Conventional Computational Fluid Dynamics Research Articles

Prediction of Losses in Small Scale Axial Air Turbine Based on CFD Modelling

Efficient small scale axial air turbines play a major role in determining the overall conversion efficiency in certain energy cycles using renewable energy sources. Loss predictions are vital for the development and optimization of such small scale turbines. Since all published loss prediction schemes were developed for large scale turbines, therefore there is a need for an effective approach to predict such losses for the small scale axial turbines. This work aims to develop a new approach to predict the losses in a small scale axial air turbine using both conventional loss models and computational fluid dynamics (CFD) simulations. Results showed that the Kacker & Okapuu model gave the closest values to the CFD simulation results thus it can be used to produce the initial turbine design that can be further optimised through CFD simulations.

A passive scalar-based method for numerical combustion

A passive scalar-based method for analyzing unsteady combustion processes has been proposed. Transport equations for passive scalars have been derived based on mixture fraction concept widely used for the description of nonpremixed combustion. These equations can be solved together with the conventional computational fluid dynamics (CFD) governing equations so that these passive scalars are readily utilized to trace the mass transport in simulations of complicated reacting flows, regardless of turbulence and chemistry models. The approach is used together with large eddy simulation to study the cavity-stabilized H2 jet combustion in a supersonic combustor, where characteristics of the mass transfer into and out of the cavity are captured and cavity residence time is obtained for the first time under reacting flow conditions.

Fractional flow reserve derived from conventional coronary angiograms and computational fluid dynamics

Fractional flow reserve derived from conventional coronary angiograms and computational fluid dynamics

Enhancing nano-scale computational fluid dynamics with molecular pre-simulations: Unsteady problems and design optimisation

We demonstrate that a computational fluid dynamics (CFD) model enhanced with molecular-level information can accurately predict unsteady nano-scale flows in non-trivial geometries, while being efficient enough to be used for design optimisation. We first consider a converging–diverging nano-scale channel driven by a time-varying body force. The time-dependent mass flow rate predicted by our enhanced CFD agrees well with a full molecular dynamics (MD) simulation of the same configuration, and is achieved at a fraction of the computational cost. Conventional CFD predictions of the same case are wholly inadequate. We then demonstrate the application of enhanced CFD as a design optimisation tool on a bifurcating two-dimensional channel, with the target of maximising mass flow rate for a fixed total volume and applied pressure. At macro scales the optimised geometry agrees well with Murray’s Law for optimal branching of vascular networks; however, at nanoscales, the optimum result deviates from Murray’s Law, and a corrected equation is presented.

Cellular Automata-based Anthropogenic Heat Simulation 1

Abstract Cellular automata (CA) models have been for several years, employed to describe urban phenomena like growth of human settlements, changes in land use and, more recently, dispersion of air pollutants. We propose to adapt CA to study the dispersion of anthropogenic heat emissions on the micro scale. Three dimensional cubic CA with a constant cell size of 0.15 m have been implemented. Simulations suggest an improvement in processing speed compared to conventional computational fluid dynamics (CFD) models, which are limited in scale and yet incapable of solving simulations on local or larger scale. Instead of solving the Navier- Stokes equations, as in CFD, only temperature and heat differences for the CA are modeled. Radiation, convection and turbulence have been parameterized according to scale. This CA- based approach can be combined with an agent-based traffic simulation to analyse the effect of driving behavior and other microscopic factors on urban heat.

Transient CFD model of full TWC converter

A computational fluid dynamics (CFD) model capable of simulating the cold start transients in a full three way catalytic (TWC) converter is developed by coupling flow and temperature field inside the converter with a detailed chemistry solver. In the proposed model, full TWC chemistry, including oxygen surface coverage based ceria reactions, along with coupled mass transfer is solved using axial integration outside the CFD framework, whereas flow, gas and solid phase energy equations and coverage equations are solved in the CFD framework. The proposed implementation allows direct portability of the kinetics optimized in 1D framework leading to significant reduction in chemistry development time. A CFD converter model developed using the proposed approach leads to 20% reduction in simulation time compared to conventional continuum CFD models. The coupled CFD TWC model is used to predict conversion over the first 150 s of an FTP drive cycle without smoothening the input data.

