2. Getting Started

Installation

TInsul can be installed using pip:

pip install tinsul

Other required libraries: numba, numpy, pandas

Examples

The main function within TInsul is called “tinsul_sim”. It requires only one input (an array of temperatures), although a number of other optional inputs can also be supplied. “temps” is a 12x3 matrix, with the rows being months of the year (starting with January), and the columns being the low, average, and high temperatures per month, respectively. Alternatively, supplying “default” to the temps parameter will use the average monthly temperatures for Washington DC. “start_month” refers to the month at which to begin the simulation, with 1 being January, 2 being February, etc.

For example:

>>> temps = [[-2, 1, 6], [-1, 3, 8], [3, 7, 13], [8, 13, 19], [14, 18, 24], [19, 24, 29], [22, 28, 31], [21, 27, 30], [17, 22, 26], [10, 15, 20], [5, 10, 14], [0, 4, 8]]

>>> start_month = 1

>>> df = tinsul_sim(temps, start_month)

The output of the tinsul_sim function will be a DataFrame containing the condition indicators for paper insulation failure (CO, CO2, Furan, Furfural, Water Content). The size of the array can be used to infer the failure time, in weeks.