자료유형 | 학위논문 |
---|---|
서명/저자사항 | Uncertainty Quantification in CompositeMaterials. |
개인저자 | Tal, David. |
단체저자명 | Columbia University. Civil Engineering and Engineering Mechanics. |
발행사항 | [S.l.]: Columbia University., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 112 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438173064 |
학위논문주기 | Thesis (Ph.D.)--Columbia University, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Jacob Fish. |
요약 | The random nature of the micro-structural attributes in materials in general and composite material systems in particular requires expansion of material modeling in a way that will incorporate their inherent uncertainty and predict its impact on |
요약 | The work presented in this essay takes a few steps towards an improved material modeling approach which encompasses structural randomness in order to produce a more realistic representation of material systems. For this end a computational frame |
요약 | Image processing and analysis in one of the material systems extended the original scope of this work to solving a machine vision and learning problem. Object segmentation for the purpose object and pattern recognition has been a long standing s |
일반주제명 | Computational physics. Statistics. |
언어 | 영어 |
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