Computational Fluid Dynamics Predictions Research Articles

One-equation turbulence models applied to practical scramjet inlet

Abstract Reynolds-averaged Navier–Stokes equations are used to simulate a practical scramjet inlet geometry using the shock-unsteadiness modified Spalart–Allmaras (SA) turbulence model. The geometry consists of fore-body ramps, expansion corners, and inlet ducts. The focus is to study the impingement of the cowl shock on the opposite wall boundary-layer. The resulting separation bubble can lead to blockage and inlet unstarts. The shock-unsteadiness correction is employed and is found to improve the computational fluid dynamics (CFD) prediction of flow separation in shock/boundary-layer interactions. The shock-unsteadiness parameter is calibrated against available experimental data of canonical flows, and the predicted flow-field is analyzed in detail. A large separation bubble size normalized to the upstream boundary-layer thickness of 4.6 is observed in the interaction region. Across the reattachment region in the interaction region, a peak value of wall pressure is observed. The inlet performance parameters are also calculated. The total pressure losses of 62% are observed across different shock waves, with an additional loss of 15% due to viscous boundary-layer effects.

The maximum likelihood ensemble filter for computational flame and fluid dynamics

Abstract The numerical solution of partial differential equations that govern fluid dynamics with turbulence and combustion is challenging due to the multiscale nature of the dynamical system and the need to resolve small-scale physical features. In addition, the uncertainties in the dynamical system, including those in the physical models and parameters, initial and boundary conditions and numerical methods, impact the computational fluid dynamics (CFD) prediction of turbulence and chemical reactions. To improve the CFD prediction, this study focuses on the development and application of a maximum likelihood ensemble filter (MLEF), an ensemble-based data assimilation (DA), for flows featuring combustion and/or turbulence. MLEF finds the optimal analysis and its uncertainty by maximizing the posterior probability density function. The novelty of the study lies in the combination of advanced DA and CFD methods for a new comprehensive application to predict engineering fluid dynamics. The study combines important aspects, including an ensemble-based DA with analysis and uncertainty estimation, an augmented control vector that simultaneously adjusts initial conditions and model empirical parameters and an application of DA to CFD modeling of combustion and flows with complex geometry. The DA performance is validated by a turbulent Couette flow. The new CFD–DA system is then applied to solve the time-evolving shear-layer mixing with methane-air combustion and the turbulent flow over a bluff-body geometry. Results demonstrate the improvement of estimates of model parameters and the uncertainty reduction in initial conditions (ICs) for CFD modeling of flames and flows by the MLEF method.

CFD prediction of full-scale ship parametric roll in head wave

With the advances in available brute-force computing power, parallel computations (overset grid technology and meta-modeling) will eventually open a path to the widespread application of full-scale computations. This study presents a computational fluid dynamics (CFD) prediction of a full-scale ship parametric roll in a regular head wave. An in-house unsteady Reynolds-averaged Navier–Stokes (URANS) CFD code was used for the simulations. The ONR Tumblehome surface combatant was selected as the research object, and the full-scale ship was studied under the same conditions as the model tests. Comparisons between the CFD results and model test results from the reference show good agreement and validate that the code could capture the details of parametric roll phenomenon in head waves. The full-scale predictions were compared with the model-scale results to assess the scale effect of the parametric roll. The induced force and moment acting on the hull under the parametric roll were analyzed. Simulations for ships with bilge keels were also performed at model- and full-scale to evaluate the effect of bilge keels. Numerical results demonstrate that the in-house URANS code could be used to predict the parametric roll characteristics for a full-scale ship at the design stage in the future.

