| ABS | Acrylonitrile Butadiene Styrene |
| ANN | Artificial Neural Network |
| ASA | Adaptive Simulated Annealing |
| CL | Custom Loss |
| CLF | Custom Loss Function |
| DIC | Digital Image Correlation |
| DOE | Design of Experiments |
| DTW | Dynamic Time Warping |
| EPS | Equivalent Plastic Strain |
| EPSF | Equivalent Plastic Strain at Failure |
| EXP | Experiment |
| FDC | Force–Displacement Curve |
| FE | Finite Element |
| GA | Genetic Algorithm |
| GBM | Gradient-Based Methods |
| GISSMO | Generalized Incremental Stress State-Dependent Damage Model |
| GD | Gradient Descent |
| HL | Hidden Layer |
| HP | Hyperparameter |
| HPO | Hyperparameter Optimization |
| IL | Input Layer |
| LFOP | Leap-Frog Algorithm |
| LH | Latin Hypercube |
| LHS | Latin Hypercube Sampling |
| MDPI | Multidisciplinary Digital Publishing Institute |
| ML | Machine Learning |
| MP | Material Parameter |
| MPI | Material Parameter Identification |
| MSE | Mean Squared Error |
| MCIC | Material Card Input Curve(s) |
| NAN | Not a Number |
| NN | Neural Network |
| OL | Output Layer |
| PEC | Plastic Poisson’s Ratio Equivalent Plastic Strain Curve |
| PI | Parameter Identification |
| PPR | Plastic Poisson’s Ratio |
| RSM | Response Surface Methodology |
| SOC | Simulation Output Curve(s) |
| TRI | Triaxiality |
| VAL | Validation |
| VPPR | Variable Plastic Poisson’s Ratio |