Evidence map›Paper›PMID 41922400›Full record

ArticleScientific reports2026

AI-driven adaptive vibration control in smart plate systems: a sustainable approach for next-generation sports engineering.

Bing Lin, Jinyu Wang, Mehran Safarpour, Murat Yaylacı

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bing LinChongqing Preschool Education College, Chongqing, 404047, China.
Jinyu WangChongqing Preschool Education College, Chongqing, 404047, China.
Mehran SafarpourDepartment of Mechanical Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran. m_safarpour@modares.ac.ir.
Murat YaylacıDepartment of Civil Engineering, Recep Tayyip Erdogan University, 53100, Rize, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current paper proposes an AI-based method for the vibration control of smart plate systems. The application is set for next-generation sports engineering, where performance enhancement is the main goal. The system consists of a core of coarse aggregate ultra-high-performance concrete (CA-UHPA) and piezoelectric face sheets, which are mounted on an elastic foundation. The properties of the material composite are foreseen based on the Halpin-Tsai models and the law of mixtures. Looking into the system's dynamic performance in a very thorough way is done using the quasi-3D theory having four variables. This theory gives the opportunity for the full consideration of the distribution of transverse shear strains and stresses throughout the plate thickness. The governing equations of the resonant response are derived by employing the concept of piezoelectricity together with Hamilton's energy principles. The elastic foundation is analyzed using both Winkler and Pasternak coefficients, thereby allowing the interaction of the plate and its support substrate to be included. The solution is achieved through using the physics-informed neural networks (PINNs) technique, which not only accurately and efficiently replaces the conventional Legendre Polynomial Expansions with deep neural networks (DNNs) for more computational efficiency and accuracy but also doubles the legacy of AI-powered methods in terms of real-time system adaptability and optimal vibration control under changing scenarios. A DNN-based verification process assists in obtaining and confirming the trustworthiness of the results. This research marks above all and the first time as a very promising new direction in the smart systems vibration control area in sports, and it is highly anticipated that the new development will have a positive impact on the performance and durability optimization of advanced sports equipment. The introduced method embodies a patent-driven technology leap in vibration control, where AI and new materials join forces to solve challenging problems.

Indexed as

AI-driven vibration controlCoarse aggregate ultra-high-performance concretePiezoelectric materialsPINNsSmart plate systems

Identifiers

PMID41922400
PMCPMC13057001

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.