Coupling Algorithms and Specific Coupling Features in CGCMs

2021 ◽  
pp. 140-156
Keyword(s):  
2020 ◽  
Author(s):  
Stefan Jendersie ◽  
Alena Malyarenko

<p>To quantify Antarctic ice mass loss and the subsequent sea level rise the geophysical modelling community is pushing towards frameworks that fully couple increasingly complex models of atmosphere, ocean, sea ice and ice sheets & shelves.  One particular hurdle remains the accurate representation of the vertical ocean-ice interaction at the base of ice shelves.  Parameterizations that are tuned to particular data sets naturally perform best in comparable ice shelf cavity environments. This poses the challenge in continental scale ocean-ice shelf models to chose one melt parameterizaton that performs sufficiently well in diverse cavity environment.  Thus adding uncertainty in ice shelf induced ocean freshening crucially affects modelled sea ice growth.  The impact magnitude of ice shelf supplied melt water on growth rates, thickness and extent of sea ice in the open ocean is currently debated in the literature.  <br>We reviewed and compared 16 commonly utilized melting/freezing parameterizations in coupled ocean-ice shelf models.  Melt rates differ hugely, in identical idealized conditions between 0.1m/yr to 3m/yr.  In this talk we present results of a realistic circum-Antarctic ice shelf and sea ice coupled ocean model (CICE, ROMS), where we look at the effects of the chosen ice shelf melt parameterization on modeled sea surface conditions and sea ice growth, regionally and circum Antarctic.</p>


PAMM ◽  
2008 ◽  
Vol 8 (1) ◽  
pp. 10987-10988 ◽  
Author(s):  
Joachim Rang ◽  
Martin Krosche ◽  
R. Niekamp ◽  
Hermann G. Matthies

Author(s):  
Long He ◽  
Keyur Joshi ◽  
Danesh Tafti

In this work, we present an approach for solving fluid structure interaction problems by combining a non-linear structure solver with an incompressible fluid solver using immersed boundary method. The implementation of the sharp-interface immersed boundary method with the fluid solver is described. A structure solver with the ability to handle geometric nonlinearly is developed and tested with benchmark cases. The partitioned fluid-structure coupling algorithm with the strategy of enforcing boundary conditions at the fluid/structure interaction is given in detail. The fully coupled FSI approach is tested with the Turek and Hron fluid-structure interaction benchmark case. Both strong coupling and weak coupling algorithms are examined. Predictions from the current approach show good agreement with the results reported by other researchers.


2015 ◽  
Vol 51 ◽  
pp. 2066-2075 ◽  
Author(s):  
Florian Lemarié ◽  
Eric Blayo ◽  
Laurent Debreu

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Ya-Ling He ◽  
Wen-Quan Tao

In this paper, numerical simulation approaches for multiscale process of heat transfer and fluid flow are briefly reviewed, and the existing coupling algorithms are summarized. These molecular dynamics simulation (MDS)–finite volume method (FVM), MD–lattice Boltzmann method (LBM), and direct simulation of Monte Carlo method (DSMC)–FVM. The available reconstruction operators for LBM–FVM coupling are introduced. Four multiscale examples for fluid flow and heat transfer are presented by using these coupled methods. It is shown that by coupled method different resolution requirements in the computational domain can be satisfied successfully while computational time can be significantly saved. Further research needs for the study of multiscale heat transfer and fluid flow problems are proposed.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7280 ◽  
Author(s):  
Adam J. Hockenberry ◽  
Claus O. Wilke

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.


2018 ◽  
Author(s):  
Adam J. Hockenberry ◽  
Claus O. Wilke

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.Significance StatementEvolutionary couplings between residues within a protein can provide valuable information about protein structures, protein-protein interactions, and the mutability of individual residues. However, the mechanistic factors that determine whether two residues will co-evolve remains unknown. We show that structural proximity by itself is not sufficient for co-evolution to occur between residues. Rather, evolutionary couplings between residues are specifically governed by interactions between side-chain atoms. By contrast, intramolecular contacts between atoms in the protein backbone display only a weak signature of evolutionary coupling. These findings highlight that different types of stabilizing contacts exist within protein structures and that these types have a differential impact on the evolution of protein structures that should be considered in co-evolutionary applications.


2020 ◽  
Author(s):  
Lars Radtke

The present work is concerned with the partitioned solution of the multifeld problem arising from a hierarchical modeling approach to cardiovascular fluid-structure interaction. Different strategies to couple the participating feld solvers are investigated in detail. This includes staggered and parallel coupling algorithms as well as different methods for convergence acceleration, spatial interpolation and temporal extrapolation of coupling quantities. In the developed modeling and simulation approach, a fully resolved model of a segment of the arterial network is coupled to reduced order models in order to account for the influence of the surrounding. There is experimental evidence that hemodynamic quantities such as the wall shear stress promote the progression cardiovascular disease. Cardiovascular FSI simulations, that can predict these quantities, are therefore of great interest and can aid in surgical planning and optimization of anastomoses shapes and graft materials. Contents...


Author(s):  
Zhengkun Feng ◽  
Azzeddine Soulai¨mani

A nonlinear computational aeroelasticity model based on the Euler equations of compressible flows and the linear elastodynamic equations for structures is developed. The Euler equations are solved on dynamic meshes using the ALE kinematic description. Thus, the mesh constitutes another field governed by pseudo-elatodynamic equations. The three fields are discretized using proper finite element formulations which satisfy the geometric conservation law. A matcher module is incorporated for the purpose of pairing the grids on the fluid-structure interface and for transferring the loads and displacements between the fluid and structure solvers. Two solutions strategies (Gauss Seidel and Schur-Complement) for solving the nonlinear aeroelastic system are discussed. Using second order time discretization schemes allows us to use large time steps in the computations. The numerical results on the AGARD 445.6 aeroelastic wing compare well with the experimental ones and show that the Schur-complement coupling algorithm is more robust than the Gauss-Seidel algorithm for relatively large oscillation amplitudes.


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