東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Analysis Methods for Post Occupancy ...

Singh, Vipul.

Linked to FindBook

Google Book

Amazon

博客來

Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring./
Author:	Singh, Vipul.
Description:	191 p.
Notes:	Source: Masters Abstracts International, Volume: 49-05, page: 2765.
Contained By:	Masters Abstracts International49-05.
Subject:	Engineering, Architectural. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1491907
ISBN:	9781124619316

Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring.
Singh, Vipul.

Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring. - 191 p.

Source: Masters Abstracts International, Volume: 49-05, page: 2765.

Thesis (M.S.)--Arizona State University, 2011.

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.

ISBN: 9781124619316Subjects--Topical Terms:

1671790
Engineering, Architectural.

Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring.
LDR:03633nam 2200349 4500 001 1403413
005 20111115085238.5
008 130515s2011 ||||||||||||||||| ||eng d
020 $a 9781124619316
035 $a (UMI)AAI1491907
035 $a AAI1491907
040 $a UMI $c UMI
100 1 $a Singh, Vipul. $3 1682671
245 1 0 $a Analysis Methods for Post Occupancy Evaluation of Energy-Use in High Performance Buildings Using Short-Term Monitoring.
300 $a 191 p.
500 $a Source: Masters Abstracts International, Volume: 49-05, page: 2765.
500 $a Adviser: T. Agami Reddy.
502 $a Thesis (M.S.)--Arizona State University, 2011.
520 $a 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.
520 $a 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.
520 $a 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.
520 $a 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.
590 $a School code: 0010.
650 4 $a Engineering, Architectural. $3 1671790
650 4 $a Architecture. $3 523581
650 4 $a Energy. $3 876794
690 $a 0462
690 $a 0729
690 $a 0791
710 2 $a Arizona State University. $b Architecture. $3 1682672
773 0 $t Masters Abstracts International $g 49-05.
790 1 0 $a Reddy, T. Agami, $e advisor
790 1 0 $a Bryan, Harvey $e committee member
790 1 0 $a Addison, Marlin $e committee member
790 $a 0010
791 $a M.S.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1491907