JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Comparison of Sensitivity Analysis Methods for Building Energy Simulations in Early Design Phases: Once-at-a-time (OAT) vs. Variance-based Methods
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : KIEAE Journal
  • Volume 16, Issue 2,  2016, pp.17-22
  • Publisher : Korea Institute of Ecological Architecture and Environment
  • DOI : 10.12813/kieae.2016.16.2.017
 Title & Authors
Comparison of Sensitivity Analysis Methods for Building Energy Simulations in Early Design Phases: Once-at-a-time (OAT) vs. Variance-based Methods
Kim, Sean Hay;
  PDF(new window)
 Abstract
Purpose: Sensitivity analysis offers a good guideline for designing energy conscious buildings, which is fitted to a specific building configuration. Sensitivity analysis is, however, still too expensive to be a part of regular design process. The One-at-a-time (OAT) is the most common and simplest sensitivity analysis method. This study aims to propose a reasonable ground that the OAT can be an alternative method for the variance-based method in some early design scenarios, while the variance-based method is known adequate for dealing with nonlinear response and the effect of interactions between input variables, which are most cases in building energy simulations. Method: A test model representing the early design phase is built in the DOE2 energy simulations. Then sensitivity ranks between the OAT and the Variance-based methods are compared at three U.S. sites. Result: Parameters in the upper rank by the OAT do not much differ from those by the Main effect index. Considering design practices that designers would chose the most energy saving design option first, this rank similarity between two methods seems to be acceptable in the early design phase.
 Keywords
Sensitivity Analysis;Building Energy Simulation;Once-at-a-time;OAT;Variance based method;Main effect index;
 Language
English
 Cited by
 References
1.
ASHRAE Advanced Energy Design Guides, ASHRAE, https://www.ashrae.org/standards-research--technology/advanced-energy-design-guides

2.
Morris, M. D. (1991). Factorial sampling plans for preliminary computational experiments. Technometrics, 33, 161-174. crossref(new window)

3.
Saltelli, A., K. Chan, and M. Scott (Eds.) (2000). Sensitivity Analysis. Wiley Series in Probability and Statistics. New York: John Wiley and Sons.

4.
Autodesk Green Building Stuido, Autodesk, http://gbs.autodesk.com

5.
Iman, R.L.; Davenport, J.M.; Zeigler, D.K. (1980). Latin hypercube sampling (program user's guide).

6.
Storlie, C.B., Swiler, L.P., Helton, J.C., and Sallaberry, C.J. (2009), Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models, Reliability Engineering & System Safety 94(11): 1735-1763 crossref(new window)