Full CFD Simulations Research Articles

Inductive plasma excitation forcing configuration on reduction of tip distorted inflow effect on the aerodynamic stability of axial compressor rotor

This research delves into the mitigating impacts of dielectric barrier discharge (DBD) plasma excitation induced forcing orientation against the detrimental consequences of distinct radial tip distortions which in turn affect the axial compressor rotor performance and alters the flow structure at the tip region. Full annulus transient CFD simulation was utilized to evaluate the consequences of plasma actuation at distorted conditions with different blockage percentages. Beyond flow field and frequency analysis, the study further characterized rotor performance under different conditions by evaluating key performance metrics, including total pressure rise coefficient, stall margin variation, and span-wise rotor inlet velocity distribution. The injection of momentum caused by plasma actuators to the low-energy region behind the distortion screens proved to be effective on rotor aerodynamic stability facing radial tip distortion. In the case where 15 % of the inlet area was blocked, the stall margin varied from -8 % to -3.5 % with axial plasma actuators in action. However, the best configuration of plasma actuators for the enhancement of the stall margin and flow characteristics was identified to have opposite forcing direction with respect to the rotor rotational velocity. Additionally, these actuators suppressed frequencies caused by fluctuations in the rotor blade row tip leakage vortex, suggesting an improvement in the flow pattern within the rotor tip area.

Experimental and numerical validation of a hybrid method for modelling the wake flow of two in-line wind turbines

To forecast the wake flow and power reduction affecting downstream turbines reliably and accurately, a hybrid wake model CFD(ALM)-IDWM was improved, in which the forecasting of Vθmax is improved from linear to cubic. Then, a partially overlapping computational domain is added behind the far-wake domain of upstream wind turbine to calculate the aerodynamic performance of a downstream wind turbine, and the numerical model of full CFD(ALM) and CFD(ALM)-IDWM for two in-line wind turbines are developed. Subsequently, a wind tunnel model test on two in-line wind turbines was carried out to validate the full CFD(ALM) model firstly. Subsequently, the hybrid model of CFD(ALM)-IDWM is numerically validated by the full CFD(ALM) simulations. The results show that CFD(ALM)-IDWM cannot only predict the wake characteristics such as vortices and wakes in the wake region more accurately, but can also accurately simulate the average values of the downstream turbine thrust and torque. By ignoring certain flow field details including acceleration, turbulent viscosity, and Reynolds stress during the simulation process, the computational time is reduced. Base on the same CFD(ALM), the computation time of CFD(ALM)-IDWM was approximately 60% of that of full CFD(ALM). The longer the computational domain of IDWM, the greater reduction in computational time.

Multi-fidelity modeling and analysis of a pressurized vessel-pipe-safety valve system based on MOC and surrogate modeling methods

A pressurized vessel-pipe-safety valve (PVPSV) combination is a commonly used configuration in nuclear power plants, and a good numerical model is essential for the system design, sizing and performance optimization. However, owing to the large-scale and cross-scale features, it is still a challenge to build a system level numerical model with both high accuracy and efficiency. To overcome this, a novel system level modeling method which can synthesize the advantages of various models is proposed in this paper. For system modeling, the analytical approach, the method of characteristics (MOC) and the surrogate model approach are respectively adopted to predict the dynamics of the pressure vessel, the connecting pipe and the safety valve, and different models are connected through data interfaces. With this system model, dynamic simulations were carried out and both the stable and the unstable system responses were obtained. For the model verification purpose, the simulation results were compared with those obtained from experiments and full CFD simulations. A good agreement and a better efficiency were obtained, verifying the ability of the model and the feasibility of the modeling method proposed in this paper.

