Applications of Mathematical Models in Engineering

Edited by
April 2022
418 pages
  • ISBN978-3-0365-3847-1 (Hardback)
  • ISBN978-3-0365-3848-8 (PDF)

This book is a reprint of the Special Issue Applications of Mathematical Models in Engineering that was published in

Computer Science & Mathematics
Physical Sciences
Public Health & Healthcare

The most influential research topic in the twenty-first century seems to be mathematics, as it generates innovation in a wide range of research fields. It supports all engineering fields, but also areas such as medicine, healthcare, business, etc. Therefore, the intention of this Special Issue is to deal with mathematical works related to engineering and multidisciplinary problems.

Modern developments in theoretical and applied science have widely depended our knowledge of the derivatives and integrals of the fractional order appearing in engineering practices. Therefore, one goal of this Special Issue is to focus on recent achievements and future challenges in the theory and applications of fractional calculus in engineering sciences.

The special issue included some original research articles that address significant issues and contribute towards the development of new concepts, methodologies, applications, trends and knowledge in mathematics.

Potential topics include, but are not limited to, the following:

Fractional mathematical models; Computational methods for the fractional PDEs in engineering; New mathematical approaches, innovations and challenges in biotechnologies and biomedicine; Applied mathematics; Engineering research based on advanced mathematical tools.

  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
fractional order IMC; first order plus dead-time processes; event-based implementation; numerical simulations; comparative closed loop results; nonlinear wave phenomen; RBF; local RBF-FD; stability; unmanned aerial vehicle (UAV); quaternion-based estimator; low-cost design; automatic optical inspection; kinetic theory; parallel robots; robust control; sliding mode control; basinI; basinII; mean pressure head; pressure head with different probabilities of occurrence; standard deviation of the pressure fluctuations; statistical modeling; USBR; desalination; humidification-dehumidification; waste heat recovery; mathematical model; yearly analysis; thermo-economics; multi-objective optimization; cruise altitude; fuel consumption; time to climb; Hermite-Simpson method; trajectory optimization; terminal residual analysis (TRA); m-σ terminal residual analysis (m-σ TRA); power transformer; stray losses; analytical methods; finite element method; gridshell structures; shape ratio; length ratio; regularity; particle swarm optimization; genetic algorithm; hybrid nanofluid; dual solutions; mixed convection; stagnation point; radiation; stability analysis; machine learning; eXterme Gradient Boosting; Computation Fluid Dynamics; blade vibration; unsteady aerodynamic model; active disturbance rejection control (ADRC); multiobjective optimization; time delay systems; tuning rules; soft robotics; robust control; fractional calculus; CACSD toolbox; operating point linearization; automatic uncertainty bound computation; Model-in-the-Loop simulation; hybrid simulation; robust control; ℋ control; μ synthesis; DC-to-DC power converters; buck; boost; SEPIC; rainfall-runoff model; curve number; inferential statistics; 3D runoff difference model; model calibration; PAT model; modified affinity laws; hydraulic simulation tool; μ-synthesis; robust control; fractional-order control; swarm optimization; artificial bee colony optimization; CNC machine; mixed sensitivity; DK iteration; Linear Matrix Inequality; biotechnology; fermentation process; batch bioreactors; modeling; control system design and synthesis; linear control; adaptive control; model reference adaptive control; control system realization; robust control; mixed-sensitivity; μ-synthesis; fractional-order control; FO-PID; twin rotor aerodynamic system

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