Mechanical and microscopic characterization of expansive soils modified by water-soluble polymers.

With the advancement of ecological and environmental protection construction, the research on the modification of expansive soil using environmentally friendly polymers can make up for the harm to the ecological environment caused by traditional modification. Mechanical and microscopic properties of modified expansive soils were analyzed through indoor tests. The results showed that the liquid limit and plasticity index decreased by 52.

Solid waste shape description and generation based on spherical harmonics and probability density function.

Transport and separation processes of solid waste can only be modelled successfully with discrete element methods in case the shape of the particles can be described accurately. The existing techniques for morphological data acquisition, such as computed tomography, laser scanning technique, optical interferometer, stereo photography and structured light technique, are laborious and require a large amount of realistic solid waste samples. Therefore, there is a pressing need for an alternative method to describe the shape of solid waste particles and to generate multiple variations of particles with almost similar shapes.

A robust identification method for nonferrous metal scraps based on deep learning and superpixel optimization.

End-of-life vehicles (ELVs) provide a particularly potent source of supply for metals. Hence, the recycling and sorting techniques for ferrous and nonferrous metal scraps from ELVs significantly increase metal resource utilization. However, different kinds of nonferrous metal scraps, such as aluminium (Al) and copper (Cu), are not further automatically classified due to the lack of proper techniques.

Operation parameters optimization of a separating system for non-ferrous metal scraps from end-of-life vehicles based on coupled simulation.

End-of-life vehicles (ELVs) provide a particularly potent source of non-ferrous metal scraps. At presents, conveyor belt and air-jet nozzle are widely used in the existing separation system for non-ferrous metal scraps. Parameters such as shape of the scraps, conveyor belt speed (v), nozzle air pressure (P) and nozzle angle (α) have a significant influences on the separating accuracy and efficiency.

Bio-Inspired PHM Model for Diagnostics of Faults in Power Transformers Using Dissolved Gas-in-Oil Data.

Prognostics and Health Management (PHM) is an emerging technique which can improve the availability and efficiency of equipment. A series of related optimization of the PHM system has been achieved due to the growing need for lowering the cost of maintenance. The PHM system highly relies on data collected from its components.

Machine Learning-Based Sensor Data Modeling Methods for Power Transformer PHM.

An emerging prognostic and health management (PHM) technology has recently attracted a great deal of attention from academies, industries, and governments. The need for higher equipment availability and lower maintenance cost is driving the development and integration of prognostic and health management systems. PHM models depend on the smart sensors and data generated from sensors.