Influence of train roof boundary layer on the pantograph aerodynamic uplift: A proposal for a simplified evaluation method

The mean contact force between pantograph collectors and contact wire is affected by the aerodynamic uplift generated by aerodynamic forces acting on pantograph components. For a given pantograph geometry, orientation and working height, aerodynamic forces are strongly influenced by the position of the pantograph along the train roof, since an aerodynamic boundary layer grows along the train.This paper shows the experimental results of aerodynamic uplifts of full-scale pantographs located at four different positions along the roof of a high-speed train and adopts CFD simulations to examine the effect of the boundary layer velocity profile on the measured experimental forces. It is quantitatively demonstrated that the same pantograph located at different positions along the train roof can show relevant differences in the aerodynamic uplift, only due to the different flow characteristics.Moreover, a new simplified methodology is proposed to evaluate the aerodynamic uplifts at different positions of the pantograph along the train. Results of the proposed methodology are validated against full scale experimental results and full CFD simulations exploiting the complete model of the pantograph installed on the train roof.

Non-axisymmetric complete flow conditioning gauzes

This paper presents a novel methodology for the design of a gauze that produces distributions of stagnation pressure, swirl angle, pitch angle and turbulence intensity, tailored in both the radial and circumferential directions. A distortion gauze is made from a large number of small-scale circumferential and radial blades with tailored thickness and camber distributions. By controlling the blade design independently in both the radial and circumferential directions, the target inflow pattern can be achieved. 1D correlations are used to initialise the blades and they are refined using full 3D CFD simulations. The final design is additively manufactured for use in rotating rigs. In this paper, the method has been used to reproduce four target inflow patterns with large variations in stagnation pressure and flow angularity. Two examples model the inlet flow distortion seen at the aerodynamic interface plane of an aft-mounted boundary layer ingesting fan. The final two examples model the inlet distortion at inlet to an axial compressor spool caused by upstream structural struts in a swan neck duct. The gauzes are shown to replicate the structures of the target flow in an experimental test. These kind of flow structures would be extremely difficult or impossible to replicate in an experiment in any other way.Graphical abstract

Efficient and high-resolution simulation of pollutant dispersion in complex urban environments by island-based recurrence CFD

We applied data-based recurrence CFD (rCFD) to model pollutant dispersion in near-field flow configurations. In case of complex topologies, the global-domain version of rCFD fails to account for local recurrent flow features. We therefore developed a novel island-based version of rCFD, which partitions the computational domain to isolate islands of high recurrence prominence, and subsequently defines a distinct recurrence path for each of these islands. We applied island-based rCFD to pollutant dispersion for two side-by-side cubical buildings with three different gap widths in between them and a real urban environment. We showed that numerical predictions of pollutant dispersion by island-based rCFD were in excellent agreement with full CFD simulations, thus outperforming the global-domain version of rCFD. In both applications, island-based rCFD simulations ran three orders of magnitude faster than corresponding full CFD simulations. In the second application, this speed-up enabled real-time simulations on a computational grid of 10 million cells.

Optimized design of obstacle sequences for microfluidic mixing in an inertial regime.

Mixing is a basic but challenging step to achieve in high throughput microfluidic applications such as organic synthesis or production of particles. A common approach to improve micromixer performance is to devise a single component that enhances mixing through optimal convection, and then sequence multiple such units back-to-back to enhance overall mixing at the end of the sequence. However, the mixing units are often optimized only for the initial non-mixed fluid composition, which is no longer the input condition for each subsequent unit. Thus, there is no guarantee that simply repeating a single mixing unit will achieve optimally mixed fluid flow at the end of the sequence. In this work, we analyzed sequences of 20 cylindrical obstacles, or pillars, to optimize the mixing in the inertial regime (where mixing is more difficult due to higher Péclet number) by managing their interdependent convection operations on the composition of the fluid. Exploiting a software for microfluidic design optimization called FlowSculpt, we predicted and optimized the interfacial stretching of two co-flowing fluids, neglecting diffusive effects. We were able to quickly design three different optimal pillar sequences through a space of 3220 possible combinations of pillars. As proof of concept, we tested the new passive mixer designs using confocal microscopy and full 3D CFD simulations for high Péclet numbers (Pe ≈ O(105-6)), observing fluid flow shape and mixing index at several cross-sections, reaching mixing efficiencies around 80%. Furthermore, we investigated the effect of the inter-pillar spacing on the most optimal design, quantifying the tradeoff between mixing performance and hydraulic resistance. These micromixer designs and the framework for the design in inertial regimes can be used for various applications, such as lipid nanoparticle fabrication which has been of great importance in vaccine scale up during the pandemic.

