PSI - Issue 80

Vinit Vijay Deshpande et al. / Procedia Structural Integrity 80 (2026) 327–338 Vinit V. Deshpande et al./ Structural Integrity Procedia 00 (2019) 000 – 000

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4. Conclusion The work focusses on modelling electrical resistance of 2D composite specimens made up of circular conductive particles embedded in polymer matrix. A typical method of modelling such systems is a Resistor Network method which is easily scalable but is inaccurate due to the way the particle resistance is modelled. The best available method of modelling particle resistance is analytical solutions to the Laplace equation. However, this method fails in the presence of complex inter-particle contact. This work demonstrates use of a generative AI method called cGAN to model the current flow in the composite specimens and shows that it gives much better accuracy then the Resistor Network method. In future studies, the cGAN method will be used to model larger microstructures to predict resistances at the scale of applications.

Acknowledgements This research was supported by the Hessian Ministry of Higher Education, Research, Science and the Arts, Germany within the Framework of the “Programm zum Aufbau eines akademischen Mittelbaus an hessischen Hochschulen”. Romana Piat acknowledge the support of DFG through project PI 785/9 -1.

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