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High-performance modeling of concrete ageing Habera, Michal ; Zilian, Andreas in Proceedings in Applied Mathematics and Mechanics (in press) Long-term behaviour of concrete structural elements is very important for evaluation of its health and serviceability range. The phenomena that must be considered are complex and lead to coupled ... [more ▼] Long-term behaviour of concrete structural elements is very important for evaluation of its health and serviceability range. The phenomena that must be considered are complex and lead to coupled multiphysics formulations. Such formulations are difficult not only from physical perspective, but also from computational perspective. In this contribution attention to computational efficiency and effective implementation is payed. Presented model for concrete ageing is based on microprestress-solidification (MPS) theory of Bazant [1], Kunzel’s model for heat and moisture transport [2] and Mazars model for damage [3]. Ageing linear viscoelastic response, which is immanent to MPS theory and concrete creep, leads to ordinary differetial equation for internal variables solved for every quadrature/nodal point. Numerical structure of the finite element discretisation is examined. Few simplifications on physical model lead to a very efficient linear algebra problem for which standard preconditioned Krylov solvers are reviewed. In parallel, weak and strong scaling tests are performed. All results are produced within open-source finite element framework FEniCS [4]. These models are usually a basis for more involved thermo-hygro-chemo-mechanical (THCM) models with migrating chemical species. It is anticipated, that presented results will help practitioners or other structural engineerers with the choice of suitable and efficient methods for long-term concrete modeling. [less ▲] Detailed reference viewed: 178 (22 UL)Frictional interactions for non-localised beam-to-beam and beam-inside-beam contact ; Lengiewicz, Jakub ; Zilian, Andreas et al in International Journal for Numerical Methods in Engineering (in press) This contribution presents the extensions of beam-to-beam and beam-inside-beam contact schemes of the same authors towards frictional interactions. Since the schemes are based on the beams’ true surfaces ... [more ▼] This contribution presents the extensions of beam-to-beam and beam-inside-beam contact schemes of the same authors towards frictional interactions. Since the schemes are based on the beams’ true surfaces (instead of surfaces implicitly deduced from the beams’ centroid lines), the presented enhancements are not only able to account for frictional sliding in the beams’ axial directions, but also in the circumferential directions. Both the frictional beam-to-beam approach as well as the frictional beam-inside-beam approach are applicable to shear-deformable and shear-undeformable beams, as well as to beams with both circular and elliptical cross-sections (although the cross-sections must be rigid). A penalty formulation is used to treat unilateral and frictional contact constraints. FE implementation details are discussed, where automatic differentiation techniques are used to derive the implementations. Simulations involving large sliding displacements and large deformations are presented for both beam-to-beam and beam-inside-beam schemes. All simulation results are compared to those of the frictionless schemes. [less ▲] Detailed reference viewed: 42 (1 UL)A hybrid MGA-MSGD ANN training approach for approximate solution of linear elliptic PDEs Dehghani, Hamidreza ; Zilian, Andreas E-print/Working paper (2020) We introduce a hybrid "Modified Genetic Algorithm-Multilevel Stochastic Gradient Descent" (MGA-MSGD) training algorithm that considerably improves accuracy and efficiency of solving 3D mechanical problems ... [more ▼] We introduce a hybrid "Modified Genetic Algorithm-Multilevel Stochastic Gradient Descent" (MGA-MSGD) training algorithm that considerably improves accuracy and efficiency of solving 3D mechanical problems described, in strong-form, by PDEs via ANNs (Artificial Neural Networks). This presented approach allows the selection of a number of locations of interest at which the state variables are expected to fulfil the governing equations associated with a physical problem. Unlike classical PDE approximation methods such as finite differences or the finite element method, there is no need to establish and reconstruct the physical field quantity throughout the computational domain in order to predict the mechanical response at specific locations of interest. The basic idea of MGA-MSGD is the manipulation of the learnable parameters’ components responsible for the error explosion so that we can train the network with relatively larger learning rates which avoids trapping in local minima. The proposed training approach is less sensitive to the learning rate value, training points density and distribution, and the random initial parameters. The distance function to minimise is where we introduce the PDEs including any physical laws and conditions (so-called, Physics Informed ANN). The Genetic algorithm is modified to be suitable for this type of ANN in which a Coarse-level Stochastic Gradient Descent (CSGD) is exploited to make the decision of the offspring qualification. Employing