Optimization of an axial fan for air cooled condensers

We report on the low noise optimization of an axial fan specifically designed for the cooling of CSP power plants. The duty point presents an uncommon combination of a load coefficient of 0.11, a flow coefficient of 0.23 and a static efficiency ηstat > 0.6. Calculated fan Reynolds number is equal to Re = 2.85 x 107. Here we present a process used to optimize and numerically verify the fan performance. The optimization of the blade was carried out with a Python code through a brute-force-search algorithm. Using this approach the chord and pitch distributions of the original blade are varied under geometrical constraints, generating a population of over 24000 different possible individuals. Each individual was then tested using an axisymmetric Python code. The software is based on a blade element axisymmetric principle whereby the rotor blade is divided into a number of streamlines. For each of these streamlines, relationships for velocity and pressure are derived from conservation laws for mass, tangential momentum and energy of incompressible flows. The final geometry was eventually chosen among the individuals with the maximum efficiency. The final design performance was then validated through with a CFD simulation. The simulation was carried out using a RANS approach, with the cubic k -  low Reynolds turbulence closure of Lien et al. The numerical simulation was able to verify the air performance of the fan and was used to derive blade-to-blade distributions of design parameters such as flow deviation, velocity components, specific work and diffusion factor of the optimized blade. All the computations were performed in OpenFoam, an open source C++- based CFD library. This work was carried out under MinWaterCSP project, funded by EU H2020 programme

predicting the performance of an industrial centrifugal fan incorporating cambered plate impeller blades

Application of computational methods to industrial fan design processes has progressed steadily over the past decade. The reducing cost of the computer hardware upon which codes run has brought the hardware within the reach of all industrial fan designers. However, the cost of commercially available codes remains high. Open source codes provide industrial fan designers with an alternative. The finite volume open-source solver OpenFOAM has been used by scholars to predict the performance of industrial centrifugal fans incorporating impeller blades constructed from cambered plate, but not by industrial fan designers. This paper presents a modelling approach which we developed for application as part of an industrial fan manufacturers order related design process. We compare numerical performance predictions with experimental results both at peak pressure and at peak efficiency conditions. As a further possible investigation, the simulated flow field is used to predict the patterns of erosion of the impeller

Forced Convection Heat Transfer from a Finite-Height Cylinder

[EN] This paper presents a large eddy simulation of forced convection heat transfer in the flow around a surface-mounted finite-height circular cylinder. The study was carried out for a cylinder with height-to-diameter ratio of 2.5, a Reynolds number based on the cylinder diameter of 44 000 and a Prandtl number of 1. Only the surface of the cylinder is heated while the bottom wall and the inflow are kept at a lower fixed temperature. The approach flow boundary layer had a thickness of about 10% of the cylinder height. Local and averaged heat transfer coefficients are presented. The heat transfer coefficient is strongly affected by the free-end of the cylinder. As a result of the flow over the top being downwashed behind the cylinder, a vortex-shedding process does not occur in the upper part, leading to a lower value of the local heat transfer coefficient in that region. In the lower region, vortex-shedding takes place leading to higher values of the local heat transfer coefficient. The circumferentially averaged heat transfer coefficient is 20 % higher near the ground than near the top of the cylinder. The spreading and dilution of the mean temperature field in the wake of the cylinder are also discussed.The simulation was carried out using the supercomputing facilities of the Steinbuch Centre for Computing (SCC) of the Karlsruhe Institute of Technology. MGV has been partially supported by grant TRA2012-37714 of the Spanish Ministry of Economy and Competitiveness.García Villalba, M.; Palau-Salvador, G.; Rodi, W. (2014). Forced Convection Heat Transfer from a Finite-Height Cylinder. Flow, Turbulence and Combustion. 93(1):171-187. https://doi.org/10.1007/s10494-014-9543-7S171187931Ames, F., Dvorak, L.: Turbulent transport in pin fin arrays: experimental data and predictions. J. Turbomach. 128(1), 71–81 (2006)Armstrong, J., Winstanley, D.: A review of staggered array pin fin heat transfer for turbine cooling applications. J. 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Identification of losses in turbomachinery with machine learning

One of the issues of handling large CFD datasets and process them to derive important design correlations is the limitation in automating the post-processing of data. Machine learning techniques, developed to process large unlabelled dataset, can play a key role on this subject. In this work an unsupervised approach to isolate different flow features inside a 2D cascade is proposed and validated. The approach relies on machine learning methods and in particular on Exploratory Data Analysis (EDA) and Principal Component Analysis for the pre-processing of the data and on K-means clustering for the post-processing. The K-means algorithm was trained on a Design of Experiments (DoE) of over 140 cases of 2D linear cascade configurations to identify the boundary layer on the profiles and the wake downstream. Validation resulted in a perfect capability of identifying the regions of interest. Then a possible exploitation of this method is presented, to compute pressure losses downstream of the cascade and train an artificial neural network to make a regression able to extend data to all the possible combinations of geometrical and operating parameters of the cascade. The same algorithm was applied to 3D flow cascades of profiles with sinusoidal leading edges to stress its extrapolation capability in case of flow regimes not present in the training DoE