A data assimilation methodology for reconstructing turbulent flows around aircraft

This paper proposes a new approach for the study of complex turbulent flows of aeronautics that integrates experimental fluid dynamics (EFD), employing methods such as wind tunnel experiments, and computational fluid dynamics (CFD) by using a data assimilation technique. The approach aims at representing complex turbulent flows more properly than conventional EFD and CFD approaches by estimating the proper angle of attack, the proper Mach number, and the proper turbulent viscosity, which are the three uncertainty factors in EFD and CFD. To this end, the ensemble transform Kalman filter (ETKF), a sequential advanced data assimilation method, is employed for the estimation and applied to transonic flows around the RAE 2822 airfoil (two-dimensional flow) and transonic flows around the ONERA M6 wing (three-dimensional flow). The results computed using the angles of attack, Mach numbers, and turbulent viscosities estimated by the ETKF diminish the discrepancies between the results of standard computations and experiments. These findings show the effectiveness of this approach, which combines EFD and CFD using data assimilation to represent complex turbulent flows.

Consistent lattice Boltzmann equations for phase transitions.

Unlike conventional computational fluid dynamics methods, the lattice Boltzmann method (LBM) describes the dynamic behavior of fluids in a mesoscopic scale based on discrete forms of kinetic equations. In this scale, complex macroscopic phenomena like the formation and collapse of interfaces can be naturally described as related to source terms incorporated into the kinetic equations. In this context, a novel athermal lattice Boltzmann scheme for the simulation of phase transition is proposed. The continuous kinetic model obtained from the Liouville equation using the mean-field interaction force approach is shown to be consistent with diffuse interface model using the Helmholtz free energy. Density profiles, interface thickness, and surface tension are analytically derived for a plane liquid-vapor interface. A discrete form of the kinetic equation is then obtained by applying the quadrature method based on prescribed abscissas together with a third-order scheme for the discretization of the streaming or advection term in the Boltzmann equation. Spatial derivatives in the source terms are approximated with high-order schemes. The numerical validation of the method is performed by measuring the speed of sound as well as by retrieving the coexistence curve and the interface density profiles. The appearance of spurious currents near the interface is investigated. The simulations are performed with the equations of state of Van der Waals, Redlich-Kwong, Redlich-Kwong-Soave, Peng-Robinson, and Carnahan-Starling.

An automated procedure for the optimal positioning of guide plates in a flow manifold using Box complex method

Flow splits and manifolds are encountered in many industrial processes such as heat recovery systems to feed reactant streams and take out product streams. Depending on the application, the flow distribution among the several outlets may be equal or unequal. In this paper we describe a computational method for achieving desired flow distribution in a flow manifold using optimally positioned guide plates. For multiple outlet streams, determining the orientation of the guide plates is a non-trivial problem. The positioning of one guide plate will have an effect on the flow rate through the other outlets. This effect cannot be estimated from simple models but can be calculated using computational fluid dynamics (CFD) simulation of the corresponding flow problem. However, a conventional CFD simulation cannot predict the optimal location of the guide plates. In view of this, we pose the flow distribution problem as a constrained optimization problem and use a well-established algorithm coupled to a computational fluid dynamics (CFD)-based flow solver to develop an automated procedure for the optimal positioning of the guide plates. The robustness of the procedure is illustrated for both equal and unequal flow distributions in a one-inlet, four-outlet manifold with guide plates of fixed and variable lengths.

Innovative Grid-Based Vorticity–Velocity Solver for Analysis of Vorticity-Dominated Flows

Unsteady vorticity-dominated flows are prevalent in a wide variety of engineering applications and are particularly challenging to predict efficiently. Perhaps in no other application is this more apparent than rotorcraft, where prediction is complicated by a wide variety of interactional aerodynamics between strong vortical wakes shed from rotating components and various bodies and wings immersed in the flow. While conventional computational fluid dynamics methods are equipped with the modeling capabilities to support these flow behaviors, they are subject to significant numerical diffusion whose practical import is that high computational costs involving large grids, complex adaptation methods, and high interpolation orders are required to produce sufficiently accurate simulations and prevent the artificial diffusion of vortical structures. Hybrid computational fluid dynamics methods that couple a body-fitted solver to a vorticity–velocity method hold considerable promise in alleviating these costs while effectively preserving vorticity. However, several fundamental and long-standing issues identified with vorticity–velocity methods have precluded their wider adoption. Here, the four most prominent concerns are addressed: 1) maintaining a solenoidal vorticity field; 2) supporting a low-dissipation/dispersion scheme on a general multiresolution grid; 3) providing a consistent and efficient implementation of the viscous terms; and 4) properly including the unsteady pressure contributions.