Development and Validation of an Accurate 1D Model for Pressure Drop in Complex Coolant Piping Systems of Hybrid and Electric Vehicles

<div class="section abstract"><div class="htmlview paragraph">The development of efficient, reliable, and affordable Hybrid and Electric Vehicles (xEVs) relies on optimized Vehicle Thermal Management System (VTMS) architecture and control strategies. Compared to conventional vehicles, xEVs have more complex VTMS due to additional powertrain components and cooling circuits to meet distinct thermal requirements. The cooling circuits comprise a combination of hoses, straight, and bent pipes to route coolant flow around obstacles between powertrain components at distinct locations in the vehicle. The increased length and geometrical complexity of these piping systems, compared to conventional vehicles, results in increased pressure losses. Thus, accurate predictions of pressure drop within these piping systems is critical for component selection for an optimized VTMS. Numerical simulations are often used to study interactions between components from a system-level perspective allowing early stage rapid assessment of performance. In this work, an accurate 1D model for pressure drop in piping systems is developed based on literature review and validated using 3D Computational Fluid Dynamics (CFD) predictions. The 1D model is implemented in the software tool GT-SUITE which is used for integrated 0D/1D/3D multi-physics system simulation of the entire VTMS. The CFD calculations are performed using GT-CONVERGE. Overall, the pressure drop predictions of the 1D model are in good agreement with the 3D CFD for a range of Reynolds numbers including laminar, transition, and turbulent regimes and even when significant losses are present due to flow redevelopment after bends. Typically, commercial tools often ignore flow redevelopment and were originally developed for high Reynolds number flows. A typical battery electric vehicle is constructed in GT-SUITE and results indicate that deviations on pressure drop predictions lead to significant deviations on pump operating conditions and isentropic efficiency. The 1D model allows fast and accurate simulations over a broad range of complex piping configurations for an optimized VTMS.</div></div>

Lagrangian Trajectory Simulation of Platelets and Synchrotron Microtomography Augment Hemodynamic Analysis of Intracranial Aneurysms Treated With Embolic Coils.

As frequency of endovascular treatments for intracranial aneurysms increases, there is a growing need to understand the mechanisms for coil embolization failure. Computational fluid dynamics (CFD) modeling often simplifies modeling the endovascular coils as a homogeneous porous medium (PM), and focuses on the vascular wall endothelium, not considering the biomechanical environment of platelets. These assumptions limit the accuracy of computations for treatment predictions. We present a rigorous analysis using X-ray microtomographic imaging of the coils and a combination of Lagrangian (platelet) and Eulerian (endothelium) metrics. Four patient-specific, anatomically accurate in vitro flow phantoms of aneurysms are treated with the same patient-specific endovascular coils. Synchrotron tomography scans of the coil mass morphology are obtained. Aneurysmal hemodynamics are computationally simulated before and after coiling, using patient-specific velocity/pressure measurements. For each patient, we analyze the trajectories of thousands of platelets during several cardiac cycles, and calculate residence times (RTs) and shear exposure, relevant to thrombus formation. We quantify the inconsistencies of the PM approach, comparing them with coil-resolved (CR) simulations, showing the under- or overestimation of key hemodynamic metrics used to predict treatment outcomes. We fully characterize aneurysmal hemodynamics with converged statistics of platelet RT and shear stress history (SH), to augment the traditional wall shear stress (WSS) on the vascular endothelium. Incorporating microtomographic scans of coil morphology into hemodynamic analysis of coiled intracranial aneurysms, and augmenting traditional analysis with Lagrangian platelet metrics improves CFD predictions, and raises the potential for understanding and clinical translation of computational hemodynamics for intracranial aneurysm treatment outcomes.

Optimising the computational domain size in CFD simulations of tall buildings

Recently, there has been a growing interest in utilizing computational fluid dynamics (CFD) for wind resistant design of tall buildings. A key factor that influences the accuracy and computational expense of CFD simulations is the size of the computational domain. In this paper, the effect of the computational domain on CFD predictions of wind loads on tall buildings is investigated with a series of sensitivity studies. Four distinct sources of domain error are identified which include wind-blocking effects caused by short upstream length, flow recirculation due to insufficient downstream length, global venturi effects due to large blockage ratios, and local venturi effects caused by insufficient clearance between the building and top and lateral domain boundaries. Domains based on computational wind engineering guidelines are found to be overly conservative when applied to tall buildings, resulting in uneconomic grids with a large cell count. A framework for optimizing the computational domain is proposed which is based on monitoring sensitivity of key output metrics to variations in domain dimensions. The findings of this paper help inform modellers of potential issues when optimizing the computational domain size for tall building simulations.

