TPMplt package

TPMplt, short for thermal processing-map plot, is a tool-kit for constructing dynamic material model (DMM) and corresponding visualization

Installation

Installation from github:

if(! "devtools" %in% installed.packages()) install.packages("devtools")
devtools::install_github("CubicZebra/TPMplt")

Installation from CRAN:

install.packages("TPMplt")

Main functions

TPMplt is a tool-kit for building and visualizing the dynmaic materials model (DMM), suggested by Prasad and Gegel. It provides an easy approach to calculate constructive functions and other related material constants based on a given strain condiiton. 2D and 3D processing-maps with temperature as its x axis, while logarithm strain rate as its y axis are also available.

Workflow

Workflow Overview
Workflow Overview

Multi-function polynomial fitting

The function AllPF() can apply polynomial fitting for all user-customized subsections for all raw stess-strain curves.

The raw data will be like:

Raw stress-strain curves
Raw stress-strain curves

After multi-functional polynomial fitting, the curves will be:

Fitted stress-strain curves
Fitted stress-strain curves

Temperature correction

Before making the processing maps, temperature correction should be applied. By calling the function TCorrect() to the raw data, the fitted result will be:

Temperature-corrected stress-strain curves
Temperature-corrected stress-strain curves

Computation for dynamic material model and output corresponding figures

The key function to build dynamic material model (DMM) from raw data is achieved by DMMprocess(). This function has two most important arguments: InteractMode and ConsFun. The argument InteractMode control the output of figures and parameters computed for DMM, here’re some examples:

Temperature-corrected stress-strain curves
Temperature-corrected stress-strain curves

Related parameters will be printed out in console when InteractMode is TRUE:

Print of related parameters
Print of related parameters

Processing Map Preview

Tranditional 2D processing map

Afer making the model and applying regression, the 2D processing map can be generated as:

Preview of 2d processing map
Preview of 2d processing map

The background in gradient colors informs the stability coefficient \(\xi\) while the contours reminds the power dissipation efficiency \(\eta\).

3D processing maps

\(\xi\) and \(\eta\) can also be respectively generated using the 3D plot function. The result will be as:

3D processing map
3D processing map

Contact

Author: ZHANG Chen

Mail: 447974102@qq.com