Fractal theory has gained increasing attention across various engineering disciplines due to its ability to model complex, self-similar, and multiscale phenomena. This paper presents a comprehensive review of fractal applications in biomedical, mechanical, civil, environmental, and materials engineering. In particular, fractal analysis has enabled optimizing porous scaffolds in biomaterials to improve tissue integration and mechanical performance. In biomedical signal processing, fractal algorithms have improved the detection and classification of neurological disorders, particularly through electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) complexity measures. Additionally, fractal-based models have been effectively used in environmental engineering to improve the prediction and control of pollution dispersion in heterogeneous landscapes. This paper also outlines key theoretical foundations, computational methods, and domain-specific innovations, while identifying current challenges and future directions. By integrating these advances, this review provides a roadmap for using fractal theory in both theoretical research and practical applications.
FRACTAL THEORY: A COMPREHENSIVE REVIEW OF APPLICATIONS ACROSS ENGINEERING DISCIPLINES
Porcaro C.;
2025
Abstract
Fractal theory has gained increasing attention across various engineering disciplines due to its ability to model complex, self-similar, and multiscale phenomena. This paper presents a comprehensive review of fractal applications in biomedical, mechanical, civil, environmental, and materials engineering. In particular, fractal analysis has enabled optimizing porous scaffolds in biomaterials to improve tissue integration and mechanical performance. In biomedical signal processing, fractal algorithms have improved the detection and classification of neurological disorders, particularly through electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) complexity measures. Additionally, fractal-based models have been effectively used in environmental engineering to improve the prediction and control of pollution dispersion in heterogeneous landscapes. This paper also outlines key theoretical foundations, computational methods, and domain-specific innovations, while identifying current challenges and future directions. By integrating these advances, this review provides a roadmap for using fractal theory in both theoretical research and practical applications.
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