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 Using Splitters to Control Secondary Flow

2017 ◽  
Vol 139 (09) ◽  
pp. 58-59
Author(s):  
C. Clark ◽  
G. Pullan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Kinetic Energy ◽  
Secondary Flow ◽  
Boundary Layers ◽  
Experimental Tests ◽  
Optimization Techniques ◽  
Automated Optimization

This article elaborates the concept of splitter vanes in controlling secondary flow. Secondary flow vortices are formed by the rotation of vorticity filaments, located in the endwall boundary layers, as the filaments move through the passage. The connection between the number of stators and the secondary kinetic energy suggests that the only way to significantly reduce the mixing loss is to increase the number of blades in the row. The designs evaluated were produced with fast turn-around computational fluid dynamics (10 minutes per solution) and automated optimization techniques. Experimental tests showed that the theory was correct, and that by increasing vane count, the secondary kinetic energy was reduced by up to 80%.

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 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.

Development of a Computational Fluid Dynamics Model to Simulate Three-Dimensional Gap Resonance Driven by Surface Waves

2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Hongchao Wang ◽  
Scott Draper ◽  
Wenhua Zhao ◽  
Hugh Wolgamot ◽  
Liang Cheng
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Computational Cost ◽  
Three Dimensional ◽  
Domain Size ◽  
Experimental Results ◽  
Mode Shapes ◽  
Transient Wave ◽  
Mesh Topology ◽  
Gap Resonance

This paper expounds the process of successfully establishing a computational fluid dynamics (CFD) model to accurately reproduce experimental results of three-dimensional (3D) gap resonance between two fixed ship-shaped boxes. The ship-shaped boxes with round bilges were arranged in a side-by-side configuration to represent a floating liquefied natural gas offloading scenario and were subjected to NewWave-type transient wave groups. We employ the open-source CFD package openfoam to develop the numerical model. Three-dimensional gap resonance differs from its two-dimensional (2D) counterpart in allowing spatial structure along the gap and hence multiple modes can easily be excited in the gap by waves of moderate spectral bandwidth. In terms of numerical setup and computational cost, a 3D simulation is much more challenging than a 2D simulation and requires careful selection of relevant parameters. In this respect, the mesh topology and size, domain size and boundary conditions are systematically optimized. It is shown that to accurately reproduce the experimental results in this case, the cell size must be adequate to resolve both the undisturbed incident waves and near-wall boundary layer. By using a linear iterative method, the NewWave-type transient wave group used in the experiment is accurately recreated in the numerical wave tank (NWT). Numerical results including time series of gap responses, resonant amplitudes and frequencies, and mode shapes show excellent agreement with experimental data.

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.

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.

The Influence of Metamodeling Techniques on the Multidisciplinary Design Optimization of a Radial Compressor Impeller

2012 ◽  
Author(s):  
Christopher Chahine ◽  
Joerg R. Seume ◽  
Tom Verstraete
Keyword(s):  
Fluid Dynamics ◽  
Design Optimization ◽  
Design Space ◽  
Optimization Algorithms ◽  
Computational Cost ◽  
Computational Time ◽  
Radial Compressor ◽  
Compressor Impeller ◽  
The Impact ◽  
Low Computational Cost

Aerodynamic turbomachinery component design is a very complex task. Although modern CFD solvers allow for a detailed investigation of the flow, the interaction of design changes and the three dimensional flow field are highly complex and difficult to understand. Thus, very often a trial and error approach is applied and a design heavily relies on the experience of the designer and empirical correlations. Moreover, the simultaneous satisfaction of aerodynamic and mechanical requirements leads very often to tedious iterations between the different disciplines. Modern optimization algorithms can support the designer in finding high performing designs. However, many optimization methods require performance evaluations of a large number of different geometries. In the context of turbomachinery design, this often involves computationally expensive Computational Fluid Dynamics and Computational Structural Mechanics calculations. Thus, in order to reduce the total computational time, optimization algorithms are often coupled with approximation techniques often referred to as metamodels in the literature. Metamodels approximate the performance of a design at a very low computational cost and thus allow a time efficient automatic optimization. However, from the experiences gained in past optimizations it can be deduced that metamodel predictions are often not reliable and can even result in designs which are violating the imposed constraints. In the present work, the impact of the inaccuracy of a metamodel on the design optimization of a radial compressor impeller is investigated and it is shown if an optimization without the usage of a metamodel delivers better results. A multidisciplinary, multiobjective optimization system based on a Differential Evolution algorithm is applied which was developed at the von Karman Institute for Fluid Dynamics. The results show that the metamodel can be used efficiently to explore the design space at a low computational cost and to guide the search towards a global optimum. However, better performing designs can be found when excluding the metamodel from the optimization. Though, completely avoiding the metamodel results in a very high computational cost. Based on the obtained results in present work, a method is proposed which combines the advantages of both approaches, by first using the metamodel as a rapid exploration tool and then switching to the accurate optimization without metamodel for further exploitation of the design space.

Improving Computational Fluid Dynamics Simulations for the Spallation Neutron Source Jet-Flow Target

2016 ◽  
Author(s):  
C. Barbier ◽  
E. Dominguez-Ontiveros
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Neutron Source ◽  
Jet Flow ◽  
Computational Time ◽  
Spallation Neutron Source ◽  
Mean Flow ◽  
Cfd Simulations ◽  
Flow Measurements ◽  
Piv Measurements

A liquid mercury target is used at Oak Ridge National Laboratory’s (ORNL [1]) Spallation Neutron Source (SNS [2]) to generate neutrons. The mercury is flowing in a stainless steel containment vessel for neutron spallation, but also to cool the vessel itself. Computational Fluid Dynamics (CFD) simulations have been used to estimate the temperature and pressure fields needed for the thermal stress analysis. Because of the geometry complexity, the high turbulence number, and the computational time requirements, generating a quality mesh that can accurately capture the flow and heat transfer has always been a challenge. However, with today’s High Performance Computing (HPC) advances, larger and larger meshes can now be used and better accuracy can be achieved. In this study, two meshing methods were used for the SNS jet-flow target: automatic tetrahedral method (ANSYS meshing) and manual hexahedral meshing (ICEM-CFD). Both methods are compared in terms of quality, size, ease of generation, convergence, and user-friendliness. Both meshes were used with ANSYS-CFX to simulate the steady, Newtonian, single phase, isothermal, incompressible and turbulent flow in the target. The Shear Stress Transport (SST) k-ω model developed by Menter [3] was used for turbulence modeling. The accuracy of the CFD simulations are tested against experimental data presented in the current paper. An in-depth series of Particle Image Velocimetry (PIV) measurements performed on a “visual jet-flow target”, an acrylic replica target running with water, are presented in the paper. Since flow measurements in mercury are difficult, a water loop was built to investigate the flow in the target and a potential gas injection in the flow to mitigate the pressure wave [4]. A PIV system on a precise translation stage was setup on the water loop to perform detailed and accurate PIV measurements. Mean flow velocity fields were used to validate the CFD simulations. The paper concludes on the choice for mesh generation for future target analysis, and the path forward for CFD simulations for the future SNS targets.

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