High-fidelity Computational Fluid Dynamics Research Articles

Neuro-Fuzzy Network-Based Reduced-Order Modeling of Transonic Aileron Buzz

In the present work, a reduced-order modeling (ROM) framework based on a recurrent neuro-fuzzy model (NFM) that is serial connected with a multilayer perceptron (MLP) neural network is applied for the computation of transonic aileron buzz. The training data set for the specified ROM is obtained by performing forced-motion unsteady Reynolds-averaged Navier Stokes (URANS) simulations. Further, a Monte Carlo-based training procedure is applied in order to estimate statistical errors. In order to demonstrate the method’s fidelity, a two-dimensional aeroelastic model based on the NACA651213 airfoil is investigated at different flow conditions, while the aileron deflection and the hinge moment are considered in particular. The aileron is integrated in the wing section without a gap and is modeled as rigid. The dynamic equations of the rigid aileron rotation are coupled with the URANS-based flow model. For ROM training purposes, the aileron is excited via a forced motion and the respective aerodynamic and aeroelastic response is computed using a computational fluid dynamics (CFD) solver. A comparison with the high-fidelity reference CFD solutions shows that the essential characteristics of the nonlinear buzz phenomenon are captured by the selected ROM method.

A numerical investigation to analyze effect of turbulence and ground clearance on the performance of a roof top vertical–axis wind turbine

Recent attempts to discover energy–efficient and cost–effective power generation systems unleash tremendous capabilities of urban rooftops vertical–axis wind turbines (VAWT). Their advantages of Omni–directionality, low noise and less maintenance cost allow direct integration to urban neighborhood having unstable wind conditions. Despite continuous effort to investigate performance under a range of operating conditions, aspects such as Turbulent Intensity (TI) and ground clearance remain relatively less explored. Such effects originate either due to sharp topographical variations or placement of the turbine blades in proximity to the ground. In the present work, we perform a parametric study to quantify the performance of VAWT under various levels of TI and ground clearance. We conduct high fidelity Computational Fluid Dynamics (CFD) simulations using ANSYS Fluent and k−ε turbulence model. The H-type VAWT is employed having rated power of 1.5kW, diameter (D)of 2.5mchord length (c) of 0.2m and operates at prescribed wind speed (U0)of 12.0m/sand Tip Speed Ratio (TSR) of 1.5–4.5. We determine the performance of turbine under four levels of TI i.e., 0%, 5%, 15%25%at five ground clearance levels of 1.0c,2.5c,4.0c,7.5cand 10.0c. The results show a performance loss of 30.10%, 20.65%, 10.65% at turbine clearance heights of 1.0c,2.5c, 4.0c respectively. The height of 7.5c yield higher and more consistent performance under given operating conditions. The results for induced turbulence identify a decrease in the performance up to 45.42% corresponding to 25%TI level.

CFD simulation of corium flow through an end fitting of a pressurised heavy water reactor

This study investigates the numerical simulation of corium relocation during a hypothetical accident, focussing on the modelling of core melt, its solidification and redistribution. This paper presents results of a high-fidelity computational fluid dynamics (CFD) simulation of an ex-vessel corium flow through a horizontal end fitting geometry, a pressurized heavy water reactor (PHWR) relevant configuration. The objective of this work is to simulate the corium progression within the end fitting of a PHWR to assess the suitability of two viscosity models using a CFD code; Siemens STAR-CCM+. This first-of-a-kind, exploratory study demonstrates the potential of the existing CFD models for modeling corium spreading within the end fitting geometry. Mixed convection turbulent corium flow in the end-fitting has been modeled in the three-dimensional CFD simulations. Transient simulations using the volume-of-fluid approach and melting-solidification models were performed to predict the corium melt spread within the end fitting. Two suitable temperature-dependant models for corium viscosity were tested, one being empirical viscosity model by Ramacciotti and the other mechanistic viscosity model available in STAR-CCM+. The unique flow features such as the Rayleigh-Bénard instability could be observed using the Ramacciotti empirical viscosity modelling approach. A qualitative assessment of the results was undertaken, showing that the CFD model has predicted the corium spreading behaviour that is consistent with the expectations based on engineering judgement and experience. This kind of simulations are expected to serve as a guidance in planning lab-scale experiments and aid in CFD-informed modeling improvements for integral (or system) codes going forward.

