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reduced order modeling

miquel.aguirre's picture

1 PhD position in Real time Solid Mechanics & 3D Printing - Marie Curie ITN project Meditate - ESR03

1 Early Stage Researcher (ESR) PhD position in biomechanics offered within the framework of the project MeDiTATe (The medical digital twin for aneurysm prevention and treatment) funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions (MSCA) Innovative Training Networks (ITN) with Grant Agreement No. 859836. MeDiTATe is a European Industrial Doctorate (EID).

Haoran Wang's picture

Modeling Uncertainties in Molecular Dynamics Simulations Using A Stochastic Reduced-Order Basis

We've recently published our new study about Uncertainty Quantification in Molecular Dynamics (MD) Simulations. Due to the selection of functional forms of interatomic potentials or the numerical approximation, MD simulations may predict different material behavior from experiments or other high-fidelity results. In this study, we used Stochastic Reduced Order Modeling (SROM) to achieve

(1) mechanical behavior of graphene predicted by MD simulations in good agreement with the continuum model which has been calibrated by experiments;

mbessa's picture

[June 5 | USNC/TAM2018] Short-course on data-driven modeling in mechanics and materials science

Dear colleagues in academia and industry,

We are organizing the first short course on data-driven computational mechanics and materials science at the 18th US National Congress on Theoretical and Applied Mechanics (USNC/TAM) in Chicago on June 5th, 2018. See description of short-course SC007 in the following website:

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.

karelmatous's picture

A nonlinear manifold-based reduced order model

A new perspective on model reduction for nonlinear multi-scale analysis of heterogeneous materials. In this work, we seek meaningful low-dimensional structures hidden in high-dimensional multi-scale data.

breit's picture

WCCM 2012: Minisymposium on Multidisciplinary Design Optimization in Computational Mechanics

Call for Abstracts (Deadline: November 30, 2011)

As a part of WCCM 2012 (10th World Congress on Computational Mechanics)

Submit Your Abstract (Choose mini-symposium MS-073)

Organizers: Piotr Breitkopf, Weihong Zhang, Rajan Filomeno Coelho 

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