Fatigue Database of Additively Manufactured Alloys

Fatigue is a process of mechanical degradation that is usually assessed based on empirical rules and experimental data obtained from standardized tests. Fatigue data of engineering materials are commonly reported in <em>S</em>-<em>N</em> (the stress-life relation), <em>e</em>-<em>N</em> (the strain-life relation), and d<em>a</em>/d<em>N</em>- <em>ΔK</em> (the relation between the fatigue crack growth rate and the stress intensity factor range) data. Fatigue and static mechanical properties of additively manufactured (AM) alloys, as well as the types of materials, parameters of AM, processing, and tests are collected from thousands of scientific articles till the end of 2022 using natural language processing, machine learning, and computer vision techniques. The results show that the performance of AM alloys could reach that of conventional alloys although data dispersion and system deviation are present. The database (FatigueData-AM2022) are formatted in compact structures, hosted in an open repository, and analyzed to show their patterns and statistics. The quality of data collected from the literature is measured by defining rating scores for datasets reported in individual studies and through the fill rates of data entries across all the datasets. The database also serves as a high-quality training set for data processing using machine learning models. Data extraction and analysis procedures are outlined and the tools are publicly released. A unified language of fatigue data is suggested to regulate data reporting for the fatigue performance of materials to facilitate data sharing and the development of open science.

疲劳是一类力学退化过程，通常依托经验法则与标准化试验获取的实验数据开展评估。工程材料的疲劳数据通常以S-N（应力-寿命关系）、e-N（应变-寿命关系）以及da/dN-ΔK（疲劳裂纹扩展速率与应力强度因子幅之间的关系）三类形式进行报道。本数据集通过自然语言处理、机器学习与计算机视觉技术，从截至2022年底的数千篇学术文献中采集了增材制造（AM）合金的疲劳与静态力学性能数据，同时涵盖材料品类、增材制造工艺参数、加工流程及试验相关信息。研究结果显示，尽管存在数据离散性与系统偏差，增材制造合金的性能可媲美传统合金。该数据库（FatigueData-AM2022）采用紧凑结构进行格式化存储，托管于开源仓库中，并通过分析揭示了数据的分布规律与统计特征。通过为单篇文献报道的数据集定义评分等级，并统计全量数据集的数据条目填充率，完成了对采集数据的质量评估。该数据库同时可作为机器学习模型开展数据处理的高质量训练集。本文概述了数据提取与分析流程，并公开了配套工具。为规范材料疲劳性能的数据报道以促进数据共享与开放科学发展，本文提出统一疲劳数据的表述规范。