Electrochemical Modeling of PEM Fuel Cells

New alternatives to traditional petrol vehicles are required to reform the transport industry, which currently contributes nearly 30% of all greenhouse gas emissions in North America. One such alternative is Fuel Cell Electric Vehicles. Fuel cells directly convert chemical energy contained in fuels, such as hydrogen, into electricity, and hence provide a hybrid solution that combines the advantages of internal combustion engines and battery. However, the higher cost, lower durability, and lack of fueling infrastructure have typically hindered their commercialization. In order to address the first two challenges, it is crucial to understand the electrochemical behavior of fuel cells via mathematical models. Such models range from lumped models, which provide simple formulas for voltage-current response curves, to full CFD simulations, which can resolve complex physical phenomena in space and time but come at a high computational cost. The aim of this work is to provide intermediate models for proton-exchange membrane (PEM) fuel cells that are as accurate as possible while solvable in real-time.In this work, we begin with a two-dimensional model of a PEM fuel cell based on Refs. [1] and [2]. The two dimensions are the “along-the-channel” dimension, and the “through-cell” dimension, which is much thinner. This model characterizes mass- and heat-transport related phenomena and hence facilitates water management in cells and membrane electrode assemblies. By nondimensionalizing the model and considering various physically relevant parameter limits, we derive a simplified reduced-order model that accurately reproduces the results of the full model at a much smaller computational cost. The reduced-order model has distributed states along the channel and lumped states in the through-plane dimension.We compare our final reduced-order model to experimental measurements of spatial channel and GDL water distributions obtained using neutron imaging [3]. We find generally good agreement but identify some innate discrepancies. In order to improve the accuracy of our model, we use the Field Inversion and Machine Learning (FIML) modeling paradigm [4, 5]. This consists of inverse modeling to identify the spatial distribution of model discrepancies, and machine learning to learn the dependence of these fields on other model states and hence allow predictive modeling. A key advantage over purely data-driven methods is that the solutions must always satisfy physical laws enforced by the mathematical model, and so only limited data is required. We apply the FIML methodology to our PEM fuel cell model, and hence learn corrections that reduce discrepancies with the experimental data. We show that improved agreement with the experimental data can be obtained in operating conditions that were not used to train the model. The authors acknowledge funding from Toyota Motor Engineering and Manufacturing North America.

Dynamic models and control system design for heated channels in a Canadian SCWR

The proposed Canadian SCWR is based on the concept of the CANDU reactor. However, the dynamic characteristics of the SCWR significantly differ from the CANDU reactor because of the special heat transfer phenomenon of the supercritical water in the fuel bundle. Thus, it is important to design a control system to maintain the SCWR operating at the required operating point when it is subjected to disturbances. The transient CFD simulations of the heated channels in a Canadian SCWR are conducted in order to obtain the dynamic relationship between the inputs and outputs of the SCWR. Then, the linear dynamic control models are constructed by the system identification technique based on the dynamic relationship between the inputs and outputs obtained from the CFD simulations. The linear dynamic models are validated using the results from the full scale non-linear CFD simulations. Based on the linear dynamic models, a closed-loop control system, which consists two PID controllers, is designed. The performance evaluation of the proposed control system is also carried in this work.

