张小强,云泽,蒋庆梅,等. X80M管道全自动焊环焊缝热影响区冷却时间预测模型[J]. 油气储运,2025,44(4):1−9.
引用本文: 张小强,云泽,蒋庆梅,等. X80M管道全自动焊环焊缝热影响区冷却时间预测模型[J]. 油气储运,2025,44(4):1−9.
ZHANG Xiaoqiang, YUN Ze, JIANG Qingmei, et al. Prediction model for cooling time in the heat-affected zone of girth welds in fully automatic welding of X80M pipeline[J]. Oil & Gas Storage and Transportation, 2025, 44(4): 1−9.
Citation: ZHANG Xiaoqiang, YUN Ze, JIANG Qingmei, et al. Prediction model for cooling time in the heat-affected zone of girth welds in fully automatic welding of X80M pipeline[J]. Oil & Gas Storage and Transportation, 2025, 44(4): 1−9.

X80M管道全自动焊环焊缝热影响区冷却时间预测模型

Prediction model for cooling time in the heat-affected zone of girth welds in fully automatic welding of X80M pipeline

  • 摘要:
    目的 受厚壁管道多层多道焊热输入的影响,环焊缝热影响区组织经历循环的升温与降温过程。为避免生成淬硬组织导致冷裂纹产生,需严格把控接头冷却速率。探究焊接工艺与环焊接头热影响区温度由800 ℃冷却至500 ℃所需时间t8/5之间的关联,对控制焊接热输入、提高接头性能具有决定性作用。
    方法 以管径为1 219 mm、壁厚为22 mm 的X80M管道环焊接头作为研究对象,建立基于全自动焊工艺的有限元模型,并结合单、双焊炬工艺特点编写热源程序,利用实验接头焊层形貌信息确定热源参数。计算焊接温度场数据,并与实验点位热循环数据进行对比验证模型计算准确性;选择各焊层对应热影响区点位进行热循环信息统计分析,并通过改变焊接电流与焊接速度调节焊接热输入,获得t8/5的变化规律,最后拟合得到冷却时间预测公式。
    结果 当热输入较小时,与比减小焊接速度相比,增大焊接电流对t8/5的影响更大;当热输入较大时,与增加焊接电流相比,减小焊接速度对t8/5的影响更大。在相同的热输入变化条件下,两者导致的计算误差不超过6%。
    结论 利用所建立的有限元模型计算焊接热参数,误差较小,模型准确、可用。相较于焊接电流,调整焊接速度将会使峰值温度与t8/5数值分布出现较大波动,为保证焊接稳定性,推荐优先调整焊接电流。根据模拟所得焊接热循环曲线,新提出不包含经验参数的t8/5预测公式,预测精度较传统经验公式提高了10%以上。

     

    Abstract:
    Objective Due to the heat input from multi-layer and multi-pass welding of thick-wall pipelines, the microstructure in the heat-affected zone (HAZ) of girth welds experiences a cyclic heating and cooling process. To prevent cold cracks resulting from a hardened structure, it is essential to strictly control the cooling rate of the joints. Investigating the relationship between the welding procedure and the cooling time (t8/5) required for the HAZ of girth welds to cool from 800 °C to 500 °C plays a decisive role in controlling welding heat input and enhancing joint performance.
    Methods The study focused on the girth welds of a 1 219 mm×22 mm X80M pipeline. A finite element model was developed based on the fully automatic welding procedure, and a heat source program was designed to reflect single- and dual-torch welding characteristics. Heat source parameters were established using experimental data on weld layer morphology. The calculated welding temperature field data were compared with experimental thermal cycle data to validate the model’s accuracy. By analyzing the thermal cycle information of the HAZ for each weld layer and adjusting welding heat input through changes in welding current and speed, the t8/5 variation was determined, leading to the development of a cooling time prediction formula through fitting.
    Results At low heat input, increasing the welding current significantly affected t8/5 more than decreasing the welding speed. Conversely, at high heat input, decreasing the welding speed had a greater impact on t8/5 than increasing the welding current. However, under the same heat input change conditions, the calculation error from either adjustment did not exceed 6%.
    Conclusion The developed finite element model effectively calculates thermal parameters for the welding procedure with minimal error, demonstrating both accuracy and reliability. Adjusting the welding speed results in greater fluctuations in peak temperature and t8/5 distribution compared to adjusting the welding current; therefore, prioritizing adjustments to the welding current is recommended to maintain welding stability. A new t8/5 prediction formula, devoid of empirical parameters, has been proposed based on simulated weld thermal cycle curves, enhancing prediction accuracy by over 10% compared to traditional empirical formulas.

     

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