Aerodynamically induced noise of a lift-offset coaxial rotor with pitch attitude in high-speed forward flight

This paper investigates both acoustics and performance of a lift-offset coaxial rotor based on a first-principles and high-fidelity CFD (Computational Fluid Dynamics) and CSD (Computational Structural Dynamics) loose coupling approach in high-speed forward flight at different vehicle pitch attitudes. The pitch attitudes selected for this research are −5∘, 0∘, and 5∘. Detailed aerodynamic analyses are performed at two flight speeds: 150 (278 km hr−1) and 200 knots (370 km hr−1). A total of six major unsteady aerodynamic interactions are identified: 1) hub-wake interaction, 2) self-BVI (blade-vortex interaction), 3) parallel rotor-to-rotor BVI, 4) blade-crossover events, 5) root-induced BVI, and 6) reversed-flow-edge-vortex interactions. The strength of these interactions is found to be dependent on vehicle pitch attitude. The cases with a negative pitch attitude show significantly stronger impulsive pressure pulses, which is found to be induced by parallel rotor-to-rotor BVIs of the lower rotor. It is shown that the positive and zero pitch attitude cases tend to dominate the acoustic region on the starboard side of the coaxial rotor, whereas the negative pitch attitude case shows higher acoustic pressure peaks on the port side. Overall, the high-speed case with a positive pitch attitude shows significant improvement in rotor aerodynamic efficiency, rotor acoustics, and vehicle power performance at high speed. The hemispherical acoustic simulation results also show that the noise is less likely to propagate in the forward direction at a positive pitch attitude in high-speed forward flight.

Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles

The objective of this work was to investigate a multifidelity modeling approach to accurately and efficiently predict the aerothermal response of a large-diameter deployable hypersonic entry vehicle in Mars entry. A cokriging-based multifidelity modeling approach was developed that used several refinements including lower–upper decomposition for parallelization, distance weighted root-mean-square error adaptive sampling, and surface distribution parameterization using Hicks–Henne bump functions. Several computational tools of varying fidelity were investigated to model the surface convective heat flux, shear stress, pressure, and radiative heat flux in the multifidelity modeling process. The multifidelity model was found to have a mean convective heat rate error of 4.6%, a mean pressure force error of 0.81%, a mean shear force error of 2.86%, and a mean radiative heat rate error of 11.1% when compared to high-fidelity computational fluid dynamics simulations. Compared to a single-fidelity model, the multifidelity model required approximately one-half the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of constructing and evaluating the multifidelity model were approximately one and five orders of magnitude less, respectively, than one high-fidelity model simulation.

CFD Prediction of Tip Vortex Aging in the Wake of a Multi-MW Wind Turbine

In the present study, prediction from high-fidelity Computational Fluid Dynamics (CFD) simulations of the tip vortex aging in the near-wake of a multi-MW wind turbine is evaluated and compared to in-situ measurements as well as results of a semi-empirical model. Optimized tip vortex refinement is also introduced to investigate the influence of the grid topology on the vortex evolution. The grid refinement affects only the vortex core size and a reduction of the core radius by a factor of 3.4 was achieved with the chosen parameters. On the refined setup, vortex core sizes and strength are comparable with in-situ Unmanned Aircraft System (UAS) based measurements at 0.5 rotor radius downstream of the wind turbine. A comparison of the aging function with a semi-empirical vortex helix model shows a good agreement with the refined CFD results, but the core size predicted by the model is smaller than in simulations and experiments.