Continuous and Discrete Adjoint Approach Based on Lattice Boltzmann Method in Aerodynamic Optimization Part I: Mathematical Derivation of Adjoint Lattice Boltzmann Equations

AbstractThe significance of flow optimization utilizing the lattice Boltzmann (LB) method becomes obvious regarding its advantages as a novel flow field solution method compared to the other conventional computational fluid dynamics techniques. These unique characteristics of the LB method form the main idea of its application to optimization problems. In this research, for the first time, both continuous and discrete adjoint equations were extracted based on the LB method using a general procedure with low implementation cost. The proposed approach could be performed similarly for any optimization problem with the corresponding cost function and design variables vector. Moreover, this approach was not limited to flow fields and could be employed for steady as well as unsteady flows. Initially, the continuous and discrete adjoint LB equations and the cost function gradient vector were derived mathematically in detail using the continuous and discrete LB equations in space and time, respectively. Meanwhile, new adjoint concepts in lattice space were introduced. Finally, the analytical evaluation of the adjoint distribution functions and the cost function gradients was carried out.

Multi-Scale Analysis for Automotive PEM Fuel Cell System: Macro-Scale Analysis

Distributions in reactant species concentration in a Proton Exchange Membrane Fuel Cell (PEMFC) cause distributions in local current density, temperature and water over the area of a PEMFC. These can lead to effects such as flooding and dehydration thus causing stresses in different regions of the fuel cell [1]. Changing operating conditions and design parameters including their properties inside PEMFC system such as flow field configurations, gas diffusion layer (GDL), and membrane electrode assembly (MEA) could impact the cell performance and uniformity in distributions [2-4]. Providing high oxygen concentration in the cathode at high current density operations is critically important to enhance the area specific power density [5, 6]. Thus, mass transport overpotential at high current density is the major barrier to achieving high power density with acceptable operational robustness. Experimental investigation of mass transport is not sufficient to understand mass transport overpotential because of its inability to resolve water saturation-dependent properties in the gas diffusion layer (GDL). An objective of this work is to develop a multi-phase modeling capability to simulate fuel cell performance at high current density region where mass transport overpotential is dominant. Material and design solutions arising from the implementation of this mathematical model are expected to enhance area specific power density of conventional state-of-the art PEMFCs.The conventional computational fluid dynamic (CFD) technique will be used to predict the heat and mass transports in macro-scaled flow-field geometry as shown in Fig. 1. The CFD based meso-scaled Thermal Lattice Boltzmann Method (TLBM) will be introduced to give the solution of gas/liquid transport solution in the porous media. A TLMB GDL model with fixed boundary conditions, such as a constant volumetric injection over an entire GDL surface, represents ex-situexperimental conditions very well [7]. Figure 2 shows an image of the simulation for the condensed water percolated through the GDL. A unique aspect of this work will be to integrate the TLBM GDL model with a CFD based fuel cell electrochemistry model so that the GDL boundary conditions will be dynamic and the water flux entering the GDL will be a function of the dynamic and local water production within the catalyst layer. This fully-integrated simulation will yield a direct prediction of the hydrated in-situ performance by enabling the natural development of water distribution within the GDL. This multi-scaled modeling technique will be able to facilitate the development of advanced mass transport design, which is material sets of GDL and flow field interaction, to enhance the performance and the operational robustness.

Layout synthesis of fluid channels using generative graph grammars

AbstractThis paper presents a new technique for shape and topology optimization of fluid channels using generative design synthesis methods. The proposed method uses the generative abilities of graph grammars with simulation and analysis power of conventional computational fluid dynamics methods. The graph grammar interpreter GraphSynth is used to carry out graph transformations, which define different topologies for a given multiple-inlet multiple-outlet problem. After evaluating and optimizing the generated graphs, they are first transformed into meaningful three-dimensional shapes. These solutions are then analyzed by a computational fluid dynamics solver for final evaluation of the possible solutions. The effectiveness of the proposed method is checked by solving a variety of available test problems and comparing them with those found in the literature. Furthermore, by solving very complex large-scale problems, the robustness and effectiveness of the method is tested. To extend the work, future research directions are presented.

