Modeling, Simulation and Applications of Fractal/Fractional Calculus to Engineering Materials
A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 44
Special Issue Editors
Interests: fractional modeling; complex viscoelastic behaviors; power-law frequency-dependent attenuation
Special Issues, Collections and Topics in MDPI journals
Interests: fractional derivative constitutive modeling of viscoelastic materials; multiscale mechanical modeling of cement-based composites
Interests: nonlinear analysis; material modeling; extreme loading; constitutive modelling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Constitutive modeling of engineering materials presents significant challenges, requiring advanced mathematical approaches to accurately capture complex material behaviors. Fractal and fractional calculus, distinguished by their power-law kernels, offer a promising framework for precise stress–strain relationship prediction with remarkable parameter efficiency. Successful applications of fractional or fractal viscoelasticity and plasticity span diverse material systems, including polymers, metals, soils and rocks, and cementitious materials. Recent years have also witnessed growing global interest in applying fractal and fractional models to multiscale analyses and dynamic characterization of engineering materials. Concurrently, the integration of artificial intelligence (AI) techniques with fractional/fractal calculus has emerged as a rapidly evolving research frontier.
This Special Issue seeks to showcase cutting-edge advancements in constitutive modeling through fractal and fractional calculus, along with their engineering applications. We invite high-quality contributions across various formats, including review articles, original research papers, and technical notes. Relevant topics encompass, but are not limited to, the following:
- Constitutive modeling based on fractal/fractional calculus;
- Theoretical developments in generalized fractional/fractal operators;
- Advanced numerical algorithms for fractional differential equations;
- Multiscale modeling applications of fractal/fractional approaches;
- Applications of fractional models in dynamic analyses;
- Application AI to fractional/fractal systems.
Dr. Wei Cai
Dr. Xianglong Su
Prof. Dr. Wojciech Sumelka
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Fractal and Fractional is an international peer-reviewed open access monthly 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 2700 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
- constitutive models
- fractional/fractal viscoelasticity
- fractional/fractal viscoplasticity
- numerical methods
- multiscale modeling
- dynamic analyses
- artificial intelligence (AI)
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