Preliminary results for a data-driven uncertainty quantification framework in wire + arc additive manufacturing using bead-on-plate studies-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Preliminary results for a data-driven uncertainty quantification framework in wire + arc additive manufacturing using bead-on-plate studies

Published:2023-02-16 Issue:11-12 Volume:125 Page:5519-5540
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Lee Junhee,Jadhav Sainand,Kim Duck Bong,Ko Kwanghee

Funder

Institute of Information and Communication Technology Planning & Evaluation

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-023-11015-x.pdf

Reference93 articles.

1. Tennøe S, Halnes G, Einevoll GT (2018) Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis in computational neuroscience. Front Neuroinformatics 12:49. https://doi.org/10.3389/fninf.2018.00049

2. Shridhar K, Laumann F, Liwicki M (2019) A comprehensive guide to bayesian convolutional neural network with variational inference. arXiv preprint arXiv:1901.02731. https://doi.org/10.48550/arXiv.1901.02731

3. Hu Z, Mahadevan S (2017) Uncertainty quantification and management in additive manufacturing: current status, needs, and opportunities. Int J Adv Manuf Technol 93(5):2855–2874. https://doi.org/10.1007/s00170-017-0703-5

4. Hamdia KM, Msekh MA, Silani M, Vu-Bac N, Zhuang X, Nguyen-Thoi T, Rabczuk T (2015) Uncertainty quantification of the fracture properties of polymeric nanocomposites based on phase field modeling. Compos Struct 133:1177–1190. https://doi.org/10.1016/j.compstruct.2015.08.051

5. Nath P, Hu Z, Mahadevan S (2018) Modeling and uncertainty quantification of material properties in additive manufacturing. In: Proceedings of 2018 AIAA Non-Deterministic Approaches Conference. p 0923. https://doi.org/10.2514/6.2018-0923

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3