Search

The critical penetration condition is an essential component of studies on the mechanism of sink vortex formation. However, the condition and its transition process are unknown. To address this issue, we constructed a Rankine-vortex-based fluid mechanic model, and proposed a Helmholtz-equation-based solution method to acquire the critical penetration condition. The two-phase mass suction-extraction mechanism of the Ekman boundary layer was discussed. Numerical results show that the critical penetration condition is dependent on the initial velocity components; if the initial disturbances are enhanced, the suction-extraction height and Ekman layer thickness increase. A particle image velocimetry (PIV)-based observation experimental platform was developed, and the effectiveness of the proposed method was verified. The vortex core boundary was observed first, so the radius of the vortex core could be acquired precisely.

Particle-wall collision is a complex liquid-solid coupling matter approximating to a chaotic state. Previous research mainly focused on the issues of particle trajectory and near-wall flow field, but the particle-wall collision mechanism and contact effects are unclear. To address this, a coupled computational fluid dynamics and discrete element method (CFD-DEM) modeling method is proposed. Firstly, flow field profiles are acquired by the CFD method as the initial motion conditions. Then, the particles are regarded as rigid bodies, and the data interactions between CFD and DEM are implemented by calculating for interaction force and void fraction. The results show that there are radial texture phenomena on the particle trajectories caused by the flowing interference; the central region has the lowest velocity and can be regarded as the rigid core of a Rankine vortex; if inlet diameter is 20 mm, the contacting distribution with rotating superposition can reach the best uniformity; the higher viscosity can carry more particles, and the transporting ability of the fluid medium is improved; the uniform contact effects can be more easily performed by the low viscosity fluid. This research can offer theoretical relevance to the modeling for multi-phase particle fluid, and provide technical support for flow regulation in the areas of fluid-based processing, turbine blade erosion, and reactor wall abrasion.

At the late stage of continuous casting (CC) ladle teeming, sink vortex can suck the liquid slag into tundish, and cause negative influences on the cleanliness of molten steel. To address this issue, a two-phase fluid mechanical modeling method for ladle teeming was proposed. Firstly, a dynamic model for vortex suction process was built, and the profiles of vortex flow field were acquired. Then, based on the level set method (LSM), a two-phase 3D interface coupling model for slag entrapment was built. Finally, in combination with high-order essentially non-oscillatory (ENO) and total variation diminishing (TVD) methods, a LSM-based numerical solution method was proposed to obtain the 3D coupling evolution regularities in vortex suction process. Numerical results show that the vortex with higher kinetic energy can form an expanded sandglass-shape region with larger slag fraction and lower rotating velocity; there is a pressure oscillation phenomenon at the vortex penetration state, which is caused by the energy shock of two-phase vortex penetration coupling.

At the late stage of continuous casting (CC) ladle teeming, sink vortex can suck the liquid slag into tundish, and cause negative influences on the cleanliness of molten steel. To address this issue, a two-phase fluid mechanical modeling method for ladle teeming was proposed. Firstly, a dynamic model for vortex suction process was built, and the profiles of vortex flow field were acquired. Then, based on the level set method (LSM), a two-phase 3D interface coupling model for slag entrapment was built. Finally, in combination with high-order essentially non-oscillatory (ENO) and total variation diminishing (TVD) methods, a LSM-based numerical solution method was proposed to obtain the 3D coupling evolution regularities in vortex suction process. Numerical results show that the vortex with higher kinetic energy can form an expanded sandglass-shape region with larger slag fraction and lower rotating velocity; there is a pressure oscillation phenomenon at the vortex penetration state, which is caused by the energy shock of two-phase vortex penetration coupling.

A Pattern Recognition method based on wavelet packet and artificial neural is proposed for solid-liquid two-phase flow characteristic parameters and the non-linear relationship between flow pattern. This method firstly established the physical and dynamic model, then set a monitoring point. To get the optimum wavelet tree and its information entropy, six floors of wavelet packet was used to decompose the collected velocity fluctuation signal. Transported the proper vector which is component by information entropy into Back Propagation neural network to train and identify. The recognition results show that this method can effectively overcome the subjectivity of traditional identification methods. It has good recognition effect, thus provide an effective choice for solid-liquid two-phase flow pattern recognition.

Soft Abrasive Flow Machining (SAFM) was presented as a new finishing process about the existing problems that the irregular surface of plastic mould was polishing difficultly. The paper first introduced the working principle and feature of SAMF. Secondly, the main influences of SAFM were analyzed. The problem of technology and theory urgent to settle was discussed. At the last, the technology development of SAFM was expected.

