A Framework for Joint Simulation of Distributed FMUs

2019 ◽  
pp. 43-53
Author(s):  
Hang Ji ◽  
Junhua Zhou ◽  
Luan Tao ◽  
Xiao Song ◽  
Guoqiang Shi ◽  
...  
Keyword(s):  
Joint Simulation

Simulation of Valve Position Feedback Mechanism Based on Pro/E and ADAMS

2014 ◽  
Vol 721 ◽  
pp. 244-248
Author(s):  
You Jun Fan ◽  
Fei Li ◽  
Hua Tian Zhao
Keyword(s):  
Feedback Mechanism ◽  
Dynamics Model ◽  
Joint Simulation ◽  
Force And Motion ◽  
Motion State ◽  
Position Feedback ◽  
Displacement Angle ◽  
Valve Position ◽  
Relationship Of ◽  
The Relationship

In traditional valve position feedback mechanism design, it is tested repeatedly and improvement after processing prototype, the process is complex and workload. Using Pro/E and ADAMS, the overall mechanical structure of the valve position feedback mechanism for joint simulation, and an analysis of the kinematics and dynamics model, simplified the design process of the repeated calculation, get the relationship of stem displacement-angle between gear, gear meshing force and motion state of the stem, the simulation value compared with the theoretical value, tallies with the data and shows that the simulation is reasonable.

scholarly journals Research on Intelligent Vehicle Path Planning Based on Rapidly-Exploring Random Tree

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yangyang Shi ◽  
Qiongqiong Li ◽  
Shengqiang Bu ◽  
Jiafu Yang ◽  
Linfeng Zhu
Keyword(s):  
Convergence Speed ◽  
Random Tree ◽  
Tree Search ◽  
Vehicle Model ◽  
Turning Angle ◽  
Tree Algorithm ◽  
Slow Convergence ◽  
Joint Simulation ◽  
Simulation Based ◽  
Vehicle Path

Aiming at the problems of large randomness, slow convergence speed, and deviation of Rapidly-Exploring Random Tree algorithm, a new node is generated by a cyclic alternating iteration search method and a bidirectional random tree search simultaneously. A vehicle steering model is established to increase the vehicle turning angle constraint. The Rapidly-Exploring Random Tree algorithm is improved and optimized. The problems of large randomness, slow convergence speed, and deviation of the Rapidly-Exploring Random Tree algorithm are solved. Node optimization is performed on the generated path, redundant nodes are removed, the length of the path is shortened, and the feasibility of the path is improved. The B-spline curve is used to insert the local end point, and the path is smoothed to make the generated path more in line with the driving conditions of the vehicle. The feasibility of the improved algorithm is verified in different scenarios. MATLAB/CarSim is used for joint simulation. Based on the vehicle model, virtual simulation is carried out to track the planned path, which verifies the correctness of the algorithm.

scholarly journals Optimization Algorithm and Joint Simulation to Micro Thermal Deformation Using Temperature Measurement in the Orifice of Hydraulic Valve

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1136
Author(s):  
Qianpeng Chen ◽  
Hong Ji ◽  
Hongke Zhao ◽  
Jing Zhao
Keyword(s):  
Optimization Algorithm ◽  
Quantitative Research ◽  
Thermal Deformation ◽  
Measurement Data ◽  
Sharp Edge ◽  
Large Drop ◽  
Joint Simulation ◽  
Valve Orifice ◽  
Spool Valve ◽  
Hydraulic Valve

When exposed to viscous heating, hydraulic valve orifices experience thermal deformation, which causes spool clamping and actuator disorder. Quantitative research on thermal deformation can help reveal the micro-mechanism of spool clamping. In this study, miniature thermocouples are embedded into a valve orifice with an opening size of 1 mm to measure temperature distribution. An optimization algorithm based on measurement data (M-OA) for the thermal deformation of the valve orifice is proposed. The temperature and thermal deformation of the valve orifice are calculated through Fluent and Workbench joint simulation, with the measurement data serving as boundary conditions. Results show that, for a valve orifice with a valve wall length of 18 mm, when the temperature of the sharp edge is at 60 °C, thermal deformation measures 7.7 μm via observation and 7.62803 μm via M-OA, indicating that the M-OA method is reliable. The results of the joint simulation can be accepted because measurements of temperature reached an accuracy rate of 95%, and that of deformation reached 82.7%. A large drop in pressure led to a rapid increase in temperature, causing serious thermal deformation of the valve orifice. With an inlet pressure of 3 MPa, the temperature of the sharp edge reached 72.9 °C within 110 min, and radial thermal deformation can reach 8.3 μm. Such deformation poses great risk of spool clamping for a spool valve of Φ36 mm.

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