Research ArticleResearch on Simulink/Fluent Collaborative Simulation Zoomingof Marine Gas Turbine
Zhi-taoWang, Jian Li, Tie-lei Li, and Shu-ying Li
College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China
Correspondence should be addressed to Tie-lei Li; ltl [email protected]
Received 30 September 2016; Accepted 15 December 2016; Published 2 March 2017
Academic Editor: Wu Deng
Copyright © 2017 Zhi-tao Wang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Based on the detailed analysis of collaborative running interface of Simulink/Fluent, a system simulation for the rated workingcondition as well as variable working condition of marine gas turbine has been achieved, which can improve the simulationefficiency of marine gas turbine by developing simulation model of combustor with Fluent and simulation models of othercomponents with Simulink. The result shows that the Simulink/Fluent collaborative simulation zooming can make the innerworking conditions of combustor be observed specifically, based on the overall performance matching analysis; thus an effectivetechnical means for the structural optimization design of combustor has been provided.
1. Introduction
System simulation technology is an effective means formarine gas turbine modular design, and simulation modelswith different dimension are selected for different compo-nents according to the need of research in the process ofsimulation to achieve the simulation zooming, so that a rea-sonable balance can be found between the degree of model’sfineness and time-consuming of simulation, thus to improvethe simulation efficiency. For example, during the overallscheme design, conducting system simulation just with 0Dcomponent models can basically meet the need of the overallperformance matching analysis; when designing the struc-tural optimization for a component, what is needed to do isjust the distribution parameter calculation to the component,while the other components can still select 0D model. Thusdetailed research for the inner mechanism to the componentcan be performed on the basis of overall performancematching.
In the process of modular modeling, one can make fulluse of various types of commercial simulation software whichhave different characteristics. Usually, each kind of commer-cial simulation software belongs to a specific science fieldand supports the simulationmodel of specific dimension. Forexample, Matlab/Simulink is accomplished in dynamic sys-temmodeling and simulation, which can be used to establish
the gas turbine control system or the 0D simulation modelof other components appropriately; Fluent specializes inanalyzing fluid field and temperature field, which is suitable toestablish 2Dor 3Ddimensional steady state simulationmodelof combustor. Using the collaborative running interface ofSimulink/Fluent, the simulation models established by twokinds of simulation software are coupled together to achievethe simulation zooming, which has been applied in simula-tion research of many science fields [1–5].
In order to expand the application field and enhance theversatility, Fluent provides the following interface for users[1]: Fluent/UDF is written based on C language to deal withthe nonfixed boundary conditions or dynamic grid comput-ing and other personalized applications; Fluent/Journal isused to record the operation sequence on the Fluent/GUI andthen Fluent can be started by the external program includingcommand with Journal parameter, so that simulation task isautomatically operated according to the operation sequencein Journal. The simulation results at calculation regionalboundary can be stored in specified text file by Fluent tofacilitate sharing data with external program.
S-Function is the computer language description of theSimulink simulation module and it also provides a variety oflanguage version templates which can be used to customizethe simulation module by researchers. S-Function is com-posed of a number of callback functions. Figure 1 shows the
HindawiApplied Computational Intelligence and So ComputingVolume 2017, Article ID 8324810, 8 pageshttps://doi.org/10.1155/2017/8324810
2 Applied Computational Intelligence and Soft Computing
Run Simulink
Callback methods: Perform tasks:mdlInitializeSizes() Initialize module
mdlOutputs() Calculate outputs
mdlDerivatives() Calculate derivatives
Sim
ulat
ion
loop
mdlTerminate() Free memory
Inte
gral
step
Figure 1: Invocation mode of Simulink/S-Function.
invocationmode for themain callback functions (M languageversion) by the Simulink solver at different simulation stagesof fixed step algorithm [6]. At the initialization stage ofthe simulation, Simulink solver calls the callback function“mdlInitializeSizes()” to determine simulation module statequantity, initial state value, sampling time, and other basicinformation; at each integral step of simulation loop stage,Simulink solver calls the callback function “mdlOutputs()” tocalculate output data value of the simulation module; if thereis a continuous state in the simulation module, the Simulinksolver needs to call the callback function “mdlDerivatives()”to achieve integral for the continuous state; at the end ofthe simulation, Simulink solver calls the callback function“mdlTerminate()” to release the storage space. It should benoted that the Simulink solver will call the correspondingcallback function of all the simulation modules in sequence.For example, at each integral step of simulation loop stage,Simulink solver will call the callback function “mdlOut-puts()” of all the simulation modules in sequence andthen call “mdlDerivatives()” function of all the simulationmodules.
