High-fidelity Computational Fluid Dynamics Research Articles

Experimental study of a suspended subsea module at different positions in the splash zone

During the lifting of submerged marine modules, the highest dynamic loads occur in the splash zone. These forces are highly dynamic and cannot easily be estimated with sufficient accuracy using simple calculations or high-fidelity computational fluid dynamics because of their irregular and complex geometries. We conducted an experimental study in a wave tank to investigate the dynamics of a large subsea module in the splash zone subject to irregular waves. The experiments were conducted using a 1:8 scale model of a subsea module, similar to that designed by Offshore Oil Engineering Co., Ltd., for the subsea pipeline from the Wenchang gas fields to the Yacheng pipeline. The model was examined at five different positions relative to the free surface, from completely above the surface to fully submerged. The resulting data are analyzed in the time and frequency domains. Spectral analysis and a dynamic effect parameter are used to analyze the dynamic loads on the subsea module. Several time-domain numerical analyses are performed with different peak periods, and the tension of the sub-slings is obtained. The experimental results for the relative forces and motions of the subsea module are presented, providing a reference for the design of other similar modules and their installation and validation data for computational modeling.

Cooling system design for the internal combustion engine of a BWB UAV prototype

The current study presents an analytical design methodology for a compact thermal management system (cooling system) of a high-power density internal combustion rotary engine. The engine is installed on a fixed wing, tactical Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV) prototype that has been developed for the aerial delivery of cargo and lifesaving supplies. The design methodology is based mainly on a low-fidelity thermodynamic model and on high-fidelity Computational Fluid Dynamics (CFD) analyses. The results are validated against wind tunnel experiments for the cooling system of the engine. The overall methodology is divided into two distinct segments, the design of the heat exchanger (HEX) and the sizing of the cold-air inlet ducts. The low-fidelity thermodynamic model is based on 0D and 1D textbook methods and well-established formulae from the existing literature. The thermodynamic model is used for the calculation of the geometrical characteristics of the HEX. The high-fidelity CFD modeling is employed to yield a more detailed investigation of the flow field around the HEX and provide information about whether the airflow velocity requirements, for the 0D and 1D model, are met. Additionally, the detailed CFD computations assist the design of high-efficiency inlet ducts, in order to secure optimal airflow through the HEX and around the engine compartment. Using the proposed methodology, a functional HEX experimental prototype is designed and manufactured, as a proof of concept, in order to be thoroughly examined on a test rig in laboratory conditions. Multiple experiments are conducted in a variety of inlet temperatures and airflow velocities, for the validation and fine-tuning of the overall proposed design methodology. The study concludes with the final HEX design, as well as an analysis of its integration aspects on the tactical BWB UAV prototype.

High-Fidelity CFD Validation and Assessment of Ducted Propellers for Aircraft Propulsion

This paper presents validation and assessment of ducted propellers for aircraft propulsion. Numerical methods and simulation strategies are put forward, including steady/unsteady high-fidelity computational fluid dynamics (CFD) simulations and simpler momentum-based methods. The validation and comparisons of the methods are made using a ducted propeller proposed by NASA. Simulations are also performed and analyzed at extended advance ratios, blade pitch setting, and cross-wind angles. Comparisons are also made with open propeller counterparts. The ducted propeller shows superior performance over its unducted counterpart in hover and at low advance ratios. The major thrust gain is identified from the combination of duct leading-edge suction and the higher pressure at the diffuser exit. The propeller is off-loaded due to the higher inflow velocities. The ducted propeller is also shown to have less intrusive wake features at low axial speeds. However, as the advance ratio increases, the duct thrust contribution becomes negative and the ducted propeller becomes deficient, due to growing high-pressure areas at the leading edge. At cross-wind, high-fidelity CFD simulations offer accurate aerodynamic loads predictions despite the complex flow features. The duct surface separation is found to be delayed due to the propeller suction, while the propeller is shown shielded by the duct, thereby suffering less from the unbalanced inflow velocities. Decomposition of induced velocities by each part is carried out and presented. A large, nonlinear extra induction component, due to mutual interactions of the duct and the propeller, is observed and found favorable for the performance augmentation.

Aeromechanical Analysis of a Complete Wind Turbine Using Nonlinear Frequency Domain Solution Method

Abstract The high-fidelity computational fluid dynamics (CFD) simulations of a complete wind turbine model usually require significant computational resources. It will require much more resources if the fluid–structure interactions (FSIs) between the blade and the flow are considered, and it has been the major challenge in the industry. The aeromechanical analysis of a complete wind turbine model using a high-fidelity CFD method is discussed in this paper. The distinctiveness of this paper is the application of the nonlinear frequency domain solution method to analyze the forced response and flutter instability of the blade as well as to investigate the unsteady flow field across the wind turbine rotor and the tower. This method also enables the aeromechanical simulations of wind turbines for various interblade phase angles in a combination with a phase shift solution method. Extensive validations of the nonlinear frequency domain solution method against the conventional time domain solution method reveal that the proposed frequency domain solution method can reduce the computational cost by one to two orders of magnitude.

