scholarly journals Parameter Optimization and Prediction Model of Induction Heating for Large-Diameter Pipe

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Xiurong Fang ◽  
Jia Lu ◽  
Junfeng Wang ◽  
Jinhui Yang
Keyword(s):  
Prediction Model ◽  
Induction Heating ◽  
Process Parameters ◽  
Pipeline Steel ◽  
Large Diameter ◽  
Outer Wall ◽  
Design Parameters ◽  
Heating Process ◽  
Influence Of Process Parameters ◽  
Heating Device

The parameters of induction heating of large-diameter pipes have a direct effect on the final processing quality of the elbow, and the complexity of multifield coupling of magnetothermal force in induction heating can make it impossible to quantitatively optimize the design parameters of the induction heating device. In this paper, X80 pipeline steel induction heating is taken as the research object, and a corresponding numerical model is established. The influence of induction heating process parameters on the heating temperature of pipeline steel under the skin effect is determined. First, the influence of process parameters on the heating effect of pipeline steel is quantified by orthogonal test. Then, taking the optimum temperature difference between the inner and outer wall of X80 pipeline steel during the induction heating process as a target, the optimal process parameter set of the pipe induction heating is determined by using neural network genetic algorithm. Finally, comparing the relevant test criteria of the regression equation, the optimum mathematical prediction model of the outer wall temperature of the pipe induction heating process is obtained, which provides a theoretical basis for optimization of the process parameters of the pipe-based induction heating device.

Sensitivity Analysis of Design Parameters in Transverse Flux Induction Heating Device

2020 ◽  
Vol 30 (4) ◽  
pp. 1-6 ◽  
Author(s):  
Jiancheng C. Wu ◽  
Shaopeng P. Wang ◽  
Youhua H. Wang ◽  
Chengcheng Liu
Keyword(s):  
Sensitivity Analysis ◽  
Induction Heating ◽  
Design Parameters ◽  
Heating Device ◽  
Transverse Flux

Numerical Simulation on Induction Heating Process for Crankshaft Shrink Fitting

2012 ◽  
Vol 215-216 ◽  
pp. 1111-1117
Author(s):  
Qing Lei Zhang ◽  
Bai Yu Zhao ◽  
Jing Kuan Guo
Keyword(s):  
Numerical Simulation ◽  
Temperature Field ◽  
Induction Heating ◽  
Heating Process ◽  
Technological Parameters ◽  
Effect Factors ◽  
Large Size ◽  
Heating Device ◽  
Shrink Fitting ◽  
Frequency Current

Based on induction heating theory, a finite elementmodel for electromagnetic-temperature field has been developed. The simulation of induction heating process in large size crankshaft shrink fitting is carried out by using FEA software ANSYS. With temperature and deformation distribution being calculated, the characteristics and effect factors in the induction heating process are also analyzed. In conclusion, the optimized crankshaft heating techonology could be estabished by adjusting technological parameters of the heating device. Specifically, frequency, current, heating position, etc.

scholarly journals Simulation of induction heating technology for the production of seamless large diameter tees

2018 ◽  
Vol 245 ◽  
pp. 04002
Author(s):  
Iurii Murashov ◽  
Vyacheslav Shestakov ◽  
Vladimir Skornyakov ◽  
Irina Savelieva
Keyword(s):  
Mathematical Model ◽  
Induction Heating ◽  
Cooling System ◽  
Large Diameter ◽  
Experimental Studies ◽  
Spiral Inductor ◽  
Heating Process ◽  
Operating Modes ◽  
Flat Spiral ◽  
Heating Technology

The article is dedicated to nonstationary simulation of induction heating technology for the production of seamless large diameter tees. A mathematical model of induction heating process representing a multi-physical (heat transfer and electromagnetism) task for technology of tees production is developed. Numerical simulation was carried out for a flat spiral inductor. The developed model was verified according to the results of experimental studies. The hydrodynamic 3D mathematical model is developed for the design of the inductor cooling system. Optimal operating modes are determined by simulation results and confirmed by experimental data. The calculation results are presented for pipes with wall thicknesses: 15 mm, 40 mm, 60 mm, 70 mm.

Optimization of Pipe Induction Bending Process Parameters

2017 ◽  
Author(s):  
T. S. Kathayat ◽  
Rajesh K. Goyal ◽  
Richard Hill ◽  
Tushal Kyada
Keyword(s):  
Induction Heating ◽  
Process Parameters ◽  
Water Pressure ◽  
Large Diameter ◽  
Water Flow Rate ◽  
Microstructural Analysis ◽  
Mechanical Tests ◽  
Complex Process ◽  
Bending Process ◽  
Bending Radius

Hot pushed induction heating is a bending process used to bend pipes having a small bending radius with a large diameter. This is a complex process since it involves mechanical process of bending and thermal process of localized induction heating. This paper deals with the optimization of induction bending process parameters such as bending speed, water flow rate, water pressure, air pressure and induction coil to water coil distance. Mother pipes of size 464 mm OD × 20.60 mm and grade API 5L X65MS/MO were used to make trial bends of 5D radius in 30° angle. Trial bends were subjected to mechanical tests and microstructural analysis to evaluate the effects of selected process parameters.