Making use of external interface of Fluent and Simulink,the following three approaches can achieve Simulink/Fluentcollaborative simulation: Fluent is embedded in Simulink [4,5]; that is, Fluent simulation model is encapsulated to a sim-ulation module which has the same attribute and operationstylewith the build-inmodule and participates in the runningof the Simulink simulation model; Simulink is embedded inFluent [1]; that is, Simulink simulationmodel is compiled intoC function for Fluent/UDF to call; Simulink and Fluent runparallelly that is to achieve simulation collaboration throughthe global variate [1] or a kind of process blocking technology[2, 3]. As the first approach has more advantages in versatilityand flexibility, it has become the mainstream of currentapplication.
The general idea to develop the collaborative runninginterface of Simulink/Fluent, based on the first approach, is asfollows [4, 5]: develop interface program based on Simulink/S-Function; start Fluent with command including Journalparameter; store the update values of the S-Function inputports into a text file; access the text file by Fluent/UDF andusing these values to dealwith nonfixed boundary conditions;
at last, Fluent will store the simulation results of the calcula-tion regional boundary into another text file and S-Functionwill access this text file to propagate its values to Simulinkvia output ports. Because many boundary conditions andphysical parameters in Fluent simulation model cannot bemodified by UDF, the interface developed by the idea men-tioned above cannot be applied in some specific fields.
In Methodology, a new collaborative running interfaceof Simulink/Fluent is developed, which is also inside therange of the first approach. Compared with the existing one,the new collaborative running interface provides boundaryconditions for Fluent environment by modifying parametersof Journal directly, instead of tedious UDF programming.
In Application, the simulation zooming research is con-ducted that takes triaxial gas turbine of a certain type as phys-icalmodel, establishing 2D simulationmodel for the combus-tor with Fluent, establishing system simulation model whichconsists of 0D component simulation models with Simulink.The 2D simulation model of combustor is embedded in theSimulink environment by encapsulating the written collab-orative running interface of Simulink/Fluent to S-Functionmodule.
2. Methodology
2.1. Collaborative Running Interface of Simulink/Fluent. Flu-ent/Journal and Simulink/S-Function have the followingfeatures: Journal uses standard syntax format to recordoperation sequence; Fluent is able to read the Journal whichis saved as text format; S-Function can call the powerful Mfunctions to read, write, andmodify the text file. Consideringthese features, it can be used to modify the parameters in theJournal text file directly to deal with the nonfixed boundarycondition, which can avoid the tedious UDF programming.Based on the idea above, this paper developed the Simulink/Fluent collaborative running interface of a certain type tri-axial gas turbine simulation zooming, using the M languageversion template of S-Function. Figure 2 shows the workflowof Simulink/Fluent collaborative running interface. The dot-ted line 1 in Figure 2 denotes that the Simulink solver alwaysstarts Fluent with command including Journal parameter ateach integral step. The dotted line 2 in Figure 2 denotesthat, according to the current simulation time, the simulationresults (Cas and Dat document) generated by Fluent arerenamed by the Simulink solver at each integral step to avoidthe automatic coverage of the Fluent simulation results. Forexample, when the current simulation time is 1 s, the sim-ulation results are renamed “1 s.cas” and “1 s.dat”; when thecurrent simulation time is 1.05 s, the simulation results arerenamed “1.05 s.cas” and “1.05 s.dat.”
2.2. Mathematical Model of Marine Gas Turbine
2.2.1. Combustor. While the combustion process of liquidfuel in the combustor is simulated by distributed parameter,assumptions are typically made as follows [7]: chemical reac-tion occurs with the liquid fuel in gas-phase; the inner andsurface of fuel droplet only change physically, and the carriermobility of droplet is less than 5%; the process of turbulent
Applied Computational Intelligence and Soft Computing 3
Read the conditions and parametersof inlet boundary of combustor
The Fluent is ending?
