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Two stress regime‐dependent creep constitutive equations, that is, two‐regime Norton (2RN) model and Sin‐hyperbolic (Sinh) model, are adopted to numerically investigate the influence of constitutive equation and friction on the measurement of steady‐state creep strain rate based on five types small specimens. Results show that the influence of constitutive equation and friction depends strongly on the type of small specimen. A measurement error of more than 19 times may occur if the 2RN model is used, while the use of the Sinh model is able to generate a consistently lower measurement error. Of all small specimens, the cantilever beam testing (CaBT) is revealed to exhibit the best comprehensive performance in terms of measurement error and response to friction. To validate numerical findings, creep tests on the CaBT specimen of P91 steel are conducted at 600°C. Finally, recommendations on the choice of small specimen for obtaining creep strain rate are made. Highlights: Sinh model is better in describing stress regime‐dependent creep behavior.Influence of friction is strongly dependent on the type of small specimen.Small cantilever beam testing has the best comprehensive performance.Attention should be paid to selecting the constitutive equation and specimen type. [ABSTRACT FROM AUTHOR]

Objective: The mechanical condition and tactile evaluation of skin are essential for the development of skin care products. Most of the existing commercial instruments and studies aim to evaluate the skin surface by pressing it for hardness or by using imaging sensors, but there have been few instrumental measurements employing rubbing motion. Here, we have developed a sensor specialized for tactile sensation and the contact phenomenon during skin rubbing. Methods: The developed sensor has three features: It can measure body parts including cheeks and arms, automate the rubbing motion of the probe and measure vibration and friction simultaneously. It is hand‐held, with metal probes that rub the skin surface while rotating under a motor drive; it has an accelerometer and a force sensor beneath the probe measuring vibration and friction forces. To evaluate the validity of the sensor's measurements, artificial skin models were measured using the developed sensor and commercially available sensors and the results were compared. The relationship between the sensor output, surface roughness measurement and sensory evaluation was also investigated. Additionally, we evaluated the inter‐rater reliability when measuring actual skin. Results: The measurements of five artificial skin models with different surface shapes showed a high correlation (r = 0.99) between the vibration intensity values evaluated by the developed sensor and those measured by a tri‐axial acceleration sensor attached to a fingernail. The correlation coefficient between the vibration intensity values and surface roughness was r = 0.91, and the correlation with the sensory evaluation score of roughness was r = 0.99. The friction coefficients measured by the developed sensor and the force plate had r = 0.93, based on measurements of five artificial skin models with different friction conditions. The inter‐rater correlation coefficients between the three participants of the developed sensor were as high as 0.92 and 0.94 for the vibration and friction measurements respectively. Conclusion: The vibration intensities and friction coefficients from the sensor were highly correlated with those of the conventional sensor. The inter‐rater reliability was also high. The developed sensor can be useful for tactile evaluation in skin‐care product development. [ABSTRACT FROM AUTHOR]

Pavement skid resistance measurement is a fundamental component of roadway management and maintenance. Most traditional approaches rely on manual operations or heavy devices, which lead to a labor‐intensive, inefficient, and vulnerable testing environment. Precise laser scanning technology lays a solid foundation for effective and continuous pavement friction measurement. This paper proposed an automated pavement friction estimation model using 3D point cloud data and a deep neural network. The fine‐grained texture data of over 800 pavement sections with various anti‐skidding abilities were collected. The impact of the multi‐scale textures on pavement friction was separated and analyzed via two‐dimensional wavelet decomposition. A multi‐input fusion network with deep aggregation modules was designed to fuse the features of sub‐images generated by wavelet decomposition. The results show that the average prediction error is 0.0935, outperforming most state‐of‐the‐art models. The impact of different texture scales on friction estimation is then revealed. The proposed method provides a new tool for effective and large‐scale pavement friction evaluation. [ABSTRACT FROM AUTHOR]

Objective: Drawing parallels from rheotribology can be used to develop a robust instrumental protocol for non‐subjective characterization, product development and design of topical dosage forms with desired sensory attributes. However, instrumental characterization of cosmetic products can be influenced by the measurement protocol, thixotropy, flow anomalies like shear banding or wall slip and nature of the film formed on the skin surface. In this study, we evaluated the influence of above parameters on the instrumental sensory evaluation of 12 topical formulations of different galenic forms. Methods: Oscillatory strain sweep measurements (SAOS and LAOS) were performed to investigate the influence of frequency and wall slip on the material parameters. The textural attributes at different consumer touchpoints were evaluated by accounting time‐dependent simulation of viscoelastic flow. Further, the influence of film thickness and sample drying on the tactile properties of the topical formulations were studied on a non‐biological skin model using a sliding probe tribometer. Results: The study shows that the flow properties of the semi‐solid formulations depend on the timescale of the problem. A few formulations exhibited wall slip to varying degrees in the linear viscoelastic regime where the behaviour was found not to be characteristic of a particular topical dosage form. The material functions obtained from the Lissajous plots suggest that the non‐linear flow behaviour of different galenic forms is least influenced by the boundary conditions imposed by the measurement geometry. The results were statistically analysed using principal component analysis where the attributes used for discriminating skin creams during pick up and rub out are found to be closely associated with non‐linear rheology. The friction coefficient exhibited speed dependence where it formed different parametric group with rheological data depending on the lubrication regime. Conclusion: The study highlights that correlations are possible amongst rheological, tribological and instrumental textural analysis data, which can act an impetus for the development of models to predict attributes that drive perception at different consumer touchpoints. However, the choice of instrumental settings, anomalies associated with rheological measurements and friction dependence on a number of parameters can influence the model prediction. [ABSTRACT FROM AUTHOR]