Documents published in Scipedia

• Carbon Neutral Concrete – Challenges and Solutions for Sustainable Future

  M. Plançon, Z. Shu Qiang, J. Wong

  DBMC 2023.

  
  

  Abstract

  As the climatic impact is becoming a more important topic for most of the nations which signed the COP 26 accords; many concrete and cement companies have announced their carbon reduction ambitions. Although the CO2 reduction pace varies from one country / company to the other, many of them have clearly stated their commitment towards concrete carbon neutrality in 2050. As a result, we can observe the accelerated emergence of a multitude of new technologies targeting the reduction of carbon content in concrete. The presentation proposed will go over the consequences for the concrete industry of this construction industry’s endeavor climatic impact reduction. It will explain some of the main challenges paving the cement and concrete industry’s journey towards carbon neutrality. It will deep dive in the principles and impacts of the most recent and advanced regulations in terms of low carbon construction such as, for example, RE2020 in France. It will also illustrate some of the realistic solutions currently implemented to reduce the carbon footprint of concrete and cement and adapt to this new market environment, including the use of the latest loT technology which allows the concrete producer to improve their material management, operational efficiency as well as the commercial leverage. In a world where raw materials scarcity becomes increasingly stringent, it will also explore the solutions for the concrete industry to promote circular economy. Finally, it will describe the most probable paths towards carbon neutral concrete and how they will inevitably include environmental footprint reduction beyond climatic impact.

  Abstract
  As the climatic impact is becoming a more important topic for most of the nations which signed the COP 26 accords; many concrete and cement companies have announced their [...]

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• A posteriori error estimation for second-order optimally convergent G/XFEM

  M. Bento, S. Proença, C. Duarte

  admos2023.

  
  

  Abstract

   This work presents a ZZ-BD a posteriori error estimator tailored for 3-D linear elastic fracture mechanics problems that are approximated by second-order pFEM-GFEM formulations. The proposed error estimator is shown to estimate well discretization errors in the energy norm, with the estimated discretization error converging at the same rate as the exact discretization error. Also, the computed effectivity indexes are close to the optimal value of 1 for a LEFM problem that exhibits 3-D effects.

  Abstract
   This work presents a ZZ-BD a posteriori error estimator tailored for 3-D linear elastic fracture mechanics problems that are approximated by second-order pFEM-GFEM formulations. [...]

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• Digital Twins as an enabling technology for disruptive improvement of computational methods in marine engineering.

  T. Kvamsdal

  marine2023.

  
  

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• The physical models: an embarrassment to viscous naval hydrodynamics

  M. Visonneau

  marine2023.

  
  

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• IA: Finding patterns in a stochastic marine world

  R. Molina

  marine2023.

  
  

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• Numerical Modeling to Advance Offshore Wind Energy Technology

  J. Jonkman

  marine2023.

  
  

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• Modelling and simulation of multiscale particulate flows using physics-informed data-driven methods. Applications in naval and marine engineering

  E. Oñate

  marine2023.

  
  

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• Mooring systems for Marine Renewable Energy

  K. Sharman

  marine2023.

  
  

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• High-Order Mesh Generation and Warping for Biomedical Simulations

  S. Shontz

  admos2023.

  
  

  Abstract

  There are numerous challenges in generating high-quality meshes of cardiac anatomies due to the complex geometry of the heart, its curvature, and its motion. More generally, computational modeling of anatomical models bounded by curved surfaces can benefit from the use of high-order curved meshes. Using such meshes ensures that the curvature is captured correctly in the corresponding mesh. In addition, for a fixed level of accuracy, pairing a high-order mesh with a high-order PDE solver requires fewer mesh elements hence making the mesh generation and PDE solve much less computationally expensive. The use of high-order meshes in dynamic simulations helps prevent instabilities. In this talk, we first present our advancing front-based high-order tetrahedral mesh generation method for finite element meshes. While most existing high-order mesh generation methods employ a computer-aided design (CAD) model to represent the boundary surface, our method requires only the element vertices and connectivities. Thus, it can employ a high-order surface mesh which was generated from medical image segmentation masks or a CAD model. Our method then directly generates a high-order volume mesh and applies mesh optimization to utilize the higher degrees of freedom and further improve the mesh quality. Second, we present our high-order mesh warping algorithm for tetrahedral meshes, which allows us to perform time-dependent deformations present in biomedical applications. Our method is based on a finite element formulation for hyperelastic materials. We employ the two-parameter incompressible Mooney-Rivlin model with appropriate material properties to represent the continuum model. We use Newton iteration to solve the nonlinear elasticity equations obtained from the Mooney-Rivlin model and equilibrium conditions; the solution to the nonlinear elasticity equations then yields the deformed mesh. Finally, we use our methods to generate several second-order tetrahedral meshes of anatomical models obtained from medical images and CAD models and apply several time-dependent deformations. We conclude with a vision for research in mesh generation for biomedical simulation. This talk represents joint work with Fariba Mohammadi, University of Michigan, and Cristian Linte, Rochester Institute of Technology

  Abstract
  There are numerous challenges in generating high-quality meshes of cardiac anatomies due to the complex geometry of the heart, its curvature, and its motion. More generally, [...]

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• Adaptive multilevel Monte Carlo for risk averse optimization

  F. Nobile

  admos2023.

  
  

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