Statistical Fatigue Analysis of the SH-60B Servo Beam Rail Component

Abstract

Statistical methods were researched to better understand the effect of the flight loads on the servo beam rail component of the SH-60B helicopter. The extreme value distribution and the Weibull distribution were used to model the distribution of flight loads. Specifically, the flight loads for the symmetric pullout maneuver were studied. Both models successfully represented the data, although more data are required to be fully confident in these representations. Different flight characteristics indicate that various factors such as gross weight, airspeed, and collective position effect the distribution of loads. The model runs indicate a good representation of the individual runs in fatigue life calculations. The damage calculated for the Sikorsky substantiation load run was less conservative than the model run. In addition, the maximum load of the substantiation run was only in the 45th percentile of the load distribution estimated using an extreme value distribution for loads. The damage calculated for the Sikorsky substantiation load run was more conservative than the damage calculated for the individual runs which was reduced as much as 100 times when corrected for mean load. Fatigue Analysis, SH-60B, Weibull Distribution Analysis, Extreme Value Distribution Analysis, Servo Beam Rail.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1992
Accession Number
ADA257474

Entities

People

  • Sally Degozzaldi

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Aeronautical Engineering
  • Aircrafts
  • Airspeed
  • Counting Methods
  • Distribution Functions
  • Engineering
  • Failure Mode And Effect Analysis
  • Fatigue Life
  • Flight Speeds
  • Goodness Of Fit Tests
  • Helicopters
  • Load Distribution
  • Probability Distributions
  • Random Variables
  • Statistical Analysis
  • Statistical Distributions
  • United States

Readers

  • Aerospace Engineering
  • Computational Modeling and Simulation
  • Statistical inference.