Yes
No
Rewrite the text file of Fluent/Journalafter modifying the parameters
Read the text file of Fluent/Journal
Run Fluent using command with parameters of Journal
Read and output the data in the textfile
Simulink/S-Function
Read the original Case & Data(simulation initialization; set theboundary conditions)
Complete iterations?No
Run Fluent
Solve the 2D simulation model ofthe combustor
End Fluent
Fluent/Journal
Yes
Save the simulation results at the boundary of computational domaininto a text file
Sharing thedata in thetext file
Save Case & Data as name with timeinformation
Initialize module
mdlInitializeSizes()
mdlOutputs()
Free memorymdlTerminate()
①
②
Save Case & Data(simulation results for postprocessing)
Figure 2: Workflow of Simulink/Fluent collaborative running interface.
diffusion combustion of liquid fuel can be treated as theliquid-phase particles motion of Lagrange coordinates alongtheir orbits and gas-phase turbulent flow and chemical reac-tion process of Euler coordinates, the two processes coupledto each other to achieve the continuous heat and masstransfer between discrete-phase and continuous-phases; theheat and mass transfer in the combustion process of gaseousfuel only occurs in the continuous-phases; the combustionflow field is in the states of thermodynamic equilibrium andchemical equilibrium. On the basis of these assumptions, themathematical model of distribution parameter of combustoris established, including gas-phase basic control equation [8–10], RNG 𝑘-𝜀 turbulence model [11], EDC combustion model[12–15], and control equations of discrete-phase [16–18].
2.2.2. The Other Components. This paper takes triaxial gasturbine of a certain type as physical model (as it is shown inFigure 3). The main mathematical model established accord-ing to the traditional method of volume inertia is as follows:
𝑑𝑛LT𝑑𝑡 = 900𝐽LT𝜋2𝑛LT {𝐺LT𝐶𝑝𝑔𝑇5 [1
− (1 − 1𝑒LT(𝑘𝑔−1)/𝑘𝑔 )𝜂LT]
C
LCHC
LTHT
PT
1 2 3 4 5 6
7
Figure 3: Physical model of triaxial gas turbine.
− 𝐺LC𝐶𝑝𝑎𝑇1 (𝛽LC(𝑘𝑎−1)/𝑘𝑎 − 1)𝜂LC }
𝑑𝑛HT𝑑𝑡 = 900𝐽HT𝜋2𝑛HT{𝐺HT𝐶𝑝𝑔𝑇4 [1
− (1 − 1𝑒HT(𝑘𝑔−1)/𝑘𝑔
)𝜂HT]
− 𝐺HC𝐶𝑝𝑎𝑇2 (𝛽HC(𝑘𝑎−1)/𝑘𝑎 − 1)
𝜂HC}
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Table 1: Main performance parameters of triaxial gas turbine of acertain type.
Performance parameters Design values𝑇2 (K) 486.1𝑇3 (K) 769.9𝑇4 (K) 1542.8𝑇5 (K) 1241𝑇6 (K) 1056.2𝐺𝑎 (kg/s) 82.1𝐺𝑓 (kg/s) 1.62𝑛HT (rpm) 9740𝑛LT (rpm) 7436𝑛PT (rpm) 3270𝜂GT 34.94%𝑁GT (kw) 24265
𝑑𝑛PT𝑑𝑡 = 900𝐽PT𝜋2𝑛PT (𝑁PT − 𝐿)𝐺𝑓 = 𝑓 (𝑛PT)𝑑𝑝2𝑑𝑡 = 𝑅𝑎𝑇2𝑉LC∼HC
(𝐺LC − 𝐺HC)𝑑𝑝3𝑑𝑡 = 𝑅𝑎𝑇3𝑉𝐶 (𝐺𝑏in + 𝐺𝑓 − 𝐺𝑏out)𝑇3 = 𝑓 (ℎ3)𝑑𝑝5𝑑𝑡 = 𝑅𝑔𝑇5𝑉HT∼LT
(𝐺HT − 𝐺LT)𝑑𝑝6𝑑𝑡 = 𝑅𝑔𝑇6𝑉LT∼PT (𝐺LT − 𝐺PT) ,
(1)
where 𝑉LC∼HC is the volume between low-pressure compres-sor and high-pressure compressor; subscript 𝑎, subscript 𝑔,and subscript 𝑓 are air, gas, and fuel; and subscript 𝑏in andsubscript 𝑏out are inlet and outlet of combustor; refer toFigure 3 for the meaning of other subscripts.
Make use of 𝐺𝑓, 𝐺𝑏in, 𝑝3, and 𝑇3, the distributed param-eter model of combustor outputs 𝑝4 and 𝑇4, which areprocessed with average method at the output boundary ofcombustor.