An overset RaNS prediction and validation of full scale stern wake for 1,600TEU container ship and 63,000 DWT bulk carrier with an energy saving device

Two merchant ships (1,600TEU container ship, 63,000DWT bulk carrier with a type of pre-swirl duct energy saving device in the stern) are subjected to viscous CFD analysis aiming to investigate the capability of viscous CFD to estimate stern wake in full scale. Rigorous validations are made for the computational results of resistance, propulsion parameters and local flow fields using available measurement data both in model and full scale for the two vessels. The verification study for the container ship in full scale shows the difficulty to achieve grid convergence in propulsion parameters, yet the solution difference for these parameters are mostly below 1.7% of fine grid (~12M cells) solution. The effect of surface roughness becomes apparent not only in powering estimation but also in nominal and total wake distributions. The propeller rotation speed for the container ship in full scale is estimated well by the present CFD within 0.2% of difference compared to the measured data in full scale when the surface roughness is considered in the computation. The total wake in full scale in the vicinity of stern/ESD predicted by the present CFD simulation agree very well to the optical measurement data when the surface roughness is taken into consideration. Investigation of the total wake for the bulk carrier implies that the ESD should be designed based on the flow including both scale effect and the surface roughness. Throughout the validation and investigation of the present computational results in full scale, several common practices are suggested for predicting stern flow using full scale viscous CFD simulation together with the existing recommended procedures and guidelines by the ITTC.

Projection-based and neural-net reduced order model for nonlinear Navier–Stokes equations

This paper presents complete steps for the construction and solution algorithm for a projection-based reduced order model coupled with an artificial neural net model. The reduced model is constructed based on the Galerkin projection of the equations governing the physical processes on reduced subspaces obtained by the Proper Orthogonal Decomposition method. The projection is done using numerical discretisation schemes implemented in the commonly used OpenFOAMⓇ platform. The neural net model is trained using the Nonlinear AutoRegressive eXogenous model network (NARX) architecture. The reduced order models are demonstrated for true predictions of incompressible flows at low Reynolds numbers driven by various boundary conditions. Compared with the full CFD simulations, this model shows excellent agreement while only requiring a fraction of the computational resources.

Can pulsation unsteadiness increase the convective heat transfer in a pipe flow? A systematic study

Unsteady laminar and turbulent pipe flows subjected to a constant temperature gradient in axial direction are investigated based on asymptotic considerations. The thermal boundary condition is that of a constant wall heat flux for a steady flow. The unsteadiness is induced by a sinusoidal pressure gradient with different amplitudes and frequencies. The asymptotic analysis is performed with the help of selected CFD simulations. The simulation model is a pipe which is assumed to be infinitely long with an ideal condition of fully developed flow at the pipe entrance. For laminar flows there is no effect with respect to the time averaged heat transfer performance. For turbulent flows appreciable heat transfer enhancement only occurs with large amplitudes and low frequencies. The asymptotic analysis with CFD results are in accordance with the conclusions according to full CFD simulations. Their computational costs, however, are several orders lower. The study shows that, prior to expensive CFD simulations, an asymptotic analysis with CFD simulations at ideal conditions can be considered to find the trend with respect to the parameters of interest.

Actuator 기법을 이용한 프로펠러 3축 성분 힘/모멘트 해석

For aerodynamic performance and stability analysis of distributed propulsion aircraft which adopt many propellers/rotors, all the 3-axial components forces and moments must be properly taken into account. In this study, two actuator methods have been established to be capable of numerical simulations including all the force and moment components produced by rotor/propeller. A procedure in which the 3-axial components are transformed from the aerodynamic force and moment of blade elements has been added to actuator disk method(ADM) and actuator surface method(ASM). The numerical analyses are carried out for a single propeller of quad tilt propeller(QTP) at various flight conditions including the variation of side slip angle. The results are compared with wind tunnel test data and full CFD simulation with overset grid. All the force and moment components are found to agree very well in terms of engineering purposes and the present methods are identified to be numerically very efficient compared to full CFD. Power-on effect and longitudinal stability of the full configuration of QTP is further analyzed by carrying out the additional numerical simulations. The results indicate that the present methods is practically very useful to investigate the aerodynamic performance of distributed propulsion aircraft.

