Flamelet Versus Detailed Chemistry LES for a Liquid Fueled Gas-Turbine Combustor: A Comparison of Accuracy and Computational Cost

2021 ◽  
Author(s):  
Megan Karalus ◽  
Piyush Thakre ◽  
Graham Goldin ◽  
Dustin Brandt
Keyword(s):  
Gas Turbine ◽  
Computational Cost ◽  
Chemical Mechanism ◽  
Lagrangian Model ◽  
Radial Temperature ◽  
Detailed Chemistry ◽  
Combustion Models ◽  
Acceleration Techniques ◽  
Flamelet Generated Manifold ◽  
Unburned Hydrocarbons

Abstract A Honeywell liquid-fueled gas turbine test combustor, at idle conditions is numerically investigated in Simcenter STAR-CCM+ version 2020.3. This work presents Large Eddy Simulation (LES) results using both the Flamelet Generated Manifold (FGM) and detailed chemistry combustion models. Both take advantage of a hybrid chemical mechanism (HyChem) which has previously demonstrated very good accuracy for real fuels such as Jet-A with only 47 species. The objective of this work is to investigate the ability of FGM and detailed chemistry modeling to capture pollutant formation in an aero-engine combustor. Comparisons for NOx, CO, Unburned Hydrocarbons, and Soot are made, along with the radial temperature profile. To fully capture potential emissions, a soot moment model, and Zeldovich NOx model are employed along with radiation. A comparison of results with and without chemistry acceleration techniques for detailed chemistry is included. Then, computational costs are assessed by comparing the performance and scalability of the simulations with each of the combustion models. It is found that the detailed chemistry case with clustering can reproduce nearly identical results to detailed chemistry without any acceleration if CO is added as a clustering variable. With the Lagrangian model settings chosen for this study, the detailed chemistry results compared more favorably with the experimental data than FGM, however there is uncertainty in the secondary breakup parameters. Sensitivity of the results to a key parameter in the spray breakup model are provided for both FGM and Complex Chemistry (CC). By varying this breakup rate, the FGM case can predict CO, NOx, and Unburned Hydrocarbons equally well. The smoke number, however, is predicted most accurately by CC. The cost for running detailed chemistry with clustering is found to be about 4 times that of FGM for this combustor and chemical mechanism.

Flamelet Versus Detailed Chemistry LES for a Liquid Fueled Gas-Turbine Combustor: A Comparison of Accuracy and Computational Cost

2021 ◽  
Author(s):  
Megan Karalus ◽  
Piyush Thakre ◽  
Graham Goldin ◽  
Dustin Brandt
Keyword(s):  
Gas Turbine ◽  
Computational Cost ◽  
Chemical Mechanism ◽  
Lagrangian Model ◽  
Radial Temperature ◽  
Detailed Chemistry ◽  
Combustion Models ◽  
Flamelet Generated Manifold ◽  
Unburned Hydrocarbons ◽  
Complex Chemistry

Abstract A Honeywell liquid-fueled gas turbine test combustor, at idle conditions is numerically investigated in Simcenter STAR-CCM+. This work presents Large Eddy Simulation (LES) results using both the Flamelet Generated Manifold (FGM) and Complex Chemistry (CC) combustion models. Both take advantage of a hybrid chemical mechanism (HyChem) which has previously demonstrated very good accuracy for real fuels such as Jet-A with only 47 species. The objective of this work is to investigate the ability of FGM and CC to capture pollutant formation in an aero-engine. Comparisons for NOx, CO, Unburned Hydrocarbons, and Soot are made, along with the radial temperature pro?le. Computational costs are assessed by comparing the performance and scalability of the simulations with each of the combustion models. It is found that the CC case with clustering can reproduce nearly identical results to that without acceleration if CO is added as a clustering variable. With the Lagrangian model settings chosen for this study, the CC results compared more favorably with the experimental data than FGM, however there is uncertainty in the secondary breakup parameters. Sensitivity of the results to a key parameter in the spray breakup model are provided for both FGM and CC. By varying this breakup rate, the FGM case can predict CO, NOx, and Unburned Hydrocarbons equally well. The smoke number, however, is predicted most accurately by CC. The cost for running CC with clustering is found to be about 4 times that of FGM for this combustor and chemical mechanism.

