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This purpose of the paper is to examine the multi-channel cyclone created at the Vilnius Gediminas Technical University (VGTU) Research Institute of Environmental Protection. The paper aims to predict the possible trajectories of solid particle motion in the cyclone with reference to the mechanical forces only.

The numerical calculations were performed on the basis of experimental results. The system of differential equations describing particle motion in the cyclone is analysed and numerically solved using Runge–Kutta–Fehlberg method. Research consists of three examples that illustrate the impact of particle density and velocity on collection and analyses the particle motion trajectories in the first and second channels of the cyclone.

Numerical calculations were performed according to the data from Vilnius Gediminas Technical University Research Institute of Environmental Protection. The particulate matter of wood ash and granite were used. The collection of solid particles of different size was examined when the air inflow velocity varies from 10 to 20 m/s. The possible motion trajectories of the solid particles are defined and the parameters of collected particles have been discussed.

The obtained results can be used for the analysis of air cleaning efficiency and particulate matter removal from air in a multi-channel cyclone.

The results lead us to improve the structure of the cyclone so as to effectively collect the solid particles of different size.

This paper presents the results obtained for the multi-channel cyclone created at the Vilnius Gediminas Technical University Research Institute of Environmental Protection.

The purpose of this paper is to establish a new two-phase Discrete Element Method (DEM) model to investigate the movement of fresh concrete which consists of mortar and aggregate. The established DEM model was adopted to simulate the mixing process of fresh concrete based on the commercial software package PFC3D. The trajectories of particles and particle clusters were recorded to analyze the mixing behavior from different scales. On one hand, the macro-scale movement was obtained to make the mixing process visualization. On the other hand, the relative micro movement of the single particle and particle clusters was also monitored to further study the mixing mechanism of the fresh concrete.

A new two-phase DEM model was designed to simulate the movement of fresh concrete which consists of mortar and aggregate. The linear-spring dashpot model was used to model all the contacts between particle and particle/wall to characterize the viscidity of fresh concrete. Moreover, two sets of parallel bond models were employed to characterize the contact between the mortar particles and mortar/coarse aggregate particles, namely the pbond1 and pbond2. The hybrid treatment enables the current DEM model to handle the yield behavior.

The mixing process of fresh concrete is mainly composed by the transportation in the x-direction and the overturn and fall off in the y- and z-directions. With these movements in different directions, the concrete particles can be fully mixed in the mixing drum.

A new two-phase DEM model was proposed and used to simulate the mixing process of fresh concrete. The outcomes of the simulation would be helpful for making the transporting truck visualization and the movement behavior of fresh concrete observable. The model can provide dynamic information of particles to reveal the interaction mechanism of fresh concrete in the truck mixer which is extremely difficult to obtain on-line in physical experiments or building site.

The attractiveness of functionally graded composites lies in the possibility of a gradual spatial change of their properties such as hardness, strength and wear resistance. The purpose of this paper is to discuss the use of electromagnetic buoyancy to separate the reinforcement particles during the casting process of such a composite.

The basic problem encountered in the process of casting composites is to obtain electromagnetic buoyancy and simultaneously to avoid a flow of the liquid metal which destroys the desired composite structure. In this paper the authors present the methodology of numerical optimization of inductor geometry in order to homogenize the electromagnetic force field distribution.

The optimization method based on searching the solution subspace created by applying knowledge of the modelled process physics proved better than the universal local optimization methods. These results were probably caused by the complex shape of the criterion function hypersurface characterized by the presence of local minima.

Due to their characteristics, functionally graded composites are of great interest to the automotive, aerospace and defense industries. In the case of metal matrix composites casting techniques (as the presented one) are the most effective methods of producing functionally graded materials.

The paper presents the optimization of a new process of casting functionally graded composites in a low-frequency alternating electromagnetic field. The process involves problems that did not occur previously in the area of electromagnetic processing of materials. The paper proposes the use of special design of inductors to homogenize the electromagnetic force field.

The purpose of this paper is to investigate an intelligent control for water hydraulic position servo system which is intent to be used in remote control robot for fusion reactor. The dynamic model of water hydraulic servo control system is built and proportional–integral–derivative (PID) controller is used.

PID control is the most common control algorithm used in industry and has been a conventional tool used to operate closed-loop control system; however, it is very difficult to achieve high accuracy and fast response by using the traditional way to tune its perimeters. To improve the control performance, optimization algorithm can be applied to search the best parameters of PID. This paper presents a search algorithm using particle swarm with H₂ control standards objective function to optimize PID parameters.

By comparing simulation and mock-up experiments’ results from different control methods, the particle swarm optimization algorithm presents better performance and is more effective for tuning PID parameters.

This paper presents an effective way to ensure safety and efficiency for remote handling maintenances of China Fusion Engineering Test Reactor.

Motion capture system (MoCap) has been used in measuring the human body segments in several applications including film special effects, health care, outer-space and under-water navigation systems, sea-water exploration pursuits, human machine interaction and learning software to help teachers of sign language. The purpose of this paper is to help the researchers to select specific MoCap system for various applications and the development of new algorithms related to upper limb motion.

This paper provides an overview of different sensors used in MoCap and techniques used for estimating human upper limb motion.

