scholarly journals Improving Performance of Simplified Computational Fluid Dynamics Models via Symmetric Successive Overrelaxation

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2438 ◽  
Author(s):  
Vojtěch Turek
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Direct Calculation ◽  
Steady State Solution ◽  
Computational Time ◽  
Process Equipment ◽  
Successive Overrelaxation ◽  
Lower Upper ◽  
Cfd Models ◽  
Relaxation Factors

The ability to model fluid flow and heat transfer in process equipment (e.g., shell-and-tube heat exchangers) is often critical. What is more, many different geometric variants may need to be evaluated during the design process. Although this can be done using detailed computational fluid dynamics (CFD) models, the time needed to evaluate a single variant can easily reach tens of hours on powerful computing hardware. Simplified CFD models providing solutions in much shorter time frames may, therefore, be employed instead. Still, even these models can prove to be too slow or not robust enough when used in optimization algorithms. Effort is thus devoted to further improving their performance by applying the symmetric successive overrelaxation (SSOR) preconditioning technique in which, in contrast to, e.g., incomplete lower–upper factorization (ILU), the respective preconditioning matrix can always be constructed. Because the efficacy of SSOR is influenced by the selection of forward and backward relaxation factors, whose direct calculation is prohibitively expensive, their combinations are experimentally investigated using several representative meshes. Performance is then compared in terms of the single-core computational time needed to reach a converged steady-state solution, and recommendations are made regarding relaxation factor combinations generally suitable for the discussed purpose. It is shown that SSOR can be used as a suitable fallback preconditioner for the fast-performing, but numerically sensitive, incomplete lower–upper factorization.

scholarly journals Modelling of working processes of non-contact oil free vacuum pumps by computational fluid dynamics (CFD) methods

2021 ◽  
Vol 2059 (1) ◽  
pp. 012003
Author(s):  
A Burmistrov ◽  
A Raykov ◽  
S Salikeev ◽  
E Kapustin
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Mathematical Models ◽  
Cfd Models ◽  
Ansys Cfx ◽  
Sst Turbulence Model ◽  
Computational Fluid Dynamics Cfd ◽  
Dynamic Meshing ◽  
Comparison With Experimental Data

Abstract Numerical mathematical models of non-contact oil free scroll, Roots and screw vacuum pumps are developed. Modelling was carried out with the help of software CFD ANSYS-CFX and program TwinMesh for dynamic meshing. Pumping characteristics of non-contact pumps in viscous flow with the help of SST-turbulence model were calculated for varying rotors profiles, clearances, and rotating speeds. Comparison with experimental data verified adequacy of developed CFD models.

scholarly journals Computational Fluid Dynamics Model of Wells Turbine for Oscillating Water Column System: A Review

2021 ◽  
Vol 2053 (1) ◽  
pp. 012013
Author(s):  
N. Abdul Settar ◽  
S. Sarip ◽  
H.M. Kaidi
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Water Column ◽  
Cfd Simulation ◽  
Oscillating Water Column ◽  
Wells Turbine ◽  
Flow Problems ◽  
Cfd Models ◽  
Column System ◽  
Cfd Method

Abstract Wells turbine is an important component in the oscillating water column (OWC) system. Thus, many researchers tend to improve the performance via experiment or computational fluid dynamics (CFD) simulation, which is cheaper. As the CFD method becomes more popular, the lack of evidence to support the parameters used during the CFD simulation becomes a big issue. This paper aims to review the CFD models applied to the Wells turbine for the OWC system. Journal papers from the past ten years were summarized in brief critique. As a summary, the FLUENT and CFX software are mostly used to simulate the Wells turbine flow problems while SST k-ω turbulence model is the widely used model. A grid independence test is essential when doing CFD simulation. In conclusion, this review paper can show the research gap for CFD simulation and can reduce the time in selecting suitable parameters when involving simulation in the Wells turbine.

Combining Computational Fluid Dynamics (CFD) and Flow Network Modeling (FNM) for Design of a Multi-Chip Module (MCM) Cold Plate

2013 ◽  
Author(s):  
John Fernandes ◽  
Saeed Ghalambor ◽  
Akhil Docca ◽  
Chris Aldham ◽  
Dereje Agonafer ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Thermal Analysis ◽  
Computational Fluid Dynamics ◽  
Network Modeling ◽  
Computational Time ◽  
Design Parameters ◽  
Cold Plate ◽  
Original Solution ◽  
Flow Network ◽  
Computational Fluid Dynamics Cfd

The objective of the study is to improve on performance of the current liquid cooling solution for a Multi-Chip Module (MCM) through design of a chip-scale cold plate with quick and accurate thermal analysis. This can be achieved through application of Flow Network Modeling (FNM) and Computational Fluid Dynamics (CFD) in an interactive manner. Thermal analysis of the baseline cold plate design is performed using CFD to determine initial improvement in performance as compared to the original solution, in terms of thermal resistance and pumping power. Fluid flow through the solution is modeled using FNM and verified with results from the CFD analysis. In addition, CFD is employed to generate flow impedance curves of non-standard components within the cold plate, which are used as input for the Hardy Cross method in FNM. Using the verified flow network model, design parameters of different components in the cold plate are modified to promote uniform flow distribution to each active region in the chip-scale solution. Analysis of the resultant design using CFD determines additional improvement in performance over the original solution, if available. Thus, through complementary application of FNM and CFD, a robust cold plate can be designed without requiring expensive fabrication of prototypes and with minimal computational time and resources.

