Validation of a Flamelet Approach to Modelling 3-D Turbulent Combustion Within an Airspray Combustor

2002 ◽  
Author(s):  
A. G. Kyne ◽  
M. Pourkashanian ◽  
C. W. Wilson ◽  
A. Williams
Keyword(s):  
Mixture Fraction ◽  
Turbulence Models ◽  
Predictive Performance ◽  
Design Tool ◽  
Aviation Fuel ◽  
Lookup Table ◽  
Product Cycle ◽  
Discrete Phase Model ◽  
Flamelet Model ◽  
Wide Range

Over the past two decades Computational Fluid Dynamics (CFD) has become increasingly popular with the gas turbine industry as a design tool. By applying CFD techniques during the early stages of designing a product, engineers can establish the key parameters and dimensions of a system before any experimental trial and error tests are made, thus reducing the product cycle time and costs. This study compares CFD predictions with a comprehensive set of experimental measurements made at QinetiQ on the combustion of aviation fuel within a modem airspray combustor. The performances of two separate models describing the chemical interactions are compared. First, an equilibrium model was employed and linked to the 3D commercial solver, FLUENT 5.5, through a mixture fraction/PDF lookup table approach. Similarly a flamelet model was implemented using a recently developed detailed chemical reaction mechanism describing aviation fuel combustion which has previously received rigorous testing with regard to its predictive performance over a wide range of combustion conditions (Patterson et al., 2001). Both cases predicted heat transfer through a new non-adiabatic PDF lookup table generator developed within the department. This allowed the implementation of a discrete phase model that treats the fuel entering the combustor as a fine liquid spray before evaporating and arriving in the gaseous phase. Two turbulence models (k-ε and Reynolds Stress models) were also used and the results of each compared.

scholarly journals Introduction. Computational aerodynamics

2007 ◽  
Vol 365 (1859) ◽  
pp. 2379-2388 ◽  
Author(s):  
Paul G Tucker
Keyword(s):  
Complex Geometry ◽  
Weak Link ◽  
Turbulence Models ◽  
Grid Generation ◽  
Aircraft Design ◽  
Design Tool ◽  
Turbulence Modelling ◽  
Navier Stokes ◽  
Turbulence Control ◽  
Wide Range

The wide range of uses of computational fluid dynamics (CFD) for aircraft design is discussed along with its role in dealing with the environmental impact of flight. Enabling technologies, such as grid generation and turbulence models, are also considered along with flow/turbulence control. The large eddy simulation, Reynolds-averaged Navier–Stokes and hybrid turbulence modelling approaches are contrasted. The CFD prediction of numerous jet configurations occurring in aerospace are discussed along with aeroelasticity for aeroengine and external aerodynamics, design optimization, unsteady flow modelling and aeroengine internal and external flows. It is concluded that there is a lack of detailed measurements (for both canonical and complex geometry flows) to provide validation and even, in some cases, basic understanding of flow physics. Not surprisingly, turbulence modelling is still the weak link along with, as ever, a pressing need for improved (in terms of robustness, speed and accuracy) solver technology, grid generation and geometry handling. Hence, CFD, as a truly predictive and creative design tool, seems a long way off. Meanwhile, extreme practitioner expertise is still required and the triad of computation, measurement and analytic solution must be judiciously used.

scholarly journals Assessment of the Performance of Alternative Aviation Fuel in a Modern Air-Spray Combustor (MAC)

2008 ◽  
Author(s):  
I. Uryga-Bugajska ◽  
M. Pourkashanian ◽  
D. Borman ◽  
E. Catalanotti ◽  
L. Ma ◽  
...  
Keyword(s):  
Mixture Fraction ◽  
Combustion Process ◽  
Oxidation Mechanism ◽  
Design Tool ◽  
Operating Conditions ◽  
Aviation Fuel ◽  
Substantial Part ◽  
Chemical Difference ◽  
Blended Fuel ◽  
The Impact

