Documents published in Scipedia

• Machine learning model for correlating microstructural features and macroscopic properties of heterogeneous composites

  H. Zhao, C. Shen, K. Wang, R. Mu, A. Wang

  ECCOMAS 2024.

  
  

  Abstract

  This study explores the use of machine learning (ML) models in predicting the macroscopic properties of heterogeneous composites. Traditional micromechanics parameters have limitations, thus ML models with and without feature engineering are utilized. For artificial neural network (ANN) models with feature engineering, microstructural descriptors from SEM images of nickel-based superalloys are used to predict hardness. 10 descriptors are selected to reduce the computational cost of the deep neural network (DNN) with the support of the shallow neural network (SNN), and accuracy is enhanced by incorporating two additional descriptors. The result surpasses existing physics-based models. Models without feature engineering employ a convolutional neural network (CNN) to predict the effective thermal conductivity of thermal insulation composite materials. The CNN model demonstrates accurate predictions for novel microstructures. ML models can achieve more efficient predictions than traditional methods, indicating their potential in advancing materials science. In summary, harnessing artificial intelligence to capture the scattering characteristics of heterogeneous materials enables both DNN and CNN models to achieve more efficient predictions compared to traditional methods. This highlights the potential of machine learning in advancing materials science and expediting the development of materials with desired properties.

  Abstract
  This study explores the use of machine learning (ML) models in predicting the macroscopic properties of heterogeneous composites. Traditional micromechanics parameters have [...]

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• Quasi Gasdynamic Heterogeneous Model for Modeling a Mixture of Compressible Fluids

  I. Khaytaliev, E. Shilnikov, T. Elizarova

  ECCOMAS 2024.

  
  

  Abstract

  Quasi-gasdynamic type regularization is presented for a heterogeneous model of a two-fluid mixture of compressible fluids. This model allows to describe the flows of stiffened gases. The reduced four-equation model for dynamics of the heterogeneous compressible two fluid mixture with equations of state of a stiffened gas is considered. A further reduced form of this model with the excluded volume concentrations and a quadratic equation for the common pressure of the components can be called a quasi-homogeneous form. A finite difference algorithm is used, built with the finite volume method. By solving one and two dimensional test problems it is shown that the presented algorithm is a stable and reliable way to model fluid mixtures with strong shock waves.

  Abstract
  Quasi-gasdynamic type regularization is presented for a heterogeneous model of a two-fluid mixture of compressible fluids. This model allows to describe the flows of stiffened [...]

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• Deep Reinforcement Learning implementation with Physics-Informed Neural Network for Heat Conduction Control

  N. Gonçalves, J. Rodrigues

  ECCOMAS 2024.

  
  

  Abstract

  As modern systems become more complex, their control strategy can no longer solely rely on measurement data gathered by instrumentation. Instead, it must also incorporate information derived from mathematical models. The complexity of system models can result in excessively long computation times, making the control process impractical. As a solution, surrogate models are implemented to provide estimates within an acceptable timeframe for decision-making purposes. The surrogate model can be a Physics-Informed Neural Network that is used to obtain the system state on the next time step; such information can be used with a Deep Reinforcement Learning algorithm to train a control strategy based on simulations, replacing the need for running direct numerical simulations. On this work, we explore a Deep Q-Learning strategy on 1D heat conduction problem in which temperature distribution feeds a control system to activate a heat source, aiming to obtain a constant, previously defined temperature value. The main goal is to stabilize the bar temperature at the middle point of it without recurring to numerical simulations.

  Abstract
  As modern systems become more complex, their control strategy can no longer solely rely on measurement data gathered by instrumentation. Instead, it must also incorporate [...]

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• A second-order reproducing kernel for SPH method to enhance accuracy and consistency

  I. Wiragunarsa, L. Zuhal, T. Dirgantara, I. Putra

  ECCOMAS 2024.