An Assessment of Computational Fluid Dynamics Cavitation Models Using Bubble Growth Theory and Bubble Transport Modeling

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Michael P. Kinzel ◽  
Jules W. Lindau ◽  
Robert F. Kunz
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Analytic Solutions ◽  
Cfd Modeling ◽  
Computational Time ◽  
Cavitation Model ◽  
Modeling Framework ◽  
Homogeneous Models ◽  
Bubble Transport ◽  
Computational Fluid Dynamics Cfd

This effort investigates advancing cavitation modeling relevant to computational fluid dynamics (CFD) through two strategies. The first aims to reformulate the cavitation models and the second explores adding liquid–vapor slippage effects. The first aspect of the paper revisits cavitation model formulations with respect to the Rayleigh–Plesset equation (RPE). The present approach reformulates the cavitation model using analytic solutions to the RPE. The benefit of this reformulation is displayed by maintaining model sensitivities similar to RPE, whereas the standard models fail these tests. In addition, the model approach is extended beyond standard homogeneous models, to a two-fluid modeling framework that explicitly models the slippage between cavitation bubbles and the liquid. The results indicate a significant impact of slip on the predicted cavitation solution, suggesting that the inclusion of such modeling can potentially improve CFD cavitation models. Overall, the results of this effort point to various aspects that may be considered in future CFD-modeling efforts with the goal of improving the model accuracy and reducing computational time.

scholarly journals Simulating Smoke Filling in Big Halls by Computational Fluid Dynamics

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
W. K. Chow ◽  
C. L. Chow ◽  
S. S. Li
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Construction Projects ◽  
Far East ◽  
Mainland China ◽  
Convergence Criteria ◽  
Key Points ◽  
Set Up ◽  
Relaxation Factors ◽  
Smoke Filling

Many tall halls of big space volume were built and, to be built in many construction projects in the Far East, particularly Mainland China, Hong Kong, and Taiwan. Smoke is identified to be the key hazard to handle. Consequently, smoke exhaust systems are specified in the fire code in those areas. An update on applying Computational Fluid Dynamics (CFD) in smoke exhaust design will be presented in this paper. Key points to note in CFD simulations on smoke filling due to a fire in a big hall will be discussed. Mathematical aspects concerning of discretization of partial differential equations and algorithms for solving the velocity-pressure linked equations are briefly outlined. Results predicted by CFD with different free boundary conditions are compared with those on room fire tests. Standards on grid size, relaxation factors, convergence criteria, and false diffusion should be set up for numerical experiments with CFD.

scholarly journals Acceleration of a CFD Code with a GPU

2010 ◽  
Vol 18 (3-4) ◽  
pp. 193-201 ◽  
Author(s):  
Dennis C. Jespersen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Graphics Processing Unit ◽  
Computational Time ◽  
Processing Unit ◽  
Graphics Processing ◽  
Work Done

The Computational Fluid Dynamics code OVERFLOW includes as one of its solver options an algorithm which is a fairly small piece of code but which accounts for a significant portion of the total computational time. This paper studies some of the issues in accelerating this piece of code by using a Graphics Processing Unit (GPU). The algorithm needs to be modified to be suitable for a GPU and attention needs to be given to 64-bit and 32-bit arithmetic. Interestingly, the work done for the GPU produced ideas for accelerating the CPU code and led to significant speedup on the CPU.

Multi-Objective Optimization of a High Specific Speed Centrifugal Volute Pump Using Three-Dimensional Inverse Design Coupled With Computational Fluid Dynamics Simulations

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Luying Zhang ◽  
Gabriel Davila ◽  
Mehrdad Zangeneh
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Design Method ◽  
Three Dimensional ◽  
Inverse Design ◽  
Computational Time ◽  
Specific Speed ◽  
Meridional Shape ◽  
Inverse Design Method ◽  
Blade Geometry

Abstract This paper presents three different multiobjective optimization strategies for a high specific speed centrifugal volute pump design. The objectives of the optimization consist of maximizing the efficiency and minimizing the cavitation while maintaining the Euler head. The first two optimization strategies use a three-dimensional (3D) inverse design method to parametrize the blade geometry. Both meridional shape and 3D blade geometry are changed during the optimization. In the first approach, design of experiment (DOE) method is used and the pump efficiency is obtained from computational fluid dynamics (CFD) simulations, while cavitation is evaluated by using minimum pressure on blade surface predicted by 3D inverse design method. The design matrix is then used to create a surrogate model where optimization is run to find the best tradeoff between cavitation and efficiency. This optimized geometry is manufactured and tested and is found to be 3.9% more efficient than the baseline with reduced cavitation at high flow. In the second approach, only the 3D inverse design method output is used to compute the efficiency and cavitation parameters and this leads to considerable reduction to the computational time. The resulting optimized geometry is found to be similar to the computationally more expensive solution based on 3D CFD results. In order to compare the inverse design based optimization to the conventional optimization, an equivalent optimization is carried out by parametrizing the blade angle and meridional shape.

