Modelado y simulación de sistemas mecánicos complejos mediante principios de la física aplicada en ingeniería

Julio César Morocho Orellana

doi:10.70577/ASCE/1317.1345/2025

Authors

Julio César Morocho Orellana Universidad Técnica de Machala https://orcid.org/0000-0001-9211-1856

DOI:

https://doi.org/10.70577/ASCE/1317.1345/2025

Keywords:

mechanical modeling, dynamic simulation, applied physics, complex systems, digital twins, neural networks, computational tools.

Abstract

The modeling and simulation of complex mechanical systems play a central role in the development of innovative engineering solutions. This article provides a systematic and analytical review of the state of the art in modeling multicomponent mechanisms, with a focus on integrating applied physics principles and advanced computational tools. The study explores theoretical foundations of dynamic-structural modeling, ranging from Newton's laws and Lagrangian mechanics to material mechanics and vibration theory. It also addresses modern simulation techniques such as modal analysis, inverse kinematics, and multidomain co-simulation. The research identifies key methodological approaches equation-based, data-driven, and hybrid models—as well as the most commonly used tools, including MATLAB, ANSYS, SolidWorks, and Adams. The findings reveal a trend toward hybrid models that combine the precision of physics with the flexibility of machine learning, highlighting approaches such as PINNs, PINODE, and digital twins. Effective validation criteria are discussed, along with persistent challenges such as noise sensitivity, computational scalability, and the faithful representation of complex phenomena. Finally, the study outlines future research directions aimed at enhancing model accuracy, computational efficiency, and practical applicability in real-world engineering contexts.

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