Robotics & Machine Learning Daily News2024,Issue(Jun.6) :1-2.

Reports from University of Science and Technology Beijing Add New Data to Findin gs in Machine Learning (Synchronously Enhancing the Strength, Toughness, and Str ess Corrosion Resistance of Highend Aluminum Alloys Via Interpretable Machine . ..)

北京科技大学的报告为机器学习(通过可解释机器同步提高高端铝合金的强度、韧性和耐腐蚀性能)的发现增加了新的数据。 ..)

Robotics & Machine Learning Daily News2024,Issue(Jun.6) :1-2.

Reports from University of Science and Technology Beijing Add New Data to Findin gs in Machine Learning (Synchronously Enhancing the Strength, Toughness, and Str ess Corrosion Resistance of Highend Aluminum Alloys Via Interpretable Machine . ..)

北京科技大学的报告为机器学习(通过可解释机器同步提高高端铝合金的强度、韧性和耐腐蚀性能)的发现增加了新的数据。 ..)

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摘要

由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。据《中国人民日报》记者从北京发回的新闻报道称,“强度、韧性和抗应力腐蚀是高端设备制造用铝合金的关键性能,但由于合金成分复杂、时效制度多样、性能关系矛盾,阻碍了三种性能的同步提高。”本研究经费来源于国家自然科学基金(NSFC)。新闻记者引用北京科技大学的一项研究,“在此,我们提出了一种可解释的机器学习设计策略,研究了影响铝合金极限抗拉强度(UTS)、断裂韧性(KIC)、断裂韧性(KIC)的关键内在因素和元素的显式规律。”研究了合金的应力腐蚀敏感性因子(ISSRT):d价电子轨道上电子数大、沸点高、在此基础上,提出了Ti、Cr、Zr三种微合金元素,即Ti、Cr、Zr三种微合金元素。选择了三种性能同步增强的显著复合效应的新型铝合金Al-10.50Zn-2.31Mg-1.56Cu-0.09Ti-0.15Cr-0.10Zr,经RA处理后,合金的UTS、KIC和ISSRT分别为76 0±4 MPa、34.9±0.3 MPa和sdot;m1/2,13.3%±1.7%,显微组织分析表明,该合金经RA处理后几乎没有微米级的二次相。Ti、Cr和Zr的加入,形成了Al18(Cr、Ti)2Mg3和Al3Zr分散体,促进了强度、韧性和抗应力腐蚀性能的同步提高。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Beijing, People’s Re public of China, by NewsRx journalists, research stated, “Strength, toughness, a nd stress corrosion resistance are critical properties of aluminum alloys for hi gh-end equipment manufacturing. Unfortunately, the situation of complex alloy co mposition, diverse aging systems, and conflicting property relationships hinder the synchronous enhancement of three properties.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the University of Sci ence and Technology Beijing, “Here, we proposed an interpretable machine learnin g design strategy for high-end aluminum alloy. The critical intrinsic factors an d explicit laws of elements affecting the ultimate tensile strength (UTS), fract ure toughness (KIC), and stress corrosion sensitivity factor (ISSRT) of alloys w ere excavated: The elements with large number of electrons in d-valence electron orbitals, high boiling point, and low nuclear electron distance help enhance th e UTS; The elements with low density and minimized difference in first ionizatio n energy with aluminum help improve the KIC; The elements with high diffusion ac tivation energy in aluminum and high corrosion potential in seawater help reduce the ISSRT. Based on the above findings, three microalloying elements of Ti, Cr, and Zr, which have the remarkable combined effect of enhancing synchronously th e three properties, were selected, and a new advanced aluminum alloy Al-10.50Zn- 2.31Mg-1.56Cu-0.09Ti-0.15Cr-0.10Zr was designed. The UTS, KIC, and ISSRT were 76 0 +/- 4 MPa, 34.9 +/- 0.3 MPa & sdot;m1/2, and 13.3 % +/- 1.7 %, respectively, after RRA treatment. Microstructure analys is revealed that the new alloy had almost no micron secondary phase after RRA tr eatment, reducing the sites for pitting and cavity formation. The addition of Ti , Cr, and Zr formed dispersoids Al18(Cr, Ti)2Mg3 and Al3Zr, which contributed to the synchronous improvement of strength, toughness, and stress corrosion resist ance.”

Key words

Beijing/People’s Republic of China/Asi a/Alloys/Aluminum/Cyborgs/Emerging Technologies/Light Metals/Machine Learn ing/University of Science and Technology Beijing

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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