Computational Aerodynamics Study of Competing Conceptual Designs for Advanced Tactical Fighter Aircraft

Advanced tactical fighter (ATF) configurations are bound to perform high angle of attack (AoA) maneuvers. However, existing conceptual design tools available in aerospace industry are based on empirical or potential flows that cannot predict aerodynamic data in nonlinear regimes. High-fidelity computational fluid dynamics algorithms have to be incorporated during conceptual design phase for better assessment between competing configurations. In this research, steady state aerodynamic analysis is conducted to compare four conceptual designs of advanced tactical fighters through Reynolds-averaged Navier–Stokes (RANS) simulations. Prior to the study, two validation test cases were conducted based on ONERA M6 Wing and benchmark unmanned combat air vehicle (UCAV) design to assess the computational setup for the problem. Pressure based solver is used to model the flow field in subsonic, transonic and supersonic regimes at sea level for all four competing designs. The quantitative results include the aerodynamic forces and the longitudinal stability coefficient comparisons among the models and its components. The qualitative analyses include pressure distribution, eddy shedding and behavior of vortices at varying flow angle. Additionally, the empirical estimation for interpolation and post-stall extrapolation are carried out for further flight performance studies.

Particle Velocimetry, CFD, and the Role of Particle Sphericity in Cold Spray

Implementation of the cold spray (CS) technology in manufacturing and repair creates a demand for reliable quality control and process monitoring measures. In this regard, particle size and impact velocity are undoubtedly the most important control parameters in CS. Several in-flight measurement systems for particle velocimetry are now available commercially for CS. These systems provide great potential to be used as a diagnostic tool for validating CS system performance in industrial applications. However, post processing the velocimetry data is required in many instances for achieving a complete understanding of the particle flow field. In this study, particle velocimetry is used in conjunction with computational fluid dynamics (CFD) simulations to: (i) identify the physical factors that dictate the particle velocity and its variability; (ii) develop high fidelity CFD models to accurately predict particle flight parameters that cannot be measured by available experimental tools; and (iii) present the capabilities of state-of-the-art velocimeters as a reliable diagnostic tool for measuring the consistency and repeatability of CS systems in manufacturing settings. In-flight particle size, location, and velocity are measured using a commercially available velocimeter for aluminum and copper particles sprayed with supersonic nozzles using helium, nitrogen, and air by two high pressure CS systems. As a result of this work, particle sphericity was clearly identified to have strong effects on particle velocity and to be one of the main factors of the variability of particle velocity. Furthermore, methods for building a high-fidelity 3D-CFD model was presented. CFD models were validated using particle velocimetry and schlieren imaging. Finally, particle velocimetry is shown to be a valid diagnostics tool for CS with systems capable of measuring in-flight particle velocities along with particle sizes. This article also outlines steps necessary for conducting cold spray process diagnostics repeatably and reliably.

Fluid dynamics simulations show that facial masks can suppress the spread of COVID-19 in indoor environments

The coronavirus disease outbreak of 2019 has been causing significant loss of life and unprecedented economic loss throughout the world. Social distancing and face masks are widely recommended around the globe to protect others and prevent the spread of the virus through breathing, coughing, and sneezing. To expand the scientific underpinnings of such recommendations, we carry out high-fidelity computational fluid dynamics simulations of unprecedented resolution and realism to elucidate the underlying physics of saliva particulate transport during human cough with and without facial masks. Our simulations (a) are carried out under both a stagnant ambient flow (indoor) and a mild unidirectional breeze (outdoor), (b) incorporate the effect of human anatomy on the flow, (c) account for both medical and non-medical grade masks, and (d) consider a wide spectrum of particulate sizes, ranging from 10 µm to 300 µm. We show that during indoor coughing some saliva particulates could travel up to 0.48 m, 0.73 m, and 2.62 m for the cases with medical grade, non-medical grade, and without facial masks, respectively. Thus, in indoor environments, either medical or non-medical grade facial masks can successfully limit the spreading of saliva particulates to others. Under outdoor conditions with a unidirectional mild breeze, however, leakage flow through the mask can cause saliva particulates to be entrained into the energetic shear layers around the body and transported very fast at large distances by the turbulent flow, thus limiting the effectiveness of facial masks.

Torrents of torment: turbulence as a mechanism of pulsatile tinnitus secondary to venous stenosis revealed by high-fidelity computational fluid dynamics

BackgroundPulsatile tinnitus (PT) is a debilitating condition that can be caused by a vascular abnormality, such as an arterial or venous lesion. Although treatment of PT-related venous lesions has been...

Multi-point design optimization of a high-performance intake for scramjet-powered ascent flight

Scramjet engines are one of the most promising hypersonic airbreathing propulsion techniques for efficient and economic access to space. Besides capturing and compressing the air to desirable flow conditions, the intake plays a vital role in determining the intake drag, flow compression efficiency, started flow condition that governs the overall scramjet engine performance. For access to space, the flight trajectory practically comprises varying freestream conditions and altitude to enable ascent flight, constituting an optimization problem with off-design conditions as well as design and physical constraints to be considered. This paper presents the results and insights obtained from a first ever multi-point multi-objective optimization study of an axisymmetric scramjet intake conducted by means of surrogate-assisted evolutionary algorithms coupled with high-fidelity computational fluid dynamics. It aims to minimize the intake drag and maximize the compression efficiency at two differing conditions, i.e., Mach 7.7 at an altitude of 30 km and Mach 10 at 33.5 km. Key design factors for high-performance intakes that can achieve desirable flow compression for the combustor are identified by global sensitivity analysis and examining the trade-off characteristics. Underlying flow physics is elucidated by probing into the representative flowfields at two design conditions with adaptive mesh refinement so as to gain insights into phenomena and characteristics to realize scramjet-powered ascent flight. It has been found that the non-dominated solutions constitute clusters with respect to length and exit radius, with each cluster characterized by distinct tendencies in terms of compression efficiency loss, total drag, static pressure ratio and mean exit temperature. Shorter scramjet intakes have been found to be prone to flow separation due to impingement of a reflected shock off the centerline on the third ramp that causes an adverse pressure gradient.

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.