{"title":"模拟双相钢中单相应力-应变曲线的独特迭代数值方法","authors":"S. T. Tanu Halim, Eugene - Ng","doi":"10.1088/1361-651x/ad200b","DOIUrl":null,"url":null,"abstract":"\n Understanding the effects of martensite volume fractions (Vm) in dual-phase (DP) steel resulting from heat treatment is crucial for designing structures for mechanical impact resistance and optimizing manufacturing processes. DP steel's material behaviour depends heavily on its microstructure properties. While stress-strain curves for individual phases in DP steels are often determined using empirical models, extensive experimental data is required to establish empirical model constants. This research aims to achieve two main objectives: Firstly, to calibrate stress-strain curves for pure ferrite and pure martensite using limited experimental data using Micromechanical Adaptive Iteration Algorithm (MAIA). This calibration involves using stress-strain data from DP steels with varying Vm during the calibration stage and additional data for verification. Secondly, to conduct a comprehensive sensitivity analysis of MAIA to assess its capabilities and limitations. Microstructure-based finite element (FE) models, simulated with ABAQUS/Standard, are employed to predict stress-strain curves under uniaxial tensile test conditions. The MAIA approach successfully calculated ferrite and martensite stress-strain curves that could predict plastic behaviour of DP steel with different Vm, which agreed with experimental work. Key advantages of this approach include avoiding complex 3D microstructure geometries and requiring only two experimentally obtained stress-strain curves with different Vm for material constant calibration, along with another curve for validation. However, the experimental data selected for calibration must have a Vm difference between 20% to 50% and one of the DP steels must have a low martensite volume fraction. The FE micromechanical model could capture the effect of softening of martensite phase and strengthening of ferrite phase as compared to its bulk properties for DP steel. The effect of Vm on strain hardening rate was also successfully captured. This technique comes with obvious shortcomings, such as excluding crystal plasticity behaviour, and change in chemical composition within the individual phase with varying martensite volume fraction.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"125 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Unique Numerical Iterative Approach for Modelling Individual Phase Stress-Strain Curves in Dual Phase Steel\",\"authors\":\"S. T. Tanu Halim, Eugene - Ng\",\"doi\":\"10.1088/1361-651x/ad200b\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Understanding the effects of martensite volume fractions (Vm) in dual-phase (DP) steel resulting from heat treatment is crucial for designing structures for mechanical impact resistance and optimizing manufacturing processes. DP steel's material behaviour depends heavily on its microstructure properties. While stress-strain curves for individual phases in DP steels are often determined using empirical models, extensive experimental data is required to establish empirical model constants. This research aims to achieve two main objectives: Firstly, to calibrate stress-strain curves for pure ferrite and pure martensite using limited experimental data using Micromechanical Adaptive Iteration Algorithm (MAIA). This calibration involves using stress-strain data from DP steels with varying Vm during the calibration stage and additional data for verification. Secondly, to conduct a comprehensive sensitivity analysis of MAIA to assess its capabilities and limitations. Microstructure-based finite element (FE) models, simulated with ABAQUS/Standard, are employed to predict stress-strain curves under uniaxial tensile test conditions. The MAIA approach successfully calculated ferrite and martensite stress-strain curves that could predict plastic behaviour of DP steel with different Vm, which agreed with experimental work. Key advantages of this approach include avoiding complex 3D microstructure geometries and requiring only two experimentally obtained stress-strain curves with different Vm for material constant calibration, along with another curve for validation. However, the experimental data selected for calibration must have a Vm difference between 20% to 50% and one of the DP steels must have a low martensite volume fraction. The FE micromechanical model could capture the effect of softening of martensite phase and strengthening of ferrite phase as compared to its bulk properties for DP steel. The effect of Vm on strain hardening rate was also successfully captured. This technique comes with obvious shortcomings, such as excluding crystal plasticity behaviour, and change in chemical composition within the individual phase with varying martensite volume fraction.\",\"PeriodicalId\":503047,\"journal\":{\"name\":\"Modelling and Simulation in Materials Science and Engineering\",\"volume\":\"125 10\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Modelling and Simulation in Materials Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-651x/ad200b\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modelling and Simulation in Materials Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1361-651x/ad200b","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
了解热处理后双相钢(DP)中马氏体体积分数(Vm)的影响,对于设计抗机械冲击结构和优化制造工艺至关重要。DP 钢的材料性能在很大程度上取决于其微观结构特性。虽然 DP 钢中各相的应力-应变曲线通常使用经验模型确定,但需要大量实验数据来建立经验模型常数。本研究旨在实现两个主要目标:首先,使用微机械自适应迭代算法(MAIA),利用有限的实验数据校准纯铁素体和纯马氏体的应力-应变曲线。校准过程包括在校准阶段使用不同 Vm 的 DP 钢的应力应变数据,以及用于验证的其他数据。其次,对 MAIA 进行全面的敏感性分析,以评估其能力和局限性。使用 ABAQUS/Standard 模拟基于微结构的有限元 (FE) 模型,预测单轴拉伸试验条件下的应力-应变曲线。MAIA 方法成功计算了铁素体和马氏体应力-应变曲线,可以预测不同 Vm 的 DP 钢的塑性行为,这与实验结果一致。这种方法的主要优点包括:避免了复杂的三维微观结构几何形状,只需要两条实验获得的不同 Vm 的应力-应变曲线进行材料常数校准,以及另一条曲线进行验证。不过,选定用于校准的实验数据的 Vm 值必须相差 20% 至 50%,其中一种 DP 钢的马氏体体积分数必须较低。与 DP 钢的整体性能相比,有限元微观力学模型可以捕捉到马氏体相软化和铁素体相强化的影响。此外,还成功捕捉到了 Vm 对应变硬化率的影响。这种技术存在明显的缺陷,例如不包括晶体塑性行为,以及随着马氏体体积分数的变化,各相内部化学成分的变化。
A Unique Numerical Iterative Approach for Modelling Individual Phase Stress-Strain Curves in Dual Phase Steel
Understanding the effects of martensite volume fractions (Vm) in dual-phase (DP) steel resulting from heat treatment is crucial for designing structures for mechanical impact resistance and optimizing manufacturing processes. DP steel's material behaviour depends heavily on its microstructure properties. While stress-strain curves for individual phases in DP steels are often determined using empirical models, extensive experimental data is required to establish empirical model constants. This research aims to achieve two main objectives: Firstly, to calibrate stress-strain curves for pure ferrite and pure martensite using limited experimental data using Micromechanical Adaptive Iteration Algorithm (MAIA). This calibration involves using stress-strain data from DP steels with varying Vm during the calibration stage and additional data for verification. Secondly, to conduct a comprehensive sensitivity analysis of MAIA to assess its capabilities and limitations. Microstructure-based finite element (FE) models, simulated with ABAQUS/Standard, are employed to predict stress-strain curves under uniaxial tensile test conditions. The MAIA approach successfully calculated ferrite and martensite stress-strain curves that could predict plastic behaviour of DP steel with different Vm, which agreed with experimental work. Key advantages of this approach include avoiding complex 3D microstructure geometries and requiring only two experimentally obtained stress-strain curves with different Vm for material constant calibration, along with another curve for validation. However, the experimental data selected for calibration must have a Vm difference between 20% to 50% and one of the DP steels must have a low martensite volume fraction. The FE micromechanical model could capture the effect of softening of martensite phase and strengthening of ferrite phase as compared to its bulk properties for DP steel. The effect of Vm on strain hardening rate was also successfully captured. This technique comes with obvious shortcomings, such as excluding crystal plasticity behaviour, and change in chemical composition within the individual phase with varying martensite volume fraction.