2021 ◽  
Vol 9 (6) ◽  
pp. 572
Author(s):  
Luca Di Di Angelo ◽  
Francesco Duronio ◽  
Angelo De De Vita ◽  
Andrea Di Di Mascio

In this paper, an efficient and robust Cartesian Mesh Generation with Local Refinement for an Immersed Boundary Approach is proposed, whose key feature is the capability of high Reynolds number simulations by the use of wall function models, bypassing the need for accurate boundary layer discretization. Starting from the discrete manifold model of the object to be analyzed, the proposed model generates Cartesian adaptive grids for a CFD simulation, with minimal user interactions; the most innovative aspect of this approach is that the automatic generation is based on the segmentation of the surfaces enveloping the object to be analyzed. The aim of this paper is to show that this automatic workflow is robust and enables to get quantitative results on geometrically complex configurations such as marine vehicles. To this purpose, the proposed methodology has been applied to the simulation of the flow past a BB2 submarine, discretized by non-uniform grid density. The obtained results are comparable with those obtained by classical body-fitted approaches but with a significant reduction of the time required for the mesh generation.


1983 ◽  
Vol 105 (1) ◽  
pp. 83-88 ◽  
Author(s):  
H. A. Dwyer ◽  
R. J. Kee ◽  
P. K. Barr ◽  
B. R. Sanders

The transient heating of a spherical liquid particle at high Peclet number has been calculated with the use of adaptive grids for low Reynolds numbers. The use of adaptive grids greatly enhances the efficiency of the calculations and allows for the large Peclet numbers to be studied. The results of the calculations show that the transient period of internal isotherm redistribution represents a significant part of the droplet total heating. Even for the Pe = 1600 case, the initial heating period caused more than 50 percent of particle heating, and the asymptotic heating results cannot be used with good accuracy. The methods employed in the study have great potential, and will be applied to unsteady droplet evaporization and burning in future studies.


1994 ◽  
Author(s):  
R. HEJL ◽  
S. HEISTER
Keyword(s):  

2016 ◽  
Author(s):  
Thomas Reerink ◽  
Roderik van de Wal

Abstract. This paper accompanies the second OBLIMAP open source release. The package is developed to map climate fields between a general circulation model (GCM) and an ice sheet model (ISM) in both directions by using optimal aligned oblique projections, which minimize distortions. Both grids may be irregularly spaced and the ratio of the grids is allowed to differ largely. The stand-alone version of OBLIMAP is a powerful tool to map various differently gridded datasets on one uniform ISM grid with an optimal centered projection. This is demonstrated by relevant applicatons concerning the major ice caps. As this applies also for the reverse mapping direction, it can be used as an off-line coupler. Besides, OBLIMAP 2.0 is an embeddable GCM–ISM coupler, suited for high frequent on-line coupled experiments. A new fast scan method is presented as an alternative for the former time consuming grid search strategy, realising a performance gain of several orders of magnitude and enabling the mapping of high resolution datasets with a much larger number of grid nodes. Further a highly flexible masked mapping option is added. The limitations of the fast scan method with respect to unstructured and adaptive grids are discussed together with several proposed parallel implementations in order to achieve another performance gain.


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjie Guo ◽  
Guojun Dai ◽  
Jin Fan ◽  
Yifan Wu ◽  
Fangyao Shen ◽  
...  

This paper develops a mobile sensing system, the first system used in adaptive resolution urban air quality monitoring. In this system, we employ several taxis as sensor carries to collect originalPM2.5data and collect a variety of datasets, including meteorological data, traffic status data, and geographical data in the city. This paper also presents a novel method AG-PCEM (Adaptive Grid-Probabilistic Concentration Estimation Method) to infer thePM2.5concentration for undetected grids using dynamic adaptive grids. We gradually collect the measurements throughout a year using a prototype system in Xiasha District of Hangzhou City, China. Experimental data has verified that the proposed system can achieve good performance in terms of computational cost and accuracy. The computational cost of AG-PCEM is reduced by about 40.2% compared with a static grid method PCEM under the condition of reaching the close accuracy, and the accuracy of AG-PCEM is far superior as widely used artificial neural network (ANN) and Gaussian process (GP), enhanced by 38.8% and 14.6%, respectively. The system can be expanded to wide-range air quality monitor by adjusting the initial grid resolution, and our findings can tell citizens actual air quality and help official management find pollution sources.


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