Creep Age-Forming Experiment and Springback Prediction for AA2524

2012 ◽  
Vol 457-458 ◽  
pp. 122-129 ◽  
Author(s):  
Li Hua Zhan ◽  
Si Ge Tan ◽  
Ming Hui Huang ◽  
Jie Niu
Keyword(s):  
Mechanical Properties ◽  
Prediction Model ◽  
Process Parameters ◽  
Aluminium Alloys ◽  
Theoretical Basis ◽  
Age Hardening ◽  
Work Piece ◽  
Influence Of Process Parameters ◽  
Springback Prediction ◽  
Creep Age Forming

Creep age-forming (CAF) technology is a new forming method, which combined age hardening and creep forming processes into one. It is mainly used to manufacture wing panels. In this paper, a set of experimental device of creep age forming is developed and the influence of process parameters on the springback of artificially aged 2524 aluminium alloys (AA2524) are investigated. The law of the comprehensive effect of aging time, aging temperature, elastic pre-deformation radius and work-piece thickness, on creep aging springback and mechanical properties of AA2524 is obtained. Based on multiple regression analysis, springback prediction model of process parameters is established and further proven experiments have then been carried out. The result shows that the maximum springback deviation between the experimental results and the prediction ones is within 9.5%. The accuracy of springback prediction model is validated, which provides a theoretical basis for process parameter optimization and springback prediction of CAF.

scholarly journals A non-intrusive model order reduction approach for multi-physics parametrized problems - Application to induction heating process

2021 ◽  
Author(s):  
Khouloud Derouiche ◽  
Francisco Chinesta ◽  
Monzer Daoud ◽  
Khalil Traidi
Keyword(s):  
Finite Element ◽  
Real Time ◽  
Induction Heating ◽  
Process Parameters ◽  
Dimensional Space ◽  
Computational Cost ◽  
Heating Process ◽  
Reduced Basis ◽  
Finite Element Software ◽  
Low Dimensional

Finite element modeling (FEM) has recently become the most attractive computational tool to predict and optimize many industrial problems. However, the FEM becomes ineffective as far as complex multi-physics parameterized problems, such as induction heating process, are concerned because of high computational cost. This work aims at studying the possibility of applying a new approach based on the reduced order modeling (ROM) to obtain approximate solutions of a parametric problem. Basically, the effect of induction heating process parameters on some physical quantities of interest (QoI) will be analyzed under the real-time constraint. To achieve this dimensionality reduction, a set of precomputed solutions is first collected, at some sparse points in the space domain and for a properly selected process parameters, by solving the full-order models implemented in the commercial finite element software FORGE®. A Proper Orthogonal Decomposition (POD) based reducedorder model is then applied to the collected data to find a low dimensional space onto which the solution manifold could be projected and an approximated solution for new process parameters could be efficiently computed in real time. Besides, the POD is applied to build a reduced basis and to compute their corresponding modal coefficients. It is then followed by artificial intelligence techniques for regression purpose, such as sparse Proper Generalized Decomposition, to fit the low dimensional POD modal coefficients. Hence, the problem can be solved with a much lower dimension compared to the initial one. It was shown that a good approximation of the QoI was provided, in low-data limit, using a single POD modal coefficient as a response for the regression methods. However, the obtained approximation accuracy needs to be enhanced.

The effect of process parameters on cell morphology in cellular aluminium alloy fabricated by powder compression and the induction heating process

2003 ◽  
Vol 217 (2) ◽  
pp. 201-211 ◽  
Author(s):  
S W Youn ◽  
C G Kang
Keyword(s):  
Mechanical Properties ◽  
Aluminium Alloy ◽  
Induction Heating ◽  
Process Parameters ◽  
Cell Structure ◽  
Heating Process ◽  
Pressing Pressure ◽  
Foaming Process ◽  
Powder Compression ◽  
Foaming Temperature

In a foaming process, accurate control of the foaming temperature and heating rate is very important in terms of reproducibility of mechanical properties. Generally, foaming of the precursor is performed in an electric furnace, which is preheated at temperatures higher than the desired temperature. In this case, accurate control of the precursor temperature is difficult. In this study, cellular aluminium alloy having a closed cell structure is fabricated by applying the powder compact method and an induction heating process. The induction heating process was used for foaming of the precursor in order to improve the reproducibility of mechanical properties. To establish the cellular aluminium fabrication conditions, the effects of process parameters such as the titanium hydride content (0.3-1.5 wt%), pressing pressure of the foamable precursor (50-150 kN) and the foaming temperature (610-690°C) on the pore morphology were investigated and porosities (%)-foaming temperature curves were obtained.

Experimental and Simulation Study of Microstructure of the Aluminium Alloy 319s in Induction Reheating Process

2012 ◽  
Vol 192-193 ◽  
pp. 281-286 ◽  
Author(s):  
Nan Nan Song ◽  
Fan Zhang ◽  
You Feng He ◽  
Qiang Zhu
Keyword(s):  
Induction Heating ◽  
Process Parameters ◽  
Liquid Fraction ◽  
Quantitative Relationship ◽  
Heating Process ◽  
Time Interval ◽  
Short Time Interval ◽  
Compressor Wheel ◽  
Semi Solid ◽  
Reheating Process

Semi-solid processing of metallic alloys has been developing over the last 30 years. Millions of components are now manufactured by semi-solid processing. A semi-solid processing so called thixoforming requires reheating the feedstock to a semi-solid state in relatively short time interval with a uniform temperature distribution as well as an optimum liquid fraction. Microstructure, which makes significant impact on processing parameters and quality of the component, changes during the reheating process. The main objective of this study is to establish a quantitative relationship of the microstructure and the induction heating process parameters of the aluminum alloy 319s. This quantitative relationship is employed in the numerical simulation of calculating solid/liquid fraction changes during induction heating process. The simulation results are then successfully applied in aiding optimization of process parameters to make an automobile engine turbocharger compressor wheel, which has very complex geometry.

Sign in / Sign up

Export Citation Format

Share Document