the presented approach, a considerable improvement in both accuracy and efficiency, compared with standard training algorithms such classical SGD and Adam optimiser, is observed. The local displacement accuracy is studied and ensured by introducing the results of Finite Element Method (FEM) at sufficiently fine mesh as the reference displacements. A slightly more complex problem is solved ensuring the feasibility of the methodology [less ▲] Detailed reference viewed: 60 (0 UL)Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation Kozlowski, Diego ; Dusdal, Jennifer ; Pang, Jun et al E-print/Working paper (2020) Over the last century, we observe a steady and exponentially growth of scientific publications globally. The overwhelming amount of available literature makes a holistic analysis of the research within a ... [more ▼] Over the last century, we observe a steady and exponentially growth of scientific publications globally. The overwhelming amount of available literature makes a holistic analysis of the research within a field and between fields based on manual inspection impossible. Automatic techniques to support the process of literature review are required to find the epistemic and social patterns that are embedded in scientific publications. In computer sciences, new tools have been developed to deal with large volumes of data. In particular, deep learning techniques open the possibility of automated end-to-end models to project observations to a new, low-dimensional space where the most relevant information of each observation is highlighted. Using deep learning to build new representations of scientific publications is a growing but still emerging field of research. The aim of this paper is to discuss the potential and limits of deep learning for gathering insights about scientific research articles. We focus on document-level embeddings based on the semantic and relational aspects of articles, using Natural Language Processing (NLP) and Graph Neural Networks (GNNs). We explore the different outcomes generated by those techniques. Our results show that using NLP we can encode a semantic space of articles, while with GNN we are able to build a relational space where the social practices of a research community are also encoded. [less ▲] Detailed reference viewed: 28 (8 UL)Beam-inside-beam contact: Mechanical simulations of slender medical instruments inside the human body Magliulo, Marco ; Lengiewicz, Jakub ; Zilian, Andreas et al in Computer Methods and Programs in Biomedicine (2020), 196 Background and Objective This contribution presents a rapid computational framework to mechanically simulate the insertion of a slender medical instrument in a tubular structure such as an artery, the ... [more ▼] Background and Objective This contribution presents a rapid computational framework to mechanically simulate the insertion of a slender medical instrument in a tubular structure such as an artery, the cochlea or another slender instrument. Methods Beams are employed to rapidly simulate the mechanical behaviour of the medical instrument and the tubular structure. However, the framework’s novelty is its capability to handle the mechanical contact between an inner beam (representing the medical instrument) embedded in a hollow outer beam (representing the tubular structure). This “beam-inside-beam” contact framework, which forces two beams to remain embedded, is the first of its kind since existing contact frameworks for beams are “beam-to-beam” approaches, i.e. they repel beams from each other. Furthermore, we propose contact kinematics such that not only instruments and tubes with circular cross-sections can be considered, but also those with elliptical cross-sections. This provides flexibility for the optimization of patient-specific instruments. Results The results demonstrate that the framework’s robustness is substantial, because only a few increments per simulation and a few iterations per increment are required, even though large deformations, large rotations and large curvature changes of both the instrument and tubular structure occur. The stability of the framework remains high even if the modulus of the inner tube is thousand times larger than that of the outer tube. A mesh convergence study furthermore exposes that a relatively small number of elements is required to accurately approach the reference solution. Conclusions The framework’s high simulation speed originates from the exploitation of the rigidity of the beams’ cross-sections to quantify the exclusion between the inner and the hollow outer beam. This rigidity limits the accuracy of the framework at the same time, but this is unavoidable since simulation accuracy and simulation speed are two competing interests. Hence, the framework is particularly attractive if simulation speed is preferred over accuracy. [less ▲] Detailed reference viewed: 189 (25 UL)Eco-construction for sustainable development (Econ4SD) – Konzepte für Materialbanken Zilian, Andreas ; Waldmann, Daniele ; Hertweck, Florian et al Presentation (2020, October 16) Detailed reference viewed: 19 (2 UL)Eco-construction for sustainable development (Econ4SD) – Konzepte für Materialbanken Zilian, Andreas ; Waldmann, Daniele ; Hertweck, Florian et al in Kaliske, Michael (Ed.) 24. Dresdner Baustatik-Seminar: Reality - Modeling - Structural Design (2020, October) This contribution presents the joint research project Econ4SD – Eco-construction for sustainable development which investigates at the University of Luxembourg various aspects of sustainable design ... [more ▼] This contribution presents the joint research project Econ4SD – Eco-construction for sustainable development which investigates at the University of Luxembourg various aspects of sustainable design, construction and operation to support a resource-efficient circular economy in the construction sector. In this context the fundamental approach of Design for deconstruction assumes a central role and is being discussed together with the complementary concept of Material banks and their digital twinning at the level of components, buildings and markets. [less ▲] Detailed reference viewed: 34 (3 UL)Poroelastic model parameter identification using artificial neural networks: on the effects of heterogeneous porosity and solid matrix Poisson ratio Dehghani, Hamidreza ; Zilian, Andreas in Computational Mechanics (2020), 66 Predictive analysis of poroelastic materials typically require expensive and time-consuming multiscale and multiphysics approaches, which demand either several simplifications or costly experimental tests ... [more ▼] Predictive analysis of poroelastic materials typically require expensive and time-consuming multiscale and multiphysics approaches, which demand either several simplifications or costly experimental tests for model parameter identification. This problem motivates us to develop a more efficient approach to address complex problems with an acceptable computational cost. In particular, we employ artificial neural network (ANN) for reliable and fast computation of poroelastic model parameters. Based on the strong-form governing equations for the poroelastic problem derived from asymptotic homogenisation, the weighted residuals formulation of the cell problem is obtained. Approximate solution of the resulting linear variational boundary value problem is achieved by means of the finite element method. The advantages and downsides of macroscale properties identification via asymptotic homogenisation and the application of ANN to overcome parameter characterisation challenges caused by the costly solution of cell problems are presented. Numerical examples, in this study, include spatially dependent porosity and solid matrix Poisson ratio for a generic model problem, application in tumour modelling, and utilisation in soil mechanics context which demonstrate the feasibility of the presented framework. [less ▲] Detailed reference viewed: 83 (4 UL)Continuous solution of poroelastic problems using Artificial Neural Networks Dehghani, Hamidreza ; Zilian, Andreas Presentation (2020, January 13) Detailed reference viewed: 44 (3 UL)Contact between shear-deformable beams with elliptical cross-sections Magliulo, Marco ; Zilian, Andreas ; Beex, Lars in Acta Mechanica (2020), 231 Slender constituents are present in many structures and materials. In associated mechanical models, each slender constituent is often described with a beam. Contact between beams is essential to ... [more ▼] Slender constituents are present in many structures and materials. In associated mechanical models, each slender constituent is often described with a beam. Contact between beams is essential to incorporate in mechanical models, but associated contact frameworks are only demonstrated to work for beams with circular cross-sections. Only two studies have shown the ability to treat contact between beams with elliptical cross-sections, but those frameworks are limited to point-wise contact, which narrows their applicability. This contribution presents initial results of a framework for shear-deformable beams with elliptical cross-sections if contact occurs along a line or at an area (instead of at a point). This is achieved by integrating a penalty potential over one of the beams’ surfaces. Simo-Reissner Geometrically Exact Beam (GEB) elements are employed to discretise each beam. As the surface of an assembly of such beam elements is discontinuous, a smoothed surface is introduced to formulate the contact kinematics. This enables the treatment of contact for large sliding displacements and substantial deformations. [less ▲] Detailed reference viewed: 114 (6 UL)Isogeometric analysis of thin Reissner-Mindlin shells: locking phenomena and B-bar method ; ; et al in Computational Mechanics (2020), 65(5), 1323-1341 We propose a local type of B-bar formulation, addressing locking in degenerated Reissner–Mindlin shell formulation in the context of isogeometric analysis. Parasitic strain components are projected onto ... [more ▼] We propose a local type of B-bar formulation, addressing locking in degenerated Reissner–Mindlin shell formulation in the context of isogeometric analysis. Parasitic strain components are projected onto the physical space locally, i.e. at the element level, using a least-squares approach. The formulation allows the flexible utilization of basis functions of different orders as the projection bases. The introduced formulation is much cheaper computationally than the classical $$\bar{B}$$B¯ method. We show the numerical consistency of the scheme through numerical examples, moreover they show that the proposed formulation alleviates locking and yields good accuracy even for slenderness