Because of the liquid phase’s driving action, particles would be collided the surface and impacted with each other in the flow passage, the surface will be machined though the continuous action of impact force and friction force. The finishing results of structural surface is related to the collision frequency and the pressure, abrasion situation in different area of the structural surface can be analyzed obviously by investigating dynamic characteristic and distribution of particle group. Based on coupled wave theory of liquid-solid two phases flow, using mixture model which belongs to Euler-Euler multiphase flow model and realizable turbulence model, turbulence effects of liquid-solid two-phase flow in the wall is numerical simulated and some parameters such as turbulent velocity and turbulent energy are calculated with different particles concentration in the flow passage which has V-shaped texture and semicircular cross-section. The simulation results show that the disorder degree of turbulence can be improved by assembling V-shaped constrained component, because V-shaped passage is benefit of eddy current’s generation. As the concentration of particles being enhanced, the velocity of particle would be increased in a certain range, turbulence energy reduces gradually, fluctuation margin of particle volume fraction is smaller and smaller, and curves of every kind of parameters change as continuous oscillation, area of surface corresponded with crest of the curve. The concentration of particles should be selected properly and different particles distribution and finishing performance would be obtained with different particles concentration.

As it was difficult to solve the near wall characteristics of flow field in softness abrasive flow machining (SAFM) on mould structural surface, a method for simulation the flow characteristics based on the low Re number k-ε model was proposed in this paper. The greater curvature of small size tube was used as specific simulation object. The motion law of particles and related parameters were calculated and the precision machining mechanism of SAFM was discussed. Simulation results show that the micro cutting of abrasive flow mainly appears as the transposition of cutting location influenced by the particle pressure, and as the variation of machining efficiency influenced by near-wall particle velocity. Thus via control of the inlet velocity and its corresponding machining time, it is supposed to work out the machining process according with the machining requirements. By tracking near-wall particles, it can be confirm that the movement of near-wall abrasive particles is similar to stream-wise vortices. The cutting traces on workpiece surfaces assume disorderly arrangement, so the feasibility of SAFM method can be reaffirmed.

This paper brought forward an intelligent computer aided instruction (ICAI) modeling method oriented to parallel robot instruction. According to the learning-origin structure of mechanical specialty students, the study process and cognition characteristics were analyzed, and the comparative research on their quality performance in parallel robot direction was carried out. The ICAI model was established oriented to parallel robot practical instruction combining machine learning and artificial intelligence method. Aiming at the basic instruction requirements of mechanical engineering specialty, the innovation mechanism of this area was researched, and the instruction strategies optimized and realization method were provided. Experiments proved that this method can simulate the implementation course of parallel robot instruction, and improve the instruction effects validly.

The soft abrasive flow machining was proposed for solving the problems of difficult contact finishing in course of mould manufacturing. It could reach the specular level and control turbulence abrasive flow. Based on the topological structure transformation of LSM, a two- dimensional model of the two-phase flow is established. This mechanics model with the SIMPLE (semi-implicit method for pressure-linked equations) algorithm incorporated is used to simulate the movement of the turbulent flow by using of k-ε model. The computed results show that this 2D model can preferably simulate the movement of the two-phase flow, and the characteristic parameters of abrasive two-phase flow are derived.

As far as the controllability of turbulence flow field surface effect of the soft abrasive flow was concerned, to begin with the analysis of the motion of the particle in the flow field, the paper studied the motion law of particle in the flow field, especially in the boundary layer. Based on the fluid-solid two-phase flow coupling style, it established the single particle dynamics model. Then it established the realizable k-ε model, in the light of the numerical simulation of turbulent flow. With the adoption of the computational method of SIMPLEC, it asked for the velocity and the pressure of fluid in the U-shaped flow passage, the velocity and the motion law of particles with different granularities and velocity, in the boundary layer. Experimentation results tell us that the original velocity plays a leading role in the motion trajectory of particles. The diameter influenced the particles motion trajectory in some degree.

According to liquid-solid two-phase flow model for the complexity of adaptation, as well as the impact of the concentration of particles, and we put forward a new method of considering the turbulent influence of particle concentration. Basing on the different turbulent control methods of the liquid-solid two-phase flow, we established the unified second-moment turbulence model. Using fluent software can realize turbulence model considering the particle pressure’s influence on particle’s concentration, and solve the problems of particle concentration and the flow passage control method. The simulation results showed that considering the concentration of particle’s influence on the pressure of the solid phase can accurately express the model of liquid-solid two-phase turbulent flow pattern.

