Taiwan also faces the difficulties mentioned above. The tangible cultural heritage sites and the important cultural relics are mainly composed of wood and masonry. Resistance to natural and manmade disasters is mostly insufficient, especially to fire caused by earthquakes. The research method of this article included analyzing the data collected from field post-disaster investigations following the fire in 1995, as well as conducting computer simulations with computational fluid dynamics (CFD). Therefore, this study discusses the fire risk caused by earthquakes toward tangible cultural heritage sites with a performance verification of resilience in a worst-case scenario.
4.3. Mesh for the FDS Parallel Process
FDS was used to divide the research space into small grids for calculation. Grids with different thicknesses or dimensions significantly affect the accuracy of the calculation results. The xyz
ratio of grids varies widely, leading to errors in the calculation result even when using very thin grids. Thus, it is recommended to cut the simulation space into a number of numerical grids close in shape to a cube (i.e., close to an xyz
ratio of 1:1:1), as shown in Figure 3
. The building was cut into six meshes, and each mesh was assigned to a central processing unit (CPU) for calculation. This study focused on the technical threshold of FDS for simulating large spaces, such as historical groups of buildings at tangible cultural heritage sites, handling both the efficiency and the accuracy of the simulation. The concept of resource sharing in parallel processed involves combining the computing power of multiple cores, thereby reducing the amount of data processed by a single computer via data exchange between computers in adjacent meshes. Then, all the processed data are transferred to the host computer for consolidation, as would happen in calculations using a single super computer [17
]. The background details related to the mesh, grids, CPUs, and simulation can be seen in Table 4
. Each mesh involved 1,012,500 to 1,350,000 grids, and each CPU had a 3.6 GHz/hexa core, with 8 GB random-access memory (RAM), used for the full-scale fire simulation. The total number of grids in the six meshes was 6,412,500.
The brief results of the two designs involving full-scale buildings and narrow ranges in a single house show that the performance in terms of space dimension, area, and CPUs of the parallel design was much better, except for the CPU time which was similar at 45 h, as shown in Figure 4
The temperature profile of the full-scale simulation (nine temples) was much clearer than the local-scale range of the FDS. In fact, taking 45 h to finish a 600 s simulation with 6.4 million grids is very helpful for researchers or designers pursuing ideal input data modification.
Therefore, the computing time is much shorter than that of a personal computer, and the actual results can overcome the limitation of the space range to achieve full-size simulations of large spaces while taking into account the research results of precision, validity, and range.
The input data of FDS parallel processes are described below for six CPU design scenarios with 6,412,500 grids, obeying the regulation of a Poisson solver based on fast Fourier transforms (FFTs); each grid’s dimensions followed the form of 2l
, where l
, and n
are integers [19
]. The instructions for the input data of the six CPUs were as follows with the definition of grid size and dimensions of six meshes:
&MESH ID = ‘Mesh1’, IJK = 60,225,75, XB = 28.0,40.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 0/GRIDs = 1,012,500 = [(40.0 − 28.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2];
&MESH ID = ‘Mesh2’, IJK = 60,225,75, XB = 40.0,52.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 1/GRIDs = 1,012,500 = [(52.0 − 40.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2];
&MESH ID = ‘Mesh3’, IJK = 60,225,75, XB = 52.0,64.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 2/GRIDs = 1,012,500 = [(64.0 − 52.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2];
&MESH ID = ‘Mesh4’, IJK = 60,225,75, XB = 64.0,76.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 3/GRIDs = 1,012,500 = [(76.0 − 64.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2];
&MESH ID = ‘Mesh5’, IJK = 60,225,75, XB = 76.0,88.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 4/GRIDs = 1,012,500 = [(88.0 − 76.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2];
&MESH ID = ‘Mesh6’, IJK = 80,225,75, XB = 88.0,104.0,14.0,59.0,0.0,15.0, MPI_PROCESS = 5/GRIDs = 1,350,000 = [(104.0 − 88.0)/0.2] × [(59.0 − 14.0)/0.2] × [(15.0 − 0.0)/0.2].
The fire simulation calculation of a single computer is limited by the size of the space, thereby only presenting the fire phenomenon in a limited space. The data calculation involves a single mesh for a single CPU, as shown by the blue dotted line in Figure 3
. The parallel process diagram of FDS instead featured six meshes assigned to six CPUs to complete the 76 m × 45 m × 15 m full-scale simulation of the building, as shown by the red line in Figure 3
and Figure 4
The left side of Figure 5
shows the limited range of a fire simulation, whereby the temperature near the ignition source can reach 650 °C, which is much higher than the temperature value safe for human life of 60 °C, shown as the black area. The critical temperature of wood (260 °C) was also reached, presenting the possibility of igniting adjacent wooden objects and structures of tangible cultural heritages made of wood. The temperature near the fire source could reach 650 °C after ignition in the main hall for 600 s. However, it is not possible to know whether the temperature in other parts of the main hall reached the dangerous wood critical temperature of 260 °C. On the right side of Figure 5
, a temperature of 670 °C was reached in 10 min due to a general fire source with damage to adjacent buildings. The full-area simulation on the right side of Figure 5
shows that the temperature of the main hall could reach 670 °C and expand from the opening door, as shown by the black curve. It is helpful to understand the full picture of the simulation for the whole area before planning the design of a protective strain mechanism.