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基于小冲孔试验的钢合金极限抗拉强度新预测方法

A New Prediction Method for the Ultimate Tensile Strength of Steel Alloys with Small Punch Test.

作者信息

Calaf Chica Jose, Bravo Díez Pedro Miguel, Preciado Calzada Mónica

机构信息

Department of Civil Engineering, University of Burgos, Avenida Cantabria s/n, 09007 Burgos, Spain.

出版信息

Materials (Basel). 2018 Aug 21;11(9):1491. doi: 10.3390/ma11091491.

DOI:10.3390/ma11091491
PMID:30134585
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6163175/
Abstract

The load⁻deflection curve acquired from the Small Punch Test (SPT) is used to obtain the mechanical properties of materials using different correlation methods. The scattering level of these regressions tends to be high when a wide set of materials is analyzed. In this study, a correlation method based on a specific slope of the SPT curve was proposed to reduce scattering. Assuming the Ramberg⁻Osgood hardening law, the dependence of the SPT curve slope on the yield strength and the hardening coefficient is demonstrated by numerical simulations (FEM). Considering that the ultimate tensile strength could be obtained from the hardening coefficient, a response surface of the ultimate tensile strength with the yield strength and SPT curve slope, along with its equation, is presented for steel alloys. A summary of steel mechanical properties, based on the Boiler and Pressure Vessel Code (BPVC) and limited to yield strengths lower than 1300 MPa, is shown to select a set of experimental tests (tensile tests and SPTs) for which the range is completely covered. This experimental analysis validates the previous FEM analyses and the validity of the proposed correlation method, which shows more accurate correlations compared to the current methods.

摘要

从小冲孔试验(SPT)获得的载荷-挠度曲线用于通过不同的关联方法获取材料的力学性能。当分析多种材料时,这些回归的离散程度往往较高。在本研究中,提出了一种基于SPT曲线特定斜率的关联方法以减少离散性。假设采用兰伯格-奥斯古德硬化定律,通过数值模拟(有限元法)证明了SPT曲线斜率与屈服强度和硬化系数的相关性。考虑到极限抗拉强度可由硬化系数得出,给出了合金钢极限抗拉强度与屈服强度和SPT曲线斜率的响应面及其方程。基于《锅炉和压力容器规范》(BPVC)并限于屈服强度低于1300MPa,展示了钢力学性能的总结,以选择一组完全覆盖该范围的实验测试(拉伸试验和SPT试验)。该实验分析验证了先前的有限元分析以及所提出关联方法的有效性,与当前方法相比,该方法显示出更准确的相关性。

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