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ssc-367 - Ship Structure Committee

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~. \“<br />

life of a structure,cannot be defined bya closed-formmathematical<br />

function. Most often a numerical long-termdensity function of the<br />

stress range is used to determine the fatigue damage and the method<br />

is identifiedas the “long-termnumerical method”. If the long-term<br />

stress range density function is idealized, an approximate density<br />

function can be used. “Weibull” distribution is one commonly<br />

accepted shape parameter used to describe the long-term stress<br />

density function. The fatigue damage computed is closed<br />

form. Incorporating the Weibull shape parameter is generally<br />

referred to as the “Long-TermClosed-FormMethod”.<br />

6.2.3 Uncertainties and Gaps in Stress SDectrum Develo~ment<br />

There are several important variables contribut<br />

uncertainties in the development of the spectrum.<br />

ng to the<br />

Analysis assumptions substantially influence the calculated<br />

results. The most important of these is the selection of scatter<br />

diagram blocks. While atypical scatterdiagram has40t060 blocks<br />

(each representingthe joint probabilityof Hs and T), these blocks<br />

are often arbitrarily grouped into 10 to 15 super blocks to<br />

facilitate analyses. In addition to the uncertainties introduced<br />

dueto lumpingof these blocks,validityof Rayleighdistributionis<br />

also jeopardizeddue to limitednumber of blocksdefining the entire<br />

environment.<br />

Other analyses uncertainties result from the use or omission of<br />

various parameters (rainflow counting, Weibull d stribution) and<br />

their validity for the problem at hand.<br />

Work carried out by various investigatorshave he” ped enhance the<br />

reliability of spectral fatigue analysis. Chen and Maurakis<br />

(Reference6.10) offer a close form spectralfatigue analysesmethod<br />

that eliminates some of the uncertainties due to analyses<br />

assumptions and computational procedures. The computer program<br />

developed, incorporating the self-contained algorithm, appears to<br />

minimize the uncertainties due to analytical assumptions (i.e.,<br />

6-12

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