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uncertainty quantification

mbessa's picture

MS1801 @ WCCM2018 -> Data-driven Methods and Applications: from Physics-informed Learning Machines to Optimization Under Uncertainty

Dear colleagues,

We encourage you to submit your abstracts to minisymposium 1801 of the 13th World Congress on Computational Mechanics (New York City, from July 22 to 27 of 2018). This minisymposium focuses on:

1. recently developed methods for data-driven approaches;

2. data-driven applications to fluids, structures and materials involving (but not limited to) machine learning, uncertainty quantification and/or optimization.

jguilleminot_duke's picture

Postdoctoral and PhD positions in Stochastic Computational Mechanics, Duke University

Several positions at the PhD and postdoctoral levels are available in the group of Prof. Guilleminot at Duke University. The ideal candidates should have a particular interest in conducting interdisciplinary research at the interface of computational mechanics, materials science and uncertainty quantification. Topics of interest include (but are not limited to) stochastic modeling and computational frameworks for large-scale nonlinear materials and systems, statistical inverse problems and multiscale approaches.

PhD position available at the University of Luxembourg - Additive Layer Manufacturing - Multi-scale Uncertainty Quantification

Context

Profs. Thierry J. Massart (Universite Libre de Bruxelles), Ludovic Noels (Universite de Liege) and Stephane P.A.
Bordas (University of Luxembourg) have recently been awarded a joint research project by the FNRS and FNR.
The project focuses on the mechanical behavior of discrete metallic materials, such as metal foams and printed metallic structures

PhD opportunities

Opening for a new Master student in the Computational Mechanics group, Georgia Southern University

The Computational Mechanics group at Georgia Southern University, led by Dr. Xuchun Ren, is looking for a new Research Assistant, who are capable of and interested in performing high-quality research on engineering design. The research, supported by  U.S. National Science Foundation and Startup Funding, entails building a solid mathematical foundation, devising efficient numerical algorithms, and developing practical computational tools for stochastic topology optimization.

Opening for two new Ph.D. students in the Computational Mechanics group, The University of Iowa.

Choose a channel featured in the header of iMechanica: 

The Computational Mechanics group at The University of Iowa, led by Professor S. Rahman, is looking for two new Ph.D. students, who are capable of and interested in performing high-quality research on isogeometric methods and uncertainty quantification. The research, supported by U.S. National Science Foundation, requires building a solid mathematical foundation, devising efficient numerical algorithms, and developing practical computational tools, all associated with stochastic isogeometric analysis of complex materials and structures. A substantial background in solid mechanics with coding experience in finite-element or similar methods is a must; exposures to uncertainty quantification and probabilistic methods are highly desirable.

Opening for two new Ph.D. students in the Computational Mechanics group, The University of Iowa.

The Computational Mechanics group at The University of Iowa, led by Professor S. Rahman, is looking for two new Ph.D. students, who are capable of and interested in performing high-quality research on isogeometric methods and uncertainty quantification. The research, supported by U.S. National Science Foundation, requires building a solid mathematical foundation, devising efficient numerical algorithms, and developing practical computational tools, all associated with stochastic isogeometric analysis of complex materials and structures. A substantial background in solid mechanics with coding experience in finite-element or similar methods is a must; exposures to uncertainty quantification and probabilistic methods are highly desirable.

LONGQ's picture

fast method for optimal experimental design

Shannon-type expected information gain can be used to evaluate the
relevance of a proposed experiment subjected to uncertainty. The
estimation of such gain, however, relies on a double-loop integration.
Moreover, its numerical integration in multi-dimensional cases, e.g.,
when using Monte Carlo sampling methods, is therefore computationally
too expensive for realistic physical models, especially for those
involving the solution of partial differential equations. In this work,
we present a new methodology, based on the Laplace approximation for the
integration of the posterior probability density function (pdf), to
accelerate the estimation of the expected information gains in the model
parameters and predictive quantities of interest. We obtain a

Postdoctoral Fellowship at Northwestern University in Stochastic Multiscale Analysis and Design

We are seeking applicants for a Postdoctoral Fellowship in “stochastic multiscale analysis and design” in the Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA. Applicants are expected to have expertise in the following areas: solid mechanics, uncertainty quantification, finite element modeling, and engineering optimization. The candidate is expected to have a strong background in statistical analysis. Prior experience with material microstructure characterization via image processing, and model uncertainty quantification is preferred.

Uncertainty quantification in mechanics

Modern composite structures have a wide spread in their failure stress.  Advanced multiphysics codes can have a wide range of predicted behavior for nominally the same inputs.  How do we certify the design of such structures or the accuracy of such codes?

karelmatous's picture

Uncertainty Quantification (UQ) in Computational Science Workshop

I would like to inform you that the Computational Science and Engineering at the University of Illinois at Urbana-Champaign is organizing a workshop on Uncertainty Quantification (UQ) in Computational Science on June 11-12, 2007. There is no registration fee for this workshop !!!

Please visit: http://www.cse.uiuc.edu/uq/

karelmatous's picture

Uncertainty Quantification (UQ) in Computational Science Workshop

Choose a channel featured in the header of iMechanica: 

I would like to inform you that the Computational Science and Engineering at University of Illinois at Urbana-Champaign is organizing a workshop on Uncertainty Quantification (UQ) in Computational Science on June 11-12, 2007. There is no registration fee for this workshop !!!

 

Please visit: http://www.cse.uiuc.edu/uq/

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