Conjugate heat transfer model for feedback control and state estimation in a volumetric solar receiver

Open volumetric solar receivers (VSRs) are a promising technology for concentrated solar power plants due to their capability to provide heat using ambient air as the working fluid operating at temperatures over 700°C. Nevertheless, VSRs are challenged by the unsteadiness and high intensity of the radiation flux, which may cause unreliable or unsafe outflow temperatures, and may compromise the lifetime of the porous ceramic absorbers due to extreme thermal loads, thermal shock or thermal fatigue. We propose a data assimilation framework to address these matters using blower actuation, measurements from sensors located in the outflow stream of air, and a model for the conjugate heat transfer in an open VSR. We formulate said model and compare it against full three-dimensional CFD simulations to show that it captures the relevant dynamics while reducing the computational cost enough to allow for online calculations. A linear quadratic Gaussian (LQG) controller is used with the model to perform simultaneous state estimation and feedback control in three simulated scenarios. Our framework proves capable of stabilizing outflow air temperatures during the passing of a cloud, estimating the radiation flux hitting the absorber during daily operation, monitoring temperature cycling in the solid matrix, and avoiding extreme temperature gradients during start-up procedures. Artificial noise and disturbances are added to the system for all scenarios and the LQG controller proves to be robust, rejecting disturbances and attenuating noise, as well as compensating for model uncertainty.

UH-60A Rotor Analysis with an Accurate Dual-Formulation Hybrid Aeroelastic Methodology

Dual-solver hybrid methodologies that couple fluid solvers in different regions of the flowfield have been developed to accelerate convergence with minimal compromises in accuracy. A new dual-solver hybrid analysis framework that addresses some of the major shortcomings of prior dual-solver hybrid methodologies has been developed through an academic–industry partnership. In this effort, one of the hybrid solvers, comprising of a computational fluid dynamics–computational structural dynamics (CFD-CSD) solver coupled with a Lagrangian wake-panel module, is assessed. The hybrid solver’s ability to replicate the accuracy of the more expensive CFD-CSD approach and its ability to capture the physics of the rotor system are presented. The criteria that have been evaluated include integrated aerodynamic performance quantities, structural loads and moments, and near-body wakes. If the best practices extracted from this analysis are applied, the analysis with a reduced off-body CFD mesh is able to predict forward-flight rotor behavior that is within 4% of a full CFD simulation with up to 70% cost savings. This accuracy has been assessed on both high-speed and high-thrust flight conditions and has been quantitatively verified for aerodynamic, structural, and hub variables of interest at a number of radial blade stations for a frequency range of 0–16/rev.

A novel wake model for yawed wind turbines

One of the current major challenges in wind energy is to maximize energy production of wind farms. One approach in this effort is through control of wind turbine wake interactions, since undesirable wake interactions can introduce additional mechanical stresses on turbines, leading to early failures and reduce overall energy production of wind farms. To develop control strategies that can minimize wake interactions, it is essential to simulate wake behaviors accurately and quickly. In this work, a fast and accurate turbine wake model capable of modeling turbine wakes under yaw is presented. This model builds upon the work of existing wake models and is capable of producing results comparable to that of conventional full CFD simulations using a fraction of the computational cost. The accuracy and speed of the proposed model allows for the development of real-time turbine control strategies to maximize power output. The results of the proposed model are validated with previous numerical and experimental data.

