Bayesian inference-based decision of fatigue life model for metal additive manufacturing considering effects of build orientation and post-processing

被引：16

作者：

Doh, Jaehyeok ^{[1
,2
]}

Raju, Nandhini ^{[3
,4
]}

Raghavan, Nagarajan ^{[2
,4
]}

Rosen, David W. ^{[4
,5
]}

Kim, Samyeon ^{[4
,6
]}

机构：

[1] Gyeongsang Natl Univ, Sch Mech Engn, Jinju Si 52725, Gyeongsangnam D, South Korea

[2] Singapore Univ Technol & Design SUTD, Engn Prod Dev EPD Pillar, 8 Somapah Rd, Singapore 487372, Singapore

[3] Univ Cent Florida, Dept Mech & Aerosp Engn, Orlando, FL 32816 USA

[4] Singapore Univ Technol & Design, Digital Mfg & Design Ctr, 8 Somapah Rd, Singapore 487372, Singapore

[5] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA

[6] Jeonju Univ, Dept Mech Syst Engn, Jeonju Si 55069, Jeollabuk Do, South Korea

来源：

INTERNATIONAL JOURNAL OF FATIGUE | 2022年 / 155卷

基金：

新加坡国家研究基金会;

关键词：

Bayesian inference; Metal additive manufacturing; Fatigue life model; Uncertainty quantification; Weighted-Equivalent Metric (WEM); MARAGING-STEEL; 300; MECHANICAL-PROPERTIES; BEHAVIOR; PERFORMANCE; EVOLUTION; STRENGTH; FRACTURE;

D O I：

10.1016/j.ijfatigue.2021.106535

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This study proposes a Bayesian inference-based decision framework to quantify the physical uncertainty based on fatigue life tests on maraging steel according to post-processing treatments and build orientations. Uncertainty quantification of fatigue life models is performed to determine the most suitable models for the metal additive manufacturing process by employing Bayesian inference. To select one of the fatigue life models, we introduce a weighted-equivalent metric (WEM) to compare the evaluation results from different statistical metrics. By evaluating the WEM value, the logistic model and Zhurkov fatigue life model are identified as the suitable fatigue life models for maraging steel.

引用

页数：18