Modeling of Pollutant Formation in Gas Turbine Combustors Using Fast Reactor Network Model

2020 ◽  
Author(s):  
Piyush Thakre ◽  
Ivana Veljkovic ◽  
Vincent Lister ◽  
Graham Goldin
Keyword(s):  
Gas Turbine ◽  
Network Model ◽  
Chemical Mechanism ◽  
Combustion Model ◽  
Detailed Chemistry ◽  
Pollutant Formation ◽  
Flamelet Generated Manifold ◽  
Temperature Solution ◽  
Reactor Network ◽  
Industrial Gas Turbine

Abstract We present a robust, fast, and highly-automated Reactor Network model within a single simulation framework in Simcenter STAR-CCM+. An industrial gas turbine combustor operating at 3 bar is numerically investigated using the GRI 3.0 chemical mechanism. A baseline CFD solution with RANS and Flamelet Generated Manifold combustion model was used to create the network of reactors. A number of model variations have been investigated, such as the use of constant pressure vs. perfectly stirred reactors. Two options for the temperature solution are considered, namely temperature mapped from the CFD solution and temperature computed from an equation of state. Different numbers of reactors are investigated to understand the overall sensitivity on the key combustion results. It was found that with appropriate clustering variables, using a few thousand reactors provide a reasonable representation of the species fields. The simulation results are compared with the available experimental data for the combustor. The NOx and CO emissions predictions with the Reactor Network model perform better than the baseline CFD model. The Reactor Network model was about ∼3 orders of magnitude faster than a detailed chemistry CFD of the same combustor.

Comparison of Performance of Flamelet Generated Manifold Model With That of Finite Rate Combustion Model for Hydrogen Blended Flames

2021 ◽  
Author(s):  
Sourabh Shrivastava ◽  
Ishan Verma ◽  
Rakesh Yadav ◽  
Pravin Nakod ◽  
Stefano Orsino
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Combustion Characteristics ◽  
Combustion Model ◽  
Finite Rate ◽  
Reaction Progress ◽  
Progress Variable ◽  
Combustion Models ◽  
Flamelet Generated Manifold ◽  
Chemistry Modeling

Abstract International Air Transport Association (IATA) sets a 50% reduction in 2005 CO2 emissions levels by 2050, with no increase in net emissions after 2020 [1]. The association also expects the global aviation demand to double to 8.2 billion passengers per year by 2037. These issues have prompted the aviation industry to focus intensely on adopting sustainable aviation fuels (SAF). Further, reduction in CO2 emission is also an active area of research for land-based power generation gas turbine engines. And fuels with high hydrogen content or hydrogen blends are regarded as an essential part of future power plants. Therefore, clean hydrogen and other hydrogen-based fuels are expected to play a critical role in reducing greenhouse gas emissions in the future. However, the massive difference in hydrogen’s physical properties compared to hydrocarbon fuels, ignition, and flashback issues are some of the major concerns, and a detailed understanding of hydrogen combustion characteristics for the conditions at which gas turbines operate is needed. Numerical combustion analyses can play an essential role in exploring the combustion performance of hydrogen as an alternative gas turbine engine fuel. While several combustion models are available in the literature, two of the most preferred models in recent times are the flamelet generated manifold (FGM) model and finite-rate (FR) combustion model. FGM combustion model is computationally economical compared to the detailed/reduced chemistry modeling using a finite-rate combustion model. Therefore, this paper aims to understand the performance of the FGM model compared to detailed chemistry modeling of turbulent flames with different levels of hydrogen blended fuels. In this paper, a detailed comparison of different combustion characteristics like temperature, species, flow, and NOx distribution using FGM and finite rate combustion models is presented for three flame configurations, including the DLR Stuttgart jet flame [2], Bluff body stabilized Sydney HM1 flame [3] and dry-low-NOx hydrogen micro-mix combustion chamber [4]. One of the FGM model’s essential parameters is to select a suitable definition of the reaction progress variable. The reaction progress variable should monotonically increase from the unburnt region to the burnt region. The definition is first studied using a 1D premixed flame with different blend ratios and then used for the actual cases. 2D/3D simulations for the identified flames are performed using FGM and finite rate combustion models. Numerical results from both these models are compared with the available experimental data to understand FGM’s applicability. The results show that the FGM model performs reasonably well for pure hydrogen and hydrogen blended flames.

