You are not logged in You are not logged in to this journal. Log In

Journal of Structural Engineering / Volume 137 / Issue 12 / TECHNICAL PAPERS

LOG IN or SELECT A PURCHASE OPTION:

Peak Factors for Non-Gaussian Load Effects Revisited

J. Struct. Eng. 137, 1611 (2011); http://dx.doi.org/10.1061/(ASCE)ST.1943-541X.0000412 (9 pages)

Dae Kun Kwon, M.ASCE1 and Ahsan Kareem, Dist.M.ASCE2

1Research Assistant Professor, Dept. of Civil Engineering and Geological Sciences, Univ. of Notre Dame, Notre Dame, IN 46556 (corresponding author). E-mail: dkwon@nd.edu
2Robert M. Moran Professor, Dept. of Civil Engineering and Geological Sciences, Univ. of Notre Dame, Notre Dame, IN 46556. E-mail: kareem@nd.edu

View MapView Map

(Submitted 11 May 2010; accepted 18 April 2011; posted ahead of print 20 April 2011)

The estimation of the extreme of non-Gaussian load effects for design applications has often been treated tacitly by invoking a conventional peak factor on the basis of Gaussian processes. This assumption breaks down when the loading process exhibits non-Gaussianity, in which a conventional peak factor yields relatively nonconservative estimates because of failure to include long tail regions inherent to non-Gaussian processes. To realistically capture the salient characteristics of non-Gaussian load effects and incorporate these in the estimates of their extremes, this study examines the peak factor for non-Gaussian processes, which can be used for estimating the expected value of the positive and negative extremes of non-Gaussian load effects. The efficacy of previously introduced analytical expressions for the peak factor of non-Gaussian processes on the basis of a moment-based Hermite model is evaluated and the variance of the estimates in standard deviation is derived. In addition, some improvements to the estimation of the peak factor and its standard deviation are discussed. Examples, including immediate applications to other areas, illustrate the effectiveness of this model-based peak factor approach.

© 2011 American Society of Civil Engineers

Acknowledgments

The writers are grateful for the financial support, in part, provided by the NSF Grant No. CMMI 06-01143 and the Global Center of Excellence at Tokyo Polytechnic University, Tokyo, funded by MEXT, Japan.

Article Outline

  1. Introduction
  2. Theoretical Background
    1. Conventional Peak Factor for Gaussian Processes
    2. Translation Process Model for Non-Gaussian Processes
    3. Moment-Based Hermite Model
  3. Non-Gaussian Peak Factor
    1. Expected Value of the Peak Factor
    2. Standard Deviation of Non-Gaussian Peak Factor
  4. Improvements in the Estimation of Non-Gaussian Peak Factor
    1. Modified Hermite Model
    2. Revised Hermite Model
    3. Limitation of the Improvement Techniques
  5. Parametric Study of Non-Gaussian Peak Factor
    1. Measured Pressure Fluctuations on a Full-Scale Low-Rise Building
    2. Time Histories of TLP Sway and Wind Pressure in the Roof of Low-Rise Building Model
    3. Comparison with windPRESSURE (NIST)
  6. Concluding Remarks

KEYWORDS

RELATED DATABASES

To view database links for this article, you need to log in.

ARTICLE DATA

Digital Object Identifier
http://dx.doi.org/10.1061/(ASCE)ST.1943-541X.0000412

PUBLICATION DATA

ISSN

0733-9445 (print)  
1943-541X (online)

Publisher

American Society of Civil Engineers

For access to fully linked references, you need to log in.

Figures (6) Tables (3)

Access to article objects (figures, tables, multimedia) requires a subscription; log in to view available files.
(Access to supplementary files, where available, is free for this journal.)

Access to article objects (figures, tables, multimedia) requires a subscription; log in to view available files.
(Access to supplementary files, where available, is free for this journal.)


Close

Your Recent History Recent History Help

Recently Viewed

  1. Peak Factors for Non-Gaussian Load Effects Revisited
  2. Storm and Gust Duration Effects on Design Wind Loads for Glass
  3. Experimental Study on Fire Resistance of Building Seismic Rubber Bearings
  4. Probabilistic Capacity Models and Fragility Estimates for Steel Pedestals Used to Elevate Bridges
  5. Reliability Acceptance Criteria for Deteriorating Elements of Structural Systems
close