Vibration Analysis Of Nitinol Shape Memory Alloy In Carbon Fibre Reinforced Polymer Composites

Samson, R. Manoj; Prakash, M.; Nirmal, R.; Vajpayee, Gaurav

doi:10.1088/1757-899x/912/5/052029

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…One way to enhance characteristics is by reinforcing fibres, particles, and sheets. Piezoelectric particles, SMA wires, magnetorheological, electrorheological, carbon fibres, glass fibres, natural fibres, and other materials are utilised in conjunction [5,6].…”

Section: Introductionmentioning

confidence: 99%

A machine learning approach for investigation of the natural frequency of a nitinol-reinforced composite beam

Rane,

Patil,

Raykar

et al. 2023

Eng. Res. Express

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Many applications are using composites to improve performance and reduce weight, but it is essential to know the different properties of the composite before manufacturing. Properties like natural frequency and elastic modulus are also crucial in many applications. The use of shape memory alloys (SMA) composite has increased in the last few years due to various advantages of the shape memory alloys, like a shift in natural frequency and elastic modulus during phase transformation. Hence it is essential to know the composite’s natural frequency and elastic modulus before constructing it. Although experimental and numerical methods for calculating natural frequency exist, they are time-consuming and infrastructure-dependent. This paper explores relationships between SMA composite construction parameters and natural frequency to predict it better. Nitinol-reinforced silicon rubber composite beams are investigated with various parametric combinations using an orthogonal array. Different machine-learning techniques are applied for natural frequency prediction after training models on numerical results from varied construction combinations. The study identifies the best-performing algorithm and provides tuning recommendations. Linear regression model, Ridge regression model, and Decision Tree regression are the best-performing algorithms for the dataset in this paper. A weighted sum method finds optimal construction parameters for maximum natural frequency. These models can predict natural frequency before construction and the shift during SMA phase transformation. The research aids in designing SMA-reinforced beams by identifying optimal parameters like volume fraction, location, and activation pattern, targeting maximum natural frequency. The composite studied in this research shows a maximum natural frequency of 19.58 Hz for a 3.53% volume fraction of SMA, 3 mm distance of reinforcement, all wires activated, and austenite temperature.

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Section: Introductionmentioning

confidence: 99%

A machine learning approach for investigation of the natural frequency of a nitinol-reinforced composite beam

Rane,

Patil,

Raykar

et al. 2023

Eng. Res. Express

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Optimization of a shift in the natural frequency of a nitinol-reinforced composite beam

Patil,

Rane,

Kumbhar

2024

Int J Interact Des Manuf

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On the replacement of steel by NITINOL as coupling agent in automobile shaft

Barik

Samal

Behera

et al. 2021

ISSS J Micro Smart Syst

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Automobile couplings generally fail due to excessive misalignment in shafts and torque overload which ultimately generates vibration in the assembly. These vibrations weaken the coupling structure and ultimately get transmitted to the shaft leading to fatigue failure. Additionally, the complexity in the design of standard coupling is related to lower durability. In this system, when the radial space is larger, it triggers a bulkier transmission. Shape memory alloy such as NITINOL is a special class of smart material that possesses superelasticity which means it can retain deformation of about 8%. This material has a high degree of strength, greater elastic and shear modulus than existing coupling materials, such as steel, and has unique vibration damping features. Coupling made of NITINOL is simple in design and requires lesser space with minimal maintenance. They provide higher durability and are much reliable in operation over a wide range of temperatures. This paper aims to review the NITINOL material used in coupling technology industries and the parameters governing its shape memory effect. The knowledge gathered from this work enables to further extend the technological contribution to NiTi coupling at large-scale production in the automobile sector with direct effect on longer life for the transmission system.

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Vibration Analysis Of Nitinol Shape Memory Alloy In Carbon Fibre Reinforced Polymer Composites

Cited by 6 publications

References 17 publications

A machine learning approach for investigation of the natural frequency of a nitinol-reinforced composite beam

A machine learning approach for investigation of the natural frequency of a nitinol-reinforced composite beam

Optimization of a shift in the natural frequency of a nitinol-reinforced composite beam

On the replacement of steel by NITINOL as coupling agent in automobile shaft

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