Fractional Calculus Approach to Reproduce Material Viscoelastic Behavior, including the Time–Temperature Superposition Phenomenon

Genovese, Andrea; Farroni, Flavio; Sakhnevych, Aleksandr

doi:10.3390/polym14204412

Cited by 12 publications

(6 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The modeling of rheological behavior is necessary to develop general models for all materials or categories of materials used for bioprinting. Different approaches are currently used, from empirical models to phenomenological ones [ 32 , 34 , 84 , 111 , 112 , 113 , 122 , 217 , 230 ].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Rheology as a Tool for Fine-Tuning the Properties of Printable Bioinspired Gels

Bercea¹

2023

Molecules

View full text Add to dashboard Cite

Over the last decade, efforts have been oriented toward the development of suitable gels for 3D printing, with controlled morphology and shear-thinning behavior in well-defined conditions. As a multidisciplinary approach to the fabrication of complex biomaterials, 3D bioprinting combines cells and biocompatible materials, which are subsequently printed in specific shapes to generate 3D structures for regenerative medicine or tissue engineering. A major interest is devoted to the printing of biomimetic materials with structural fidelity after their fabrication. Among some requirements imposed for bioinks, such as biocompatibility, nontoxicity, and the possibility to be sterilized, the nondamaging processability represents a critical issue for the stability and functioning of the 3D constructs. The major challenges in the field of printable gels are to mimic at different length scales the structures existing in nature and to reproduce the functions of the biological systems. Thus, a careful investigation of the rheological characteristics allows a fine-tuning of the material properties that are manufactured for targeted applications. The fluid-like or solid-like behavior of materials in conditions similar to those encountered in additive manufacturing can be monitored through the viscoelastic parameters determined in different shear conditions. The network strength, shear-thinning, yield point, and thixotropy govern bioprintability. An assessment of these rheological features provides significant insights for the design and characterization of printable gels. This review focuses on the rheological properties of printable bioinspired gels as a survey of cutting-edge research toward developing printed materials for additive manufacturing.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Another approach is fractional calculus [ 113 ], which is able to predict the complete viscoelastic behavior. The application of the fractional calculus allowed a reasonable fitting of both the creep and recovery steps [ 111 , 112 ]:

…”

Section: Rheological Parameters As Key Characteristics For Extrusion-...mentioning

confidence: 99%

Rheology as a Tool for Fine-Tuning the Properties of Printable Bioinspired Gels

Bercea¹

2023

Molecules

View full text Add to dashboard Cite

show abstract

“…The principle of time-temperature superposition (TTS), or frequency-temperature superposition, was used to expand this type of analysis. This analysis provides an opportunity to determine the temperature dependence of the rheological behavior of thermoplastic polymer and to expand the limits of unknown temperature frequencies [21].…”

Section: Dynamic Mechanical Analysismentioning

confidence: 99%

Dynamic Mechanical Properties of PVC Plastics in the Formation of Microstructures with Novel Magnetostrictor

et al. 2023

View full text Add to dashboard Cite

Molding in thermoplastic polymers using ultrasonic hot embossing technology is promising due to its high precision reproducibility. To understand, analyze and apply the formation of polymer microstructures by the ultrasonic hot embossing method, it is necessary to understand dynamic loading conditions. The Standard Linear Solid model (SLS) is a method that allows analyzing the viscoelastic properties of materials by representing them as a combination of springs and dashpots. However, this model is general, and it is challenging to represent a viscoelastic material with multiple relaxations. Therefore, this article aims to use the data obtained from dynamic mechanical analysis for extrapolation in a wide range of cyclic deformations and to use the obtained data in microstructure formation simulations. The formation was replicated using a novel magnetostrictor design that sets a specific temperature and vibration frequency. The changes were analyzed on a diffractometer. After the diffraction efficiency measurement, it was found that the highest quality structures were formed at a temperature of 68 °C, a frequency of 10 kHz, a frequency amplitude of 1.5 µm and a force of 1 kN force. Moreover, the structures could be molded on any thickness of plastic.

show abstract

“…In addition, these quantities are really useful for selecting the best vehicle setup to ensure the proper use of tires during races. For this aspect, it is also essential to characterize the tires from both a mechanical and thermal point of view [17][18][19], and this is related to the evaluation of the forces acting on the tires and the optimal thermal window of the same. In this way, it is possible to understand how to maximize the best overall vehicle performance, taking into account the tire/road interaction phenomena.…”

Section: Introductionmentioning

confidence: 99%

Four-Wheeled Vehicle Sideslip Angle Estimation: A Machine Learning-Based Technique for Real-Time Virtual Sensor Development

Napolitano Dell’Annunziata,

Ruffini,

Stefanelli

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

In the last few decades, the role of vehicle dynamics control systems has become crucial. In this complex scenario, the correct real-time estimation of the vehicle’s sideslip angle is decisive. Indeed, this quantity is deeply linked to several aspects, such as traction and stability optimization, and its correct understanding leads to the possibility of reaching greater road safety, increased efficiency, and a better driving experience for both autonomous and human-controlled vehicles. This paper aims to estimate accurately the sideslip angle of the vehicle using different neural network configurations. Then, the proposed approach involves using two separate neural networks in a dual-network architecture. The first network is dedicated to estimating the longitudinal velocity, while the second network predicts the sideslip angle and takes the longitudinal velocity estimate from the first network as input. This enables the creation of a virtual sensor to replace the real one. To obtain a reliable training dataset, several test sessions were conducted on different tracks with various layouts and characteristics, using the same reference instrumented vehicle. Starting from the acquired channels, such as lateral and longitudinal acceleration, steering angle, yaw rate, and angular wheel speeds, it has been possible to estimate the sideslip angle through different neural network architectures and training strategies. The goodness of the approach was assessed by comparing the estimations with the measurements obtained from an optical sensor able to provide accurate values of the target variable. The obtained results show a robust alignment with the reference values in a great number of tested conditions. This confirms that the adoption of artificial neural networks represents a reliable strategy to develop real-time virtual sensors for onboard solutions, expanding the information available for controls.

show abstract

Fractional Calculus Approach to Reproduce Material Viscoelastic Behavior, including the Time–Temperature Superposition Phenomenon

Cited by 12 publications

References 27 publications

Rheology as a Tool for Fine-Tuning the Properties of Printable Bioinspired Gels

Rheology as a Tool for Fine-Tuning the Properties of Printable Bioinspired Gels

Dynamic Mechanical Properties of PVC Plastics in the Formation of Microstructures with Novel Magnetostrictor

Four-Wheeled Vehicle Sideslip Angle Estimation: A Machine Learning-Based Technique for Real-Time Virtual Sensor Development

Contact Info

Product

Resources

About