Recent concerns over energy security and environmental considerations have highlighted the importance of finding alternative aviation fuels. It is expected that coal and biomass derived fuels will fulfil a substantial part of these energy requirements. However, because of the physical and chemical difference in the composition of these fuels, there are potential problems associated with the efficiency and the emissions of the combustion process. Over the past 25 years Computational Fluid Dynamics (CFD) has become increasingly popular with the gas turbine industry as a design tool for establishing and optimising key parameters of systems prior to starting expensive trials. In this paper the performance of a typical aviation fuel, kerosene, an alternative aviation fuel, biofuel and a blend have been examined using CFD modelling. A comprehensive understanding of the kinetics of the reaction for bio aviation fuels at both high and low temperature is necessary to perform reliable simulations of ignition, combustion and emissions in an aero-engine. A novel detailed reaction mechanism was used to represent the aviation fuel oxidation mechanism. The fuel combustion is calculated using a 3D commercial solver using a mixture fraction/pdf approach. Firstly, the study demonstrates that CFD predictions compare favourably with experimental data obtained by QinetiQ for a Modern Airspray Combustor (MAC) when used with traditional jet fuel (kerosene). Furthermore, the 3D CFD model has been refined to use the laminar flamelet model (LFM) approach that incorporates recently developed chemical reaction mechanisms for the bio-aviation fuel. This has enabled predictions for the bio-aviation fuel to be made. The impact of using the blended fuel has been shown to be very similar in performance to that of the 100% kerosene, confirming that aircraft running on 20% blended fuel should have no significant reduction in performance. It was also found that for the given operating conditions there is a significant reduction in performance when 100% biofuel is used. Additionally, interesting predictions were obtained, related to NOx emissions for the blend and 100% biofuel.

scholarly journals Enhanced discrete phase model for multiphase flow simulation of blood flow with high shear stress

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110080
Author(s):  
Zheqin Yu ◽  
Jianping Tan ◽  
Shuai Wang
Keyword(s):  
Blood Flow ◽  
Shear Stress ◽  
Multiphase Flow ◽  
Experimental Verification ◽  
Flow Simulation ◽  
Turbulence Models ◽  
Phase Model ◽  
Force Model ◽  
Discrete Phase Model ◽  
Discrete Phase

Shear stress is often present in the blood flow within blood-contacting devices, which is the leading cause of hemolysis. However, the simulation method for blood flow with shear stress is still not perfect, especially the multiphase flow model and experimental verification. In this regard, this study proposes an enhanced discrete phase model for multiphase flow simulation of blood flow with shear stress. This simulation is based on the discrete phase model (DPM). According to the multiphase flow characteristics of blood, a virtual mass force model and a pressure gradient influence model are added to the calculation of cell particle motion. In the experimental verification, nozzle models were designed to simulate the flow with shear stress, varying the degree of shear stress through different nozzle sizes. The microscopic flow was measured by the Particle Image Velocimetry (PIV) experimental method. The comparison of the turbulence models and the verification of the simulation accuracy were carried out based on the experimental results. The result demonstrates that the simulation effect of the SST k- ω model is better than other standard turbulence models. Accuracy analysis proves that the simulation results are accurate and can capture the movement of cell-level particles in the flow with shear stress. The results of the research are conducive to obtaining accurate and comprehensive analysis results in the equipment development phase.

scholarly journals Multi-material braids for multifunctional laminates: conductive through-thickness reinforcement

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Caroline O’Keeffe ◽  
Laura Rhian Pickard ◽  
Juan Cao ◽  
Giuliano Allegri ◽  
Ivana K. Partridge ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Carbon Fibre ◽  
Electromagnetic Interference ◽  
Design Tool ◽  
Electrically Conductive ◽  
Current Collection ◽  
Wide Range ◽  
Predictive Design ◽  
The Right ◽  
Metal Wires

AbstractConventional carbon fibre laminates are known to be moderately electrically conductive in-plane, but have a poor through-thickness conductivity. This poses a problem for functionality aspects that are of increasing importance to industry, such as sensing, current collection, inductive/resistive heating, electromagnetic interference (EMI) shielding, etc. This restriction is of course more pronounced for non-conductive composite reinforcements such as glass, organic or natural fibres. Among various solutions to boost through-thickness electrical conductivity, tufting with hybrid micro-braided metal-carbon fibre yarns is one of the most promising. As a well-characterised method of through thickness reinforcement, tufting is easily implementable in a manufacturing environment. The hybridisation of materials in the braid promotes the resilience and integrity of yarns, while integrating metal wires opens up a wide range of multifunctional applications. Many configurations can be produced by varying braid patterns and the constituting yarns/wires. A predictive design tool is therefore necessary to select the right material configuration for the desired functional and structural performance. This paper suggests a fast and robust method for generating finite-element models of the braids, validates the prediction of micro-architecture and electrical conductivity, and demonstrates successful manufacturing of composites enhanced with braided tufts.