  
  

  Abstract

  The application of smoothed particle hydrodynamics (SPH) encounters challenges related to consistency, stability, and accuracy. Inconsistencies in SPH arise from non-uniform particle distribution and a lack of neighboring particles at the boundary, leading to numerical instability and inaccurate particle approximations. Various methods have been proposed to address these issues. One such framework is the corrected SPH, designed to ensure consistency of the method. In this work, performance of some correction procedures are analysed through gradient calculations of a function. The root mean square error of the gradient approximation is analysed to justify the method’s convergence and accuracy

  Abstract
  The application of smoothed particle hydrodynamics (SPH) encounters challenges related to consistency, stability, and accuracy. Inconsistencies in SPH arise from non-uniform [...]

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• A 3D Particle Model For Reinforced Concrete Fracture Aanalysis

  N. Azevedo, M. Farinha, S. Oliveira

  ECCOMAS 2024.

  
  

  Abstract

  A numerical model for the analysis of reinforced concrete structures must incorporate tools capable of representing the formation and propagation of cracks, their effect on the overall behavior of the structure, and the interaction between reinforcement and concrete. Detailed rigid particle models (PM) that take directly into consideration the physical mechanisms and the influence of the material aggregate structure have gained relevance and have shown to be able to predict, evaluate and understand cracking phenomena in concrete. The 3D particle models correlate well with experimental results from concrete specimens, particularly in terms of elastic response, peak values, fracture process and fracture location. This paper presents the 3D explicit formulation of steel reinforcement bars using discrete elements with cylindrical geometry. The incorporation of steel elements allows the particle model to be applied to the analysis of fracture in reinforced concrete structures. The rigid elements of cylindrical geometry interact with the concrete, modeled by spherical particles, through a contact interface. The model is validated in three-point beam bending tests, without transverse steel reinforcement. The numerical results obtained show that the proposed model correctly simulates the actual behavior, representing the fracture evolution process and the load displacement relationship for different steel ratios.

  Abstract
  A numerical model for the analysis of reinforced concrete structures must incorporate tools capable of representing the formation and propagation of cracks, their effect on [...]

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• Modeling small scale processes in Antarctic sea ice

  R. Pathak, T. Ricken, S. Thoms, S. Seyedpour, B. Kutschan

  ECCOMAS 2024.

  
  

  Abstract

  The Antarctic sea ice, which undergoes annual freezing and melting, plays a signif icant role in the global climate cycle. Adverse environmental conditions in the Southern Ocean influence the extent and amount of ice in the Marginal Ice Zones (MIZ), the BioGeo- Chemical (BGC) cycles, and their interconnected relationships. The ’Pancake’ floes are a composition of porous sea ice matrix with interstitial brine, nutrients, and biological com- munities inside the pores. To realistically model these multi-phasic and multi-component coupled processes, the extended Theory of Porous Media (eTPM) is used to develop mod- els capable of simulating the different seasonal variations. All critical variables like salinity, ice volume fraction, and tem perature, among others, are considered and have their equations of state. The phase transition phenomenon is approached through a micro-macro linking scheme. A Phase- field solidification model coupled with salinity is used to model the micro-scale freezing processes and up-scaled to the macro scale eTPM model. This allows for modeling the salt trapped inside the pores. For the biological part, a BGC flux model for sea ice is also set up to simulate the algal species present in the sea ice matrix. Processes like photosynthesis are dependent on temperature and salinity, and are derived through an ODE-PDE coupling with the eTPM model. Academic sim ulations and results are presented as validation for the mathematical model. These high-fidelity models will eventually lead to their incorporation into large-scale global climate models.

  Abstract
  The Antarctic sea ice, which undergoes annual freezing and melting, plays a signif icant role in the global climate cycle. Adverse environmental conditions in the Southern [...]

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• Lightweight AMG preconditioners for CFD simulations on symmetric domains

  À. Alsalti-Baldellou, C. Janna, X. Álvarez-Farré, F. Trias

  ECCOMAS 2024.

  
  

  Abstract
  Download

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• Performance analysis of parallel-in-time techniques in modern supercomputers

  J. Plana-Riu, F. Trias, À. Alsalti-Baldellou, G. Colomer, A. Oliva

  ECCOMAS 2024.

