scholarly journals Computational Fluid Dynamics Modelling of Liquid–Solid Slurry Flows in Pipelines: State-of-the-Art and Future Perspectives

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1566
Author(s):  
Gianandrea Vittorio Messa ◽  
Qi Yang ◽  
Oluwaseun Ezekiel Adedeji ◽  
Zdeněk Chára ◽  
Carlos Antonio Ribeiro Duarte ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Local Level ◽  
Methodological Approach ◽  
Theoretical Modelling ◽  
Predictive Capacity ◽  
Pipe Flows ◽  
Cfd Models ◽  
Slurry Flows ◽  
Complex Phenomena

Slurry pipe transport has directed the efforts of researchers for decades, not only for the practical impact of this problem, but also for the challenges in understanding and modelling the complex phenomena involved. The increase in computer power and the diffusion of multipurpose codes based on Computational Fluid Dynamics (CFD) have opened up the opportunity to gather information on slurry pipe flows at the local level, in contrast with the traditional approaches of simplified theoretical modelling which are mainly based on a macroscopic description of the flow. This review paper discusses the potential of CFD for simulating slurry pipe flows. A comprehensive description of the modelling methods will be presented, followed by an overview of significant publications on the topic. However, the main focus will be the assessment of the potential and the challenges of the CFD approach, underlying the essential interplay between CFD simulations and experiments, discussing the main sources of uncertainty of CFD models, and evaluating existing models based on their interpretative or predictive capacity. This work aims at providing a solid ground for students, academics, and professional engineers dealing with slurry pipe transport, but it will also provide a methodological approach that goes beyond the specific application.

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.

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.

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 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.

Good modelling practice in applying computational fluid dynamics for WWTP modelling

2015 ◽  
Vol 73 (5) ◽  
pp. 969-982 ◽  
Author(s):  
Edward Wicklein ◽  
Damien J. Batstone ◽  
Joel Ducoste ◽  
Julien Laurent ◽  
Alonso Griborio ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Working Group ◽  
Companion Paper ◽  
Cfd Modelling ◽  
Cfd Models ◽  
Water Association ◽  
Computational Fluid Dynamics Cfd ◽  
Cfd Applications ◽  
International Water

Computational fluid dynamics (CFD) modelling in the wastewater treatment (WWT) field is continuing to grow and be used to solve increasingly complex problems. However, the future of CFD models and their value to the wastewater field are a function of their proper application and knowledge of their limits. As has been established for other types of wastewater modelling (i.e. biokinetic models), it is timely to define a good modelling practice (GMP) for wastewater CFD applications. An International Water Association (IWA) working group has been formed to investigate a variety of issues and challenges related to CFD modelling in water and WWT. This paper summarizes the recommendations for GMP of the IWA working group on CFD. The paper provides an overview of GMP and, though it is written for the wastewater application, is based on general CFD procedures. A forthcoming companion paper to provide specific details on modelling of individual wastewater components forms the next step of the working group.

Benchmarking Computational Fluid Dynamics for Application to PWR Fuel

2002 ◽  
Author(s):  
L. D. Smith ◽  
M. E. Conner ◽  
B. Liu ◽  
B. Dzodzo ◽  
D. V. Paramonov ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Temperature Fields ◽  
Cfd Modeling ◽  
Spacer Grid ◽  
Cfd Models ◽  
Computational Mesh ◽  
Transfer Testing ◽  
Visualization Techniques

The present study demonstrates a process used to develop confidence in Computational Fluid Dynamics (CFD) as a tool to investigate flow and temperature distributions in a PWR fuel bundle. The velocity and temperature fields produced by a mixing spacer grid of a PWR fuel assembly are quite complex. Before using CFD to evaluate these flow fields, a rigorous benchmarking effort should be performed to ensure that reasonable results are obtained. Westinghouse has developed a method to quantitatively benchmark CFD tools against data at conditions representative of the PWR. Several measurements in a 5×5 rod bundle were performed. Lateral flowfield testing employed visualization techniques and Particle Image Velocimetry (PIV). Heat transfer testing involved measurements of the single-phase heat transfer coefficient downstream of the spacer grid. These test results were used to compare with CFD predictions. Among the parameters optimized in the CFD models based on this comparison with data include computational mesh, turbulence model, and boundary conditions. As an outcome of this effort, a methodology was developed for CFD modeling that provides confidence in the numerical results.

scholarly journals Computational fluid dynamics for turbomachinery internal air systems

2007 ◽  
Vol 365 (1859) ◽  
pp. 2587-2611 ◽  
Author(s):  
John W Chew ◽  
Nicholas J Hills
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Three Dimensional ◽  
Internal Flow ◽  
Eddy Simulation ◽  
Cfd Models ◽  
Geometrical Features ◽  
Air System ◽  
Buoyancy Driven Flows ◽  
Flow Phenomena

Considerable progress in development and application of computational fluid dynamics (CFD) for aeroengine internal flow systems has been made in recent years. CFD is regularly used in industry for assessment of air systems, and the performance of CFD for basic axisymmetric rotor/rotor and stator/rotor disc cavities with radial throughflow is largely understood and documented. Incorporation of three-dimensional geometrical features and calculation of unsteady flows are becoming commonplace. Automation of CFD, coupling with thermal models of the solid components, and extension of CFD models to include both air system and main gas path flows are current areas of development. CFD is also being used as a research tool to investigate a number of flow phenomena that are not yet fully understood. These include buoyancy-affected flows in rotating cavities, rim seal flows and mixed air/oil flows. Large eddy simulation has shown considerable promise for the buoyancy-driven flows and its use for air system flows is expected to expand in the future.

scholarly journals Computational fluid dynamics and virtual aeroengine modelling

2009 ◽  
Vol 223 (12) ◽  
pp. 2821-2834 ◽  
Author(s):  
J W Chew ◽  
N J Hills
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Parallel Computing ◽  
Large Scale ◽  
Numerical Solutions ◽  
Mechanical Analysis ◽  
Cfd Models ◽  
Engine Design ◽  
Massively Parallel Computing ◽  
User Friendly

Use of large-scale computational fluid dynamics (CFD) models in aeroengine design has grown rapidly in recent years as parallel computing hardware has become available. This has reached the point where research aimed at the development of CFD-based ‘virtual engine test cells’ is underway, with considerable debate of the subject within the industrial and research communities. The present article considers and illustrates the state-of-the art and prospects for advances in this field. Limitations to CFD model accuracy, the need for aero-thermo-mechanical analysis through an engine flight cycle, coupling of numerical solutions for solid and fluid domains, and timescales for capability development are considered. While the fidelity of large-scale CFD models will remain limited by turbulence modelling and other issues for the foreseeable future, it is clear that use of multi-scale, multi-physics modelling in engine design will expand considerably. Development of user-friendly, versatile, efficient programs and systems for use in a massively parallel computing environment is considered a key issue.

scholarly journals Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Jihad A. Badra ◽  
Fethi Khaled ◽  
Meng Tang ◽  
Yuanjiang Pei ◽  
Janardhan Kodavasal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Internal Combustion Engines ◽  
Optimization Problems ◽  
Combustion Engine ◽  
Methodological Approach ◽  
System Optimization ◽  
Operating Conditions ◽  
Attractive Alternative

Abstract Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. In this work, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

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