## 4 Results and Discussion
### Sensitivity Tests  
This section describes the sensitivity analysis performed to identify the body motion parameters where the results were more sensitive and prone to changes. These parameters were _Acceleration Relaxation_ (_AR_), which acts to reduce the acceleration directly; _Acceleration Damping_ (_AD_), used to eliminate the divergence generated from sudden acceleration events and proportional to the magnitude of the acceleration; _Inner Distance_ (_ID_), the extension of the region of motion of the fluid around the solid body; and, finally, _Outer Distance_ (_OD_), which refers to the extent of the mesh transformation region around the body. The _inner_ and _outer_ distances are equivalent to diffusivity; however, as a function of distance. In reviewing the literature, not much information was found on these body motion parameters and few authors mention the topic, e.g., [PERSON] et al. (2019); [PERSON] et al. (2019) investigated _mesh morphing_ and _overset grid_ methods, comparing their results with the data from an experimental tank of the WaveStar device, inferring that the use of the _overset grid_ method is computationally more expensive and a thorough model setup is required; hence, _inner_ and _outer_ distances could be parameterized by the buoy's radii or length. The adopted values here are within the ranges previously considered. The grid points in the range _ID_ < \(D\) < _OD_ were deformed while the object was moving and, often, the _ID_ values were in the order of the boundary layer thickness, and _OD_ was limited by the nearest domain boundary ([PERSON] et al., 2018; [PERSON] et al., 2018). The analysis was performed considering the variation in the coefficients at a constant radius \(R\) = 0.25 m, and the values are shown in Table 4. The simulations were labeled as P1 to P9, performed for periods of 4 and 8 s. For each test, a total of 100 wave periods was simulated without crashing. The nine cases presented in Table 4 were divided into five groups, testing a combination of different parameters. Table 5 shows the P1-P9 tests that were labeled after the parameter examined in addition to the wave period. For example, in test OD-4T, cases P1 and P2 were compared, where only the _Outer Distance_ parameter was modified and the rest remained unchanged; test ID-4T analyzed the differences between P3 and P4, where only the _Inner Distance_ parameter was modified, and so forth. The analysis of the _AR_ parameter was omitted because no considerable effect was noted for the adopted values, which represent the rate of the decrease in acceleration. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Case** & **T (s)** & **AR** & **AD** & **ID** & **OD** \\ \hline P1 & & 0.7 & 1.0 & 0.001 & 1.5 \\ P2 & & 0.7 & 1.0 & 0.001 & 2.0 \\ P3 & 4 & 0.5 & 0.5 & 0.001 & 1.5 \\ P4 & & 0.5 & 0.5 & 0.0001 & 1.5 \\ P5 & & 0.7 & 0.75 & 0.001 & 1.5 \\ \hline P6 & & 0.7 & 0.75 & 0.001 & 1.5 \\ P7 & & 0.7 & 1.0 & 0.001 & 1.5 \\ P8 & & 0.5 & 0.5 & 0.001 & 1.5 \\ P9 & & 0.5 & 0.5 & 0.00001 & 1.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Coefficients of the simulation cases for the sensitivity tests for \(H\) = 1.0 m, \(T\) = 4 s, and 8 s, conducted for a buoy with \(R\) = 0.25 m. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Buoy** & **_T = 4 s_** & **_T = 8 s_** \\ \hline \multicolumn{3}{c}{**Computation Time (Hours)**} \\ \hline \(R_{1}\) & 127.23 & 260.23 \\ \(R_{2}\) & 226.01 & 491.94 \\ \(R_{3}\) & 615.93 & 1246.81 \\ \(R_{4}\) & 1196.84 & 2390.67 \\ \(R_{5}\) & 2027.45 & 3488.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Computation time using the mesh morphing method. These tests were initially assessed by calculating the instantaneous power by multiplying the instantaneous values of the torque (\(\tau\)) and angular velocity (\(\omega_{r}\)): the output power was calculated as the average of the instantaneous power over the time of the simulation.