  
  

  Abstract

  This paper aims to improve the e ciency of large-scale turbulent simulations by improving the arithmetic intensity of the operations. This is done by applying a parallel-in time ensemble averaging technique so that multiple ow states are run simultaneouslly in the same device. This transforms sparse matrix-vector products into sparse matrix-matrix products, improving the arithmetic intensity. The performance of these operations as well as the speed-ups generated in the operation itself, in the whole iteration and an estimation in the whole simulation is presented, so that for cases in which the averaging interval is signi cantlly longer than the transition interval, remarkable speed-ups in the whole iteration are obtained.

  Abstract
  This paper aims to improve the e ciency of large-scale turbulent simulations by improving the arithmetic intensity of the operations. This is done by applying a parallel-in [...]

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• A Hybrid Hexahedral Solid-shell Element with Self-equilibrated Stresses for the Geometrically Nonlinear Static Analysis of Composite Laminated Structures

  G. Zucco, F. Liguori, A. Madeo

  ECCOMAS 2024.

  
  

  Abstract

  Hybrid nite elements with self-equilibrated assumed stresses have proven to pro vide several advantages for analysing shell structures. They guarantee high performance when using coarse meshes and accurately represent the stress eld. Additionally, they do not require assumptions about the displacement eld within the element domain, and the integration is ef ciently performed only along their contours. This work exploits those advantages to develop a solid-shell nite element for the geometrically nonlinear static analysis of composite laminated structures. In particular, an eight-node nite element, which has 24 displacement variables and 18 stress parameters, is developed. The displacement eld is described only by translations, eliminating the need for complex nite rotation treatments in large displacement problems. A Total Lagrangian formulation is used with the Green-Lagrange strain tensor and the second Piola-Kirchho stress tensor. Thickness locking is cured using an assumed natural strain formu lation for the transversal normal stress, and the assumed stress eld eliminates shear locking. Then, for the analysis of linear-elastic problems, no domain integration is needed, and all the element operators are obtained by line integrals. The resulting formulation is e cient and allows for easy implementation. Computed numerical results show the accuracy and robustness of the presented element when used for both the linear elastic static and geometrically nonlinear elastic static analysis of composite laminated shell structures.

  Abstract
  Hybrid nite elements with self-equilibrated assumed stresses have proven to pro vide several advantages for analysing shell structures. They guarantee high performance when [...]

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• Hierarchic Large Rotation Shell Model with Warping: Isogeometric Formulation and Modeling of Alternating Stiff/Soft Laminates

  D. Magisano, A. Corrado, L. Leonetti, J. Kiendl, G. Garcea

  ECCOMAS 2024.

  
  

  Abstract

  This paper presents a hierarchic large rotation Kirchho-Love shell model with warping. Two unknowns are introduced for each through-the-thickness function warping, rep resenting its amplitudes in two directions tangent to the shell surface. NURBS are used to approximate reference surface displacement and warping amplitudes in the weak form. The transverse shear strains depend only on the warping parameters linearly and are free from lock ing. A patch-wise reduced integration avoids membrane locking and improves e ciency. Focus is given to composites made up of multiple sti layers coupled with soft interlayers. The alternat ing layup with high sti ness ratios induces a signi cant sectional warping with transverse shear strains concentrated in the soft layers. Two warping models are investigated: WI) all sti layers maintain the same director orthogonal to the deformed surface with independent transverse shear deformations of the soft layers; WZ) a single zigzag function linking these deformations. The numerical tests con rm the great accuracy of the hierarchic shell model in reproducing the solid solution with a small number of discrete parameters, provided that the correct warping model is chosen. WI is reliable for all alternating layups. WZ reduces the unknowns to ve per surface point, regardless of the number of layers, and is accurate for uniform soft layers

  Abstract
  This paper presents a hierarchic large rotation Kirchho-Love shell model with warping. Two unknowns are introduced for each through-the-thickness function warping, rep resenting [...]

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