PLOT.TTS: Time-Temperature Superposition (TTS) plots

In TTS: Master Curve Estimates Corresponding to Time-Temperature Superposition

Time-Temperature Superposition (TTS) plots

Description

Plots of TTS results: experimental data, horizontal and vertical shifts, TTS data, TTS Master Curve fitting with B-Splines and bootstrap confidence intervals are deployed.

Usage

PLOT.TTS(x)

Arguments

x	TTS object.

Details

TTS plots are performed from the outputs of TTS function: data, aT, bT, TTS.data, TTS.gam y residuals.

Value

The following values are returned:

PLOT.data()	Generic function to plot the experimental data. By default log10.module versus log10.frequency.
PLOT.aT()	Generic plot of the horizontal shifts corresponding to each curve (modulus versus frequency) obtained on temperature.
PLOT.bT()	Generic plot of the vertical shifts corresponding to each curve (modulus versus frequency) obtained on temperature.
PLOT.TTS.data()	Generic plot of the experimental data horizontally and vertically shifted with respect to a the curve corresponding to the reference temperature.
PLOT.TTS.gam()	Generic plot of the Master Curve B-splines estimation with bootstrap confidence intervals at 95 per cent.
PLOT.res()	Generic plot of the residuals of Master Curve B-splines fitting.

Author(s)

Antonio Meneses [e-mail], Salvador Naya [e-mail] and Javier Tarrio-Saavedra [e-mail]

References

Naya, S., Meneses A., Tarrio-Saavedra, J., Artiaga R., Lopez-Beceiro, J. and Gracia-Fernandez C. (2013) New method for estimating shift factors in time-temperatura superposition models. Journal of Thermal Analysis and Calorimetry. ISSN 1388-6150. DOI 10.1007/s10973-013-3193-1.

Williams, M. L. (1964) Structural analysis of Viscoelastic materials. AIAA Journal, 785-808.

Artiaga R., Garcia A. Fundamentals of DMA. In: 'Thermal analysis. Fundamentals and applications to material characterization' (ed.: Artiaga R.) Publicaciones de la Universidade da Coruna, A Coruna, Spain, 183-206 (2005).

Examples

## TTS object applied to PC dataset.
data(PC)
Derive <- TTS(PC)
x <- Derive
## Generic plots for TTS analysis
PLOT <- PLOT.TTS(x)
names(PLOT)
##[1] "PLOT.data"     "PLOT.aT"       "PLOT.bT"       "PLOT.TTS.data"
##[5] "PLOT.TTS.gam"  "PLOT.res"
## Generic plots of: data, aT, bT, TTS.data, TTS.gam and res
PLOT$PLOT.data(main="PLOT: Data",xlab="log10.Frequency (rad/s)",ylab="log10.E'(Pa)")
PLOT$PLOT.aT(main="PLOT: horizontal translation factors", xlab="Temperature", ylab="aT")
PLOT$PLOT.bT(main="PLOT: vertical translation factors", xlab="Temperature",ylab="bT")
PLOT$PLOT.TTS.data(xlab="log10.Frequency (rad/s)",ylab="log10.E'(Pa)")
PLOT$PLOT.TTS.gam( xlab="log10.Frequency (rad/s)", ylab = "log10.E'(Pa)",
main = "Fitted gam, Bootstrap confidence intervals",
sub = "Reference temperature = 150 degrees celsius")
PLOT$PLOT.res(main="TTS: gam residual", xlab="Fitted", ylab="Standardized residuals")

TTS documentation built on March 7, 2023, 8:02 p.m.