Mona Dannert

Mona Dannert
Leibniz Universität Hannover · Institute of Mechanics and Computational Mechanics

Master of Science

About

14
Publications
3,715
Reads
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99
Citations
Citations since 2016
13 Research Items
99 Citations
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
Introduction
Within my PhD topic I am dealing with imprecise random fields containing aleatory and epistemic uncertainties. Inclusion of such fields - e.g. as material parameters - in terms of stochastic finite element method (SFEM) leads to high computational costs. For this reason, sophisticated sampling methods are key elements of my research. Additionally, the propagation of such fields through an SFEM simulation to estimate the quantities of interest as a probability box is investigated.
Additional affiliations
March 2017 - March 2020
SPP 1886
Position
  • Researcher
Description
  • Research activity within the priority program SPP 1886 of the German Research Foundation (DFG)
October 2016 - present
Leibniz Universität Hannover
Position
  • Research Assistant
Description
  • PhD student, teaching assistant (Engineering Mechanics A & B, Mechanics of Elastic Bodies, Numerical Mechanics, Mechanics of Solids)
April 2015 - October 2015
Peter the Great St.Petersburg Polytechnic University
Position
  • Master's Student
Description
  • Research semester within the Master studies
Education
April 2015 - October 2015
April 2014 - September 2016
Leibniz Universität Hannover
Field of study
  • Computational Engineering
October 2010 - April 2014
Leibniz Universität Hannover
Field of study
  • Civil and Environmental Engineering

Publications

Publications (14)
Article
This work presents an hp-adaptive variant of multi-element polynomial chaos expansion (ME-gPCE), referred to as anisotropic multi-element polynomial chaos expansion (AME-gPCE). The main advantage of the proposed framework is that the basis functions of the local gPCE are selected adaptively within each local element. The p-adaptivity allows the ord...
Article
This work presents an hp-adaptive variant of multi-element polynomial chaos expansion (ME-gPCE), referred to as anisotropic multi-element polynomial chaos expansion (AME-gPCE). The main advantage of the proposed framework is that the basis functions of the local gPCE are selected adaptively within each local element. The p-adaptivity allows the ord...
Article
Full-text available
Sophisticated sampling techniques used for solving stochastic partial differential equations efficiently and robustly are still in a state of development. It is known in the scientific community that global stochastic collocation methods using isotropic sparse grids are very efficient for simple problems but can become computationally expensive or...
Article
This work presents a numerical Galerkin scheme based on discontinuous Legendre polynomials (DLPG) to solve the integral eigenvalues problem known as Fredholm integral equation of a second kind which is mainly used for random fields representation by means of Karhunen-Loève expansion. The main advantages of the proposed method are the simple applica...
Conference Paper
In order to describe spatially uncertain parameters by random fields, the underlying autocorrelation structure in engineering structures is usually not known. The idea of imprecise random fields is to acknowledge this lack of knowledge by adding epistemic uncertainties. Within this contribution the influence of the correlation length is studied. I...
Article
Full-text available
Imprecise random fields consider both, aleatory and epistemic uncertainties. In this paper, spatially varying material parameters representing the constitutive parameters of a damage model for concrete are defined as imprecise random fields by assuming an interval valued correlation length. For each correlation length value, the corresponding rando...
Conference Paper
Considering an uncertain correlation length of the input random fields described by a Karhunen-Loève expansion leads to a probability-box approach for the stochastic finite element computation. But, these computations are highly costly. Then, a stochastic collocation method using sparse grids within a Smolyak algorithm is proposed to reduce the com...
Article
In structural analysis with multivariate random fields, the underlying distribution functions, the autocorrelations, and the crosscorrelations require an extensive quantification. While those parameters are difficult to measure in experiments, a lack of knowledge is included. Therefore, polymorphic uncertainty models are attained by involving uncer...
Conference Paper
In order to regard mixed aleatory and epistemically uncertain random fields within stochastic finite element method, a probability box approach using stochastic collocation method is introduced. The influence of an interval‐valued correlation length on the output is investigated.
Article
The buckling load of cylindrical shells is heavily dependent on geometric imperfections and other non-traditional imperfections such as scattering wall thicknesses or loading imperfections. In this paper, the probabilistic perturbation load approach (PPLA) is proposed. This procedure is independent from costly measurements of geometric imperfection...
Article
Full-text available
Dynamic buckling of an elastic column under compression at constant speed is investigated assuming the first buckling mode. Two cases are considered: (i) an imperfect naturally curved column~(Hoff's statement), and (ii) a perfect column with an initial lateral deflection. The range of parameters where the maximum load supported by a column exceeds...
Article
Dynamic buckling of an elastic column under compression at constant speed is investigated assuming the first-mode buckling. Two cases are considered: (i) an imperfect column (Hoff's statement), and (ii) a perfect column having an initial lateral deflection. The range of parameters, where the maximum load supported by a column exceeds Euler static f...

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Projects

Projects (2)
Project
PhD thesis aiming to quantify and propagate mixed (i.e. aleatory and epistemic) uncertainties in terms of imprecise random fields. The main challenge is an adequate modelling of the uncertain input parameters as well as an efficient model propagation, especially when high stochastic dimensions and/or non-linear models are involved.
Project
This project (NA 330/12-1) is a part of the Priority Programme SPP 1886, funded by the German Research Foundation (DFG). Aim of this project is to investigate efficient approaches to consider mixed (aleatory and epistemic) uncertain random fields within a non-linear finite element analysis. The approaches are tested and discussed with regard to their applicability in damage mechanics.