USAGE OF DIGITAL TOOLS FOR THE OPTIMUM PROPELLER DESIGN

The usage of more sophisticated design and analysis tools have become prevalent in all industries. In order to get the true value out of these numerical tools, the actual design requirements need to be defined properly and in general, this leads to the question of how to find the right balance between conflicting requirements. More feedback on the performance of a design can be obtained with usage of numerical simulations within the design evaluation phase and with digital data collection tools in the operational phase. With the implementation of CFD simulations in the design cycle, unforeseen deviations with model testing campaigns and actual full scale sea trials has reduced, and collection of actual vessel operational data, in combination with a system simulation approach generates further insight in the actual operation, which can be used to further fine-tune the design philosophy. Detailed evaluation of the results from full scale CFD simulations have revealed interesting phenomena related to the Reynolds scaling effects of ducted propellers.

Process control of through-flow reactor operation by real-time recurrence CFD (rCFD) simulations – Proof of concept

We resolve dynamic species transport in a turbulent through-flow reactor by means of recurrence CFD (rCFD). In order to incorporate rCFD into a process control loop, the existing real-time simulation methodology (Pirker and Lichtenegger, 2018) has been further developed significantly.First and foremost, we propose an interpolation methodology which enables the representation of intermediate pseudo-periodic flows in-between two recurrence databases. Interpolated rCFD predictions agree very well with corresponding full CFD results with respect to mean concentration, concentration histograms as well as spatial line profiles and temporal point monitors of concentration. We further apply interpolated rCFD to unsteadily varying through-flow conditions, achieving consistently good predictions. Next, we considered reactive and non-isothermal flow. Still, rCFD predictions agree very well with full CFD simulations with respect to the unsteadily evolving fields of species concentration and temperature. At the same time rCFD simulations run four orders of magnitude faster than corresponding full CFD simulations, yielding faster-than-real-time predictions of the evolving concentration fields.This paves the way towards a rCFD-based process control, such that (1) a recurrence database is selected based on process dynamics before (2) point probe of passive scalars are extrapolated by rCFD to high-resolution field data, which are (3) reduced to descriptive scalars, serving for (4) process actuation.We prove the feasibility of rCFD-based process control for (i) outflow concentration control and for (ii) local hot-spot suppression.

Simplified partitioning model to simulate high pressure under-expanded jet flows impinging vertical obstacles

Various reduced-order models have been developed to quickly model high pressure underexpanded jets. One example is the two-layer partitioning model which was developed to model underexpanded jets, but it has not been evaluated for high pressure jets with obstacles in the jet flow region. This research describes an improved two-layer partitioning model based on the Abel-Noble equation of state that is applied here to model horizontal jet flows impacting a vertical obstacle with validations against high pressure gas experiments, full CFD simulations and a revised notional nozzle model based on the Abel-Noble equation of state. The improved two-layer partitioning model accurately predicts the gas concentrations on the obstacle for a 15 MPa underexpanded jet while consuming much less computational resources and time compared with the full CFD simulation.

Efficient time-extrapolation of single- and multiphase simulations by transport based recurrence CFD (rCFD)

We present a novel recurrence CFD (rCFD) method for the efficient simulation of passive scalar transport in pseudo-periodic flows.rCFD transfers full CFD(-DEM) simulations into a purely Lagrangian description of scalar transport by evaluating trajectories of fluid tracers and discrete particles. These trajectories are subsequently converted into cell to cell shift operations, resulting in data shift pattern on a computational grid. Finally, a recurrence process, based on the statistics of the full CFD(-DEM) simulation, controls the sequence of consecutive frames of data shift patterns.First, we applied rCFD to species transport in single-phase large eddy simulations, yielding excellent agreement with corresponding full CFD simulations. Second, we addressed heat transfer in a bubbling fluidized bed, yielding acceptable agreement with corresponding CFD-DEM simulations. In both cases, simulation times were reduced by more than four orders of magnitude without losing spatial resolution, resulting in faster than real-time simulations.Subsequently, we discuss existing model limitations such as (i) process periodicity, (ii) passiveness of transport, (iii) data storage requirements and (iv) physical diffusion and sketch possible future remedies. Concluding, we consider rCFD a promising bridging technology between full CFD simulations and online process prediction.