contrast guidelines as well as surface reflectance recommendations.
ContributorsTural, Mehmedalp (Author) / Bryan, Harvey (Thesis advisor) / Kroelinger, Michael D. (Committee member) / Ozel, Filiz (Committee member) / Arizona State University (Publisher)
Created2011