Computational Fluid Dynamics Modelling of a Load Sensing Proportional Valve

2019 ◽  
Author(s):  
Alessandro Corvaglia ◽  
Giorgio Altare ◽  
Roberto Finesso ◽  
Massimo Rundo
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Steady State ◽  
Complex Geometry ◽  
Ansys Fluent ◽  
Proportional Valve ◽  
Fluid Forces ◽  
Load Sensing ◽  
Cfd Models ◽  
Dynamics Modelling

Abstract In this paper, two 3D CFD models of a load sensing proportional valve are contrasted. The models were developed with two different software, Simerics PumpLinx® and ANSYS Fluent®. In both cases the mesh was dynamically modified based on the fluid forces acting on the local compensator. In the former, a specific template for valves was used, in the latter a user-defined function was implemented. The models were validated in terms of flow rate and pressure drop for different positions of the main spool by means of specific tests. Two configurations were tested: with the local compensator blocked and free to regulate. The study has brought to evidence the reliability of the CFD models in evaluating the steady-state characteristics of valves with complex geometry.

New Evolutionary Techniques for Optimization of Energy Systems Utilizing Computational Fluid Dynamics

2003 ◽  
Author(s):  
Douglas S. McCorkle ◽  
Kenneth M. Bryden
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Evolutionary Algorithms ◽  
Computational Cost ◽  
Solution Space ◽  
Optimization Techniques ◽  
Computational Time ◽  
Feed Forward Neural Network ◽  
Thermal Fluids ◽  
Fluid Systems

Optimization techniques that search a solution space without designer intervention are becoming important tools in the engineering design of many thermal fluid systems. Evolutionary algorithms are among the most robust of these optimization methods because the ability to optimize many designs simultaneously makes evolutionary algorithms less susceptible to premature convergence. However application of evolutionary algorithms to thermal and fluid systems described by high fidelity models (e.g. computational fluid dynamics) has been limited due to the high computational cost of the fitness evaluation. This paper presents a novel technique that combines two technologies used in the optimization of thermal fluids systems. The first is graph based evolutionary algorithms that are implemented to help increase the diversity of the evolving population of designs. The second is an algorithm utilizing a feed forward neural network that develops a stopping criterion for computational fluid dynamics solutions. This reduces the time required for each future evaluation in the evolutionary process and allows for more complex thermal fluids systems to be optimized. In the system examined here the overall reduction in computational time is approximately 8 times.

scholarly journals Propagation of Input Uncertainty in Presence of Model-Form Uncertainty: A Multifidelity Approach for Computational Fluid Dynamics Applications

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jian-Xun Wang ◽  
Christopher J. Roy ◽  
Heng Xiao
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Parameter Space ◽  
Uncertainty Propagation ◽  
High Fidelity ◽  
Sampling Errors ◽  
Uncertainty Distribution ◽  
Cfd Models ◽  
Computational Fluid Dynamics Cfd ◽  
Cfd Applications

Proper quantification and propagation of uncertainties in computational simulations are of critical importance. This issue is especially challenging for computational fluid dynamics (CFD) applications. A particular obstacle for uncertainty quantifications in CFD problems is the large model discrepancies associated with the CFD models used for uncertainty propagation. Neglecting or improperly representing the model discrepancies leads to inaccurate and distorted uncertainty distribution for the quantities of interest (QoI). High-fidelity models, being accurate yet expensive, can accommodate only a small ensemble of simulations and thus lead to large interpolation errors and/or sampling errors; low-fidelity models can propagate a large ensemble, but can introduce large modeling errors. In this work, we propose a multimodel strategy to account for the influences of model discrepancies in uncertainty propagation and to reduce their impact on the predictions. Specifically, we take advantage of CFD models of multiple fidelities to estimate the model discrepancies associated with the lower-fidelity model in the parameter space. A Gaussian process (GP) is adopted to construct the model discrepancy function, and a Bayesian approach is used to infer the discrepancies and corresponding uncertainties in the regions of the parameter space where the high-fidelity simulations are not performed. Several examples of relevance to CFD applications are performed to demonstrate the merits of the proposed strategy. Simulation results suggest that, by combining low- and high-fidelity models, the proposed approach produces better results than what either model can achieve individually.

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