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Numerical Modelling and Experimental Testing of 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 October 2026 | Viewed by 870

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Guest Editor
Faculty of Civil Engineering and Architecture, Kielce University of Technology, Kielce, Poland
Interests: diagnostics of structures and engineering installations; diagnostic systems based on the acoustic emission method; the use of machine learning and AI in the analysis of structural and material failure mechanisms based on acoustic signals; destructive and non-destructive testing of structural elements made of wood, concrete, steel, and composite materials
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Special Issue Information

Dear Colleagues,

The rapid development of modern engineering structures and advanced materials requires a comprehensive understanding of their mechanical behavior, durability, and failure mechanisms. In recent decades, the integration of numerical modelling with experimental investigations has become an essential approach in materials science and structural engineering. Numerical techniques, including finite element modelling, multiscale simulations, and data-driven computational methods, enable researchers to predict the behavior of materials and structures under complex loading and environmental conditions. At the same time, experimental testing provides indispensable validation of theoretical models and offers valuable insight into the real mechanisms governing material degradation and structural damage. The continuous advancement of sensing technologies, non-destructive testing methods, and modern data analysis tools—particularly machine learning and artificial intelligence—has significantly expanded the possibilities for monitoring, diagnosing, and understanding the performance of engineering materials and structures.

This Special Issue aims to present and disseminate recent advances in the field of numerical modelling and experimental testing of materials. The objective is to bring together high-quality research contributions addressing theoretical developments, innovative experimental techniques, and practical engineering applications related to material characterization, structural diagnostics, and failure analysis. We welcome original research articles as well as review papers that explore both fundamental aspects and applied approaches in materials engineering and structural health monitoring.

Topics of interest include, but are not limited to, the following:

  • Numerical modelling of material behavior and structural performance;
  • Experimental characterization and testing of engineering materials;
  • Destructive and non-destructive testing techniques;
  • Structural health monitoring and diagnostics of engineering structures;
  • Acoustic emission methods in material and structural evaluation;
  • Application of machine learning and artificial intelligence in material analysis;
  • Failure mechanisms, damage detection, and durability assessment of materials and structures.

Dr. Aleksandra Krampikowska
Guest Editor

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-anonymized 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 modelling
  • experimental testing
  • material characterization
  • structural health monitoring
  • non-destructive testing
  • acoustic emission
  • failure mechanisms
  • machine learning in materials science
  • engineering materials
  • structural diagnostics

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Published Papers (2 papers)

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Research

25 pages, 4601 KB  
Article
Design of a Recessed Honeycomb Structure with a Nested Star Configuration and Study of Its Static Mechanical Properties
by Xinlin Wang, Guiwei Liu, Lei Lei and Weihang Peng
Materials 2026, 19(11), 2296; https://doi.org/10.3390/ma19112296 - 28 May 2026
Viewed by 216
Abstract
Negative Poisson’s ratio materials show great potential in aerospace, automotive engineering, and military protection owing to their unique deformation behavior and superior mechanical properties. Nevertheless, current negative Poisson’s ratio honeycomb structures suffer from an inherent conflict between stiffness and energy absorption, along with [...] Read more.
Negative Poisson’s ratio materials show great potential in aerospace, automotive engineering, and military protection owing to their unique deformation behavior and superior mechanical properties. Nevertheless, current negative Poisson’s ratio honeycomb structures suffer from an inherent conflict between stiffness and energy absorption, along with poorly understood mechanical regulation mechanisms in complex three-dimensional nested configurations. To address these issues, this paper proposes a novel Cross Re-entrant Hexagon Nested Star-shaped Cell (CRNSC). Through theoretical derivation, finite element simulation, and quasi-static compression experiments, the mechanical properties and energy absorption characteristics of the structure are systematically investigated. A geometric characterization system based on length, angle, and thickness parameters is established. The results show that the cell wall thickness significantly increases the relative density, while the angle θ between the inner inclined strut and the horizontal line induces polarity reversal of the Poisson’s ratio. The outer inclined strut angle α and the inner angle θ exhibit monotonic or nonlinear regulatory effects on the equivalent Poisson’s ratio and the effective Young’s modulus, respectively. The optimal load-bearing configuration (α = 65°, θ = 35°) achieves a peak stress of 1.01 MPa, and the optimal deformation configuration (α = 55°, θ = 25°) reaches an ultimate strain of 4%. Theoretical, simulated, and experimental results are in good agreement with errors below 7%, validating the model’s effectiveness. Full article
(This article belongs to the Special Issue Numerical Modelling and Experimental Testing of Materials)
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24 pages, 12841 KB  
Article
Profilometric Quantification of Wear-Track Degradation in FFF Kevlar-Reinforced ASA Composites
by Patricia Isabela Brăileanu, Marius-Teodor Mocanu and Nicoleta Elisabeta Pascu
Materials 2026, 19(10), 2135; https://doi.org/10.3390/ma19102135 - 19 May 2026
Viewed by 262
Abstract
Fused filament fabrication (FFF) produces components with characteristic topographical features that influence their tribological behavior. Because conventional roughness parameters may not fully describe the localized surface degradation of reinforced FFF polymers, this study evaluates the wear-track evolution of FFF aramid fiber-reinforced Acrylonitrile Styrene [...] Read more.
Fused filament fabrication (FFF) produces components with characteristic topographical features that influence their tribological behavior. Because conventional roughness parameters may not fully describe the localized surface degradation of reinforced FFF polymers, this study evaluates the wear-track evolution of FFF aramid fiber-reinforced Acrylonitrile Styrene Acrylate (ASA) composites using a comparative profilometric framework based on pre-wear and post-wear measurements. Specimens with different infill configurations underwent dry sliding Ball-on-Disc tribological testing, followed by profilometric wear-track analysis and optical microscopy inspection. The macroscopic wear response exhibited a non-monotonic dependence on infill configuration. Under the present experimental conditions, the 30% infill configuration showed the most favorable average wear response, with the lowest wear volume and specific wear rate, whereas the 90% infill configuration showed the highest material loss. To compare the surface modifications induced by sliding, three derived relative profilometric descriptors were evaluated: Surface Texture Alteration Index (STAI), Peak Deformation Index (PDI) and Material Ratio Preservation Index (MRPI). These descriptors were used as complementary comparative parameters rather than replacements for standardized roughness or Abbott–Firestone-based measurements. Statistical analysis showed a very strong association between maximum wear-track depth and calculated volumetric material loss, indicating that deeper wear-track profiles were consistently associated with higher material removal within the investigated dataset. Furthermore, correlation analysis suggested that the initial material ratio may be more closely associated with the subsequent wear response than the initial arithmetic mean roughness. This study indicates that combining wear volume, wear-track geometry, optical microscopy and relative profilometric descriptors provides a useful comparative approach for evaluating degradation in FFF Kevlar-reinforced ASA components under sliding conditions. Full article
(This article belongs to the Special Issue Numerical Modelling and Experimental Testing of Materials)
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