Validation of Chemistry Acceleration Techniques With an Industrial Gas Turbine

2019 ◽  
Author(s):  
George Mallouppas ◽  
Graham Goldin ◽  
Yongzhe Zhang ◽  
Piyush Thakre ◽  
Jim Rogerson
Keyword(s):  
Gas Turbine ◽  
Relative Increase ◽  
Detailed Chemistry ◽  
Pollutant Formation ◽  
Eddy Simulation ◽  
Acceleration Techniques ◽  
Wide Range ◽  
German Aerospace ◽  
Computational Resources ◽  
Industrial Gas Turbine

Abstract Two different numerical techniques for chemistry acceleration are examined with Large Eddy Simulation of a commercial swirl industrial gas turbine combustor operating at 3 bar. This work presents the results for SGT-100 Dry Low Emission (DLE) gas turbine provided by Siemens Industrial Turbomachinery Ltd. The related experimental study was performed at the German Aerospace Centre, DLR, Stuttgart, Germany. LES with detailed chemistry calculations is an attractive tool to study turbulent premixed flames in industrial gas turbine combustors, because it can help understand turbulence-chemistry interactions, detailed flame characteristics and pollutant formation. Detailed chemistry can capture kinetically dominated processes such as ignition, extinction and pollutant formation. However, computational resources required for such calculations are often prohibitive due to the computational costs of transporting and integration of a large number of species with a wide range of chemical time-scales. Chemistry acceleration techniques can substantially reduce run-time with ideally a small loss in accuracy. Therefore, the purpose of this work is to quantify the relative increase in performance and potential loss in accuracy with two chemistry acceleration techniques namely Clustering, Dynamic Mechanism Reduction (DMR) and their combination. The results show that the different chemistry acceleration techniques do not compromise the time averaged flow statistics. However, there are some differences in NO and CO emissions. Chemistry acceleration techniques yield up to ∼3 times speed-up of the simulation.

scholarly journals Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Hsuan-Ming Huang ◽  
Ing-Tsung Hsiao
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Low Dose ◽  
Computational Cost ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Acceleration Techniques ◽  
Reconstruction Methods ◽  
Speed Up ◽  
Phantom Studies

Background and Objective. Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques.Methods. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively.Results. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method.Conclusions. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

NMHC and VOC Speciation of the Exhaust Gas From a Gas Turbine Engine Using Alternative, Renewable and Conventional Jet A-1 Aviation Fuels

2014 ◽  
Author(s):  
Mohamed A. Altaher ◽  
Hu Li ◽  
Simon Blakey ◽  
Winson Chung
Keyword(s):  
Gas Turbine ◽  
Gas Turbine Engine ◽  
Aviation Fuel ◽  
Exhaust Gas ◽  
Turbine Engine ◽  
Fuel Blends ◽  
Auxiliary Power ◽  
Unburned Hydrocarbons ◽  
Full Power ◽  
Two Stages

This paper investigated the emissions of individual unburned hydrocarbons and carbonyl compounds from the exhaust gas of an APU (Auxiliary Power Unit) gas turbine engine burning various fuels. The engine was a single spool, two stages of turbines and one stage of centrifugal compressor gas turbine engine, and operated at idle and full power respectively. Four alternative aviation fuel blends with Jet A-1 were tested including GTL, hydrogenated renewable jet fuel and fatty acid ester. C2-C4 alkenes, benzene, toluene, xylene, trimethylbenzene, naphthalene, formaldehyde, acetaldehyde and acrolein emissions were measured. The results show at the full power condition, the concentrations for all hydrocarbons were very low (near or below the instrument detection limits). Formaldehyde was a major aldehyde species emitted with a fraction of around 60% of total measured aldehydes emissions. Formaldehydes emissions were reduced for all fuels compared to Jet A-1 especially at the idle conditions. There were no differences in acetaldehydes and acrolein emissions for all fuels; however, there was a noticeable reduction with GTL fuel. The aromatic hydrocarbon emissions including benzene and toluene are decreased for the alternative and renewable fuels.