Assessment of a machine-learnt adaptive wall-function in a compressor cascade with sinusoidal leading edge

Near-wall modelling is one of the most challenging aspects of CFD computations. In fact, integration-to-the-wall with low-Reynolds approach strongly affects accuracy of results, but strongly increases the computational resources required by the simulation. A compromise between accuracy and speed to solution is usually obtained through the use of wall functions, especially in RANS computations, which normally require that the first cell of the grid to fall inside the log-layer (50 < y+ < 200) [1]. This approach can be generally considered as robust, however the derivation of wall functions from attached flow boundary layers can mislead to non-physical results in presence of specific flow topologies, e.g. recirculation, or whenever a detailed boundary layer representation is required (e.g. aeroacoustics studies) [2]. In this work, a preliminary attempt to create an alternative data-driven wall function is performed, exploiting artificial neural networks (ANNs). Whenever enough training examples are provided, ANNs have proven to be extremely powerful in solving complex non-linear problems [3]. The learner that is derived from the multi-layer perceptron ANN, is here used to obtain two-dimensional, turbulent production and dissipation values near the walls. Training examples of the dataset have been initially collected either from LES simulations of significant 2D test cases or have been found in open databases. Assessments on the morphology and the ANN training can be found in the paper. The ANN has been implemented in a Python environment, using scikit-learn and tensorflow libraries [4][5]. The derived wall function is implemented in OpenFOAM v-17.12 [6], embedding the forwarding algorithm in run-time computations exploiting Python3.6m C_Api library. The data-driven wall function is here applied to k-epsilon simulations of a 2D periodic hill with different computational grids and to a modified compressor cascade NACA aerofoil with sinusoidal leading edge. A comparison between ANN enhanced simulations, available data and standard modelization is here performed and reported

Leading Edge Bumps In Ventilation Fan

We report on a numerical study on the performance of an innovative axial flow fan for large tunnel ventilation. Taking a lead from a previous biomimetic analysis on the performance of the flippers of the humpback whale, this whale-fan was designed with sinusoidal-like leading edge that mimic the tubercles of the whale. We found that this provided a resistance to stall and improved lift recovery in post-stall operations. The sinusoidal profile of the leading edge allowed to control the distribution of vorticity on the suction surface of the blades and increase the stall margin of the device. The paper discusses the design methodology that was followed to correlate the sinusoidal shape of the leading edge of the blade with the desired vorticity distribution at the trailing edge that was needed to control separation. In the paper we show the results of numerical computations carried out with the finite volume open-source code Open FOAM on the whale-fan as well as a baseline fan with straight leading edge. Reynolds Averaged Navier-Stokes equations for incompressible flow were solved with a nonlinear (cubic) eddy-viscosity k-ε model that was found able to control the eddy viscosity distribution in order to account for anisotropy of Reynolds stresses and better reproduce the three-dimensional properties of the flow field. The paper shows the performance chart of the whale-fan, derived from numerical computations, and gives an insight of the fluid flow mechanisms that are generated by the sinusoidal leading edge on the suction surface of the fan. A comparison with the baseline fan with straight leading edge is provided in order to highlight how the shape of the leading edges affect the performance of the fan. Copyright © 2013 by ASME

LES of heat transfer in a channel with a staggered pin matrix

Flow and heat transfer through a matrix of 8 x 8 cylindrical adiabatic rods in a staggered arrangement and connecting two non-isothermal walls of a plane channel have been studied with LES using an in-house unstructured ¯nite-volume computational code. The results for the mean °ow properties agree well with the experimental data of Ames et al. [1]. The instantaneous velocity and temperature ¯elds, vortical structures and their wall-signatures, unsteadiness and three-dimensionality - none of which is accessible to exper- iments, have been analyzed to gain a better insight into the °ow dynamics and its e®ects on the local and averaged heat transfer

The application of sinusoidal blade-leading edges in a fan-design methodology to improve stall resistance

Taking inspiration from previous biomimetic studies on the performance of humpback whale flippers, this paper reports a programme of work to design a 'whale-fan' that incorporates a sinusoidal leading-edge blade profile that mimics the tubercles on humpback whales flippers. Previous researchers have used two-dimensional cascades of aerofoils to study the effects of a sinusoidal profile on aerofoil lift and drag performance. The research was primarily concerned with elucidating the fluid-flow mechanisms induced by the sinusoidal profile and the impact of those mechanisms on aerofoil performance. The results indicate that a sinusoidal leading-edge profile has improved lift recovery post-stall and, thus, is inherently more aerodynamically resistant to the effect of stall. The reported research focuses on the application of previous research conducted with infinite span cascades of aerofoils to the design and optimisation of a finite span aerofoil. The paper presents the assumptions when developing a three-dimensional aerofoil-design methodology that correlates the sinusoidal profile of the blade-leading edge with the desired vorticity distribution at the trailing edge. The authors apply the developed methodology to the design of a fan blade's tip region to control separation at the trailing edge. The paper presents numerically derived whale-fan performance characteristics and compares them with both numerically and experimentally derived performance characteristics of the baseline fan