Advances in Applied Mathematics, Mechanics and Engineering, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".

Deadline for manuscript submissions: 30 March 2026 | Viewed by 855

Special Issue Editors


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Guest Editor
Faculty of Mechanics, University of Craiova, 200512 Dolj, Romania
Interests: industrial and biological robots; mechanisms; car bodies and mechanical transmissions; computer-aided design; modeling and simulation with finite elements
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Faculty of Mechanics, University of Craiova, 200512 Dolj, Romania
Interests: geometric modeling; finite element analysis; modeling technological processes; programming languages development of API applications on commercial graphics cores; virtual prototyping
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Applied Mathematics, Mechanics, and Engineering cover many research domains, and this issue represents a fountain flowing with innovative development. This Special Issue aims to create a research core of high-quality refereed articles discussing various aspects of applied mathematics in mechanics, and mechanical engineering modeling phenomena and their peculiarities. Thus, the proposed topics will highlight research articles dedicated to the mathematical modeling of technical problems arising in domains such as engineering, applied mechanics, medicine, robotics, science, technology, etc.

This Special Issue will be represented by high-quality articles related to the following interest topics:

  • Mechanical systems modeling; simulations methodology, and algorithms.
  • Dynamic analysis of mechanical systems.
  • Kinematics of mobile mechanical systems and their application.
  • Vibrations and impact phenomena modeling.
  • Mathematical models applied in mechanical engineering.

Prof. Dr. Nicolae Dumitru
Dr. Adrian Sorin Rosca
Guest Editors

Manuscript Submission Information

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Keywords

  • computational mechanics
  • kinematics
  • dynamics and control of mechanical systems
  • modeling and simulations in biomechanics
  • robotics and mechatronics
  • experimental mechanics
  • composite materials
  • algorithms
  • advanced methods for optimizing in mechanical engineering

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Published Papers (2 papers)

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Research

34 pages, 6658 KB  
Article
Computational Method for Dynamic Analysis of Multibody Systems with Deformable Elements
by Sorin Dumitru, Nicolae Dumitru, Cristian Copilusi and Adrian Sorin Rosca
Mathematics 2025, 13(17), 2797; https://doi.org/10.3390/math13172797 - 31 Aug 2025
Viewed by 417
Abstract
The dynamics of mechanical systems with fast motions and dynamic loads are strongly influenced by the deformability of kinematic elements. The finite element method and the superposition of rigid body motion with deformable body motion allow us to determine a new structure for [...] Read more.
The dynamics of mechanical systems with fast motions and dynamic loads are strongly influenced by the deformability of kinematic elements. The finite element method and the superposition of rigid body motion with deformable body motion allow us to determine a new structure for the matrices that define the mechanical system equations of motion. Meshing the kinematic elements into finite elements causes the unknowns of the problem to no longer be displacement functions but rather nodal displacements. These displacements are considered as a linear combination of modal shapes and modal coordinates. This method is applied to a drive mechanism of an internal combustion engine with three pistons mounted in line. The system is driven by the pressure exerted by the gas on the piston head, which was experimentally determined. The longitudinal and transversal deformations of the connecting rod are determined, including the nodal displacements. These results were verified through virtual prototyping on the 3D model, using multibody system theory and the finite element method. The recorded differences are mainly explained by the type, size, and shape of the used finite elements. Experimental analysis allows us to determine the connecting rod kinematic and dynamic parameters as functions of time and frequency variation. The developed method is flexible and can be easily adapted to systems with fast motions in which, during operation, impact forces appear in joints for various reasons. Full article
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25 pages, 16252 KB  
Article
Investigation of Resonance Modes in Iced Transmission Lines Using Two Discrete Methods
by Rui Chen, Wanyu Bao and Mengqi Cai
Mathematics 2025, 13(15), 2376; https://doi.org/10.3390/math13152376 - 24 Jul 2025
Viewed by 216
Abstract
To investigate the oscillation modes of iced transmission lines, this study introduces a forcing term into the galloping equation and applies two discretization approaches: Discrete Method I (DMI), which directly transforms the partial differential equation into an ordinary differential form, and Discrete Method [...] Read more.
To investigate the oscillation modes of iced transmission lines, this study introduces a forcing term into the galloping equation and applies two discretization approaches: Discrete Method I (DMI), which directly transforms the partial differential equation into an ordinary differential form, and Discrete Method II (DMII), which first averages dynamic tension along the span. The finite element method is employed to validate the analytical solutions. Using a multiscale approach, amplitude-frequency responses under primary, harmonic, and internal resonance are derived. Results show that DMII yields larger galloping amplitudes and trajectories than DMI, with lower resonant frequencies and weaker geometric nonlinearities. In harmonic resonance, superharmonic and subharmonic modes (notably 1/2) are more easily excited. Under 2:1:2 internal resonance, amplitude differences in the vertical (z) direction are more sensitive to the discretization method, whereas the 1:1:1 case shows minimal variation across directions. These findings suggest that the choice of discretization significantly influences galloping behavior, with DMII offering a more conservative prediction. Full article
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