Review of Hybrid Emissions Prediction Tools and Uncertainty Quantification Methods for Gas Turbine Combustion Systems

2017 ◽  
Author(s):  
Sajjad Yousefian ◽  
Gilles Bourque ◽  
Rory F. D. Monaghan
Keyword(s):  
Uncertainty Quantification ◽  
Gas Turbine ◽  
Kinetic Modelling ◽  
Computational Cost ◽  
Chemical Kinetic ◽  
Design Development ◽  
Deterministic Models ◽  
Prediction Tools ◽  
Gas Turbine Combustion ◽  
Combustion Systems

There is a need for fast and reliable emissions prediction tools in the design, development and performance analysis of gas turbine combustion systems to predict emissions such as NOx, CO. Hybrid emissions prediction tools are defined as modelling approaches that (1) use computational fluid dynamics (CFD) or component modelling methods to generate flow field information, and (2) integrate them with detailed chemical kinetic modelling of emissions using chemical reactor network (CRN) techniques. This paper presents a review and comparison of hybrid emissions prediction tools and uncertainty quantification (UQ) methods for gas turbine combustion systems. In the first part of this study, CRN solvers are compared on the bases of some selected attributes which facilitate flexibility of network modelling, implementation of large chemical kinetic mechanisms and automatic construction of CRN. The second part of this study deals with UQ, which is becoming an important aspect of the development and use of computational tools in gas turbine combustion chamber design and analysis. Therefore, the use of UQ technique as part of the generalized modelling approach is important to develop a UQ-enabled hybrid emissions prediction tool. UQ techniques are compared on the bases of the number of evaluations and corresponding computational cost to achieve desired accuracy levels and their ability to treat deterministic models for emissions prediction as black boxes that do not require modifications. Recommendations for the development of UQ-enabled emissions prediction tools are made.

An Onion Peeling Reconstruction of the Spatial Characteristics of Entropy Waves in a Model Gas Turbine Combustor

2017 ◽  
Author(s):  
Dominik Wassmer ◽  
Felix Pause ◽  
Bruno Schuermans ◽  
Christian Oliver Paschereit ◽  
Jonas P. Moeck
Keyword(s):  
Gas Turbine ◽  
Reaction Zone ◽  
Equivalence Ratio ◽  
Acoustic Noise ◽  
Accurate Determination ◽  
Time Of Flight ◽  
Spark Discharge ◽  
Turbine Stage ◽  
Radial Temperature ◽  
Reconstructed Temperature

Entropy noise affects thermoacoustic stability in lean pre-mixed gas turbine combustion chambers. It is defined as acoustic noise that is emitted at the first turbine stage due to the acceleration of entropy waves that are advected from the reaction zone in the combustor to the turbine inlet. These non-isentropic temperature waves are caused by equivalence ratio fluctuations which are inherently present in a technically premixed combustion system. To experimentally study the generation and transport of entropy waves, an estimation of the spatial distribution of the entropy spots is highly valuable as it allows the accurate determination of the cross-section averaged entropy, which is the relevant quantity for the formation mechanism of entropy noise at the turbine stage. In this work, a time-of-flight based temperature measurement method is applied to a circular combustion test rig equipped with a premixed swirl-stabilized combustor. Downstream of the burner, an electric spark discharge is employed to generate a narrow acoustic pulse which is detected with a circumferentially arranged microphone array. The measured time of flight of the acoustic signal corresponds to the line-integrated inverse of the speed of sound between the acoustic source and each microphone. By modulating a share of the injected gaseous fuel, equivalence ratio fluctuations are generated upstream of the reaction zone and consequently entropy spots are advected through the axial measurement plane. The spark discharge is triggered at distinct phase angles of the entropy oscillation, thus allowing a time resolved-analysis of the thermo-acoustic phenomenon. Estimating the spatial temperature distribution from the measured line integrated inverse speed of sounds requires tomographic reconstruction. A Tikhonov regularized Onion Peeling is employed to deduce radial temperature profiles. To increase the number of independent data, the spark location is radially traversed, which enhances the resolution of the reconstructed temperature field. A phantom study is conducted, which allows the assessment of the capabilities of the reconstruction algorithm. By means of the reconstructed radial entropy field, spatially resolved entropy waves are measured and their amplitudes and phases are extracted. The characteristics of the entropy waves measured in this way correspond well to former studies.