Considering the demand of precision in mould structural surface polishing method, a new method based on soft abrasive flow machining(SAFM) was proposed, which was supposed to achieve polydirectional and multi-angle cutting acting on the surface of the workpiece by utilizing the irregular motion of both wear particles and the media in turbulence flow. Thus as the monodirectional marks on the machined surfaces was eliminated, the disadvantage in machining precision in conventional abrasive flow machining(AFM) method would be overcome. According to the particle distribution characteristics of SAFM, a two-phase dynamic model of abrasive flow oriented to SAFM combined with Discrete Phase Model(DPM) was built to analog simulation with the software Fluent. Sequently the mechanism of ultraprecision machining towards mould structural surface was analyzed briefly. Simulation results show that the abrasive efficiency along the flow passage can be influenced by the development of turbulence and the distribution of dispersed phase. Thus there a specific region can be obtained in the passage in which the abrasive efficiency is relatively stable.

To solve the problems of ladle slag detection system (SDS), such as high cost, short service life, and inconvenient maintenance, a new SDS realization method based on hidden Markov model (HMM) was put forward. The physical process of continuous casting was analyzed, and vibration signal was considered as the main detecting signal according to the difference in shock vibration generated by molten steel and slag because of their difference in density. Automatic control experiment platform oriented to SDS was established, and vibration sensor was installed far away from molten steel, which could solve the problem of easy power consumption by the sensor. The combination of vector quantization technology with learning process parameters of HMM was optimized, and its revaluation formula was revised to enhance its recognition effectiveness. Industrial field experiments proved that this system requires low cost and little rebuilding for current devices, and its slag detection rate can exceed 95%.

To solve the problems of ladle slag detection system (SDS), such as high cost, short service life, and inconvenient maintenance, a new SDS realization method based on hidden Markov model (HMM) was put forward. The physical process of continuous casting was analyzed, and vibration signal was considered as the main detecting signal according to the difference in shock vibration generated by molten steel and slag because of their difference in density. Automatic control experiment platform oriented to SDS was established, and vibration sensor was installed far away from molten steel, which could solve the problem of easy power consumption by the sensor. The combination of vector quantization technology with learning process parameters of HMM was optimized, and its revaluation formula was revised to enhance its recognition effectiveness. Industrial field experiments proved that this system requires low cost and little rebuilding for current devices, and its slag detection rate can exceed 95%.

Based on a large number of investigation and analysis for slag detection system (SDS), a kind of automatic SDS using vibration measurements had been put forward in this paper. After studying casting process from ladle to pouring box and protection casting supporting mechanical structure, vibration dynamics model of supporting structure was established, also variation of steel water impact force and influencing factors of inspecting spot vibration are analyzed. Theories of wavelet, wavelet package and their applications in signal processing are presented. Vibration signal of steel water was processed by the way of wavelet package, then its eigenvector and tolerance range were obtained, and that can realize effective identification for steel water status. Experimental results indicate that this system is very effective and achieves anticipated outcomes.

Establishment of a reasonable expert system integrated developing environment (ES-IDE) is a critical factor for developing ES promptly and effectively. By current investigation and analysis of related technology, a kind of IDE for fault diagnosis expert system (FDES) on the base of Protégé+CLIPS+Eclipse tool-chain was brought forward. The model of FDES was realized by Protégé and described by ontological analysis method. Combined with CLIPS, inference engine and knowledge base (KB) were realized and applied to diagnose and deduce, the developing period of ES core framework was shortened, and flexibility of system was increased. Based on component principle, every system module was encapsulated in form of Eclipse plug-in, so users can reconstruct and reconfigure to compile and make ES application instance uniformly according to their specific demands. Industry experiments prove that this system can generate FDES in a shorter period, has strong transplanting ability and friendly human-computer interface.

Aiming at some problems in the fields of industry monitoring technology (IMT) such as bad dynamic ability and poor versatility, this paper brought forward a kind of intelligent Status monitoring and Fault diagnosis Network System (SFNS) based on UPnP-Universal Plug and Play. The model for fault diagnosis network system was established according to characteristics and requirements of IMT network, and system network architecture was designed and realized by UPnP. Using embedded system technology, real-time data collection node, monitoring center node and data storage server were designed, and that supplies powerful real-time data support for SFNS. Industry fields experiments proved that this system can realize self recognition, seamless linkage and other self adapting ability, and can break through the limitation of real IP address to achieve real-time remote monitoring on line.