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Modelling
Special Issues
The 5th Anniversary of Modelling
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The 5th Anniversary of Modelling

A special issue of Modelling (ISSN 2673-3951).

Deadline for manuscript submissions: 31 May 2026 | Viewed by 10814

Special Issue Editors

Prof. Dr. Alfredo Cuzzocrea

E-Mail Website
Guest Editor
1. DISPES Department, University of Calabria, 87036 Rende, Italy
2. Institute of High Performance Computing and Networking, Italian National Research Council, Via P. Bucci, 7/11C, 87036 Rende, Italy
Interests: database; data mining; data warehousing; distributed computing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wei Gao

E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW 2052, Australia
Interests: computational mechanics; non-deterministic modelling and methods; AI and machine learning in structural analysis and design; stochastic structural analysis and safety assessment in CAD/CAE; composite materials and structures; structural optimization and metamaterial design

Special Issue Information

Dear Colleagues,

We will celebrate the 5th Anniversary of Modelling (ISSN 2673-3951) in the year 2025. Hence, we are organizing a Special Issue to commemorate this important milestone. During the past 5 years, Modelling has significantly contributed to scientific advancements in the multidisciplinary field of modelling and simulation. As such, Modelling will continue to serve as a forum wherein novel discoveries are widely shared with the scientific community and the general public at large.

To help celebrate this important event, we warmly invite you to submit original research papers and comprehensive review articles related to the development and applications of modelling and simulation techniques for peer-review and possible publication in this Special Issue.

Prof. Dr. Alfredo Cuzzocrea
Prof. Dr. Wei Gao
Guest Editors

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. Modelling 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 1200 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

  • modelling and simulation
  • engineering
  • optimization
  • computational intelligence
  • computational mechanics
  • intelligent and expert systems

