Mathematical Modelling for Solving Engineering Problems
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 5626
Interests: mechanical engineering; manufacturing process; machining process; machine tools; vibration; damping; fatigue
Interests: control; computer science and communication; heterogeneous systems and networks; complex stochastic systems; mathematical and simulation models of heterogeneous networks; asymptotic analysis; artificial neural networks; speech analytics system; concept of artificial and human intelligence interaction; network design software; Intelligent robotic systems; hydroacoustic communication; underwater networks; uninhabited underwater vehicles; autonomous navigation; local positioning; visual odometry; mobile robots; control of moving objects
2. Director of Mechanical Characteristics Laboratory, Center for Laboratory Services, Sharif University of Technology, Tehran 11365, Iran
Interests: fatigue; structural fatigue; vehicle; shot-peening; random loading; applied mechanics; solid mechanics; structural integrity; fracture; residual stress; optimization; welding; surface treatment
Special Issues, Collections and Topics in MDPI journals
Mathematical modeling is often considered an art in formulating and solving equations rather than a science and is highly dependent on the experience and knowledge of the researchers involved. It requires both a good understanding of the nature of the process and familiarity with existing models and methods. In some practical cases, the studied phenomena are very complex, and any mathematical description is only an average approximation. Unavoidable simplifications and approximations made during the modeling process can greatly alter the predicted behavior of real-world phenomena. This is why applied mathematical modeling does not make sense without defining the purpose of modeling. Before developing a model, a specific existing problem must be explained, and the possible implications and benefits of the model must be explored. Modeling goals should be realistic, but not oversimplified. In general, the level of complexity of mathematical models varies considerably for different applied problems. In this regard, some mathematical equations for engineering problems and other phenomena in human daily life become classical equations and can be generalized for different conditions. However, for some complex issues, the derived equations are only specific to those conditions and cannot be used in similar cases. Therefore, it is necessary to carry out fundamental research by considering different conditions in an engineering problem or industrial challenge, and mathematical modeling of the system is done by fully covering the parameters affecting the system’s performance and the relationships between them. Although with the progress of science and technology various simulation software tools which can be used to analyze problems by considering initial and boundary conditions entered the market, we should not forget that behind the scenes of these tools there are mathematical relationships and models presented by scientists that can be generalized to different issues.
This Special Issue on “Mathematical Modelling for Solving Engineering Problems” focuses on advancing knowledge, specifically for the mathematical modeling of problems in different fields of engineering subjected to complex conditions, as well as their solution based on various solution techniques, including classic, data mining, machine learning, etc.
Dr. Siamak Ghorbani
Prof. Dr. Mais Farkhadov
Prof. Dr. Kazem Reza Kashyzadeh
Manuscript Submission Information
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- engineering problems
- industrial challenges
- catastrophic failures in various fields of engineering
- interdisciplinary issues
- fundamental research
- mathematical approximations
- numerical solution algorithms
- machine learning techniques