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Correction: Xu et al. Dynamic Behavior and Mechanism of Transient Fluid–Structure Interaction in Viscoelastic Pipes Based on Energy Analysis. Water 2024, 16, 1468
There were errors in the original publication [...]
Journal Article
Fractional Calculus with Applications in Mechanics
The books Fractional Calculus with Applications in Mechanics: Vibrations and Diffusion Processes and Fractional Calculus with Applications in Mechanics: Wave Propagation, Impact and Variational Principles contain various applications of fractional calculus to the fields of classical mechanics.
eBook
Modelling and Characterization of Soft Materials for Bio-Inspired Series-Elastic Actuators
In the field of Soft Robotics, viscoelasticity has been proved beneficial for human assistance applications. The human skeletal muscle system, as well as many soft materials commonly used in soft robotic applications, have viscoelastic properties. Viscoelasticity can be modelled using a set of equations known as the Linear Viscoelastic Models (LVMs). This modelling approach has two main limitations: high mathematical complexity and high computational cost. Here, these limitations are addressed in two ways. Firstly, the Piecewise Linearisation method is used to reduce the mathematical complexity of LVMs. Secondly, a modelling approach based on feedforward artificial neural networks (ANNs) is used to reduce the computational cost. The aim of both modelling approaches is to describe the non-linear, strain-dependent, and time-dependent stress response of seven thermoplastic elastomers. On the one hand, the implementation of the Piecewise Linearisation method yielded the PL-SLS model and the PL-Wiechert model. Both models were successful in predicting the viscoelastic behaviour of the materials, outperforming similar modelling tools documented in the literature. On the other hand, four different architectures of ANN models are developed, categorized in rate-dependent and rate-independent. Results highlight the rate-dependent architecture as the most suitable. The ANN models achieved a similar prediction performance as the PL models. The ANN model for the natural rubber material is further validated in a real-time simulation environment, in Simulink. This soft material is found to be the best candidate to imitate the mechanical properties of the human tendon. On the one hand, the performance prediction of the ANN models is adequate for a sine wave strain input, when the strain rate is constant. On the other hand, the response of the ANN model is unstable under variable strain rates. This highlights an important limitation of the training set used for developing the ANN models, which only contains data for three different strain rates. Finally, the three modelling tools developed in this research are a direct improvement to current modelling approaches. Nonetheless, a richer training set is required to improve the ANN models real-time response.
Dissertation
Approximation of Linear Viscoelastic Model in the 3 Dimensional Case with Mechanical Analogues of Finite Size
A linear viscoelastic model having a continuous spectrum is difficult to implement in a finite element calculation. Then approximation of this model by a generalized Kelvin Voigt model or generalized Maxwell model is another option allowing calculation. A simple method allowing approximation of a linear viscoelastic model by a generalized Kelvin Voigt or generalized Maxwell model having \"n\" bodies is proposed. This method is applied to bituminous materials. The continuous spectrum 2S2P1D model developed at the \"Ecole Nationale des Travaux Publics de l'Etat\" (ENTPE) for bituminous materials is approximated by a generalized Kelvin Voigt and a generalized Maxwell Model having any chosen number (n) of bodies. The three-dimensional case is also considered and influence of the number of chosen bodies \"n\" is presented.
Journal Article
0221 Acute Sleep Deprivation: Consequences On Healthy Face Skin. A Non-invasive Instrumental Investigation
Introduction Sleep deprivation has a strong impact on facial appearance with visible associated signs of fatigue but the impacts on skin biophysical features still remains unknown. Methods The present study investigates the impact of two consecutive nights with sleep restriction to 3 hours per night on facial skin, by using noninvasive instrumental methods for sebum (sebumeter), hydration (corneometer CM 825/Courage & Khazaka), trans-epidermal water loss (tewameter TM 210), biomechanical properties (cutometer MPA 580), pH (PH 900), desquamation (D-squameter and image analysis) quantification and image analysis (ColorFace/Newtone Technologies). Twenty-four healthy Caucasian women aged 30-55 were selected for their well-sleeping with Epworth scale, Pittsburg quality index and homogeneity of their circadian typology with Horne and Ostberg questionnaire. Sleep deprivation was controlled by actimetry, and a sleep diary. Biophysical measurements and image of the face were taken in the morning and the evening the day before and the day after the sleep deprivation. Results We observed that sebum and PIE were more intense in the afternoon than in the morning without any impact of sleep deprivation on these parameters. On the contrary, hydration of the skin surface, pH and viscoelastic properties of the skin e.g. extensibility (Uf), elasticity (Ue), and delayed extensibility (Uv) as well as well single desquamating corneocytes (invisible desquamation) and radiance were significantly reduced after sleep deprivation. Conclusion This study identifies several important skin facial parameters significantly affected by acute sleep deprivation e.g. hydration, acidity, desquamation homogeneity, viscoelastic properties and complexion luminosity and highlights the importance of the sleep quality (or length) in physiological skin homeostasis, aesthetic and comfort. Support (If Any) LVMH Research, France
Journal Article