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

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Research

20 pages, 1526 KB  
Article
A Model-Based Framework for Lithium-Ion Battery SoC Estimation Using a Tuning-Light Discrete-Time Sliding-Mode Observer
by Sajad Saberi and Jaber A. Abu Qahouq
Modelling 2026, 7(1), 42; https://doi.org/10.3390/modelling7010042 - 16 Feb 2026
Viewed by 395
Abstract
Reliable state-of-charge (SoC) estimation is crucial for safe and efficient battery management. However, it is challenging in practice. Terminal-voltage sensitivity becomes weak in open-circuit-voltage (OCV) plateau regions. Model uncertainty also persists at practical sampling periods. To tackle this issue, this paper proposes a [...] Read more.
Reliable state-of-charge (SoC) estimation is crucial for safe and efficient battery management. However, it is challenging in practice. Terminal-voltage sensitivity becomes weak in open-circuit-voltage (OCV) plateau regions. Model uncertainty also persists at practical sampling periods. To tackle this issue, this paper proposes a discrete-time, model-based SoC estimation framework. This framework combines a dual-polarization equivalent-circuit model with a tuning-light sliding-mode observer. It is specifically designed for digitally sampled battery management systems. The modeling stage includes: (i) a discrete-time DP representation suitable for embedded use, (ii) a shape-preserving PCHIP reconstruction of the OCV–SoC curve and its derivative, and (iii) an effective-slope regularization mechanism that maintains non-vanishing output sensitivity even in flat OCV regions. On top of this structure, a boundary-layer SMO is developed with output-error shaping, model-driven gain scaling, and simple bias-compensation terms based on integral correction and leaky Coulomb counting. A discrete-time Lyapunov analysis is conducted directly on the surface dynamics. This analysis shows finite-time reaching to the boundary layer and a practical limit on the steady-state error that depends on the sampling period, disturbance level, and boundary-layer width. Numerical tests on a DP model identified from experimental data indicate that the proposed method achieves SoC accuracy similar to a switching-gain adaptive SMO. The results confirm the benefits of a model-centric design. The discrete-time formulation and convergence proof, which do not depend on high sampling rates, provide robustness advantages over traditional sliding-mode methods. The proposed method also performs better than a tuned EKF in plateau regions, requiring much less tuning effort. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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23 pages, 8010 KB  
Article
Uncertainty-Aware Virtual Physics-Based Chloride Resistance Analysis of Metakaolin-Blended Concrete
by Yuguo Yu, David Gardiner, Jie Sun and Kiru Pasupathy
Modelling 2026, 7(1), 16; https://doi.org/10.3390/modelling7010016 - 12 Jan 2026
Viewed by 364
Abstract
Metakaolin (MK) obtained from calcined kaolinitic clay is a highly reactive pozzolanic ingredient for use as an emerging supplementary cementitious material (SCM) in modern sustainable binder productions. It provides elevated alumina to promote formations of Alumina Ferrite Monosulfate (AFm) and Calcium-Aluminium-Silicate-Hydrate (C-A-S-H) phases, [...] Read more.
Metakaolin (MK) obtained from calcined kaolinitic clay is a highly reactive pozzolanic ingredient for use as an emerging supplementary cementitious material (SCM) in modern sustainable binder productions. It provides elevated alumina to promote formations of Alumina Ferrite Monosulfate (AFm) and Calcium-Aluminium-Silicate-Hydrate (C-A-S-H) phases, enhancing the chloride binding capacity. However, due to inherent material uncertainty and lack of approach in quantifying hydration kinetics and chloride binding capacity across varied mixes, robustly assessing the chloride resistance of metakaolin-blended concrete remains challenging. In light of this, a machine learning-aided framework that encompasses physics-based material characterisation and ageing modelling is developed to bridge the knowledge gap. Through applying to laboratory experiments, the impacts of uncertainty on the phase assemblage of hydrated system and chloride penetration are quantified. Moreover, the novel Extended Support Vector Regression (XSVR) method is incorporated and verified against a crude Monte Carlo Simulation (MCS) to demonstrate the capability of achieving effective and efficient uncertainty-aware chloride resistance analyses. With the surrogate model established using XSVR, quality control of metakaolin towards durable design optimisation against chloride-laden environments is discussed. It is found that the fineness and purity of adopted metakaolin play important roles. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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17 pages, 4151 KB  
Article
Multiscale Modeling of Thermoplastic Matrix Composites for Cryogenic Hydrogen Storage Applications
by Brett A. Bednarcyk, Brandon L. Hearley and Evan J. Pineda
Modelling 2025, 6(4), 151; https://doi.org/10.3390/modelling6040151 - 20 Nov 2025
Cited by 1 | Viewed by 1005
Abstract
The performance of thermoplastic matrix composites for linerless Type V cryotanks is evaluated via a partially coupled, multiscale computational workflow with the objective of assessing the choice of thermoplastic matrix material under realistic conditions. Atomistic molecular dynamics simulations provide temperature-dependent stiffness, thermal expansion, [...] Read more.
The performance of thermoplastic matrix composites for linerless Type V cryotanks is evaluated via a partially coupled, multiscale computational workflow with the objective of assessing the choice of thermoplastic matrix material under realistic conditions. Atomistic molecular dynamics simulations provide temperature-dependent stiffness, thermal expansion, and yield strength data for six candidate thermoplastics. These inputs feed into a recursive micromechanics model that simulates a stress-free cooldown to liquid hydrogen temperature, followed by biaxial hoop to longitudinal loading representative of a cylindrical tank’s acreage. Progressive damage analyses predict the onset of matrix microcracking and ultimate burst behavior across four industry-relevant layups. Results highlight that [55/5/−55/−5] Double-Double or [0/±30/±60]ₛ layup architectures with low-melt poly(aryl ether ketone) or poly(ether ketone ketone) matrices deliver superior microcrack resistance, illustrating the power of this framework to guide material and layup selection for leak-resistant thermoplastic composite cryotanks. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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20 pages, 14292 KB  
Article
Non-Fourier Thermoelastic Peridynamic Modeling of Cracked Thin Films Under Short-Pulse Laser Irradiation
by Tao Wu, Tao Xue, Yazhou Wang and Kumar Tamma
Modelling 2025, 6(3), 68; https://doi.org/10.3390/modelling6030068 - 15 Jul 2025
Cited by 1 | Viewed by 2988
Abstract