Application of high-fidelity modelling approach to predict smoke and fire propagation in a nuclear fire scenario

Fire and smoke propagation from an electrical cabinet fire in a multi-compartment geometry was simulated using computational fluid dynamics (CFD) in this study. The URANS turbulence modeling approach, and variants of two-equation models available within the CFD code STAR-CCM + were tested for non-vented and vented conditions. Specifically, the ability of the turbulence models to predict the smoke and hot gas spread was analysed qualitatively. The ceiling jet and plume spilling phenomenon reported in literature was predicted in the progression of smoke propagation. It was observed that the ventilation created better mixing, enhanced the spreading of the stratified smoke layer and resulted in delayed progression of smoke propagation compared to the non-vented cases. A qualitative assessment of CFD predictions for temperature distribution was also undertaken using a slightly different geometry. It was found that the qualitative predictions obtained by the application of two-equation turbulence models for the temperature and smoke distribution were realistic and in-line with earlier studies using a similar building configuration. The findings from this study are expected to be beneficial in the assessment of existing two-equation turbulence models to predict smoke propagation in multi-compartment fires.

Liquid–Liquid Microfluidic Flows for Ultrafast 5-Hydroxymethyl Furfural Extraction

We study the effects of liquid–liquid flow patterns on the extraction of 5-hydroxymethyl furfural from the aqueous phase into an organic phase (methyl isobutyl ketone, ethyl acetate, and 2-pentanol) at ultrashort residence times of 0.2–20 s in a coiled capillary microchannel. Slug, droplet, slug-droplet, dispersed, parallel, annular, and irregular two-phase flow patterns are generated. We evaluate the extraction efficiency and the volumetric mass transfer coefficient via experiments and computational fluid dynamics (CFD). The CFD predictions are in quantitative agreement with the experimental data. The convective and diffusive contributions to the mass transfer of different flow patterns are analyzed. For all solvent pairs, the extraction efficiency varies irregularly with increasing flow rate due to changes in the mass transfer mechanism caused by a transition between flow regimes. Overall, we demonstrate >90% extraction efficiencies with high volumetric mass transfer coefficients ranging from 0.006 to 2.17 s–1. Furthermore, a merit index is defined to assess the trade-off between the fast mass transfer and the pressure drop in biphasic microchannels. In general, the mass transfer rate increases significantly at high flow rates at the expense of a high-pressure drop. The ethyl acetate/water irregular flow pattern is optimal due to a large throughput, extraction efficiency, and mass transfer coefficient, with a minimal pressure drop.

On the Leakage and Dynamic Force Coefficients of a Novel Stepped Shaft Pocket Damper Seal: Experimental and Numerical Verification

Abstract High-performance turbomachinery favors annular seals with a large damping coefficient to ensure rotor system stability. Pocket damper seals (PDSs), a variation of labyrinth seals with axial blades (ribs) and adding circumferential partition walls (ridges), produce a favorable damping performance. To further enhance the damping characteristic and reduce leakage, a novel stepped shaft PDS is hereby introduced. The invention has a unique arrangement of steps on the rotor surface, each facing an upstream rib in a pocket row. Thus, the step and a blade tip form a tight clearance (c1), while the rotor surface and the downstream blade tip make a larger clearance (c2). The convergence–divergence variation of cross-sectional areas along the flow direction increases the PDS damping coefficient. To validate the performance of the novel design, a stepped shaft PDS (c1/c2 = 0.5) with four axial ribs and eight circumferential pockets is built and tested. A comprehensive investigation, experimental and computational, produces the seal leakage and dynamic force coefficients for the stepped shaft PDS, as well as similar performance characteristics for an identical PDS with a smooth rotor surface (c1/c2 = 1, i.e., a uniform clearance PDS). The stepped shaft PDS operates with air at supply pressure (PS) ranging from 1.1 bar to 3.2 bar. The measured leakage for the stepped shaft PDS is 50% of that for the uniform clearance PDS. Computational fluid dynamics (CFD) and bulk flow model (BFM) predictions of leakage agree well with the test data. For PS = 2.3 bar, the test damping coefficient (C) for the stepped shaft PDS is ~1.5 times greater than the one for the uniform clearance PDS. With an increase in PS to 3.2 bar, the stepped shaft PDS shows a two and one half increase in damping coefficient. In comparison to the test data, a CFD model overestimates C by 29% for operation at PS = 3.2 bar, though capturing the variation trend versus whirl frequency. The BFM largely underpredicts C for the stepped shaft PDS and is abandoned for future work. Both the test data and CFD predictions demonstrate the superior damping performance of the stepped shaft PDS, thus providing a novel alternative seal configuration for turbomachinery usage.

