Mathematical, Computational and Data-Driven Methods in Mechanics, Engineering and Applied Sciences

Topic Information

Dear Colleagues,

The fields of mechanics, engineering, and applied sciences are currently undergoing a profound paradigm shift. Traditional mathematical modelling and computational simulation are increasingly being integrated with advanced data-driven approaches, including machine learning, artificial intelligence, optimization techniques, and large-scale data analytics. This convergence enables the analysis, prediction, and control of highly complex, nonlinear, uncertain, and multiscale systems, opening new opportunities for scientific discovery and engineering innovation.

The aim of this cross-journal Topic is to provide an international and multidisciplinary forum for researchers working at the intersection of mathematical modelling, computational methods, data-driven methodologies, and intelligent decision-support systems. The Topic seeks to foster synergies between theoretical developments and practical applications, bridging physics-based modelling, numerical simulation, optimization, artificial intelligence, and data analytics to address current challenges in mechanics, engineering, and applied sciences.

We welcome high-quality original research articles, reviews, and methodological contributions addressing, but not limited to, the following topics:

• Mathematical modelling and numerical methods in engineering and applied sciences;
• Computational mechanics, computational physics, and scientific computing;
• Numerical simulation of engineering systems, including solid, fluid, structural, thermal, and coupled problems;
• Data-driven, hybrid, and physics-informed modelling approaches;
• Machine learning, artificial intelligence, computational intelligence, and data analytics for scientific and engineering applications;
• Optimization, operations research, inverse problems, and parameter identification;
• Decision-support systems, multi-criteria decision-making, and intelligent engineering systems;
• Uncertainty quantification, risk analysis, reliability assessment, and predictive modelling;
• Digital twins, smart systems, Industry 4.0, and intelligent manufacturing;
• Multiphysics, multiscale, and integrated modelling of complex systems;
• High-performance computing, advanced computational algorithms, and scalable numerical frameworks;
• Integration of experimental data, sensing technologies, and computational models;
• Applications in mechanics, materials science, energy systems, environmental systems, biomechanics, manufacturing, transportation, and industrial processes.

Dr. Carlos Llopis-Albert
Dr. Carlos Devece Carañana
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Algorithms algorithms	2.6	5.4	2008	17.6 Days	CHF 1800	Submit
Applied Sciences applsci	2.9	6.1	2011	15 Days	CHF 2400	Submit
AppliedMath appliedmath	1.4	1.4	2021	20.4 Days	CHF 1200	Submit
Computation computation	2.6	5.2	2013	13.6 Days	CHF 1800	Submit
Data data	2.4	5.4	2016	19.2 Days	CHF 1600	Submit
Mathematical and Computational Applications mca	2.2	2.8	1996	23.3 Days	CHF 1600	Submit
Mathematics mathematics	2.3	5.4	2013	17.4 Days	CHF 2600	Submit

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Published Papers