An experimental and numerical analysis of the dynamic variation of the angle of attack in a vertical-axis wind turbine

Simulation methods ensuring a level of fidelity higher than that of the ubiquitous Blade Element Momentum theory are increasingly applied to VAWTs, ranging from Lifting-Line methods, to Actuator Line or Computational Fluid Dynamics (CFD). The inherent complexity of these machines, characterised by a continuous variation of the angle of attack during the cycloidal motion of the airfoils and the onset of many related unsteady phenomena, makes nonetheless a correct estimation of the actual aerodynamics extremely difficult. In particular, a better understanding of the actual angle of attack during the motion of a VAWT is pivotal to select the correct airfoil and functioning design conditions. Moving from this background, a high-fidelity unsteady CFD model of a 2-blade H-Darrieus rotor was developed and validated against unique experimental data collected using Particle Image Velocimetry (PIV). In order to reconstruct the AoA variation during one rotor revolution, three different methods-detailed in the study-were then applied to the computed CFD flow fields. The resulting AoA trends were combined with available blade forces data to assess the corresponding lift and drag coefficients over one rotor revolution and correlate them with the most evident flow macro-structures and with the onset of dynamic stall.

On the feasibility of affordable high-fidelity CFD simulations for indoor environment design and control

Computational fluid dynamics (CFD) is a reliable tool for indoor environmental applications. However, accurate CFD simulations require large computational resources, whereas significant cost reduction can lead to unreliable results. The high cost prevents CFD from becoming the primary tool for indoor environmental simulations. Nonetheless, the growth in computational power and advances in numerical algorithms provide an opportunity to use accurate and yet affordable CFD. The objective of this study is to analyze the feasibility of fast, affordable, and high-fidelity CFD simulations for indoor environment design and control using ordinary office computers. We analyze two representative test cases, which imitate common indoor airflow configurations, on a wide range of different turbulence models and discretizations methods, to meet the requirements for the computational cost, run-time, and accuracy. We consider statistically steady-state simulations for indoor environment design and transient simulations for control. Among studied turbulence models, the no-model and large-eddy simulation with staggered discretizations show the best performance. We conclude that high-fidelity CFD simulations on office computers are too slow to be used as a primary tool for indoor environment design and control. Taking into account different laws of computer growth prediction, we estimate the feasibility of high-fidelity CFD on office computers for these applications for the next decades.

Deep Learning Based Reduced Order Model for Airfoil-Gust and Aeroelastic Interaction

This work aims to model transonic airfoil–gust interaction and the gust response on transonic aileron-buzz problems using high-fidelity computational fluid dynamics (CFD) and the Long Short Term Memory (LSTM) based deep-learning approach. It first explores the rich physics associated with these interactions, which show strong flowfield nonlinearities arising from the complex shock–boundary-layer interactions using CFD. In the transonic regime, most linear reduced-order models (ROMs) fail to reconstruct the unsteady global parameters such as the lift, moment, and drag coefficients and the unsteady distributive flow variables such as velocity, pressure, and skin friction coefficients on the airfoil or in the entire computational domain due to the nonlinear shock–gust interaction. As it is well known that a deep-learning framework creates several hypersurfaces to generate a nonlinear functional relationship between the gust or structural input and the unsteady flow variables, an algorithm is proposed to overcome the limitations of linear ROMs. This algorithm consists of two integral steps, namely, a dimensionality reduction where the Discrete Empirical Interpolation Method based linear data compression approach is applied and the reduced state is trained using the LSTM based Recurrent Neural Network for the reconstruction of unsteady flow variables. The present work shows its potential for predicting transonic airfoil gust response and the aileron-buzz problem demonstrating several orders of computational benefit as compared to high-fidelity CFD.

Geometrical Optimization of Pump-As-Turbine (PAT) Impellers for Enhancing Energy Efficiency with 1-D Theory

