PLOT.TTS {TTS} | R Documentation |
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 antoniomenesesfreire@hotmail.com, Salvador Naya salva@udc.es and Javier Tarrio-Saavedra jtarrio@udc.es
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")