Finite Element Volume Analysis of Propane Preheated Air Flame Passing Through a Minichannel

2014 ◽  
Author(s):  
Masoud Darbandi ◽  
Majid Ghafourizadeh ◽  
Gerry E. Schneider
Keyword(s):  
Finite Element ◽  
Radiation Effects ◽  
Mixture Fraction ◽  
Flame Structure ◽  
Current Method ◽  
Reacting Flow ◽  
Wall Functions ◽  
Flamelet Model ◽  
Combustion Modeling ◽  
Detailed Kinetics

A hybrid finite-element-volume FEV method is extended to simulate turbulent non-premixed propane air preheated flame in a minichannel. We use a detailed kinetics scheme, i.e. GRI mechanism 3.0, and the flamelet model to perform the combustion modeling. The turbulence-chemistry interaction is taken into account in this flamelet modeling using presumed shape probability density functions PDFs. Considering an upwind-biased physics for the current reacting flow, we implement the physical influence upwinding scheme PIS to estimate the cell-face mixture fraction variance in this study. To close the turbulence closure, we employ the two-equation standard κ-ε turbulence model incorporated with suitable wall functions. Supposing an optically thin limit, it needs to take into account radiation effects of the most important radiating species in the current modeling. Despite facing with so many flame instabilities in such small size configuration, the current method performs suitably with proper convergence, and the encountered instabilities are damped out automatically. Comparing with the experimental measurements, the current extended method accurately predicts the flame structure in the minichannel configuration.

Using CFD to Enhance the Preliminary Design of High-Pressure Steam Turbines

2013 ◽  
Author(s):  
Juri Bellucci ◽  
Federica Sazzini ◽  
Filippo Rubechini ◽  
Andrea Arnone ◽  
Lorenzo Arcangeli ◽  
...  
Keyword(s):  
High Pressure ◽  
Steam Turbine ◽  
Design Tool ◽  
Tip Clearance ◽  
Large Set ◽  
Preliminary Design ◽  
Steam Turbines ◽  
High Pressure Steam ◽  
Wide Range ◽  
Pressure Steam

This paper focuses on the use of the CFD for improving a steam turbine preliminary design tool. Three-dimensional RANS analyses were carried out in order to independently investigate the effects of profile, secondary flow and tip clearance losses, on the efficiency of two high-pressure steam turbine stages. The parametric study included geometrical features such as stagger angle, aspect ratio and radius ratio, and was conducted for a wide range of flow coefficients to cover the whole operating envelope. The results are reported in terms of stage performance curves, enthalpy loss coefficients and span-wise distribution of the blade-to-blade exit angles. A detailed discussion of these results is provided in order to highlight the different aerodynamic behavior of the two geometries. Once the analysis was concluded, the tuning of a preliminary steam turbine design tool was carried out, based on a correlative approach. Due to the lack of a large set of experimental data, the information obtained from the post-processing of the CFD computations were applied to update the current correlations, in order to improve the accuracy of the efficiency evaluation for both stages. Finally, the predictions of the tuned preliminary design tool were compared with the results of the CFD computations, in terms of stage efficiency, in a broad range of flow coefficients and in different real machine layouts.

The Use of Neural Nets for Matching Fixed or Variable Geometry Compressors With Diesel Engines

2003 ◽  
Vol 125 (2) ◽  
pp. 572-579 ◽  
Author(s):  
S. A. Nelson ◽  
Z. S. Filipi ◽  
D. N. Assanis
Keyword(s):  
Diesel Engine ◽  
System Optimization ◽  
Design Tool ◽  
Neural Nets ◽  
Additional Parameter ◽  
Mathematical Function ◽  
Neural Net ◽  
Variable Geometry ◽  
Entire Family ◽  
Wide Range

A technique which uses trained neural nets to model the compressor in the context of a turbocharged diesel engine simulation is introduced. This technique replaces the usual interpolation of compressor maps with the evaluation of a smooth mathematical function. Following presentation of the methodology, the proposed neural net technique is validated against data from a truck type, 6-cylinder 14-liter diesel engine. Furthermore, with the introduction of an additional parameter, the proposed neural net can be trained to simulate an entire family of compressors. As a demonstration, a family of compressors of different sizes is represented with a single neural net model which is subsequently used for matching calculations with intercooled and nonintercooled engine configurations at different speeds. This novel approach readily allows for evaluation of various options within a wide range of possible compressor configurations prior to prototype production. It can also be used to represent the variable geometry machine regardless of the method used to vary compressor characteristics. Hence, it is a powerful design tool for selection of the best compressor for a given diesel engine system and for broader system optimization studies.

