A new numerical solver for simulating porous media flow based on immersed boundary method

Date

2018-12-14

Author

Güler, Hasan Gökhan
Liu, Xiaofeng
Jensen, Bjarne
Tomaselli, Pietro D
Baykal, Cüneyt
Arıkawa, Taro
Yalçıner, Ahmet Cevdet

Metadata

Show full item record

Item Usage Stats

172
views

0
downloads

In this study, we present and validate a new numerical solver in OpenFOAM®-v1706 called "ibmPorFoam" that is developed modifying IHFOAM (Higuera et al., 2014) with Immersed Boundary Method. IHFOAM is previously developed modifying interFoam solver of OpenFOAM® to solve flow properties in porous media. IHFOAM solves Volume Averaged Reynolds Averaged Navier-Stokes Equations, captures the free surface using Volume of Fluid method, and is capable of generating and absorbing waves. Immersed boundary method implemented in this study is based on body force approach given by Liu (2013). ibmPorFoam is validated in two parts by using k-∊ model as the turbulence closure. In the first part, a porous dam-break experiment (Lin, 1998) is studied as a 2D case study (Figure 1). Free surface measurements inside and outside the porous medium are compared with the numerical results. In the second part, 3D numerical simulations (Figure 2) are carried out to determine flow properties around a rigid, impervious box based on the experimental setup of Kleefsman et al. (2005). Numerical results are compared with the experimental results at wave gauges along the channel and pressure gauges located on the box. Both experimental cases are also simulated using IHFOAM to observe the differences in the numerical solvers. It is seen that the results of numerical simulations conducted with ibmPorFoam are in fairly well-agreement with both experimental results and numerical results from IHFOAM.

URI

https://hdl.handle.net/11511/83556

Conference Name

American Geophysical Union, Fall Meeting (2018)

Collections

Department of Civil Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A neuro-fuzzy MAR algorithm for temporal rule-based systems Sisman, NA; Alpaslan, Ferda Nur; Akman, V (1999-08-04) This paper introduces a new neuro-fuzzy model for constructing a knowledge base of temporal fuzzy rules obtained by the Multivariate Autoregressive (MAR) algorithm. The model described contains two main parts, one for fuzzy-rule extraction and one for the storage of extracted rules. The fuzzy rules are obtained from time series data using the MAR algorithm. Time-series analysis basically deals with tabular data. It interprets the data obtained for making inferences about future behavior of the variables. Fu...
A new likelihood approach to autonomous multiple model estimation Söken, Halil Ersin (Elsevier BV, 2020-04-01) This paper presents an autonomous multiple model (AMM) estimation algorithm for hybrid systems with sudden changes in their parameters. Estimates of Kalman filters (KFs) that are tuned and employed for different system modes are merged based on a newly defined likelihood function without any necessity for filter interaction. The proposed likelihood function is composed of two measures, the filter agility measure and the steady-state error measure. These measures are derived based on filter adaptation rules....
A generative model for multi class object recognition and detection Ulusoy, İlkay (2006-01-01) In this study, a generative type probabilistic model is proposed for object recognition. This model is trained by weakly labelled images and performs classification and detection at the same time. When test on highly challenging data sets, the model performs good for both tasks (classification and detection).
A Modified Parallel Learning Vector Quantization Algorithm for Real-Time Hardware Applications Alkim, Erdem; AKLEYLEK, SEDAT; KILIÇ, ERDAL (2017-10-01) In this study a modified learning vector quantization (LVQ) algorithm is proposed. For this purpose, relevance LVQ (RLVQ) algorithm is effciently combined with a reinforcement mechanism. In this mechanism, it is shown that the proposed algorithm is not affected constantly by both relevance-irrelevance input dimensions and the winning of the same neuron. Hardware design of the proposed scheme is also given to illustrate the performance of the algorithm. The proposed algorithm is compared to the corresponding...
A Favorable Weight-Based Evolutionary Algorithm for Multiple Criteria Problems SOYLU, Banu; Köksalan, Mustafa Murat (Institute of Electrical and Electronics Engineers (IEEE), 2010-04-01) In this paper, we present a favorable weight-based evolutionary algorithm for multiple criteria problems. The algorithm tries to both approximate the Pareto frontier and evenly distribute the solutions over the frontier. These two goals are common for many multiobjective evolutionary algorithms. To achieve these goals in our algorithm, each member selects its own weights for a weighted Tchebycheff distance function to define its fitness score. The fitness scores favor solutions that are closer to the Pareto...

Citation Formats

H. G. Güler et al., “A new numerical solver for simulating porous media flow based on immersed boundary method,” presented at the American Geophysical Union, Fall Meeting (2018), Washington, United States Of America, 2018, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/83556.