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Residual stress on the run out table accounting for multiphase transitions and transformation induced plasticity

机译:考虑到多相转变和相变引起的可塑性的跳动表上的残余应力

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The development of harder and thinner new steel grades requires computationally efficient numerical simulations of forming processes in order to optimize industrial conditions through parametric studies. Within this general framework, the present contribution deals with one particular process, namely the run out table. Thus, this paper focuses on the evolution of residual stresses of thin strips during cooling on the run out table. Due to the fact that the complete problem is a nonlinear multiphysics process, it is known that simulating such processes with fully coupled numerical procedures leads to high computational costs. Therefore, a simplified numerical strategy has been developed. This procedure consists of three steps: (i) solving the thermal problem coupled with multiphase transitions; (ii) computing thermal expansion, metallurgical deformation and transformation induced plasticity and (iii) solving the associated mechanical problem. Residual stress profiles through the strip thickness are also computed in order to evaluate classic flatness defects such as crossbow and longbow. A post-processing is also included in order to quantify out of plane displacements that would take place if the strip was cut off the production line. The postprocessing consists in computing at finite strain the relaxation of residual stresses when the tension applied by the coiler is released. The proposed numerical strategy has been tested on common industrial conditions. (C) 2018 Elsevier Inc. All rights reserved.
机译:为了开发更硬,更薄的新钢种,需要对成形过程进行高效计算的数值模拟,以便通过参数研究来优化工业条件。在这一总体框架内,本文稿涉及一个特定过程,即用尽表。因此,本文着眼于在跳动台上冷却期间薄带的残余应力的演变。由于完整的问题是非线性多物理场过程,因此,众所周知,使用完全耦合的数值过程模拟此类过程会导致较高的计算成本。因此,已经开发了简化的数值策略。该过程包括三个步骤:(i)解决与多相转变有关的热问题; (ii)计算热膨胀,冶金变形和相变引起的可塑性,以及(iii)解决相关的机械问题。为了评估经典的平整度缺陷(例如弓ow和长弓),还计算了整个带钢厚度的残余应力分布。还包括后处理,以量化如果带钢从生产线上被切断会发生的平面外位移。后处理包括在有限应变下计算当卷取机施加的张力释放时残余应力的松弛。建议的数值策略已在常见的工业条件下进行了测试。 (C)2018 Elsevier Inc.保留所有权利。

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