Progress in modeling of the flexible bodies beyond state-of-the-art was achieved in novel approach of defining inertia terms of the deformable bodies in the FFRF where directly a matrix calculus were applied. This allow to direct utilization of the distributed model mass. In addition, procedure efficiency was improved. As the large systems often occurs, this may have a significant effect on usability of the proposed solution. Second progress came in the form of robust damping modeling for the rope. This as well has important practical implications as no real-world rope model can operate without damping. Moreover, the additional study of the reinforcement learning control went beyond the applications found in the current literature, as the employed model of machine is complex and realistic what is rare in most applications.
The direct effect of the project is the support of the deformable components in Mevea simulations. This affects all Mevea’s customers, places mostly in Europe area, by providing reliable simulations and training simulators. Mevea’s customers include wide variety of businesses, including mining, earth-moving machinery designers, crane designers, and wood industry. This allow to design and manufacture safer and more reliable machines and allow faster and simpler introduction of skilled worker to the marked. Published papers, amplify this effect to more businesses and markets.
From wider perspective, developed solutions, may affect many areas and technologies: machine design, rapid training, model-based control, autonomous vehicles, edge computing, smart sensors, digital twins, and others. Many of those are still in development or early implementation phase and aims on revolutionizing the whole life cycle of machines and vehicles: design, manufacturing, operation, maintenance, and decommission. For sociate it means safer, more reliable, energy efficient, environmentally friendly, and maintainable products.
