Multiscale and Multidisciplinary Modeling, Experiments and Design - Call for Papers - Special Issue on Integrating Computational Intelligence with Multiscale Analysis and Multidisciplinary Design Approaches

Guest Editors:
Arkadiusz Poteralski, Silesian University of Technology, Poland
Grzegorz Dziatkiewicz, Silesian University of Technology, Poland

Submission Status: Open   |   Submission deadline: 1 April 2024

Summary and scope
This Special Issue highlights the growing importance of spatio-temporal multiscale analysis, multi-science approach and multi-disciplinarity in modeling, optimizing, identifying and understanding modern materials, processes and systems with multi-physical phenomena. The Special Issue will exemplify the application of cutting-edge computational methods and techniques, particularly computational intelligence methods.

Topics of interest include, but are not limited to:

• Application of computational intelligence to design modern materials
• Modelling of composites using a data-driven approach
• Meta-modelling for multi-criteria design of engineering systems
• Non-Fourier heat transfer modelling in ultra-short timescales
• Multiphysics for modeling modern materials

Submission guidelines
All papers must be prepared in accordance with the Instructions for Authors at: https://www.springer.com/journal/41939/submission-guidelines (this opens in a new tab).  Authors should submit through the online submission site and select article type “SI - Integrating Computational Intelligence with Multiscale Analysis and Multidisciplinary Design Approaches". 

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

Please note that the authors of selected papers presented at PCM - CMM 2023 are invited to submit an extended version of their contributions by taking into consideration both the reviewers’ comments on their conference paper, and the feedback received during presentation at the conference. It is worth clarifying that the extended version is expected to contain a substantial scientific contribution, e.g., in the form of new algorithms, experiments or qualitative/quantitative comparisons, and that neither verbatim transfer of large parts of the conference paper nor reproduction of already published figures will be tolerated. The extended versions of PCM - CMM 2023 papers will undergo the standard, rigorous journal review process and be accepted only if well-suited to the topic of this Special Issue and meeting the scientific level of the journal. Final decisions on all papers are made by the Editor-in-Chief.

Meet the Guest Editors
Arkadiusz Poteralski is an Associate Professor at the Department of Computational Mechanics and Engineering at the Silesian University of Technology, Gliwice, Poland, where he received his Ph.D. and D.Sc.. He has been a Mechanical Engineering faculty member since 2004. He is also a member of the Polish Association of Computational Mechanics, International Society of Structural and Multidisciplinary Optimization, International Association for Computational Mechanics and European Community on Computational Methods in Applied Sciences.
His research interests lie in developing the concept and methodology of optimization for selected mechanical structures. Currently, Prof. Poteralski is involved in modeling and solving research on auxetic materials. He is the author of procedure for simultaneous optimization of shape, topology and distribution of different materials for the spatial structure, which is adapted to the one scale and multi scale problems has been developed. Prof. Poteralski performed optimizations for many mechanical structures i.e.:

• optimization of shell and shell solid structures due to the shape, topology and material properties;
• optimization of termomechanical structures, 
• identification and optimization of composites structures,
• optimization of elastic vibrating systems,
• identification in acoustics problem,
• identification the material constants of piezoelectric materials.

Grzegorz Dziatkiewicz is an Associate Professor at the Department of Computational Mechanics and Engineering at the Silesian University of Technology, Gliwice, Poland, where he received his Ph.D. and D.Sc.. He has been a Mechanical Engineering faculty member since 2007. He is also a member of the Polish Association of Computational Mechanics. His research interests are in mathematical and computational methods for solving solid mechanics problems, especially those involving coupled mechanical and electromagnetic fields. He is interested in modelling composites with piezoelectric, piezomagnetic and magnetoelectroelastic phases within the micromechanical framework and in nonhomogenous thermal metamaterials described by the non-Fourier constitutive equations. His other research interests include computational intelligence methods in applications for solving such ill-posed problems as the identification and optimization of materials, systems and processes and statistical techniques for solving optimization problems under industrial conditions. Prof. Dziatkiewicz is conducting a multi-scientific doctoral project supporting optimization and learning curve control of engineering competencies in CAx systems. The multi-science approach in this project is concerned with applying the combined methods of computational intelligence, computational psychometrics and systems dynamics to model and optimize the process of competence improvement by practising engineers during individual training.