The operation of the knife-edge viscometer requires knowledge of the interfacial velocity profile in order to determine the viscous traction between the surface film and the knife edge and hence measure the surface shear viscosity of the film. The interfacial velocity profile can be obtained analytically in two limiting regimes. One is the limit of the surface shear viscosity going to infinity,...

An experimental micromagnetoflowcell viscometer was fabricated to enable viscosity measurements for microscopic quantities of liquid. The device uses measurement of the terminal velocity of superparamagnetic microparticles to determine the fluid properties. Motion of these particles is controlled by the magnetic field generated from microscopic electromagnetic loops. Analytical modelling has be...

Viscous rate effects are commonly observed in clay soils in applications that involve high strain rates such as free falling penetrometer tests. Viscous rate effects are not well studied thus affecting reliable interpretation of these applications. This paper presents an investigation of viscous rate effects in clay using laboratory rate studies covering a wide range of strain rates (6 orders o...

In this study, we propose an advanced category of a fuzzy adaptive neural network (FANN) based on feature self-enhancement unit (FSU) and statistical selection methods (SSMs). Undoubtedly, the raw data contain large amount information with varying importance. One most important tasks for regression model design is to avoid losing these details. However, cannot participate in whole training proc...

In vitro and in vivo studies were made on the sputum of chronic bronchitics using a FerrantiShirley cone and plate viscometer and a new stress relaxation method. The latter utilized a modified chemical balance and permitted study at very low shear rates. The results from simpler apparatus correlated well with the data obtained with the cone and plate viscometer. Significant reduction in four ch...

Most mango farms classify the maturity stage manually by trained workers using external indicators such as size, shape, and skin color, which can lead to human error or inconsistencies. We developed four common machine learning (ML) classifiers, k-mean, naïve Bayes, support vector machine, feed-forward artificial neural network (FANN), all of were aimed at classifying ripeness mangoes harvest. ...