Computational analysis of a 3D mucociliary clearance model predicting nasal drug uptake

Accurate and realistic predictions of the fate of nasally inhaled drugs help to understand the complex fluid-particle dynamics in the nasal cavity. Key elements of such a comprehensive numerical analysis include: (i) inhaled drug-aerosol transport and deposition with air-particle-mucus interactions; and (ii) mucociliary clearance (MCC) dynamics, including drug transport, dissolution and absorption for different nasal inlet conditions.The open-source computational fluid dynamics (CFD) toolbox, OpenFOAM, has been employed for the development of the computer simulation model. As part of the design, a novel 3D meshing technique allows for the smooth capture of both the relatively large flow domain as well as the micron-size mucus layer. This efficient meshing strategy drastically reduces the overall meshing time from hours to a matter of minutes. The effect of pharmacokinetic characteristics of drugs on dissolution, subsequent uptake and clearance were analyzed. A method to impose a boundary-driven flow velocity was introduced in order to mimic the beating of the cilia. Several drug specific parameters, such as solubility, partition coefficient and particle size, were considered. The effects of particle distribution on MCC and uptake were simulated as well. The CFD predictions show that drugs with a high partition coefficient are absorbed rapidly. Similarly, drugs with higher solubility show an appreciable increase in cumulative uptake in the epithelium. Particle size, however, plays a more nuanced role in drug uptake. Specifically, smaller particles with their relatively large surface areas, tend to dissolve quicker and are absorbed more rapidly when compared to larger particles. However, after the initial steeper increase in cumulative uptake of the smaller particles, the difference in the uptake values for the two cases is negligible. Furthermore, the initial deposition locations in the nasal cavity play an important role in overall drug uptake. Particles deposited closer to the ciliated portion of the nasal cavity (i.e. the posterior region) were more readily absorbed when compared to particles deposited closer to the unciliated nasal vestibule.

Experimental determination and computational prediction of the mixing efficiency of a simple, continuous, serpentine-channel microdevice

Micromixing devices often utilize complex architectures to mix miscible liquid streams and can be complex and expensive to fabricate. Here, we developed, built, experimentally tested, and computationally analyzed a serpentine micromixer that can be fabricated using simple tools and supplies available in non-microdevice dedicated laboratories. Fluorescence imaging was used to quantify its mixing effectiveness experimentally. A Computational Fluid Dynamics (CFD) software package (COMSOL) was used to model the micromixing process. The predictions were in excellent agreement with the experimental data. The serpentine micromixer can achieve significant levels of mixing efficiency. CFD predictions for a straight microfluidic channel of the same length as the serpentine favorably compared with previous theoretical predictions, indicating that the serpentine's mixing efficiency was vastly superior. Finally, CFD predictions were conducted for different and possibly improved designs of the basic serpentine. In all cases, the mixing efficiency was primarily associated with the number of 90o elbows in the device rather than the straight sections' length, with the first serpentine bend playing a significant role. Future design improvements should focus on incorporating as many elbows as possible in the device to maximize mixing efficiency and reduce the device size.

