Numerical simulation data underlying the scientific paper Surrogate model for FEA analysis and damage calculation used for exhaust system validationZaletel, Jan (Avtor) Oman, Simon (Avtor) Nagode, Marko (Avtor) Klemenc, Jernej (Avtor) material fatiguedamagesurrogate modelcomputational modelingneural networkdesignoptimizationThe research data consist of the training and validation datasets and the source code used for building the surrogate model. They include both input and output data as well as surrogate model parameters. The data were generated for the purpose of training and validating a surrogate model (neural network) for predicting the fatigue life of an exhaust system. The goal of the methodology using a surrogate model is to replace time consuming finite element modeling and fatigue life calculations with a computationally simpler approach for determining the location and magnitude of the maximum damage.20262026-04-01 15:28:24Neznano181332slSlovenijaOd/From 2025-12-15 do/till 2025-03-26