ThermalBC PropertiesBoundary condition for thermal model NodalThermalICs PropertiesInitial temperature at mesh nodes GeometricThermalICs PropertiesInitial temperature over a region or region boundary PDESolverOptions PropertiesAlgorithm options for solvers ...
Check for missing argument or incorrect argument data type in call to function 'specifyCoefficients'. The model is defined as follows: obj.tm_SS = createpde('thermal','steadystate'); gdm = [r0;r9;r1;r2;r3;r4;r5;r6;r7;r8]';
First, define a sinusoidal load function,sinusoidalLoad, to model a harmonic load. This function accepts the load magnitude (amplitude), thelocationandstatestructure arrays, frequency, and phase. Because the function depends on time, it must return a matrix ofNaNof the correct size whenstate.time...
The toolbox is also designed to provide users with more flexibility and capabilities when coupled with other MATLAB toolboxes including Partial Differential Equation Toolbox or Optimization Toolbox. This results in a very powerful tool that can be used within MATLAB to perform mesh generation, create...
4.1.2. Shape function order effect This subsection explores the impact of shape function order on the accuracy and efficiency of computations in the FEINN framework. Specifically, we still utilize the four cases in Fig. 3 for analysis, and the mesh size selection is the same in section 4.1....
The toolbox is also designed to provide users with more flexibility and capabilities when coupled with other MATLAB toolboxes including Partial Differential Equation Toolbox or Optimization Toolbox. This results in a very powerful tool that can be used within MATLAB to perform mesh generation, create...
The iteration steps were continued until the temperatures within the model reached equilibrium, typically after 3500 iterations. Post processing The heat flux from the frames into the surrounding air was computed from each of the runs using the wallHeatFlux (Venkatesh 2016) post processing function....
As a result of the first 7000 iterations, the network loss function converged on both the training and test sets of the random load paths data set. The loss function jumps at the beginning of the fine-tuning process when samples from cyclic loads are fed to the network. The network is ...
Therefore, the ‘radial basis function’ is chosen as the kernel type which is a non-linear kernel. According to Long et al. [23] the recommended range of optimal regularisation parameter for JDA lies within λ∈[0.001,1]. Thus, the hyperparameter (regularisation parameter = 1) adopted ...
The partition function ZT(x, t) of directed paths from the apex (0,0) to a site (x, t) on the 1 + 1 dimensional delta is calculated recursively by the relation [25,26,28] (31)ZT(x,t+1)=ZT(x-1,t)exp[-ɛ(x-1,t)/T]+ZT(x+1,t)exp[-ɛ(x+1,t)/T] where ε(x...