PSI - Issue 79

Qinghui Huang et al. / Procedia Structural Integrity 79 (2026) 291–297

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Figure 4 Schematic diagram of cyclical loading waveform.

The data reveal that as cycle count (t) increases, the accumulated plastic strain of LPBF GH4169 exhibits a nonlinear growth trend, consistent with the microdeformation mechanisms under cyclic loading. During the initial stage, the accumulated plastic strain rises rapidly. This occurs because LPBF GH4169 initially can contains a high density of dislocations, which rapidly move and proliferate under cyclic loading, significantly increasing plastic deformation. Comparative analysis of curves at different strain amplitudes shows that higher amplitudes result in greater accumulated plastic strain at equivalent cycle counts. For instance, at t = 5 (N=50 cycles, as shown in Fig. 4), the 0.25% strain amplitude corresponds to a larger accumulated plastic strain than the 0.15% ampl itude. This occurs because higher strain amplitudes generate greater internal local stresses, which more effectively promote dislocation motion and multiplication, thereby accelerating plastic strain accumulation. The results demonstrate excellent agreement between the neural network- predicted curves and the CPFEM simulation results, particularly at the 0.25% strain amplitude. The INN model effectively captures the gradual deceleration in the rate of plastic strain accumulation as the number of cycles increases. 3.2 Evaluation of model prediction performance Fig. 5 illustrates the trends of training and validation losses over epochs for three neural network models: simple, single-hidden-layer, and double-hidden-layer networks.

Figure 5 Loss curve comparison of different model architectures.