In this paper, we develop a peridynamic computational framework to analyze thermomechanical interactions in fractured thin films subjected to ultrashort-pulsed laser excitation, employing nonlocal discrete material point discretization to eliminate mesh dependency artifacts. The generalized Cattaneo–Fourier thermal flux formulation uncovers contrasting dynamic responses: [...] Read more.
In this paper, we develop a peridynamic computational framework to analyze thermomechanical interactions in fractured thin films subjected to ultrashort-pulsed laser excitation, employing nonlocal discrete material point discretization to eliminate mesh dependency artifacts. The generalized Cattaneo–Fourier thermal flux formulation uncovers contrasting dynamic responses: hyperbolic heat propagation (FT=0) generates intensified temperature localization and elevates transient crack-tip stress concentrations relative to classical Fourier diffusion (FT=1). A GSSSS (Generalized Single Step Single Solve) i-Integration temporal scheme achieves oscillation-free numerical solutions across picosecond-level laser–matter interactions, effectively resolving steep thermal fronts through adaptive stabilization. These findings underscore hyperbolic conduction’s essential influence on stress-mediated fracture evolution during ultrafast laser processing, providing critical guidelines for thermal management in micro-/nano-electromechanical systems. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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22 pages, 1972 KB  
Article
Reliability Analysis of Interface Oxidation for Thermal Barrier Coating Based on Proxy Model
by Juan Ma, Anyi Wang, Philipp Junker, Anas W. Alshawawreh, Qingya Li, Haoqi Xu and Runzhuo Xue
Modelling 2025, 6(3), 61; https://doi.org/10.3390/modelling6030061 - 3 Jul 2025
Viewed by 1023
Abstract
Thermal barrier coatings have been widely used in industrial fields where thermal damage occurs, and they are crucial for insulation technology and for the safe service of high-temperature components. So, it is critical to accurately predict the reliability of thermal barrier coatings. In [...] Read more.
Thermal barrier coatings have been widely used in industrial fields where thermal damage occurs, and they are crucial for insulation technology and for the safe service of high-temperature components. So, it is critical to accurately predict the reliability of thermal barrier coatings. In this work, an adaptive reliability analysis method based on radial basis functions is proposed, in which different shape parameters and subsets are used to initiate different radial basis function models for multiple predictions. An active learning function that comprehensively considers local uncertainty, limit state function information, and distance among samples is then used for sequential sampling, and the proposed method is validated via a four-branch series connection system. Finally, a reliability analysis is conducted on the failure of interface oxidation in thermal barrier coatings, which verifies the feasibility of the proposed method. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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17 pages, 14006 KB  
Article
Virtual Modelling Framework-Based Inverse Study for the Mechanical Metamaterials with Material Nonlinearity
by Yuhang Tian, Yuan Feng and Wei Gao
Modelling 2025, 6(1), 24; https://doi.org/10.3390/modelling6010024 - 20 Mar 2025
Cited by 14 | Viewed by 1621
Abstract
Mechanical metamaterials have become a critical research focus across various engineering fields. Recent advancements have pushed the development of reprogrammable mechanical metamaterials to achieve adaptive mechanical behaviours against external stimuli. The relevant designs strongly depend on a thorough understanding of the response spectrum [...] Read more.
Mechanical metamaterials have become a critical research focus across various engineering fields. Recent advancements have pushed the development of reprogrammable mechanical metamaterials to achieve adaptive mechanical behaviours against external stimuli. The relevant designs strongly depend on a thorough understanding of the response spectrum of the original structure, where establishing an accurate virtual model is regarded as the most efficient approach to this end up to now. By employing an extended support vector regression (X-SVR), a powerful machine learning algorithm model, this study explores the uncertainty and sensitivity analysis and inverse study of re-entrant honeycombs under quasi-static compressive loads. The proposed framework enables accurate uncertainty quantification, sensitivity analysis, and inverse study, facilitating the related design and optimisation of metastructures when extended to responsive materials. The proposed framework is considered an effective tool for uncertainty quantification and sensitivity analysis, enabling the identification of key parameters affecting mechanical performance. Finally, the inverse study approach leverages X-SVR to swiftly obtain the required structural configurations based on targeted mechanical responses. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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22 pages, 19758 KB  
Article
Global Buckling Simulation and Design of a Novel Concrete-Filled Corrugated Steel Tubular Column
by Chao-Qun Yu, Sheng-Jie Duan and Jing-Zhong Tong
Modelling 2025, 6(1), 22; https://doi.org/10.3390/modelling6010022 - 10 Mar 2025
Cited by 16 | Viewed by 1996
Abstract
A novel concrete-filled corrugated steel tubular (CFCST) column composed of corner steel bars and corrugated steel plates filled with concrete has been proposed recently. Columns with large height-to-width ratios are commonly used in practice, where they are often subjected to eccentric compression. However, [...] Read more.
A novel concrete-filled corrugated steel tubular (CFCST) column composed of corner steel bars and corrugated steel plates filled with concrete has been proposed recently. Columns with large height-to-width ratios are commonly used in practice, where they are often subjected to eccentric compression. However, there is a lack of research on their stability behavior under such conditions. This study presented a numerical analysis to evaluate the stability performance of CFCST columns under eccentric compression, with eccentricity ratios ranging from 0 to 2.0 and height-to-width ratios between 10 and 30. The numerical results indicated that the N–M interaction curve became less convex as the height-to-width ratio increased. Concrete strength and column width had a greater impact on the stability performance of the CFCST columns at low eccentricity ratios, while steel strength and steel bar width were more influential at high eccentricity ratios. The comparison between numerical and calculation results specified in AISC 360 and GB 50936 showed that both of them were unsuitable to estimate the stability performance of the column under eccentric compression. Finally, a formula was fitted, and the error was basically within 15%, which offered significantly improved accuracy over current design codes. Full article
(This article belongs to the Special Issue The 5th Anniversary of Modelling)
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