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Finite element simulations of viscoelastic flow of blade coating using the log-conformation tensor
Previous studies have demonstrated the benefits of the log-conformation formulation to model viscoelastic fluids; it increases stability at high Weissenberg numbers and ensures that the conformation tensor remains positive-definite. Many studies have applied the log-conformation tensor formulation to benchmark cases; however, relatively few studies investigate using the formulation on more complex flows. In this paper, we extend the log-conformation formulation to the manufacturing-relevant flow of blade coating. We first verify the log-conformation formulation on the benchmark problem of flow past a cylinder using the finite element method, and then apply it to the blade-coating process, in which a viscoelastic fluid entrained by a moving substrate passes under a blade at a constant web speed. We investigate various rheological effects and the resulting film thickness for the blade-coating problem, and compare the results from the log-conformation formulation to those of the original stress formulation. To this end, we show that the log-conformation formulation agrees well with other established methods, and also increases the maximum achievable web speed in the blade-coating problem.
A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows
Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR codes. In this work a novel hybrid adaptive multiresolution (HAMR) approach to AMR-based calculations is introduced to address this issue. The multiresolution (MR) smoothness indicators are used to identify regions of smoothness on the mesh where the computational cost of individual physics solvers may be decreased by replacing direct calculations with interpolation. We suggest an approach to balance the errors due to the adaptive discretization and the interpolation of physics quantities such that the overall accuracy of the HAMR solution is consistent with that of the MR-driven AMR solution. The performance of the HAMR scheme is evaluated for a range of test problems, from pure hydrodynamics to turbulent combustion.
Direct numerical simulation of the flow in the intake pipe of an internal combustion engine
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Direct numerical simulation of particulate flows with an overset grid method
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A unified high-order Eulerian method for continuum simulations of fluid flow and of elastic–plastic deformations in solids
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A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations
Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.
Side-jet effects in high-pressure turbulent flows: Direct Numerical Simulation of nitrogen injected into carbon dioxide
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Numerical simulation of fluid flow through random packs of polydisperse cylinders
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DSMC Simulations of Turbulent Flows at Moderate Reynolds Numbers.
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Simulating radiative magnetohydrodynamical flows with astrobear : implementation and applications of non-equilibrium cooling
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Subleading harmonic flows in hydrodynamic simulations of heavy ion collisions
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