Comparison of Temperature Fields and Emissions Predictions Using Both an FGM Combustion Model, With Detailed Chemistry, and a Simple Eddy Dissipation Combustion Model With Simple Global Chemistry

2017 ◽  
Author(s):  
Pierre Q. Gauthier
Keyword(s):  
Mixture Fraction ◽  
Temperature Fields ◽  
Combustion Model ◽  
Detailed Chemistry ◽  
Combustion Modeling ◽  
Flamelet Generated Manifold ◽  
Wide Range ◽  
Turbulence Effects ◽  
Air Chemistry ◽  
Dissipation Model

The detailed modeling of the turbulence-chemistry interactions occurring in industrial flames has always been the leading challenge in combustion Computational Fluid Dynamics (CFD). The wide range of flame types found in Industrial Gas Turbine Combustion systems has exacerbated these difficulties greatly, since the combustion modeling approach must be able to predict the flames behavior from regions of fast chemistry, where turbulence has no significant impact on the reactions, to regions where turbulence effects play a significant role within the flame. One of these combustion models, that is being used more and more in industry today, is the Flamelet Generated Manifold (FGM) model, in which the flame properties are parametrized and tabulated based on mixture fraction and flame progress variables. This paper compares the results obtained using an FGM model, with a GRI-3.0 methane-air chemistry mechanism, against the more traditional Industrial work-horse, Finite-Rate Eddy Dissipation Model (FREDM), with a global 2-step Westbrook and Dryer methane-air mechanism. Both models were used to predict the temperature distributions, as well as emissions (NOx and CO) for a conventional, non-premixed, Industrial RB211 combustion system. The object of this work is to: (i) identify any significant differences in the predictive capabilities of each model and (ii) discuss the strengths and weakness of both approaches.

scholarly journals Evaluating simplified chemical mechanisms within present-day simulations of the Community Earth System Model version 1.2 with CAM4 (CESM1.2 CAM-chem): MOZART-4 vs. Reduced Hydrocarbon vs. Super-Fast chemistry

2018 ◽  
Vol 11 (10) ◽  
pp. 4155-4174 ◽  
Author(s):  
Benjamin Brown-Steiner ◽  
Noelle E. Selin ◽  
Ronald Prinn ◽  
Simone Tilmes ◽  
Louisa Emmons ◽  
...  
Keyword(s):  
Computational Cost ◽  
Earth System Model ◽  
Chemical Mechanism ◽  
System Model ◽  
Earth System ◽  
Chemical Mechanisms ◽  
Trade Offs ◽  
Community Earth System Model ◽  
Time Periods ◽  
Fast Mechanism

Abstract. While state-of-the-art complex chemical mechanisms expand our understanding of atmospheric chemistry, their sheer size and computational requirements often limit simulations to short lengths or ensembles to only a few members. Here we present and compare three 25-year present-day offline simulations with chemical mechanisms of different levels of complexity using the Community Earth System Model (CESM) Version 1.2 CAM-chem (CAM4): the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) mechanism, the Reduced Hydrocarbon mechanism, and the Super-Fast mechanism. We show that, for most regions and time periods, differences in simulated ozone chemistry between these three mechanisms are smaller than the model–observation differences themselves. The MOZART-4 mechanism and the Reduced Hydrocarbon are in close agreement in their representation of ozone throughout the troposphere during all time periods (annual, seasonal, and diurnal). While the Super-Fast mechanism tends to have higher simulated ozone variability and differs from the MOZART-4 mechanism over regions of high biogenic emissions, it is surprisingly capable of simulating ozone adequately given its simplicity. We explore the trade-offs between chemical mechanism complexity and computational cost by identifying regions where the simpler mechanisms are comparable to the MOZART-4 mechanism and regions where they are not. The Super-Fast mechanism is 3 times as fast as the MOZART-4 mechanism, which allows for longer simulations or ensembles with more members that may not be feasible with the MOZART-4 mechanism given limited computational resources.

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