This paper presents a multi-objective optimization strategy for pump-as-turbines (PAT), which relies on one-dimensional theory and analysis of geometrical parameters. In this strategy, a theoretical model, which considers all possible losses incurred (mainly by the components of pipe inlet, impeller and volute), has been put forward for performance prediction of centrifugal pumps operating as turbines (PAT). With the established mathematical relationship between the efficiency of PAT (both at pump and turbine mode) and the impeller controlling variables, the geometric optimization of the PAT impeller is performed with constant rotational speed. Specifically, the optimization data consist of 50 sets of impellers generated from Latin Hypercube Sampling method with its corresponding efficiencies calculated. Subsequently, the pareto-based genetic algorithm (PBGA) was adopted to optimize the geometic parameters of the impellers through the theoretical model. To validate the theoretical optimization results, the high-fidelity Computational Fluid Dynamics (CFD) simulation and the experimental data are employed for comparison of the PAT performance. The findings show that the efficiencies of both the pump and PAT optimized variables increased by 0.27% and 16.3% respectively under the design flow condition. Based on the one-dimensional theoretical optimization results, the geometry of the impeller is redesigned to suit both pump and PAT mode operations. It is concluded that the chosen design variables (b2, β1, β2, and z) have a significant impact on the PAT efficiency, which demonstrates that the optimization scheme proposed in this study is practicable.

Computational Fluid Dynamics Based Mixing Prediction for Tilt Pad Journal Bearing TEHD Modeling—Part I: TEHD-CFD Model Validation and Improvements

AbstractThe core contributions of Part I (1) present a computational fluid dynamics (CFD)-based approach for tilting pad journal bearing (TPJB) modeling including thermo-elasto hydrodynamic (TEHD) effects with multi-mode pad flexibility, (2) validate the model by comparison with experimental work, and (3) investigate the limitations of the conventional approach by contrasting it with the new approach. The modeling technique is advanced from the author’s previous work by including pad flexibility. The results demonstrate that the conventional approach of disregarding the three-dimensional flow physics between pads (BP) can generate significantly different pressure, temperature, heat flux, dynamic viscosity, and film thickness distributions, relative to the high-fidelity CFD model. The uncertainty of the assumed mixing coefficient (MC) may be a serious weakness when using a conventional, TPJB Reynolds model, leading to prediction errors in static and dynamic performance. The advanced mixing prediction method for “BP” thermal flow developed in Part I will be implemented with machine learning techniques in Part II to provide a means to enhance the accuracy of conventional Reynolds based TPJB models.

On the spectrographic representation of cardiovascular flow instabilities

In the past decade, high-fidelity computational fluid dynamics (CFD) has uncovered the presence of high-frequency flow instabilities (on the order of 100 s of Hz) in a variety of cardiovascular applications. These fluctuations are typically reported as pulsatile velocity–time traces or fast-Fourier-transformed power-frequency spectra, often from a single point or at most a handful of points. Originally inspired by its use in spectral Doppler ultrasound, here we demonstrate the utility of the simplest form of time–frequency representation – the spectrogram – as a more comprehensive yet still-intuitive means of visualizing the potential harmonic complexity of pulsatile cardiovascular flows. After reviewing the basic theory behind spectrograms, notably the short-time Fourier transform (STFT), we discuss the choice of input parameters that inform the appearance and trade-offs of spectrograms. We show that spectrograms using STFT were able to highlight spectral features and were representative of those obtained from more complex methods such as the Continuous Wavelet transforms (CWT). While visualization properties (colourmap, filtering, smoothing/interpolation) are shown to affect the conspicuity of spectral features, the window properties (function, size, overlap) are shown to have the greatest impact on the resulting spectrogram appearance. Using a set of cerebral aneurysm CFD cases, we show that spectrograms can readily reveal the case-specific nature of the time-varying flow instabilities, whether broadband, suggesting intermittent turbulent-like flow, or narrowband, suggesting laminar vortex shedding, or some combination thereof.

