Simulation of Electrofusion Parameters of PE Saddle Pipe Based on Finite Element Analysis of Temperature Field

2021 ◽  
pp. 390-399
Author(s):  
Wenchao Yu ◽  
Qihua Yang ◽  
Wei Zhang ◽  
Yuan Chen ◽  
Jie Sun
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Temperature Field ◽  
Element Analysis

scholarly journals Numerical Simulation on Thermodynamics Performance in the Fireproof Sealing by Finite Element Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Shuai Gao ◽  
Guoqing Zhu ◽  
Yunji Gao ◽  
Guoqiang Chai ◽  
Jinju Zhou
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Temperature Field ◽  
Thermal Gradient ◽  
Thermal Flux ◽  
Ansys Software ◽  
Element Analysis ◽  
The Finite Element Analysis ◽  
Thermodynamic Performance ◽  
Temperature Time

In this paper, the finite element analysis was firstly employed to investigate the thermal analysis on two fireproof sealing models with ANSYS software under HC standard temperature-time condition. The main thermal parameters were analyzed and obtained, including temperature field, thermal flux, and thermal gradient. After comparing the two fireproof sealing models, the major conclusions are summarized as follows: In terms of temperature field, the temperature on the left side of the first model ranges from 60 to 524°C in. In contrast, the highest temperature on the left side of the second model eventually reaches below 151°C. Moreover, the vectors of thermal gradient in the first model are compared with the second model, and the temperature gradient disturbance is more obvious in the second fireproof sealing model, which is better to slow down temperature spreading. The accelerated speed of E1 and G1 is 0.0096°C/s and 0.0619°C/s partly, which are far more than C2 and F2 with values of 0.0028°C/s and 0.0078°C/s, respectively. In a word, the performance of the first fireproof sealing model is inferior to the second fireproof sealing model. The conclusions of the study are meaningful to improve the thermodynamic performance of the fireproof sealing in the converter station.

The Steady-State Temperature Field Analysis of the 3D Rolling Tire Based on Adina FEA Software

2009 ◽  
Vol 87-88 ◽  
pp. 518-523 ◽  
Author(s):  
Jing Li ◽  
Yan He ◽  
Zhen Chao Chen
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Temperature Field ◽  
Steady State ◽  
Field Analysis ◽  
Analysis Model ◽  
Element Analysis ◽  
Finite Element Analysis Model ◽  
Steady State Temperature ◽  
Steady Temperature Field

Based on the Adina finite element analysis software, 3D axisymmetric finite element analysis model of the 205/75R15 PCR tire was established, the steady temperature field of rolling tire was simulated, and the thermal distribution colored cloud diagram of steady-state temperature field of 3D rolling tire which directly shows the temperature distribution of each section of tire was analyzed to offer certain guidance to the improvement of tire structure and rubber formula.

Study on Thermal Placement Optimization of Embedded MCM

2011 ◽  
Vol 189-193 ◽  
pp. 2269-2273
Author(s):  
Chun Yue Huang ◽  
Tian Ming Li ◽  
Ying Liang ◽  
He Geng Wei
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Temperature Field ◽  
Field Distribution ◽  
Temperature Difference ◽  
Optimization Algorithm ◽  
Thermal Field ◽  
Maximum Temperature ◽  
Element Analysis ◽  
Placement Optimization

In the thermal design of embedded multi-chip module (MCM), the placement of chips has a significant effect on temperature field distributing, thus influences the reliability of the embedded MCM. The thermal placement optimization of chips in embedded MCM was studied in this paper, the goal of this work is to decrease temperature and achieve uniform thermal field distribution within embedded MCM. By using ANSYS the finite element analysis model of embedded MCM was developed, the temperature field distributing was calculated. Based on genetic algorithms, chips placement optimization algorithm of embedded MCM was proposed and the optimization chips placement of embedded MCM was achieved by corresponding optimization program. To demonstrate the effectiveness of the obtained optimization chips placement, finite element analysis (FEA) was carried out to assess the thermal field distribution of the optimization chips placement in embedded MCM by using ANSYS. The result shows that without chips placement optimizing the maximum temperature and temperature difference in embedded MCM model are 87.963°C and 2.189°C respectively, by using chips placement optimization algorithm the maximum temperature drop than the original 0.583°C and the temperature difference is only 0.694°C . It turns out that the chip placement optimization approach proposed in this work can be effective in providing thermal optimal design of chip placement in embedded MCM.

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