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Computational and Experimental Methodologies for Advanced and Sustainable Structural Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 893

Special Issue Editors


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Guest Editor
Institute of Applied Mechanics, Poznan University of Technology, Jana Pawła II 24, 60-965 Poznań, Poland
Interests: computational mechanics; corrugated cardboard; fluid mechanics; biomechanics; heat transfer; meshless methods; artificial intelligence; evolutionary algorithms; inverse problems
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Guest Editor
Department of Engineering and Applied Sciences, Università degli Studi di Bergamo, Viale G. Marconi 5, 24044 Dalmine, BG, Italy
Interests: computational mechanics; non-linear structural analysis; inverse problems; mechanics of materials; mechanics of corrugated cardboard; mechanical characterisation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advancements in engineering research have led to the widespread use of various computational techniques for structural simulations involving advanced materials, which typically exhibit non-linear behaviours. A critical aspect of these problems is selecting the appropriate constitutive model to accurately describe the material’s mechanical response. Such models have to be supported by the implementation of a robust computational framework, such as the Finite Element Method, Boundary Element Method, or meshless methods, to ensure reliable simulation results at both the material point and at the overall structural scale. These computational approaches are applied across a broad range of engineering and scientific fields, modelling a diverse array of materials, including bio-materials, eco-materials, composites, textiles, glass, timber, and paperboard, as well as more commonly used materials like metals, ceramics, and concrete.

The reliability of the above-mentioned simulations heavily depends on the accuracy of the parameters used in the governing equations of the selected constitutive models. Traditionally, these parameters are calibrated using data obtained from experiments, which may be destructive, quasi-non-destructive, or entirely non-destructive. Inverse Analysis plays a crucial role in translating experimentally measured quantities into the desired parameters. This methodology, with minimal adjustments, can also be effectively applied to the diagnostic analysis of aged or potentially damaged structural materials. The computational optimisation methods used for parameter identification in the outlined problems can benefit from novel techniques such as reduced order models, evolutionary algorithms, and artificial neural networks.

This Special Issue of Materials is devoted to the application of some of the above outlined methods combined with experimental techniques and Inverse Analysis methodologies, relating to diverse applications of structural engineering such as (but not limited to) the aeronautical, biomechanical, building, and civil and mechanical engineering fields. 

Dr. Jakub Krzysztof Grabski
Dr. Aram Cornaggia
Guest Editors

Manuscript Submission Information

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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. Materials 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.

Keywords

  • numerical methods
  • finite element method
  • meshless methods
  • boundary element method
  • reduced order models
  • artificial intelligence
  • artificial neural networks
  • evolutionary algorithms
  • inverse problems
  • inverse analysis
  • structural optimisation
  • parameter identification
  • material modelling
  • material characterisation
  • experimental material testing
  • non destructive testing
  • advanced materials
  • engineered materials
  • eco materials
  • sustainable materials
  • metamaterials

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Published Papers (2 papers)

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24 pages, 2987 KiB  
Article
Optimization of Engine Piston Performance Based on Multi-Method Coupling: Sensitivity Analysis, Response Surface Model, and Application of Genetic Algorithm
by Bin Zheng, Qintao Shui, Zhecheng Luo, Peihao Hu, Yunjin Yang, Jilin Lei and Guofu Yin
Materials 2025, 18(13), 3043; https://doi.org/10.3390/ma18133043 - 26 Jun 2025
Viewed by 186
Abstract
This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization [...] Read more.
This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization of the piston are of great significance to its efficiency and reliability. First, a three-dimensional (3D) model of the piston was constructed and imported into ANSYS Workbench for finite element modeling and high-quality meshing. Based on the empirical formula, the actual working environment temperature and heat transfer coefficient of the piston were accurately determined and used as boundary conditions for thermomechanical coupling analysis to accurately simulate the thermal and deformation state under complex working conditions. Dynamic characteristic analysis was used to obtain the displacement–frequency curve, providing key data support for predicting resonance behavior, evaluating structural strength, and optimizing the design. In the optimization stage, five geometric dimensions are selected as design variables. The deformation, mass, temperature, and the first to third natural frequencies are considered as optimization goals. The response surface model is constructed by means of the design of the experiments method, and the fitted model is evaluated in detail. The results show that the models are all significant. The adequacy of the model fitting is verified by the “Residuals vs. Run” plot, and potential data problems are identified. The “Predicted vs. Actual” plot is used to evaluate the fitting accuracy and prediction ability of the model for the experimental data, avoiding over-fitting or under-fitting problems, and guiding the optimization direction. Subsequently, the sensitivity analysis was carried out to reveal the variables that have a significant impact on the objective function, and in-depth analysis was conducted in combination with the response surface. The multi-objective genetic algorithm (MOGA), screening, and response surface methodology (RSM) were, respectively, used to comprehensively optimize the objective function. Through experiments and analysis, the optimal solution of the MOGA algorithm was selected for implementation. After optimization, the piston mass and deformation remained relatively stable, and the working temperature dropped from 312.75 °C to 308.07 °C, which is conducive to extending the component life and improving the thermal efficiency. The first to third natural frequencies increased from 1651.60 Hz to 1671.80 Hz, 1656.70 Hz to 1665.70 Hz, and 1752.90 Hz to 1776.50 Hz, respectively, significantly enhancing the dynamic stability and vibration resistance. This study integrates sensitivity analysis, response surface models, and genetic algorithms to solve multi-objective optimization problems, successfully improving piston performance. Full article
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19 pages, 9507 KiB  
Article
Mechanical Strength of Waste Materials: A Cone Penetration Testing-Based Geotechnical Assessment for the Reclamation of Landfills
by Marek Bajda, Mariusz Lech, Katarzyna Markowska-Lech, Piotr Osiński and Eugeniusz Koda
Materials 2025, 18(9), 2130; https://doi.org/10.3390/ma18092130 - 6 May 2025
Viewed by 415
Abstract
The stability and mechanical properties of municipal solid waste (MSW) deposits in closed landfills are critical for safe land reclamation and infrastructure development. This study employs Cone Penetration Testing (CPT) to evaluate the geotechnical parameters of aged waste at three closed landfill sites [...] Read more.
The stability and mechanical properties of municipal solid waste (MSW) deposits in closed landfills are critical for safe land reclamation and infrastructure development. This study employs Cone Penetration Testing (CPT) to evaluate the geotechnical parameters of aged waste at three closed landfill sites in central Poland. Key parameters, including shear strength, internal friction angle, density, and liquidity index, were assessed to determine slope stability and bearing capacity for future redevelopment. Due to the heterogeneous nature of MSW, CPT results were analyzed in conjunction with empirical correlations and nomograms to improve accuracy, so the parameters can be used for future numerical modeling and proposing new computational approaches for landfill body elastic and mechanical behavior predictions. The findings indicate significant variability in landfill waste mechanical properties, influenced by waste composition, decomposition stage, and compaction history. The study highlights CPT’s reliable detremination of geotechnical parameters for landfill restoration projects, particularly for infrastructure, creating the potential for green energy and sustainable development. The results contribute to improving engineering practices in landfill restoration and ensuring the long-term stability of post-closure land use. This study also contributes to obtaining reliable results on anthropogenic waste material mechanical parameters at both the material point and at the overall structural scale, benefiting future computational methods and modeling approaches for analyzing structural and geotechnical safety of such complex and demanding structures as landfills. Full article
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