Assessing the Applicability of the Structure-Based Turbulence Resolution Approach to Nuclear Safety-Related Issues

The accuracy of computational fluid dynamics (CFD) predictions plays a fundamental role in supporting the operation of the current nuclear reactor fleet, and even more importantly the licensing of advanced high-efficiency reactor concepts, where local temperature oscillations driven by thermal striping, cycling and stratification can limit the structural performance of vessels and components. The complexity of the geometrical configurations, coupled to the long operational transients, inhibits the adoption of large eddy simulation (LES) methods, mandating the acceptance of the more efficient Reynolds-averaged Navier-Stokes (RANS)-based models, even though they are unable to provide a complete physical description of the flow in regions dominated by complex unsteady coherent structures. A new strategy has been proposed and demonstrated at Massachusetts Institute of Technology (MIT) toward the enhancement of unsteady Reynolds-averaged Navier-Stokes (URANS) predictions, using local resolution of coherent turbulence, to provide higher fidelity modeling in support of safety-related issues. In this paper, a comprehensive assessment of the recently proposed Structure-based (STRUCT-ε) turbulence model is presented, starting from fundamental validation of the model capabilities and later focusing on a representative safety-relevant application, i.e., thermal mixing in a T-junction. Solutions of STRUCT-ε, the widely used Realizable k−ε model (RKE) and Large Eddy Simulation with Wall-Adapting Local Eddy-viscosity subgrid scale closure (LES-WALE) are compared against the experimental data. Both the velocity and temperature fields predicted by the STRUCT-ε model are in close agreement with the high-fidelity data from the experiments and reference LES solutions, across all validation cases. The approach demonstrates the potential to address the accuracy requirements for application to nuclear safety-related issues, by resolving the turbulent flow structures, while the computational efficiency provides the ability to perform consistent uncertainty quantification.

Validation of CFD predictions for flow over a full-scale formula student vehicle using PIV in real conditions

Computational Fluid Dynamics (CFD) predictions are becoming an industry standard. They allow for making accurate predictions of complex problems without requiring extensive real-world testing, as well as saving time and money. However, it has been proven many times that the classic Reynoldsaveraged Navier – Stokes (RANS) approach has its flaws and fails to provide highly accurate predictions. Even though CFD only approaches a physical solution, which can be reached only in very specific applica-tions, it usually provides enough precision for engineering purposes. To reach a convergence with real-world physics, plenty of factors must be taken into consideration like mesh, boundary conditions, and turbulence models. In order to obtain a CFD simulation that accurately represents real physics, some kind of real-world validation must take place. For aerodynamics, it is usually done in wind tunnels, which are expensive to run but provide controllable conditions to match those specified in CFD. One of the many methods used to validate the calculations is Particle Image Velocimetry (PIV). This study tries to validate CFD of a Formula Student car using PIV, but in realworld conditions, without wind tunnel. The compact size of equipment required for PIV testing and flexibility of CFD boundary conditions allow for that.

Comparison of the Computational Fluid Dynamics Predictions of Vertical Axis Wind Turbine Performance Against Detailed Pressure Measurements

Computational Fluid Dynamics (CFD) simulations are currently one of the most popular methods for the modelling of a Vertical Axis Wind Turbine (VAWT) that gives good insight on the turbine aerodynamics. The current study provides an assessment of the quality of the 2D and 3D CFD predictions of two highly recommended models in the literature, namely the SST K-omega model and the SST K-omega with the Intermittency transition model. The novelty of the study is in the kind of data that is used in the assessment. The CFD predictions of the pressure around the blade at several azimuthal angles are compared to the published experimental data measured by a high-frequency multiport pressure scanner. In addition, the predictions of the pressure contribution to the instantaneous power coefficient are compared to the experimental data. This paper sheds much new light on how the behaviour of the predictions of the SST K-omega with the intermittency transition model changes between the 2D and 3D cases and how the trends of the 2D results based on this transition model deviate from the detailed experimental data. This behaviour has not been previously investigated.

A Simple Model to Identify Dryout Location: Validation and Computational Fluid Dynamics Predictions

Prediction of dryout location is essential to identify reliable heat flux margins for the safe operation of different thermal systems. The present study proposes a simple model to predict the dryout type critical heat flux location in a circular tube and an annulus. Based on the flow topology, the annular flow boiling regime is demarcated into two zones viz., vapor flow in the core region and liquid film flow in the annular gap between the vapor core and the wall surface. An expression is derived for the dryout location which is purely a function of operating conditions and fluid properties. The dryout location and quality predictions of the present model are found to be in very good agreement and within 10% error margin against the experimental data for tube and annulus geometries. The present study is extended to investigate the effect of eccentricity on the dryout location and the inner wall temperature. It is observed that the eccentricity results in early occurrence of dryout in the narrow gap region of an eccentric annulus. Furthermore, the predictions from the present model are compared with the look-up table data, subchannel analysis and computational fluid dynamics simulation predictions.