3. Application
3.1. SimulationModel of Marine Gas Turbine. The triaxial gasturbine of a certain type is mainly used in mechanical orelectric propulsion ofmarine, whosemain performance para-meters are shown in Table 1, where 𝜂GT and𝑁GT are efficiencyand output power of marine gas turbine; refer to Figure 3 forthe meaning of other subscripts.
Figure 4: Grid structure for 2D simulation model of combustor.
3.1.1. Combustor. The Fluent environment is selected todevelop the simulation model of distributed parameter ofcombustor; the specific process is shown in Figure 4.
Discretization of Computational Domain. Taking the 3D solidmodel of loop-type flame tube of combustor of a certain typetriaxial gas turbine as reference, a 2D axisymmetric model isbuilt by the way of area average, and the discrete computa-tional domain is also built on the basis of structured grid. Asit is shown in Figure 4, the 2D model maintains the properswirl holes, primary holes, mixing holes, head, and cool-ing holes, the corresponding domain of grid is properlyencrypted, and the total number of grids is 5355.
Adding Mathematical Models and Boundary Conditions. Themathematical models described previously are sequentiallyadded to the simulation model (e.g., RNG 𝑘-𝜀 turbulencemodel). Considering the working condition of combustorand the algorithm condition used in calculation, the fol-lowing boundary conditions are added to the simulationmodel [7]: the inlet of air, including mass flow, temperature,turbulence intensity, hydraulic diameter, and average mixingfraction; the inlet of fuel, including fuel type (using liquidfuel C7H16), injection mode and swirl angle of pressureswirl atomizer, mass flow, and temperature; the outlet ofgas, including reflux temperature, turbulence intensity, andhydraulic diameter; making sure the wall is the heat insulat-ing wall and has no slip velocity, whose parameters are zero,including turbulence parameter, concentration, and normalgradient of square value of concentration pulsation.
Solver Settings. The solver of Fluent automatically makes theconvection term, diffusion term, and source term of basiccontrol equation be discrete based on the structured gridof computational domain. This paper selects Simple algo-rithm [10] to solve the discrete simulation model, whichuses “guess-correction” process, computing pressure-velocitycoupling field by use of staggered grid; the number ofiterations is 400.
3.1.2. System Simulation Model of Marine Gas Turbine. TheSimulink environment is selected to develop the system sim-ulation model which consists of 0D component simulationmodels [19, 20]. The 2D simulation model of combustor isembedded in the Simulink environment by encapsulating thewritten collaborative running interface of Simulink/Fluentto S-Function module which is named fluent sub, to carry
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5
4
3
2
1
swirl-air_17.10% (kg/s)
primary-orifice_24.95% (kg/s)
dilution-orifice_27.35% (kg/s)
head-air-01_5.2% (kg/s)
head-air-02_1.64% (kg/s)
head-air-03_2.14% (kg/s)
cooling-air-01_10.46% (kg/s)
cooling-air-02_11.16% (kg/s)
fluent_sub
assistant
Goto
From
4
3
2
1Gbout (kg/s)
Gbout (kg/s)
Gf (kg/s)
Gf (kg/s)
Gbin (kg/s)
Gbin (kg/s)
-T-
-T-
T3 (K)T3 (K)
T3 (K)
p3 (kPa)
p3 (kPa)p3 (kPa)
fboutfbout
RgboutRgbout
T4 (K)T4 (K)
p4 (kPa)p4 (kPa)
Gf_1/16 (kg/s)
Gain
Gain 1
Gain 2
Gain 3
Gain 4
Gain 5
Gain 6
Gain 7
Gain 8
Gain 9
-k-
-k-
-k-
-k-
-k-
-k-
-k-
-k-
-k-
-k-
Figure 5: 2D simulation model of combustor developed in Simulink environment.
out the simulation zooming. As it is shown in Figure 5, theassistant module on one hand plays a role of volume module,to provide combustor inlet pressure 𝑝3 for Fluent simulationmodel; on the other hand, it outputs the air-fuel ratio 𝑓𝑏outand gas constant of combustor outlet 𝑅𝑔𝑏out, which cannot beoutputted by Fluent simulation model.
Figure 1 shows the solving process of system simulationmodel; all the differential equations established according tothe method of volume inertia are calculated in the callbackmethod “mdlDerivatives(),” which achieves integral.
