scholarly journals Using Adaptive Mesh Refinement to Study Grid Resolution Effects for Shock-Boundary Layer Interactions

2018 ◽  
Author(s):  
Michael E. Olsen ◽  
Randolph P. Lillard
Keyword(s):  
Boundary Layer ◽  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Grid Resolution

Finite Volume adaptive mesh refinement based on graph applied to the Boundary Layer Problem

2011 ◽  
Vol 9 (1) ◽  
pp. 836-842
Author(s):  
Sanderson Lincohn Gonzaga de Oliveira ◽  
Mauricio Kischinhevsky ◽  
Denise Burgarelli
Keyword(s):  
Boundary Layer ◽  
Finite Volume ◽  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Boundary Layer Problem ◽  
Layer Problem

Adaptive mesh refinement method based investigation of the interaction between shock wave, boundary layer, and tip vortex in a transonic compressor

2017 ◽  
Vol 232 (4) ◽  
pp. 694-715 ◽  
Author(s):  
Jinlan Gou ◽  
Xin Yuan ◽  
Xinrong Su
Keyword(s):  
Boundary Layer ◽  
Shock Wave ◽  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Tip Vortex ◽  
Small Scale ◽  
Tip Leakage ◽  
Transonic Compressor ◽  
Mesh Convergence

Shock wave and tip leakage are important flow features at small length scales. These flow phenomena and their interactions play important roles in the performance of modern transonic fans and compressors. In most numerical predictions of these features, mesh convergence studies are conducted using overall performance data as criteria. However, less effort is made in assessing the quality of the predicted small-scale features using a mesh that yields a fairly accurate overall performance. In this work, this problem is addressed using the adaptive mesh refinement (AMR) method, which automatically refines the local mesh and provides very high resolution for the small-scale flow feature, at much less cost compared with globally refining the mesh. An accurate and robust AMR system suitable for turbomachinery applications is developed in this work and the widely studied NASA Rotor-37 case is investigated using the current AMR method. The complex interactions between the shock wave and the boundary layer, as well as those between the shock wave and the tip vortex, are accurately captured by AMR with a very high local grid resolution, and the flow mechanisms are analyzed in detail. The baseline mesh, which is considered to be “acceptable” according to the commonly used mesh convergence study, is unable to capture the detailed interaction between the shock wave and the boundary layer. Moreover, it falsely predicts the tip leakage vortex breakdown, which is a consequence of inadequate resolution in the tip region. Current work highlights the importance of a careful check of the mesh convergence, if small-scale features are the primary concern. The AMR method developed in this work successfully captures the flow details in the transonic compressor in an automatic fashion, and has been verified to be efficient compared with the globally mesh refinement or manually mesh regeneration.

Dynamic structural analysis of connecting rod through adaptive mesh refinement for different materials

2018 ◽  
Vol 50 (04) ◽  
pp. 561-570
Author(s):  
I. A. QAZI ◽  
A. F. ABBASI ◽  
M. S. JAMALI ◽  
INTIZAR INTIZAR ◽  
A. TUNIO ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Connecting Rod ◽  
Dynamic Structural Analysis

scholarly journals Convergence and quasi-optimal cost of adaptive algorithms for nonlinear operators including iterative linearization and algebraic solver

2021 ◽  
Author(s):  
Alexander Haberl ◽  
Dirk Praetorius ◽  
Stefan Schimanko ◽  
Martin Vohralík
Keyword(s):  
Adaptive Algorithm ◽  
Adaptive Mesh Refinement ◽  
Elliptic Boundary ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Picard Iteration ◽  
Optimal Rate ◽  
Stopping Criteria ◽  
Element Discretization ◽  
Fully Adaptive

AbstractWe consider a second-order elliptic boundary value problem with strongly monotone and Lipschitz-continuous nonlinearity. We design and study its adaptive numerical approximation interconnecting a finite element discretization, the Banach–Picard linearization, and a contractive linear algebraic solver. In particular, we identify stopping criteria for the algebraic solver that on the one hand do not request an overly tight tolerance but on the other hand are sufficient for the inexact (perturbed) Banach–Picard linearization to remain contractive. Similarly, we identify suitable stopping criteria for the Banach–Picard iteration that leave an amount of linearization error that is not harmful for the residual a posteriori error estimate to steer reliably the adaptive mesh-refinement. For the resulting algorithm, we prove a contraction of the (doubly) inexact iterates after some amount of steps of mesh-refinement/linearization/algebraic solver, leading to its linear convergence. Moreover, for usual mesh-refinement rules, we also prove that the overall error decays at the optimal rate with respect to the number of elements (degrees of freedom) added with respect to the initial mesh. Finally, we prove that our fully adaptive algorithm drives the overall error down with the same optimal rate also with respect to the overall algorithmic cost expressed as the cumulated sum of the number of mesh elements over all mesh-refinement, linearization, and algebraic solver steps. Numerical experiments support these theoretical findings and illustrate the optimal overall algorithmic cost of the fully adaptive algorithm on several test cases.

scholarly journals AMReX: Block-structured adaptive mesh refinement for multiphysics applications

2021 ◽  
pp. 109434202110228
Author(s):  
Weiqun Zhang ◽  
Andrew Myers ◽  
Kevin Gott ◽  
Ann Almgren ◽  
John Bell
Keyword(s):  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Uniform Mesh ◽  
Physical Processes ◽  
Structured Adaptive Mesh Refinement ◽  
Core Elements ◽  
Accelerator Design ◽  
Block Structured

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

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