Fly low: The ground effect of a barn owl (Tyto alba) in gliding flight

Birds take advantage of the ground effect to improve their flight performance by flying low over ground. In this paper, we created a high-fidelity computational fluid dynamics model of a barn owl ( Tyto alba) to study its ground effect in gliding flight. A computational fluid dynamics simulation shows that the ground effect leads to increases in the lift/drag ratio and span efficiency. Interestingly, the span efficiency exceeds one when the bird is below a certain ground clearance ( h/ c = 0.8). Such an estimation is under the condition of different weight supports; hence, there is no fair comparison for many parameters. Therefore, we used a vortex induction model validated by computational fluid dynamics to estimate the aerodynamics at different ground clearances under a constant weight support. As the ground blocks the downwash of the bird, an image wake system can equivalently replace the ground, forming a vortex system with four components: the wake vortex, bound vortex, image wake vortex and image bound vortex. The vortex induction model shows the vertical flows induced by these four vortex components. Such vertical flow can be used to estimate the drag production on the bird. As the ground clearance decreases, the drag due to the wake vortex and its image counterpart as a whole decreases, while that due to the bound vortex and its image counterpart increases slightly and then decreases. The remaining drag, namely, the zero-lift drag, undergoes a shallow “U” shape as a function of the ground clearance. We also analyzed the streamwise flow induction using this model and showed that the streamwise flow is reduced due to the ground effect, which might cause insufficient weight support at low speeds.

Comparative Study of CFD and LedaFlow Models for Riser-Induced Slug Flow

The goal of this study is to compare mainstream Computational Fluid Dynamics (CFD) with the widely used 1D transient model LedaFlow in their ability to predict riser induced slug flow and to determine if it is relevant for the offshore oil and gas industry to consider making the switch from LedaFlow to CFD. Presently, the industry use relatively simple 1D-models, such as LedaFlow, to predict flow patterns in pipelines. The reduction in cost of computational power in recent years have made it relevant to compare the performance of these codes with high fidelity CFD simulations. A laboratory test facility was used to obtain data for pressure and mass flow rates for the two-phase flow of air and water. A benchmark case of slug flow served for evaluation of the numerical models. A 3D unsteady CFD simulation was performed based on Reynolds-Averaged Navier-Stokes (RANS) formulation and the Volume of Fluid (VOF) model using the open-source CFD code OpenFOAM. Unsteady simulations using the commercial 1D LedaFlow solver were performed using the same boundary conditions and fluid properties as the CFD simulation. Both the CFD and LedaFlow model underpredicted the experimentally determined slug frequency by 22% and 16% respectively. Both models predicted a classical blowout, in which the riser is completely evacuated of water, while only a partial evacuation of the riser was observed experimentally. The CFD model had a runtime of 57 h while the LedaFlow model had a runtime of 13 min. It can be concluded that the prediction capabilities of the CFD and LedaFlow models are similar for riser-induced slug flow while the CFD model is much more computational intensive.

PadMesh: a parallel and distributed framework for interactive mesh generation software

Meshes are the input for computational fluid dynamics (CFD) analysis, whose size and quality have important impact on the simulation results. With the continuous advancement of high-fidelity CFD simulation, the scale of needed computational meshes has become larger and larger, which poses great challenges to the development of interactive mesh generation software. To address this issue, a parallel and distributed framework called PadMesh is proposed, which performs as the infrastructure for developing various interactive mesh generation software (e.g., structured, unstructured and Cartesian). First, the framework PadMesh is demonstrated, including the introduction of design principles, software architecture and key components, namely message-oriented middleware, client application, server application and parallel supporting module. Second, a parallel and distributed structured mesh generation software called PGridStar is developed based on PadMesh. Strategies are investigated on managing the visual data and distributed data for structured meshes. Finally, two functionalities of the preliminary PGridStar are presented, which validate the usability of PadMesh in developing interactive mesh generation software.

Body-force and mean-line models for the generation of axial compressor sub-idle characteristics

ABSTRACTThis paper describes the application of low-order models to the prediction of the steady performance of axial compressors at sub-idle conditions. An Euler body-force method employing sub-idle performance correlations is developed and presented alongside a mean-line approach employing the same set of correlations. The low-order tools are used to generate the characteristic lines of the compressor in the locked-rotor and zero-torque windmilling conditions. The results are compared against steady-state operating points from three-dimensional (3D) Reynolds-averaged Navier–Stokes (RANS) computational fluid dynamics (CFD) simulations. The accuracy of the low-order tools in reproducing the results from high-fidelity CFD is analysed, and the trade-off with the computational cost of each method is discussed. The low-order tools presented are shown to offer a fast alternative to traditional CFD which can be used to predict the performance in sub-idle conditions of a new compressor design during early development stages.