ratios of $$10^5$$105, and has the ability to capture deformations of thin shells using relatively coarse meshes. In addition it can be opined that the proposed method is less sensitive to locking with irregular meshes. [less ▲] Detailed reference viewed: 76 (2 UL)Non-localised contact between beams with circular and elliptical cross-sections Magliulo, Marco ; Lengiewicz, Jakub ; Zilian, Andreas et al in Computational Mechanics (2020), 65 The key novelty of this contribution is a dedicated technique to e fficiently determine the distance (gap) function between parallel or almost parallel beams with circular and elliptical cross-sections ... [more ▼] The key novelty of this contribution is a dedicated technique to e fficiently determine the distance (gap) function between parallel or almost parallel beams with circular and elliptical cross-sections. The technique consists of parametrizing the surfaces of the two beams in contact, fixing a point on the centroid line of one of the beams and searching for a constrained minimum distance between the surfaces (two variants are investigated). The resulting unilateral (frictionless) contact condition is then enforced with the Penalty method, which introduces compliance to the, otherwise rigid, beams' cross-sections. Two contact integration schemes are considered: the conventional slave-master approach (which is biased as the contact virtual work is only integrated over the slave surface) and the so-called two-half-pass approach (which is unbiased as the contact virtual work is integrated over the two contacting surfaces). Details of the finite element formulation which is suitably implemented using Automatic Di fferentiation techniques are presented. A set of numerical experiments shows the overall performance of the framework and allows a quantitative comparison of the investigated variants. [less ▲] Detailed reference viewed: 122 (44 UL)Data Centric Engineering and Data-Driven Modelling - Computational Engineering Lab Report 2019 Bordas, Stéphane ; Peters, Bernhard ; Viti, Francesco et al Report (2019) https://www.cambridge.org/core/journals/data-centric-engineering Detailed reference viewed: 66 (6 UL)Toward fluid-structure-piezoelectric simulations applied to flow-induced energy harvesters Hoareau, Christophe ; Shang, Lan ; Zilian, Andreas Poster (2019, November 15) The subject deals with the simulation of flow-induced energy harvesters. We focus in particular on the modelling of autonomous piezo-ceramic power generators to convert ambient fluid-flow energy into ... [more ▼] The subject deals with the simulation of flow-induced energy harvesters. We focus in particular on the modelling of autonomous piezo-ceramic power generators to convert ambient fluid-flow energy into electrical energy. The vibrations of an immersed electromechanical structure with large amplitude have to be taken into account in that case. One challenge consists in modelling and predicting the nonlinear coupled dynamic behaviour for the improved design of such devices. The set of governing equations is expressed in integral form, using the method of weighted residuals, and discretized with finite elements using the open source package FEniCS. Preliminary results of separated problems using FEniCS will be detailed and discussed (e.g. Navier-Stokes with or without moving meshes, nonlinear elasticity, aeroelasticity and electromechanical coupling). The objective is to validate each problem independently before coupling all the phenomena in a monolithic framework. Those simulations involve nonlinearities at many levels of modeling. The perspective of using reduced order models to limit the computational cost (in time and memory) will be discussed in an outlook to this work. [less ▲] Detailed reference viewed: 49 (6 UL)Poroelastic material characterisation by means of Artificial Neural Network Dehghani, Hamidreza ; Zilian, Andreas Presentation (2019, November 13) Poroelastic problems require multiscale and multiphysics techniques that are expensive and time-consuming, which result in either several simplifications or costly experimental tests. The latter motivates ... [more ▼] Poroelastic problems require multiscale and multiphysics techniques that are expensive and time-consuming, which result in either several simplifications or costly experimental tests. The latter motivates us to develop a more efficient approach to address more complex problems with an acceptable computational cost. In this manuscript, first, the necessary equations derived from Asymptotic homogenisation for poroelastic media are mentioned. Then, the variational formulation of the cell problems is carried out and solved by the open-source FE package FEniCS. This is followed by presenting the advantages and downsides of macroscale properties identification via asymptotic homogenisation and the application of Artificial Neural Network (ANN) to solve the issues stated as its downsides by means of bypassing the process of solving the cell problems. Finally, we study a practical example, namely, spatial dependent porosity (in macroscale) to demonstrate the feasibility of using the provided framework to include more details. Further applications, including growth and remodelling, are subjects of future articles. [less ▲] Detailed reference viewed: 66 (6 UL)On predictive modelling of yield stress increase in