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    王卫卫, 易幼平, 谢满堂. 铝合金板带热连轧轧件温度场的有限元模拟[J]. 机械工程材料, 2013, 37(7): 98-102.
    引用本文: 王卫卫, 易幼平, 谢满堂. 铝合金板带热连轧轧件温度场的有限元模拟[J]. 机械工程材料, 2013, 37(7): 98-102.
    WANG Wei-wei, YI You-ping, XIE Man-tang. Thermal Field FEM Simulation in Multi-pass Hot Rolling Process for Aluminum Plate[J]. Materials and Mechanical Engineering, 2013, 37(7): 98-102.
    Citation: WANG Wei-wei, YI You-ping, XIE Man-tang. Thermal Field FEM Simulation in Multi-pass Hot Rolling Process for Aluminum Plate[J]. Materials and Mechanical Engineering, 2013, 37(7): 98-102.

    铝合金板带热连轧轧件温度场的有限元模拟

    Thermal Field FEM Simulation in Multi-pass Hot Rolling Process for Aluminum Plate

    • 摘要: 基于MARC有限元软件建立了铝合金板带15道次热连轧二维有限元模型, 对轧制过程中各道次轧件的温度场进行了数值模拟, 分析了轧制过程中轧件温度场的变化和分布规律, 并用实测结果验证了模拟结果的准确性。结果表明: 轧制过程中轧件表面温度变化梯度最大, 越靠近中心变化梯度越小; 随轧制的进行, 表面温度呈现先下降后上升的变化规律, 中心温度和平均温度呈现先上升后下降的变化规律, 第11道次以后轧件厚度方向上温度基本一致, 温度梯度小于1 ℃; 塑性变形温升和接触温降对轧件温度场影响显著, 对流辐射温降影响相对较小; 有限元计算结果与实测结果吻合较好, 平均误差仅为1.1%。

       

      Abstract: A two-dimensional FEM model for aluminum plate in hot rolling of 15 passes was set up based on MARC software and the thermal field during hot rolling was researched by numerical simulation. The temperature variation and distribution were analyzed and the precision of calculation results was proved by the contrast of temperature simulation and measured temperature. The results show in rolling process the temperature gradient on surface was the largest. The nearer to the center, the smaller the temperature gradient. With the rolling process going on, the surface temperature decreased and then increased, but the central temperature and the average temperature gradual increased and then decreased. Besides, the temperature gradient was less than 1 ℃ in the end of the 11th pass. Moreover, the effects of heating due to plastic deformation and cooling due to contact thermal conduction on thermal field were obvious compared with the effect of coupled convective and radiative heat transfer. The simulation results were agreed well with the measured results and the average error was only 1.1%.

       

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