Title :
Assessing Laboratory and Field Measurements for Design
Author :
Niedzwecki, J.M.
Author_Institution :
Zachry Dept. of Civil Eng., Texas A&M Univ., College Station, TX
Abstract :
Present design methods rely heavily on model basin tests to validate the predictive models used in the design process for offshore structures. Data obtained from laboratory and field test program are closely held by industry; consequently the data analyzed in this study is for nearly similar but not identical deepwater platforms. The findings of this investigation are presented using contour and exceedance probability graphs. The exceedance graphs present exceedance information based upon the measured data with an overly of two different Weibull curve fit models. The first model illustrates the common two-parameter Maximum Likelihood approach, while the second explores the use of a two-parameter least-squares log Weibull model. Neither appears to be entirely satisfactory for the range considered, and the computed coefficients are found to differ only slightly. The most probable maxima are often used to help interpret the limits of experimental data that should be used. Here the most probable maximum was computed as a function Ochi´s risk parameter for two different values, as noted in the legend. This study presents some alternate ways of visualizing and interpreting data measured in either laboratory or field studies. The intent here was to highlight some points that should be considered when either interpreting data or when designing measurement programs
Keywords :
Weibull distribution; marine engineering; maximum likelihood estimation; Maximum Likelihood approach; Ochi´s risk parameter; Weibull curve fit models; contour; deepwater platforms; exceedance probability graphs; interpreting data; model basin tests; offshore structures; two-parameter least-squares log; visualizing data; Civil engineering; Data analysis; Data visualization; Design methodology; Hurricanes; Laboratories; Maximum likelihood estimation; Predictive models; Process design; Testing;
Conference_Titel :
OCEANS 2006
Conference_Location :
Boston, MA
Print_ISBN :
1-4244-0114-3
Electronic_ISBN :
1-4244-0115-1
DOI :
10.1109/OCEANS.2006.306973