Helicopter Rotor Design Using a Time-Spectral and Adjoint-Based Method

A time-spectral and adjoint-based optimization method was developed and applied to helicopter rotor design for unsteady level flight. The time-spectral method is a fast and accurate computational fluid dynamics algorithm for computing unsteady flows. It transforms the flow-governing equations into a periodic steady state by using a Fourier spectral derivative operator. An accompanying steady-state adjoint formulation was implemented in the time-spectral form of the governing equations to enable design optimization for unsteady flows. The time-spectral analysis was validated against conventional time-accurate computational fluid dynamics computation and flight test data of a UH-60A helicopter rotor during high-speed forward flight. A multidisciplinary analysis of blade structural dynamics was carried out through a comprehensive analysis coupling procedure that accounted for aeroelasticity and enforced vehicle trim. The adjoint-based design method was applied to optimize the blade shape of the UH-60A rotor. Power minimization was pursued with nonlinear constraints on the thrust and rotor drag force. The blade twist distribution, sectional airfoil shape, and outboard planform shape comprised over 100 design variables. Starting from the initial blade, the optimizer found a new design that showed improved performance. The validation results coupled with the multidisciplinary comprehensive analysis confirmed actual improvement: a 5% decrease in torque accompanied by a decrease in thrust of less than 1%.

Radiotracer Technology in Mixing Processes for Industrial Applications

Many problems associated with the mixing process remain unsolved and result in poor mixing performance. The residence time distribution (RTD) and the mixing time are the most important parameters that determine the homogenisation that is achieved in the mixing vessel and are discussed in detail in this paper. In addition, this paper reviews the current problems associated with conventional tracers, mathematical models, and computational fluid dynamics simulations involved in radiotracer experiments and hybrid of radiotracer.

Numerical modeling of carrier gas flow in atomic layer deposition vacuum reactor: A comparative study of lattice Boltzmann models

This paper characterizes the carrier gas flow in the atomic layer deposition (ALD) vacuum reactor by introducing Lattice Boltzmann Method (LBM) to the ALD simulation through a comparative study of two LBM models. Numerical models of gas flow are constructed and implemented in two-dimensional geometry based on lattice Bhatnagar–Gross–Krook (LBGK)-D2Q9 model and two-relaxation-time (TRT) model. Both incompressible and compressible scenarios are simulated and the two models are compared in the aspects of flow features, stability, and efficiency. Our simulation outcome reveals that, for our specific ALD vacuum reactor, TRT model generates better steady laminar flow features all over the domain with better stability and reliability than LBGK-D2Q9 model especially when considering the compressible effects of the gas flow. The LBM-TRT is verified indirectly by comparing the numerical result with conventional continuum-based computational fluid dynamics solvers, and it shows very good agreement with these conventional methods. The velocity field of carrier gas flow through ALD vacuum reactor was characterized by LBM-TRT model finally. The flow in ALD is in a laminar steady state with velocity concentrated at the corners and around the wafer. The effects of flow fields on precursor distributions, surface absorptions, and surface reactions are discussed in detail. Steady and evenly distributed velocity field contribute to higher precursor concentration near the wafer and relatively lower particle velocities help to achieve better surface adsorption and deposition. The ALD reactor geometry needs to be considered carefully if a steady and laminar flow field around the wafer and better surface deposition are desired.

CFD ANALYSIS OF ECONOMIZER IN A TENGENTIAL FIRED BOILER

This paper presents a simulation of the economizer zone, which allows for the condition of the shell-side flow and tube-side and tube-wall, thermal fields, and of the shell-tube heat-exchange. Selection of the economizer zone from the thermal power plant only because, it is found trends of failure that the economizer is the zone where the leakages are found more. The maximum number of cause of failure in economizer unit is due to flue gas erosion. The past failure details revels that erosion is more in U-bend areas of Economizer Unit because of increase in flue gas velocity near these bends. But it is observed that the velocity of flue gases surprisingly increases near the lower bends as compared to upper ones. The model is solved using conventional CFD techniques by STAR- CCM+ software. In which the individual tubes are treated as sub-grid features. A geometrical model is used to describe the multiplicity of heat-exchanging structures and the interconnections among them. The Computational Fluid Dynamics (CFD) approach is utilised for the creation of a three-dimensional model of the economizer coil. With equilibrium assumption applied for description of the system chemistry. The flue gas temperature, pressure and velocity field of fluid flow within an economizer tube using the actual boundary conditions have been analyzed using CFD tool. Such as the ability to quickly analyse a variety of design options without modifying the object and the availability of significantly more data to interpret the results. This study is a classic example of numerical investigation into the problem of turbulent reacting flows in large scale furnaces employed in thermal power plants for the remediation of ash deposition problems. And the experimental setup is from Chandrapur Super Thermal Power Station, Chandrapur having the unit no IV of 210 MW energy generations.

