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WeibPar - Weibull Distribution Parameter Estimation
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FEATURES

WeibPar is a stand-alone 32-bit Windows program designed for Windows XP.

INPUT:

Text file data input, and on-screen user select choices

  • Data:
    • Time Independent (Fast Fracture)
      • Uncensored Failure (single failure mechanism)
      • Censored Failure (up to 10 different failure mechanisms)
      • J-Integral (JC)
      • Fracture Toughness (K1C)
    • Time Dependent Data
      • Dynamic Fatigue (Monotonically Increasing Uniaxial Loading)

  • Specimen Geometries:
    • None (raw data option)
    • Tensile (Circular or Rectangular)
    • Bend Bar (3 pt, 4 pt, or pure bend)
    • User Input Effective Volume or Area
    • Finite Element Model (arbitrary specimen geometry)

  • Flaw Types - Volume or Surface

  • Pooled Data - different specimen geometry, uncensored data sets may be pooled

  • Data ranking formula options

  • Confidence Level options

  • Fixed Weibull Modulus and/or Weibull Threshold options

OUTPUT:

Both Text results and Graphical results are displayed on-screen and in optional output files.

  • Linear Regression - 2 and 3 parameter Weibull (Uncensored, Biased)

  • Maximum Likelihood - 2 and 3 parameter Weibull
    • Biased - Uncensored, Censored, or Pooled
    • Unbiased - Uncensored (Bain, Antle, Thomain & Bootstrap)
    • Confidence Bounds
      • Monte-Carlo Bootstrap - Bounds on the failue data (Uncensored, Censored, Pooled)
      • Bain, Antle, Thomain - Bounds on the parameter estimates (Uncensored)
      • Likelihood Ratio - Bounds on the parameter estimates (Uncensored)

  • Goodness of Fit - Log Likelihood, Sum of Squared Residuals, Correlation Coefficient, Anderson-Darling

  • Probability Density Function Plot - includes PDF of parameter estimates and a Histogram of the data

  • Parameter Estimates are Exported to the CARES Material Parameter (CMP) File for subsequent use in component reliability

OTHER:

  • WeibPar interfaces with CARES to perform the following advanced features:
    • Using a Finite Element Model for arbitrary specimen geometry parameter estimation
    • Generating confidence bounds on component reliability via Monte-Carlo bootstrap techniques

  • Generate Data - A Monte-Carlo routine is available which allows the user to randomly generate sample data sets according to user inputs for the number of data points and the 3 Weibull parameters. (Setting the threshold parameter to zero will simulate a 2 parameter data set.)

For further information please review the WeibPar User Guide.

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