3.1.3. Result Analysis
Verification of the Simulation Results on RatedWorking Condi-tion. Simulation experimental scheme is shown in Table 2, thesetting value of speed of gas turbine controller is 3270 rpm,load power is 24265 kw, and integral step is 0.05 s. As shownin Table 2, comparing with the design values of rated workingcondition [21], the errors of simulation zooming are less than5%, this preliminarily verifies the feasibility of simulationzooming research. The simulation errors of the amount offuel and work efficiency are relatively large; the reason is thefollowing: considering the limited computing capability ofmodel runtime environment, in order to reduce the time-consuming of simulation, this paper simplifies the 3D simu-lation model of combustor to the 2D one, so that the air goesevenly into the flame tube through the primary holes, mixingholes, cooling holes, and so on; in the 3D model, several
small holes are arranged around aforementioned holes in thecircumferential direction, the air goes into the flame tubethrough the small holes, this difference weakens the intensityof the air injection so that the penetration depth and itsinfluence on the combustion flow field are not as apparentas 3D model, and the central recirculation zone formed bywhich is not big enough, causing incomplete combustionof some fuel, brings about relatively large simulation errorsof the amount of fuel and work efficiency; the collaborativerunning interface of Simulink/Fluent has the versatility, ifwe can upgrade the runtime environment; selecting 3Dsimulation model of combustor to participate in simulationzooming, simulation accuracy will be improved.
Analysis of Simulation Results on VariableWorking Condition.Simulation experimental scheme is shown in Table 2; thesetting value of speed of gas turbine controller is 3000 rpm,total simulation time is 95 s, integral step is 0.05 s, load poweris 24265 kw at 0 s, 30% load power is suddenly decreased at5 s, 30% load power is suddenly decreased at 35 s again, and20% load power is suddenly decreased at 65 s finally. As it isshown fromFigures 6–9, the speed of power turbine suddenlyincreases when the load power is suddenly decreased, underthe function of gas turbine controller, the fuel flow is rapidlydecreased, leading to the initial temperature of combustorinlet, output power and speed of power turbine will changeat the same trend. From the sudden load decrease to the cor-responding steady state of gas turbine, the adjustment time
6 Applied Computational Intelligence and Soft Computing
Table 2: Verification of simulation results on rated working condi-tion.
Simulationdata Design values Simulation
zooming valuesSimulationerrors
𝑇2 (K) 486.1 484.2 0.391%𝑇3 (K) 769.9 767 0.377%𝑇4 (K) 1542.8 1563 1.309%𝑇5 (K) 1241 1239 0.161%𝑇6 (K) 1056.2 1065 0.833%𝐺𝑎 (kg/s) 82.1 83.4 1.583%𝐺𝑓 (kg/s) 1.62 1.689 4.259%𝑛HT (rpm) 9740 9887 1.509%𝑛LT (rpm) 7436 7495 0.793%𝜂GT 34.94% 34.03% 2.604%
95
×104
0.30.50.70.91.11.31.51.71.92.12.32.5
Npt
(kw
)
10 20 30 40 50 60 70 80 900t (s)
Figure 6: Simulation result of output power.
is about 10 s. The above simulation results are conforming toreality, it proves the feasibility of simulation zooming researchonce again.
The simulation zooming can conduct partially “zoom in”for a component on the basis of the overall performancematching analysis, so the inner working conditions can beobserved in detail. Seen from the invocation mode of Simu-link/S-Function and the workflow of Simulink/Fluent collab-orative running interface described previously, the simulationresults of distributed parameter of combustor can be obtainedthrough the simulation zooming research, at each integralstep, so we can analysis the inner working conditions of com-bustor on any working condition. For example, according tothe system simulation results on variable working condition,the inner working conditions of combustor on 20% workingcondition can be clearly analyzed by the simulation results ofdistributed parameter at corresponding simulation time.
Figure 10 shows the inner temperature distribution ofcombustor, the temperature range is about 465K–2700K,high-temperature zone is concentrated in center front ofcombustion flow field and both sides of central recirculationzone, under the joint action of primary air andmixing air, andit is convergent along the axial trend of combustor, formingthe more uniform mixing gas at the outlet. The maximum
950.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Gf
(kg/
s)
10 20 30 40 50 60 70 80 900t (s)
Figure 7: Simulation result of fuel flow.
952950
3000
3050
3100
3150
npt
(rpm
)
10 20 30 40 50 60 70 80 900t (s)
Figure 8: Simulation result of speed of power turbine.
