## 2 Modelling and Methods
### ANN Complete Input Dataset (CID)  
Since part of the algorithm's structure (the size of the input layer) depends on the structure of the input dataset, it was considered important to conclude the data format prior to commencing the development of the ANN itself. A brief outline of the parameters used has been given in the description of the FE models; these were further refined and structured in an appropriate CSV file format ready for reading by the algorithm. The file incorporated columns representing the independent variables defining the FE models described in previous paragraphs. A \"timestamp\" column was also added to allow for the observation and correlation of the temperature magnitude on the non-exposed face of the wall over time as the phenomenon developed. The last column of the dataset included the output of the FE model analysis, the temperature observed on the non-exposed face of the wall at a 30 sec time step when the standard Eurocode fire curve was applied to the other face. Table 3 provides a typical section of the dataset file offered to the ANN algorithm; the example reflects the values used for an internally insulated wall panel. It is apparent that not all columns were necessary for the training, testing, and evaluation of the algorithm, thus the input data was further modified and stripped into a more appropriate format as part of the \"preprocessing\" phase (see following paragraphs). Nevertheless, these variables and references are useful for an intuitive understanding of the  
Figure 5: Artificial steep modification of insulation material properties to emulate its degradation until complete destruction due to fire exposure. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Index**} & **Sample** & **Brick** & **Thermal** & **Thermal** & **Insalution** & **Insalution** & **Insalution** & **Insalution** & **Time** & **Temperature of Non-Exposed Face** \\  & **Ref** & **Density** & **Coof.** & **Emissivity** & **Thickness** & **Type** & **Position** & **Time** & **Non-Exposed Face** \\ \hline \hline \multirow{2}{*}{\(\cdots\)} & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) \\
11,449 & Smpl6-1 & 2000 & 0.8 & 0.1 & 50 & EPS & Int & 18,990 & 41.77246 \\
11,450 & Smpl6-1 & 2000 & 0.8 & 0.1 & 50 & EPS & Int & 19,020 & 41.85622 \\
11,451 & Smpl6-1 & 2000 & 0.8 & 0.1 & 50 & EPS & Int & 19,050 & 41.94014 \\
11,452 & Smpl6-1 & 2000 & 0.8 & 0.1 & 50 & EPS & Int & 19,080 & 42.02421 \\
11,453 & Smpl6-1 & 2000 & 0.8 & 0.1 & 50 & EPS & Int & 19,110 & 42.10843 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Representative example of the dataset structure and contents. input data content and structure. Variables referring to material properties were discussed in detail in previous paragraphs. Other columns include:  
* Index--variable purely counting the number of unique observations included in the data. Each temperature measurement generated by the FE model analysis (time step of 30 s) is used as a separate observation. The complete dataset includes a total of 21,630 observations. The index was excluded from any training or testing of the algorithm. * Sample reference--this variable enabled the research team to easily cross-reference between the dataset tables and the analysis files. Similarly, it was excluded from any training or testing of the neural network. * Insulation type--the data structure and ANN algorithm were developed with the intention of incorporating and analysing various insulation materials. Although the present study only considers EPS, it was considered useful to build some flexibility in the algorithm, enabling the further expansion of the scope of work in the future. It takes the values \"EPS\" and \"NoIns\", representing the insulated and non-insulated wall samples, respectively. This categorical variable was encoded into a numerical one as part of the pre-processing phase. * Insulation position--this variable represents the position of the insulation.