####################################################
### V6 Resource File                             ###
### generated on: Mon May 16 10:05:26 EDT 2011   ###
###                                              ###
### This file is designed to be delivered to the ###
### translator. 					###
####################################################
8101=Could not evaluate the design point -  response value is null.
11639=MPP - Most Probable Point of failure
13689=Actual Reliability
14027=Gradient at MVP in x-space
17511=SENSITIVITIES
24638=Bound Value
30443=Std. deviation
30860=MVP - Mean Value Point
31728=Random Variable
31808=Value has to be greater than\ 0
31922=Could not read response variable attributes
34786=Could not evaluate design point
36970=Could not evaluate the design point.
39316=Mean
50490=Reliability Index (beta)
53063=Responses at Mean Value Point: 
55648=Could not read the random variable attributes.
60016=Reliability Constraint
60739=Could not read random variable attributes
66560=Reliability Constraint: 
67554=Nominal Value
74687=Fractional Effect
85221=Could not clone context for mean value point
91232=Response
94631=Reliability Constraint results: 
97083=Bound Type
####################################################
###   Meta Model I18N string                       #
####################################################
prop.dispname.minfinitedifferencestep=Min Finite Difference Step
desc=Mean Value Reliability Method
dispname=Mean Value Method
prop.dispname.finitedifferencestepsize=Finite Difference Step Size
prop.dispname.evaluationorder=Taylor Series Order
longdesc=<b>Mean Value Reliability Method</b> <br><br> The <i>Mean Value Reliability Method</i> is a probabilistic method that comes from civil engineering, originally developed for performing structural reliability analysis. Given one or more identified random variables, the focus in structural reliability analysis is to assess the <i>probability of failure</i> - the probability of violating a constraint - of a structural component or system, resulting from performance (output) variation caused by the variation of uncertain, random (input) variables. The structural reliability is then defined as the probability of satisfying a constraint, and is equal to 1-probability of failure.\t<br><br> The Mean Value reliability method utilizes the Taylor's series expansion of failure functions g(<b>X</b>) at the mean values \u00B5<sub>x</sub> of the random variables. A first or second order Taylor's expansion is used to estimate the mean and standard deviation of the failure functions.  The mean-value reliability index is then calculated as a function of the mean and standard deviation of g(<b>X</b>): <br><br> \u03B2 = \u00B5<sub>g</sub>/\u03C3<sub>g</sub> <br><br> Given the reliability index, the probability of failure can then be calculated as P<sub>f</sub> = \u03A6(-\u03B2). <br><br> The mean value method is the most efficient of the reliability analysis methods in terms of the number of function evaluations, or simulation program executions, needed to calculate the reliability. It requires only one time failure function and sensitivity evaluations. However, the mean-value reliability index is most only accurate for linear or quadratic failure functions with normally distributed random variables.  In other situations, the mean-value reliability index loses accuracy.