Modelling and prediction of cavitation erosion in GDi injectors operated with E100 fuel

Ethanol (E100) can be utilised in spark ignition engines for passenger car vehicles. This brings a challenge to the durability of the fuel injection system components since its use can result in corrosion, further enhanced by cavitation-induced erosion. This work reports computational fluid dynamics (CFD) predictions for both the flow development and the locations prone to cavitation erosion in multi-hole gasoline direct injection (GDi) injectors operated with E100. The compressible form of the Navier–Stokes equations is solved numerically considering the motion of the injector’s needle valve. Thermodynamic and mechanical equilibrium is assumed between the liquid, vapour and non-condensable gas; E100 liquid and vapour are considered as a barotropic fluids where the corresponding variation in density with pressure and the speed of sound are estimated via a relevant equation of state; an additional transport equation is solved for simulating the non-condensable air entrainment into the injector during the dwell time between successive injections. Turbulence is modelled using both large eddy simulation (LES) and Unsteady Reynolds-averaged Navier–Stokes (URANS) considering a sector and the full nozzle geometry, respectively. Various cavitation erosion indices reported in the literature are evaluated against new durability tests of surface erosion damage obtained after 400 M injection cycles. The relevant nozzle wall erosion images are found to correlate well with the accumulated erosive power predicted from the computational model.

Uncertainty Assessment of CFD Investigation of the Nonlinear Difference-Frequency Wave Loads on a Semisubmersible FOWT Platform

Current mid-fidelity modeling approaches for floating offshore wind turbines (FOWTs) have been found to underpredict the nonlinear, low-frequency wave excitation and the response of semisubmersible FOWTs. To examine the cause of this underprediction, the OC6 project is using computational fluid dynamics (CFD) tools to investigate the wave loads on the OC5-DeepCwind semisubmersible, with a focus on the nonlinear difference-frequency excitation. This paper focuses on assessing the uncertainty of the CFD predictions from simulations of the semisubmersible in a fixed condition under bichromatic wave loading and on establishing confidence in the results for use in improving mid-fidelity models. The uncertainty for the nonlinear wave excitation is found to be acceptable but larger than that for the wave-frequency excitation, with the spatial discretization error being the dominant contributor. Further, unwanted free waves at the difference frequency have been identified in the CFD solution. A wave-splitting and wave load-correction procedure are presented to remove the contamination from the free waves in the results. A preliminary comparison to second-order potential-flow theory shows that the CFD model predicted significantly higher difference-frequency wave excitations, especially in surge, suggesting that the CFD results can be used to better calibrate the mid-fidelity tools.

Gas Labyrinth Seals: Improved Prediction of Leakage in Gas Labyrinth Seals Using an Updated Kinetic Energy Carry-Over Coefficient