A proof-of-concept study applying machine learning methods to putative risk factors for eating disorders: results from the multi-centre European project on healthy eating

2021 ◽  
pp. 1-10
Author(s):  
I. Krug ◽  
J. Linardon ◽  
C. Greenwood ◽  
G. Youssef ◽  
J. Treasure ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Logistic Regression ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Prediction Rule ◽  
Predictive Performance ◽  
Individual Risk ◽  
European Project ◽  
Wide Range

Abstract Background Despite a wide range of proposed risk factors and theoretical models, prediction of eating disorder (ED) onset remains poor. This study undertook the first comparison of two machine learning (ML) approaches [penalised logistic regression (LASSO), and prediction rule ensembles (PREs)] to conventional logistic regression (LR) models to enhance prediction of ED onset and differential ED diagnoses from a range of putative risk factors. Method Data were part of a European Project and comprised 1402 participants, 642 ED patients [52% with anorexia nervosa (AN) and 40% with bulimia nervosa (BN)] and 760 controls. The Cross-Cultural Risk Factor Questionnaire, which assesses retrospectively a range of sociocultural and psychological ED risk factors occurring before the age of 12 years (46 predictors in total), was used. Results All three statistical approaches had satisfactory model accuracy, with an average area under the curve (AUC) of 86% for predicting ED onset and 70% for predicting AN v. BN. Predictive performance was greatest for the two regression methods (LR and LASSO), although the PRE technique relied on fewer predictors with comparable accuracy. The individual risk factors differed depending on the outcome classification (EDs v. non-EDs and AN v. BN). Conclusions Even though the conventional LR performed comparably to the ML approaches in terms of predictive accuracy, the ML methods produced more parsimonious predictive models. ML approaches offer a viable way to modify screening practices for ED risk that balance accuracy against participant burden.

Validation of MISES Two-Dimensional Boundary Layer Code for High-Pressure Turbine Aerodynamic Design

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Philip L. Andrew ◽  
Harika S. Kahveci
Keyword(s):  
Boundary Layer ◽  
High Pressure ◽  
Operating Cost ◽  
Design Tool ◽  
Operating Conditions ◽  
Aerodynamic Design ◽  
High Pressure Turbine ◽  
Reduce Operating Cost ◽  
Wide Range ◽  
Dimensional Boundary

Avoiding aerodynamic separation and excessive shock losses in gas turbine turbomachinery components can reduce fuel usage and thus reduce operating cost. In order to achieve this, blading designs should be made robust to a wide range of operating conditions. Consequently, a design tool is needed—one that can be executed quickly for each of many operating conditions and on each of several design sections, which will accurately capture loss, turning, and loading. This paper presents the validation of a boundary layer code, MISES, versus experimental data from a 2D linear cascade approximating the performance of a moderately loaded mid-pitch section from a modern aircraft high-pressure turbine. The validation versus measured loading, turning, and total pressure loss is presented for a range of exit Mach numbers from ≈0.5 to 1.2 and across a range of incidence from −10 deg to +14.5 deg relative to design incidence.

Assessment of Certainty of Ventilation Processes Mathematical Modeling

2015 ◽  
Vol 725-726 ◽  
pp. 1255-1260
Author(s):  
Tamara Daciuk ◽  
Vera Ulyasheva
Keyword(s):  
Mathematical Modeling ◽  
Turbulent Flows ◽  
Turbulence Models ◽  
Field Measurements ◽  
Heat Emission ◽  
Emission Sources ◽  
Wide Range ◽  
Calculation Results ◽  
Definition Of ◽  
Semiempirical Models

Numerical experiment has been successfully used during recent 10-15 years to solve a wide range of thermal and hydrogasodynamic tasks. Application of mathematical modeling used to design the ventilation systems for production premises characterized by heat emission may be considered to be an effective method to obtain reasonable solutions. Results of calculation performed with numerical solution of ventilation tasks depend on turbulence model selection. Currently a large number of different turbulence models used to calculate turbulent flows are known. Testing and definition of applicability limits for semiempirical models of turbulence should be considered to be a preliminary stage of calculation. This article presents results of test calculations pertaining to thermal air process modeling in premises characterized by presence of heat emission sources performed with employment of different models of turbulence. Besides, analysis of calculation results and comparison with field measurements data are presented.

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