MODELING OF DYNAMIC SYSTEMS IN THE DESIGN OF MECHANICAL STRUCTURES FOR INDUSTRY
DOI:
https://doi.org/10.33042/2522-1809-2025-1-189-209-216Keywords:
kinematic analysis, engineering optimisation, structural dynamics, vibration stabilityAbstract
Modeling dynamic systems in the design of mechanical structures is a crucial area of modern engineering as it ensures increased efficiency, reliability, and resilience of equipment under changing operational conditions. The relevance of this study is driven by the necessity to develop high-tech solutions that address contemporary industrial challenges, particularly through the integration of adaptive and parametric approaches to design. The growing demands for energy efficiency, durability, and cost reduction in maintenance highlight the importance of utilizing innovative materials and modern engineering tools.
The aim of this study is to develop approaches for modeling dynamic systems using integrated parametric and adaptive methods to enhance the efficiency and resilience of mechanical structures under variable operational conditions. To achieve this aim, the study employed analytical reviews of contemporary approaches to dynamic system design, modeling of their behavior under changing loads, and comparative analysis of methods for integrating adaptive solutions into mechanical structures.
The study analyzed modern methods for modeling dynamic systems and assessed their practical efficiency in the industry. A model was developed to integrate parametric and adaptive approaches, enabling the optimization of structures while considering variable technological conditions. Key challenges were identified, including the high cost of implementation, technical limitations of software, and insufficient integration of innovations into traditional manufacturing processes.
The conclusions emphasize that the use of adaptive solutions and advanced materials significantly reduces vibrations, increases structural durability, and decreases maintenance costs. Recommendations include implementing sensor networks and digital twins for real-time equipment monitoring, as well as improving optimization models.
The prospects for further research involve developing new algorithms to enhance energy efficiency, integrating adaptive systems into industrial equipment, and creating innovative methods for predicting the technical condition of structures. This will ensure high industrial competitiveness in a dynamically changing market environment.
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