fresh cement paste Huang, Haiqin ; Zilian, Andreas in Proceedings in Applied Mathematics and Mechanics (2019), 19(1), Detailed reference viewed: 100 (3 UL)Simultaneous finite element analysis of circuit-integrated piezoelectric energy harvesting from fluid-structure interaction ; Zilian, Andreas in Mechanical Systems & Signal Processing (2019), 114 Flow-driven piezoelectric energy harvesting is a strongly coupled multiphysics phenomenon that involves complex three-way interaction between the fluid flow, the electromechanical effect of the ... [more ▼] Flow-driven piezoelectric energy harvesting is a strongly coupled multiphysics phenomenon that involves complex three-way interaction between the fluid flow, the electromechanical effect of the piezoelectric material mounted on a deformable substrate structure and the controlling electrical circuit. High fidelity computational solution approaches are essential for the analysis of flow-driven energy harvesters in order to capture the main physical aspects of the coupled problem and to accurately predict the power output of a harvester. While there are some phenomenological and numerical models for flow-driven harvesters reported in the literature, a fully three-dimensional strongly coupled model has not yet been developed, especially in the context of flow-driven energy harvesting. The weighted residuals method is applied to establish a mixed integral equation describing the incompressible Newtonian flow, elastic substrate structure, piezoelectric patch, equipotential electrode and attached electric circuit that form the multiphysics fluid-structure interaction problem. A monolithic numerical solution method is derived that provides consistent and simultaneous solution to all physical fields as well as to fluid mesh deformation. The approximate solution is based on a mixed space-time finite element discretization with static condensation of the auxiliary fields. The discontinuous Galerkin method is utilized for integrating the monolithic model in time. The proposed solution scheme is illustrated in the example of a lid driven cavity with a flexible piezoelectric bottom wall, demonstrating quantification of the amount of electrical energy extractable from fluid flow by means of a piezoelectric harvester device. The results indicate that in order to make reliable predictions on the power output under varying operational states, the realization of strong multiphysics coupling is required for the mathematical model as well as the numerical solution scheme to capture the characteristics of flow-driven energy harvesters. [less ▲] Detailed reference viewed: 211 (19 UL)Model order reduction applied to ALE‐fluid dynamics Baroli, Davide ; Zilian, Andreas in Proceedings in Applied Mathematics and Mechanics (2019) Detailed reference viewed: 67 (4 UL)Non-localized Contact Between Beams with Non-Circular Cross Sections Magliulo, Marco ; Zilian, Andreas ; Beex, Lars in Proceedings in Applied Mathematics and Mechanics (2019) In this contribution, we introduce a contact formulation between beams finite elements with (hyper)elliptical cross sections. The contact scheme allows to model scenarios in which the contact area is ... [more ▼] In this contribution, we introduce a contact formulation between beams finite elements with (hyper)elliptical cross sections. The contact scheme allows to model scenarios in which the contact area is finite or the contact area occurs along a line. Although some contact schemes are yet able to do this, they require one of the beams to have a circular cross section. Here however, we focus on non-circular cross-sections. Consequently, new projections are required, in which the beam surfaces are used explicitly to formulate contact kinematics. [less ▲] Detailed reference viewed: 117 (13 UL)Phase-field predictive model for setting of fresh self-compacting concrete Huang, Haiqin ; Zilian, Andreas in Proceedings in Applied Mathematics and Mechanics (2018), 18(1), The initial setting of fresh concrete is mainly caused by the dissolution of cement grains and the precipitation of calcium-silicate-hydrates during cement hydration. Progressing hydration drives the ... [more ▼] The initial setting of fresh concrete is mainly caused by the dissolution of cement grains and the precipitation of calcium-silicate-hydrates during cement hydration. Progressing hydration drives the transition from a dense suspension to a porous solid phase. Fresh mixture of self-compacting concrete (SCC) can be considered as a phase-changing multi-component material and can be described as a continuum at the macro scale, interacting with a set of transport-reaction-diffusion processes which in turn are driven by phenomena at the level of the microstructure. This contribution focuses on a predictive model for the setting of fresh SCC where the liquid-solid phase transition is captured by a phase-field variable using the Ginzburg-Landau type free energy function. Hydration-related chemical reactions together with heat and mass transfer are volume coupled with the mechanical behaviour and determined by the environmental conditions. The weak form of the predictive model is discretised using the finite element method and implemented with the FEniCS computational framework. [less ▲] Detailed reference viewed: 115 (9 UL) |
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