Abstract Though simple and fast, bulk-flow models (BFMs) for gas labyrinth seals (LSs) often predict the mass flow inaccurately. The BFM models rely on classical Neumann's equation model to characterize the flow through a labyrinth tooth. Presently, a computational fluid dynamics (CFD) analysis quantifies the effects of tip clearance (Cr) and operating conditions on the prediction of LS mass flow, and then derives an updated kinetic energy carry-over coefficient (μ1i) to improve the accuracy of Neumann's leakage equation. μ1i is a function of the seal tip clearance (Cr), the tooth pitch, and the total teeth number; but it does not depend on the seal supply or discharge pressures. The analysis selects a 14-teeth on stator LS (length/diameter = L/D = 0.29) with clearance Cr = (1/733)D and operating at nominal supply (Pin) and discharge (Pout) pressures equal to 73 bar and 51 bar, respectively, and at a rotor speed of 12 krpm (surface speed = 138 m/s). The CFD produces flow fields for LSs with a clearance varying from 80% to 200% of the nominal Cr, a gas supply pressure from 60 bar to 100 bar, and with various discharge pressures giving a pressure ratio (PR = Pout/Pin) ranging from 0.40 to 0.85. The numerous predictions deliver the mass flow as well as the bulk-flow velocities and cavity pressures within the seals. The kinetic energy carry-over coefficient (μ1i) increases with respect to the seal radial clearance (Cr). μ1i shows a parabolic correlation with PR; at first, μ1i increases with a rise in PR from a low value; and then, a further increase in PR leads to a decrease in μ1i. The coefficient μ1i is only sensitive to the PR and not to the magnitude of either the supply or discharge pressures. Lastly, for use with Neumann's leakage model, the CFD predictions produce an updated μ1i, a function of the seal geometry and the PR condition. Integration of the new μ1i correlation into a BFM code improves its accuracy to predict LS mass flow rate, a 19% difference against test data reduces to within 6%. A TOS LS tested by Ertas et al. (2012, Rotordynamic Force Coefficients for Three Types of Annular Gas Seals With Inlet Preswirl and High Differential Pressure Ratio,” ASME J. Eng. Gas Turbine Power, 134(4), p. 4250301) serves to further validate the accuracy of the modified leakage model.

Effect of Insulations and Coatings on Hypersonic Heat Flux Reconstruction

The present study investigates the effects of material discontinuities and thermal resistances on the temperature reconstruction and heat flux evaluation via an inverse heat transfer method in hypersonic wind-tunnel tests. Thin coating layers and adhesive interfaces support a localized multidimensional temperature perturbation that alters the near-surface field. A technique is developed for the real-time evaluation of the heat transfer based on approximating the Green’s function of the heat conduction equation in bounded complex domains and resolving the heat flux on a B-spline basis, leading to an efficient and robust algorithm. Evaluating the Green’s function for three-dimensional problems with material discontinuities is generally difficult. A new approach is developed in which the Green’s function is evaluated independently for the regular partitions of the domain, and appropriate connection conditions are derived to determine the full “system” Green’s function. This paper describes the verification, validation, and application of the approach to the heat flux reconstruction for a nonaxisymmetric flat-faced article with coating and potting interfaces. The article was tested at Mach 6 in the Virginia Tech Hypersonic wind tunnel using four temperature sensors arranged in a cross pattern on the flat face. Good agreement was obtained between computational fluid dynamics predictions and the heat flux deduced from the experiments using the new data analysis method.

Computational Fluid Dynamics Analysis of Floating Offshore Wind Turbines in Severe Pitching Conditions

Abstract The unsteady aerodynamics of floating wind turbines is more complex than that of fixed-bottom turbines, and the uncertainty of low-fidelity predictions is higher for floating turbines. Navier–Stokes computational fluid dynamics (CFD) can improve the understanding of rotor and wake aerodynamics of floating turbines, and help improving lower-fidelity models. Here, the flow field of the NREL 5 MW rotor with fixed tower, and subjected to prescribed harmonic pitching past the tower base are investigated using blade-resolved CFD compressible flow COSA simulations and incompressible flow FLUENT simulations. CFD results are also compared to predictions of the FAST wind turbine code, which uses blade element momentum theory (BEMT). The selected rotor pitching parameters correspond to an extreme regime unlikely to occur without faults of the turbine safety system, and thus relevant to extreme aerodynamic load analysis. The rotor power and loads in fixed-tower mode predicted by both CFD codes and BEMT are in very good agreement. For the floating turbine, all predicted periodic profiles of rotor power and thrust are qualitatively similar, but the power peaks of both CFD predictions are significantly higher than those of BEMT. Moreover, cross-comparisons of the COSA and FLUENT predictions of blade static pressure also highlight significant compressible flow effects on rotor power and loads. The CFD analyses of the downstream rotor flow also reveal wake features unique to pitching turbines, primarily the space- and time-dependence of the wake generation strength, highlighted by intermittency of the tip vortex shedding.