Topic Editors

Institute for Informatics and Automation, Bremen City University for Applied Sciences, D-28199 Bremen, Germany
Chair of Materials Test Engineering (WPT), TU Dortmund University, 44227 Dortmund, Germany

Multi-scale Modeling and Optimisation of Materials

Abstract submission deadline
31 May 2025
Manuscript submission deadline
31 July 2025
Viewed by
834

Topic Information

Dear Colleagues,

More than a century ago, manufactured materials’ fatigue started to be investigated, while material performance evaluation was rethought as a result of the introduction of new technical materials, testing techniques, and computer methodologies. By combining cutting-edge sensor technology with real-time photos of material behavior, it became possible to gain a better understanding of the mechanisms causing damage on a sub-microscale. Meanwhile, incorporating computational methods into multi-scale modeling techniques, continuously enhanced by an ever-increasing computer power, resulted in further insights into the optimization and design of resilient materials. The use of data-driven algorithms allowed for the successful completion of complex structure–property interactions, which would have been computationally costly had physics-based models been used alone. Although substantial research has been conducted on the topic, the materials science community is in even greater need of interdisciplinary methods for multi-scale modeling and optimization. Therefore, we welcome notable and pioneering researchers to participate in our endeavor to advance the current state of the art in this field, within the scope outlined below.

Dr. Mustafa Awd
Prof. Dr. Frank Walther
Topic Editors

Keywords

  • multi-scale modeling
  • material optimization
  • computational methods
  • fatigue analysis
  • sensor technology
  • real-time monitoring
  • sub-microscale mechanisms
  • data-driven algorithms
  • structure–property interactions
  • interdisciplinary research

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Mechanics
applmech
- 2.3 2020 21.4 Days CHF 1200 Submit
Applied Sciences
applsci
2.5 5.3 2011 17.8 Days CHF 2400 Submit
Materials
materials
3.1 5.8 2008 15.5 Days CHF 2600 Submit
Polymers
polymers
4.7 8.0 2009 14.5 Days CHF 2700 Submit
Solids
solids
2.4 3.4 2020 20.5 Days CHF 1000 Submit
Metals
metals
2.6 4.9 2011 16.5 Days CHF 2600 Submit

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Published Papers (1 paper)

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23 pages, 9957 KiB  
Article
Multi-Objective Optimization of Three-Stage Turbomachine Rotor Based on Complex Transfer Matrix Method
by Hüseyin Tarık Niş and Ahmet Yıldız
Appl. Sci. 2024, 14(22), 10445; https://doi.org/10.3390/app142210445 - 13 Nov 2024
Viewed by 370
Abstract
This study presents the complex transfer matrix method (CTMM) as an advanced mathematical model, providing significant advantages over the finite element method (FEM) by yielding rapid solutions for complex optimization problems. In order to design a more efficient structure of a three-stage turbomachine [...] Read more.
This study presents the complex transfer matrix method (CTMM) as an advanced mathematical model, providing significant advantages over the finite element method (FEM) by yielding rapid solutions for complex optimization problems. In order to design a more efficient structure of a three-stage turbomachine rotor, we integrated this method with various optimization algorithms, including genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), gravitational search algorithm (GSA), black hole (BH), particle swarm optimization (PSO), Harris hawk optimization (HHO), artificial bee colony (ABC), and non-metaheuristic pattern search (PS). Thus, the best rotor geometry can be obtained fast with minimum bearing forces and disk deflections within design limits. In the results, the efficiency of the CTMM for achieving optimized designs is demonstrated. The CTMM outperformed the FEM in both speed and applicability for complex rotordynamic problems. The CTMM was found to deliver results of comparable quality much faster than the FEM, especially with higher element quality. The use of the CTMM in the iterative optimization process is shown to be highly advantageous. Furthermore, it is noted that among the different optimization algorithms, ABC provided the best results for this multi-objective optimization problem. Full article
(This article belongs to the Topic Multi-scale Modeling and Optimisation of Materials)
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