You are currently viewing a new version of our website. To view the old version click .

Biomimetics

Biomimetics is an international, peer-reviewed, open access journal on biomimicry and bionics, published monthly online by MDPI. 

Indexed in PubMed | Quartile Ranking JCR - Q1 (Engineering, Multidisciplinary)

All Articles (2,801)

This paper proposes a Gudermannian function-based proportional–integral–derivative (G-PID) controller to enhance the transient performance of automatic voltage regulator (AVR) systems operating under highly dynamic conditions. By embedding the smooth and bounded nonlinear mapping of the Gudermannian function into the classical PID structure, the proposed controller improves adaptability to large signal variations while effectively suppressing overshoot. The controller parameters are optimally tuned using the starfish optimization algorithm (SFOA), which provides a robust balance between exploration and exploitation in nonlinear search spaces. Simulation results demonstrate that the SFOA-optimized G-PID controller achieves superior transient performance, with a rise time of 0.0551 s, zero overshoot, and a settling time of 0.0830 s. Comparative evaluations confirm that the proposed approach outperforms widely used optimization algorithms (particle swarm optimization, grey wolf optimizer, success history-based adaptive differential evolution with linear population size, and Kirchhoff’s law algorithm) and advanced AVR control schemes, including fractional-order and higher-order PID-based designs. These results indicate that the proposed SFOA optimized G-PID controller offers a computationally efficient and structurally simple solution for high-performance voltage regulation in modern power systems.

23 December 2025

Physical arrangement of the AVR within the overall power generation setup.

Global air transport has become the dominant mode of long-distance travel, carrying more than four billion passengers in 2019 and projected to exceed 8 billion by 2040. Nevertheless, limited demand and economic inefficiencies often make direct connections unfeasible, forcing many passengers to rely on transfers. In such cases, synchronizing arrivals and departures at hub airports is crucial to minimizing transfer times and maximizing passenger retention. This study investigates the synchronization problem at Istanbul Airport, one of the world’s largest hubs, using metaheuristic optimization. Three algorithms—Genetic Algorithms (GA), Modified Discrete Particle Swarm Optimization (MDPSO), and Evolutionary Strategies (ES)—were applied in parallel to optimize arrival and departure schedules for a major airline. The proposed chromosome-based framework was tested through parameter tuning and validated with statistical analyses, including ANOVA and Games–Howell pairwise comparisons. The results show that MDPSO achieved strong improvements, while ES consistently outperformed both GA and MDPSO, increasing successful passenger transfers by more than 200% compared to the original schedule. These findings demonstrate the effectiveness of evolutionary metaheuristics for large-scale airline scheduling and highlight their potential for improving hub connectivity. This framework is generalizable to other hub airports and airlines, and future research could extend it by integrating hybrid metaheuristics or applying enhanced forecasting methods and more dynamic scheduling approaches.

23 December 2025

Location of Istanbul Airport.

Background: Impaired mucus drainage from the paranasal sinuses is often associated with nasal obstruction and reduced airway function in growing patients. Orthopedic maxillary protraction and expansion techniques can enhance airway dynamics, but their underlying fluid–structure mechanisms remain insufficiently understood. Objective: To validate that the Right Angle Maxillary Protraction Appliance (RAMPA), combined with a semi-rapid maxillary expansion (sRME) intraoral device gHu-1, improves mucus drainage by enhancing nasal airflow through nasal cavity expansion. Methods: The effects of RAMPA therapy were analyzed using computational fluid dynamics (CFD) for single-phase (air) and two-phase (air–mucus) flows within the nasal cavity, employing the unsteady RANS turbulence model. Finite element method (FEM) results from prior studies were synthesized to assess changes in the center and radius of maxillary rotation induced by RAMPA-assisted sRME. A male patient (aged 8 years 7 months to 11 years 7 months) treated with extraoral RAMPA and the intraoral appliance (gHu-1) underwent pre- and post-treatment cone-beam computed tomography (CBCT) and ear, nose, and throat (ENT) evaluation. Results: FEM analysis revealed an increased radius and elevated center of maxillary rotation, producing expansion that was more parallel to the palatal plane. CFD simulations showed that nasal cavity expansion increased airflow velocity and pressure drop, enhancing the suction effect that promotes mucus clearance from the frontal sinus. Clinically, nasal passages widened, paranasal opacities resolved, and occlusal and intermolar widths improved. Conclusions: RAMPA combined with sRME improves nasal airflow and maxillary skeletal expansion, facilitating paranasal mucus clearance and offering a promising adjunctive approach for enhancing upper airway function in growing patients.

23 December 2025

(a) Schematic of RAMPA worn by a manikin; (b) diagram of external forces applied on RAMPA; (c) gHu-1 intraoral appliance from the top view.

Skin meshing is widely used to treat extensive burn injuries due to its cost-efficiency and capacity to cover large wound areas. As biomimetics focuses on deriving engineering principles from biological structure–function relationships, this review examines how to optimize skin-meshing expansion and investigates factors contributing to reported discrepancies between clinical and manufacturer-reported expansion ratios. The biology and mechanical behavior of skin layer are discussed, emphasizing the anisotropic properties govern by collagen fiber orientation associated with Langer’s lines in the dermis. The epidermis and hypodermis show isotropic properties and therefore have minimal influence on load-bearing capacity. Surveying 111 studies, the review evaluates which constitutive equations employed for skin modelling is suitable to replicate mechanical behavior of skin meshing undergoing large expansion. Elastic models fail to capture large expansion ratios. Viscoelastic and QLV are excluded due to negligible sliding of collagen fibers at slow strain rates and limited importance of hysteresis. Consequently, hyperelastic models are recognized as more suitable for predicting large deformations. Among these, the structural GOH model, which represents fiber dispersion through a probability-density function, demonstrates strong agreement with experimental data using few parameters; its damage extensions improve prediction of mesh tearing. Additionally, emerging auxetic mesh geometries with negative Poisson ratios are examined, highlighting their potential to achieve greater expansion when combined with suitable structural anisotropic constitutive models, e.g., GOH.

22 December 2025

Schematic overview of the clinical and mechanical context of skin meshing. Severe burns often require grafting, and skin meshing expands harvested skin to increase wound coverage. The mechanical response during meshing is governed primarily by the dermis and its collagen alignment along Langer’s lines. Experimental stress–stretch data (
  
    σ
    −
    λ
  
) and computational modelling are used to evaluate suitable constitutive models and meshing strategies. The review focuses on identifying an appropriate anisotropic material model and on exploring geometric optimization approaches to improve expansion outcomes.

News & Conferences

Issues

Open for Submission

Editor's Choice

Reprints of Collections

Bio-Inspired Soft Robotics
Reprint

Bio-Inspired Soft Robotics

Design, Fabrication and Applications
Editors: Yong Zhong, Pei Jiang, Sun Yi

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
Biomimetics - ISSN 2313-7673