Data-driven polynomial chaos expansions for characterization of complex fluid rheology: Case study of phosphate slurry

Data-driven sensitivity indices for models with dependent inputs using polynomial chaos expansions

Structural Safety ◽

10.1016/j.strusafe.2020.101984 ◽

2021 ◽

Vol 88 ◽

pp. 101984

Author(s):

Zhanlin Liu ◽

Youngjun Choe

Keyword(s):

Polynomial Chaos ◽

Data Driven ◽

Sensitivity Indices ◽

Polynomial Chaos Expansions

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Data-driven polynomial chaos expansions: A weighted least-square approximation

Journal of Computational Physics ◽

10.1016/j.jcp.2018.12.020 ◽

2019 ◽

Vol 381 ◽

pp. 129-145 ◽

Cited By ~ 3

Author(s):

Ling Guo ◽

Yongle Liu ◽

Tao Zhou

Keyword(s):

Polynomial Chaos ◽

Least Square ◽

Data Driven ◽

Weighted Least Square ◽

Polynomial Chaos Expansions

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Sparse Approximation of Data-Driven Polynomial Chaos Expansions: An Induced Sampling Approach

Communications in Mathematical Research ◽

10.4208/cmr.2020-0010 ◽

2020 ◽

Vol 36 (2) ◽

pp. 128-153 ◽

Cited By ~ 1

Author(s):

Ling Guo

Keyword(s):

Polynomial Chaos ◽

Sparse Approximation ◽

Data Driven ◽

Polynomial Chaos Expansions ◽

Sampling Approach

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Surrogate modeling of high-dimensional problems via data-driven polynomial chaos expansions and sparse partial least square

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2020.112906 ◽

2020 ◽

Vol 364 ◽

pp. 112906

Author(s):

Yicheng Zhou ◽

Zhenzhou Lu ◽

Jinghan Hu ◽

Yingshi Hu

Keyword(s):

Polynomial Chaos ◽

Surrogate Modeling ◽

Partial Least Square ◽

Least Square ◽

Data Driven ◽

High Dimensional ◽

Polynomial Chaos Expansions

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Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions: methodology and application to history matching for carbon dioxide storage in geological formations

Computational Geosciences ◽

10.1007/s10596-013-9350-6 ◽

2013 ◽

Vol 17 (4) ◽

pp. 671-687 ◽

Cited By ~ 24

Author(s):

Sergey Oladyshkin ◽

Holger Class ◽

Wolfgang Nowak

Keyword(s):

Carbon Dioxide ◽

History Matching ◽

Polynomial Chaos ◽

Bayesian Updating ◽

Data Driven ◽

Carbon Dioxide Storage ◽

Polynomial Chaos Expansions ◽

Geological Formations

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Construction of plastic contact deformation maps on ceramics: a case study on aluminum nitride

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100165641 ◽

1996 ◽

Vol 54 ◽

pp. 636-637

Author(s):

D. L. Callahan

Keyword(s):

Plastic Deformation ◽

Aluminum Nitride ◽

Mechanical Response ◽

Three Dimensional ◽

Bright Field Image ◽

Perfectly Plastic ◽

Contrast Analysis ◽

Deformation Patterns

Modern polishing, precision machining and microindentation techniques allow the processing and mechanical characterization of ceramics at nanometric scales and within entirely plastic deformation regimes. The mechanical response of most ceramics to such highly constrained contact is not predictable from macroscopic properties and the microstructural deformation patterns have proven difficult to characterize by the application of any individual technique. In this study, TEM techniques of contrast analysis and CBED are combined with stereographic analysis to construct a three-dimensional microstructure deformation map of the surface of a perfectly plastic microindentation on macroscopically brittle aluminum nitride.The bright field image in Figure 1 shows a lg Vickers microindentation contained within a single AlN grain far from any boundaries. High densities of dislocations are evident, particularly near facet edges but are not individually resolvable. The prominent bend contours also indicate the severity of plastic deformation. Figure 2 is a selected area diffraction pattern covering the entire indentation area.

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