Characterization of Dispersive Fluxes in Mesoscale Models Using LES of Flow over an Array of Cubes

Field studies have shown that local climate is strongly influenced by urban structures. This influences both energy consumption and the pedestrian comfort. It is thus useful to be able to simulate the urban environment to take these effects into account in building and urban design. But for computational reasons, conventional computational fluid dynamics (CFD) codes cannot be used directly on a grid fine enough to resolve all scales found in a city. For this, we use mesoscale models, variants of CFD codes in which the 3D conservation equations are solved on grids having a resolution of a few kilometers. At this resolution, the effects of subgrid scales need implicit representations. In other words, phenomena such as momentum and energy exchanges averaged over the mesoscale grid contribute necessary sources/sinks to the corresponding equations. Such spatial averaging results in additional terms called dispersive fluxes. Until now these fluxes have been ignored. To better understand these fluxes, we have conducted large eddy simulations (LESs) over an array of cubes for different inter-cube spacings. The study shows that these fluxes are as important as the turbulent fluxes and exhibit trends which are related to the eddy formations inside the canopies.

Lattice Boltzmann Method: A New Alternative for Loss Estimation

In order to estimate primary containment losses in the industry, two methods have been traditionally used: Source Models (SM) and conventional Computational Fluid Dynamics models (CFD). However, these methods have some disadvantages in terms of accuracy for the former and calculation time for the latter, making the analysis of losses inefficient. In an attempt to overcome these disadvantages, this work proposes the use of the Lattice Boltzmann method (LBM) to perform free surface simulations over loss of primary containment (LOC) scenarios. The LBM was written in C++ and the scenarios were modelled and validated through the comparison with experimental and specialized software data (FLUENT-ANSYS). It was possible to verify that the difference in simulation time between FLUENT-ANSYS and LBM increases as the grid resolution increases. Moreover, this work proves that both computational methods predict correctly the studied phenomenon. Hence, the LBM is suggested as an alternative to estimate primary containment losses, being especially attractive in complex geometry simulations that require high grid resolution.

Device Thrombogenicity Emulation: A Novel Methodology To Predict “Hot Spot” Sites of Thrombus Formation in Continuous Flow VADs

Purpose Despite the enhanced efficacy of continuous flow VADs they remain limited by thrombotic complications. High shear stresses and recirculating flow patterns, in defined VAD regions, lead to platelet activation. Recently thrombus formation was reported around the flow straightener and the rear-hub bearing of the HeartMate II VAD. We developed a novel method - Device Thrombogenicity Emulation (DTE), combining in silico device modeling + hi-resolution computational fluid dynamics (CFD) + particle tracking to determine stress accumulation histories of individual particles (platelets) and identify local intra-device regions responsible for pro-thrombotic stresses. We hypothesized that DTE would identify and predict intra-VAD sites of thrombus formation. Methods and Materials A mathematical model of the HMI was constructed. Fluid-structure simulations were conducted using Fluent CFD. Blood flow was modeled as a turbulent two-phase Newtonian fluid. Platelet trajectories were computed for 30,000 platelets and analyzed via a MATLAB code. Zones of hi stress accumulation, recirculation and stagnation were identified and compared to reported sites of thrombosis. Results Several platelet trajectories (PT) depicted the formation of well defined recirculation zones at the posterior side of the flow straightener. Other PTs formed stagnant flow patterns attaching to the rear hub or stagnant circular patterns at the entry of the impeller blades. These flow patterns directly correlated to the sites of thrombus formation in the HM II that have been reported in explant analysis. Conclusions Device Thrombogenicity Emulation offers a predictive methodology able to identify intra-VAD regions that are “hot spots,” leading to significant shear-mediated platelet activation. This methodology goes beyond present particle image velocimetry and conventional CFD which lack the resolution to identify these zones and do not calculate the dose-time response of the platelet to shear stress.