Comparative study on analytical and computational aerodynamic models for flapping wings MAVs

ABSTRACTA range of quasi-steady and unsteady aerodynamic models are used to predict the aerodynamic forces experienced by a flapping wing and a detailed comparison amongst these predictions in provided. The complexity of the models ranges from the analytical potential flow model to the computational Unsteady Vortex Lattice Method (UVLM), which allows one to describe the motion of the wake and account for its influence on the fluid loads. The novelty of this effort lies in a modification of the predicted forces as a generalisation of the leading edge suction analogy. This modification is introduced to account for the delayed stall mechanism due to leading edge flow separation. The model predictions are compared with two sets of independent experimental data and with computational fluid dynamics (CFD) simulation data available in the literature. It is found that both, the modified analytical model and the UVLM model can be used to describe the time history of the lift force, in some cases with better results than a high-fidelity CFD model. The models presented here constitute a useful basis for the aerodynamic design of bioinspired flapping-wings micro-air vehicles.

Data-driven modeling of the chaotic thermal convection in an annular thermosyphon

dentifying accurate and yet interpretable low-order models from data has gained a renewed interest over the past decade. In the present work, we illustrate how the combined use of dimensionality reduction and sparse system identification techniques allows us to obtain an accurate model of the chaotic thermal convection in a two-dimensional annular thermosyphon. Taking as guidelines the derivation of the Lorenz system, the chaotic thermal convection dynamics simulated using a high-fidelity computational fluid dynamics solver are first embedded into a low-dimensional space using dynamic mode decomposition. After having reviewed the physical properties the reduced-order model should exhibit, the latter is identified using SINDy, an increasingly popular and flexible framework for the identification of nonlinear continuous-time dynamical systems from data. The identified model closely resembles the canonical Lorenz system, having a similar structure and exhibiting the same physical properties. Finally, extensions to other flow configurations with or without control are discussed.

Automatic Shape Optimization of Patient-Specific Tissue Engineered Vascular Grafts for Aortic Coarctation.

This paper proposes a computational framework for automatically optimizing the shapes of patient-specific tissue engineered vascular grafts. We demonstrate a proof-of-concept design optimization for aortic coarctation repair. The computational framework consists of three main components including 1) a free-form deformation technique exploring graft geometries, 2) high-fidelity computational fluid dynamics simulations for collecting data on the effects of design parameters on objective function values like energy loss, and 3) employing machine learning methods (Gaussian Processes) to develop a surrogate model for predicting results of high-fidelity simulations. The globally optimal design parameters are then computed by multistart conjugate gradient optimization on the surrogate model. In the experiment, we investigate the correlation among the design parameters and the objective function values. Our results achieve a 30% reduction in blood flow energy loss compared to the original coarctation by optimizing the aortic geometry.

Numerical simulation and evaluation of spacer-filled direct contact membrane distillation module

Membrane fouling and temperature polarization are the most common issues that cause limitations to membrane distillation (MD) process. Integration of spacers has been proven to resolve those problems by inducing regions of turbulence and giving the required mechanical support to the membrane. In this work, a robust high-fidelity computational fluid dynamics simulation is carried out to assess and quantify the performance of spacer-filled DCMD module and compare it with a baseline spacer-free DCMD module. Mainly, simulations are done to delineate the problem of concentration polarization and by alternating spacers material with different thermal conductivities and different displacement configurations. The performance of these different models is demonstrated in terms of concentration boundary layer development, temperature distributions, temperature polarization coefficient (TPC), mass flux, heat flux, heat transfer coefficient, and thermal efficiency. Results show that concentration polarization can penalize mass flux by nearly 10%, and conductive spacers have favorable effect on the DCMD performance compared to spacer-free in terms of TPC by 50%, mass flux by 35%, heat flux by 31%, thermal efficiency by 1%, and top and bottom membrane surface heat transfer coefficients of, respectively, 19% and 62%. Meanwhile, the stride of the spacers in the range of 1.5–3.5 mm tends to achieve a measurable mass flux. Generally, spacers integration has confirmed the capability of reducing concentration polarization at the membrane surface. These attained improvements will accelerate industrial deployments of MD.