95900
1000
1100
1200
1300
1400
1500
1600
T4
(K)
10 20 30 40 50 60 70 80 900t (s)
Figure 9: Simulation result of temperature of combustor outlet.
4.65e + 025.87e + 027.10e + 028.32e + 029.55e + 021.08e + 031.20e + 031.32e + 031.44e + 031.57e + 031.69e + 031.81e + 031.93e + 032.06e + 032.18e + 032.30e + 032.42e + 032.55e + 032.67e + 032.79e + 032.91e + 03
Figure 10: Inner temperature distribution of combustor.
Applied Computational Intelligence and Soft Computing 7
−3.20e + 04−2.34e + 04−1.48e + 04−6.14e + 032.49e + 031.11e + 041.98e + 042.84e + 043.70e + 044.57e + 045.43e + 046.29e + 047.16e + 048.02e + 048.88e + 049.75e + 041.06e + 051.15e + 051.23e + 051.32e + 051.41e + 05
Figure 11: Inner total pressure distribution of combustor.
0.00e + 001.05e + 012.09e + 013.14e + 014.18e + 015.23e + 016.27e + 017.32e + 018.36e + 019.41e + 011.05e + 021.15e + 021.25e + 021.36e + 021.46e + 021.57e + 021.67e + 021.78e + 021.88e + 021.99e + 022.09e + 02
Figure 12: Inner velocity distribution of working fluid of combustor.
temperature of outlet section is in the central region ofcombustor, which is about 1700K. The cooling effect ofcombustor wall between the primary holes and head is worsethan it is of combustor wall after the primary holes; it can beimproved by increasing the air flow through the head.
Figure 11 shows the inner total pressure distribution ofcombustor; it can be seen that the pressure distribution ofmain zone is uniform, the combustion process is approxi-mately an isobaric process, and the pressure gradient appearsnear each hole and on both sides of central recirculation zone.The highest pressure of combustion flow field appears at theswirl holes, and there is low-pressure zone in central recircu-lation zone, which provides favorable condition for the stablecombustion of fuel. The total pressure recovery coefficient ofcombustor decreases as the load decreases (it is 0.943 and0.957 on 20% working condition and 100% working condi-tion, resp.).
Figure 12 shows the inner velocity distribution of workingfluid of combustor; it is clear that there is a central recir-culation zone formed by intersection of the swirl generatedby swirl holes and the jet-flow generated by primary holes.Meanwhile the central recirculation zone is smaller than theactual one, the reason is as described previously. The max-imum velocity of working fluid in combustion flow fieldappears at the inlet of swirl holes, about 166.5m/s, and theaverage velocity of the working fluid of the combustor outletis about 42m/s.
4. Conclusion
Firstly. A new workflow of Simulink/Fluent collaborativerunning interface is proposed, which provides boundary con-ditions for Fluent environment by modifying parameters ofJournal text directly, instead of tedious UDF programming.
Secondly. The 2D simulation model of combustor is devel-oped in the Fluent environment; the system simulationmodelwhich consists of 0D component simulation models is devel-oped in the Simulink environment; the 2D simulation modelof combustor is embedded in the Simulink environmentby encapsulating the written collaborative running interfaceof Simulink/Fluent to S-Function module, to realize thesimulation zooming.
Thirdly. The system simulation for the rated working con-dition as well as variable working condition of triaxial gasturbine of a certain type is achieved. The result on one handshows that the errors of simulation zooming are less than5%; on the other hand, it shows that the Simulink/Fluent col-laborative simulation zooming can make the inner workingconditions of combustor be observed specifically, based onthe overall performance matching analysis; thus an effectivetechnical means for the structural optimization design ofcombustor is provided.
Nomenclature
LC: Low-pressure compressorHC: High-pressure compressor𝐶: CombustorHT: High-pressure turbineLT: Low-pressure turbinePT: Power turbine𝑛: Rotor speed𝐺: Mass flow𝐽: Inertia of rotor𝛽: Pressure ratio𝜂: Efficiency𝐶𝑝: Specific heat [kJ/(kg⋅K)]𝑒: Expansion ratio𝑇: Temperature [K]𝑘: Adiabatic coefficient𝑁: Output power [kw]𝐿: Load power [kw]𝑝: Pressure [kPa]𝑅: Gas constantℎ: Specific enthalpy [kJ/kg].
Competing Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper.
Acknowledgments
The present work is supported by the FundamentalResearch Funds for the Central Universities of China (no.HEUCFZ160306).
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