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Performance Model Expressions
Performance Model Expressions

Table of Contents

Types of Forms Supported

The table below shows the model forms available for performance modeling in Pavement Analyst. Seven forms are available. You can calculate and select from each of the regression equations to choose the appropriate model.

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Linear

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y = a + bx

...

The rate of deterioration of the pavement condition is the same from year to year.

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Exponential

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y = a + becx

...

The pavement condition remains nearly constant for a number of years, and then rapidly deteriorates.

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Inverse Exponential

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y = a + becx

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The pavement condition remains nearly constant for a number of years, and then rapidly deteriorates.

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Hyperbolic

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y = a + 1 / (b + cx)

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The pavement condition deteriorates steadily with the greatest rate of deterioration occurring in the early years.

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Piecewise Linear

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y = ai + bix

(with intersection at the end points)

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You can specify up to six coordinates, and the system draws a straight line between each coordinate. This type allows you to specify points in time where the deterioration rate "jumps" to a new value, where it again remains constant until the next discontinuity.

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Power

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y = a + bxc

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This type of model is a special form of the exponential type. Like an exponential-type graph, the pavement condition remains nearly constant for a large number of years, and then rapidly deteriorates. However, the rate of deterioration is based directly on time rather than a logarithm.

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Sigmoidal

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y = a + be(-c/x)^d

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The pavement condition remains nearly constant for a number of years, then rapidly deteriorates, and then remains nearly constant again.

Where y = condition attribute being predicted, x = pavement age (in years), and a, b, c, and d = regression coefficients.

Out of the box, the list of all performance model expressions is in Performance Models List window, located under Pavement Analyst > Setup > Performance Setup > Performance Models List menu.

Create a New Performance Model Expression

To create a new performance model, perform the following steps:

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