Computational Mathematics Methods and Applications in Engineering Science

Dear Colleagues,

Engineering and applied sciences are undergoing a profound transformation, driven by the increasing power and sophistication of computational mathematics. The ability to model, simulate, and optimize complex systems has become indispensable for innovation and problem-solving across all engineering disciplines. From designing next-generation materials to optimizing sustainable energy systems and developing intelligent infrastructure, advanced computational methods are at vital for modern scientific discovery and technological advancement.

This Special Issue, "Computational Mathematics Methods and Applications in Engineering Science," will bring together leading researchers, scientists, and engineers to share their latest theoretical advancements and practical applications in this dynamic field. We seek to create a comprehensive collection of high-impact articles that not only showcase novel mathematical techniques but also demonstrate their successful application to solve pressing real-world engineering challenges. This Special Issue’s scope is intentionally broad to foster cross-disciplinary collaboration, highlighting the universal power of computational mathematics as a foundational tool for modern engineering.

We invite submissions of original research articles, comprehensive reviews, and insightful communications that bridge the gap between mathematical theory and engineering practice.

Prof. Dr. Youness El Hamzaoui
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• numerical methods for differential equations: the finite element method (FEM) and finite difference method (FDM)
• the boundary element method (BEM)
• mesh-free methods and particle methods
• numerical solutions for partial differential equations (PDEs) and ordinary differential equations (ODEs) in engineering models
• computational optimization and operations research: linear and nonlinear programming
• heuristic and metaheuristic algorithms (e.g., genetic algorithms, particle swarm optimization)
• applications in logistics, structural design, and resource management
• machine learning and artificial intelligence in engineering: neural networks, deep learning, and reinforcement learning for system modeling and control
• data-driven modeling and surrogate models for complex simulations
• applications in predictive maintenance, process control, and materials discovery
• modeling and simulation: multiphysics and multiscale modeling
• computational fluid dynamics (CFD)
• solid mechanics and structural analysis
• simulation of transport phenomena (heat, mass, and momentum)
• computational statistics and data analysis: bayesian methods and uncertainty quantification
• high-dimensional data analysis and signal processing
• statistical modeling for engineering reliability and risk assessment
• applications in engineering disciplines: civil and environmental engineering (e.g., water resource management, structural health monitoring)
• mechanical and aerospace engineering (e.g., aerodynamics, robotics, thermodynamics)
• chemical and process engineering (e.g., reactor design, separation processes)
• electrical engineering (e.g., electromagnetics, circuit simulation, control systems). materials science (e.g., computational materials design)