The existing MoCaps suffer from several issues depending on the type of MoCap used. These issues include drifting and placement of Inertial sensors, occlusion and jitters in Kinect, noise in electromyography signals and the requirement of a well-structured, calibrated environment and time-consuming task of placing markers in multiple camera systems.

This paper outlines the issues and challenges in MoCaps for measuring human upper limb motion and provides an overview on the techniques to overcome these issues and challenges.

The purpose of this paper is to present an image based method for estimating the 3D motion of rigid particles from high‐speed video footage (HSV). The computed motion can be used as either a means to generate quantitative feedback for a process or to validate the accuracy of discrete element method (DEM) simulation models.

Experiments consist of a diamond impacting an angled plate and video is captured at 4,000 frames per second. Simple image analysis is used to track the particle in each frame and to extract its 2D silhouette boundary. Using an approximate 3D model of the particle generated from a multi‐camera setup, a pose estimation scheme based on silhouette consistency is used in conjunction with a rigid body model to compute the 3D motion.

Under reasonable conditions, the method can reliably estimate the linear and angular motion of the particle to within 1 per cent of their true values.

As an example application, we demonstrate how the method can be used to validate DEM simulations of simple impact experiments captured with HSV, providing valuable insight towards further development. In particular, we investigate the effects of shape representation through sphere‐clumping and the applicability of different contact models.

The novelty of our method is its ability to accurately compute the motion associated with a real world interaction, such as an impact, which provides numerical ground truth at an individual particle level. While similar schemes have been attempted with ideal particles (e.g. spheres), the resulting models do not naturally extend to realistic particle shapes. Since our method can track real particles, real‐world processes can be better quantified.

Draping is one method used in clothing design. It is important to virtualize draping in real time, and virtual cloth handling is a key technology for this purpose. A mouse is often used for real-time cloth handling in many studies. However, gesture manipulation is more realistic than movements using the mouse. The purpose of this paper is to demonstrate virtual cloth manipulation using hand gestures in the real world.

In this study, the authors demonstrate three types of manipulation: moving, cutting, and attaching. The user’s hand coordinates are obtained with a Kinect, and the cloth model is manipulated by them. The cloth model is moved based on the position of the hand coordinates. The cloth model is cut along a cut line calculated from the hand coordinates. In attaching the cloth model, it is mapped to a dummy model and then part of the cloth model is fixed and another part is released.

This method can move the cloth model according to the motion of the hands. The authors have succeeded in cutting the cloth model based on the hand trajectory. The cloth model can be attached to the dummy model and its form is changed along the dummy model shape.

Cloth handling in many studies is based on indirect manipulation using a mouse. In this study, the cloth model is manipulated according to hand motion in the real world in real time.

This paper aims to present a method of optimal singularity-free motion planning under multiple objectives and multiple constrains for the 6-DOF parallel manipulator, which is used as an execution mechanism for the automated docking of components.

First, the distribution characteristics of the Jacobian matrix determinant in local workspace are studied based on the kinematics and a sufficient and necessary condition of singularity-free path planning in local workspace is proposed. Then, a singularity-free motion path of the end-effector is generated by a fifth-order B-spline curve and the corresponding trajectories of each actuator are obtained via the inverse kinematics. Finally, several objective functions are defined to evaluate the motion path and an improved multi-objective particle swarm optimization algorithm-based on the Pareto archive evolution is developed to obtain the optimal singularity-free motion trajectories.

If the initial pose and the target pose of the end-effector are both singularity-free, a singularity-free motion path can be planned in the local workspace as long as all the values of each pose elements in their own directions are monotonous. The improved multi-objective particle swarm optimization (IMPSO) algorithm is effective and efficient in the optimization of multi-objective motion planning model. The optimal singularity-free motion path of the end-effector is verified in the component docking test. The docking result is that the movable component is in alignment with the fixed one, which proves the feasibility and practicability of the proposed motion path method to some extent.

The proposed method has a certain novelty value in kinematic multi-objective motion planning of parallel manipulators; it also increases the application prospect of parallel manipulators and provides attractive solutions to component assembly for those organizations with limited cost and that want to find an option that is effective to be implemented.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

This paper aims to study the effects of the processing parameters in the reciprocating magnetorheological polishing (RMRP) on abrasive particle trajectory by the simulation analysis, which provides a basis for the machining uniformity of the workpiece.

The principle of the RMRP method is discussed, and a series of simulation analysis of the abrasive particle trajectory are performed to evaluate the effects of the workpiece’s rotational speed, the eccentric wheel’s rotational speed, the eccentricity and the frame gap on abrasive particle trajectory by using the RMRP method.

The processing parameters have a significant influence on the abrasive particle trajectory, and then the machining uniformity of the workpiece is affected. Under certain experimental conditions, the height difference of workpiece measuring points varies between 4 and 11 µm, and the height difference of equal radial measuring points is less than 1.5 µm by optimizing processing parameters.

In this study, the optimal processing parameters can be obtained by the simulation analysis of abrasive particle trajectory, which can replace the experimental methods to obtain the reasonable processing parameters for the machining uniformity of the workpiece. It provides references for the selection of processing parameter values in magnetorheological polishing process.