代写PY7001 Laboratory Experimental & Computational Component代做Python编程

PY7001 Laboratory

Experimental & Computational Component

Module Credit: 20%

Learning Outcomes: To understand:

A) Particular and NOX Formation by studying the effect of:

1.    Fuel mixture fraction on soot precursor production. (by Computation)

2. Fuel mixture fraction on flame temperature. (by Computation)

3. Flame temperature on NOx production.   (by Computation)

4. Fuel composition on soot precursor production. (by Experiment & Computation)

B) Burning Velocity & Flame Structure by studying the dependence of:

5. Laminar burning velocity on fuel mixture fraction. (by Computation)

6. Laminar burning velocity on fuel composition. (by Computation)

7. Flame structure vs. extent of reaction.                (by Experiment & Computation)

(using images of flame)      

C) Chemical Equilibrium by analysing how:

8. Thermodynamic equilibrium as an excellent approximation of burned gas composition and thermodynamic state.

Reporting  & Outputs:

Compare the behaviour of Fuel #1 and Fuel #2 by creating:

1. Plots of equivalence ratio vs:

a. Flame temperature.

b. Soot precursors (C2H2, C6H6).

c. NOX. 

d. Laminar burning velocity.

2. Plots of flame structure vs distance for two distinct equivalence ratios, showing:

a. Reactants.

b. Products.

c. Molecular intermediates.

d. Radical intermediates.

e. Identify the burned gas and reaction zones.

3. Where appropriate, include the results of the equilibrium calculation on each chart above.

4. From the smoke point experiments you have conducted, create plots of fuel mixture fraction vs. smoke point and fuel mixture fraction vs. threshold sooting index. Discuss this data with regard to the pertinent aspects of learning outcomes A-C, including pertinent information derived from computation as appropriate.

Discuss the major aspects of these plots and relate the observations to the molecular structure and molecular thermodynamic constants of the fuel, and fuel/air mixtures in question. Images of the smoke point flames will be provided. Relate these to your calculations by discussion.

Your report should follow the form. of a published scientific paper to the highest professional standard of publication. Paper [7] or similar should be used as an example.

Computational Methodology

You will perform. computational experiments that simulate the combustion of a real liquid fuel at a range of operating conditions. The chemical kinetic model to be used contains 253 chemical species. (“253_NOx.yaml”) [6]. Two fuels will be used, n-decane and an n-decane/iso-octane/toluene mixture at mole fraction ratio  0.427/0.33/0.243, this mixture is a model fuel for jet aviation fuel.

Cantera [1], a combustion kinetics solver, will be used to perform. the chemical kinetic calculations. Two python scripts will be provided. One simulates a freely propagating laminar flame and the other calculates gaseous mixture chemical equilibrium. You will run these scripts at different initial conditions (fuel composition, temperature, pressure, fuel mixture fraction) to meet the objectives above. Each script. produces an excel spreadsheet containing a description of the gaseous mixture at each time/position point of the simulation. From these outputs the above graphs can be plotted, and the effect of the operating conditions analysed.

Note: Freely propagating flame simulations can take several hours to complete. As such each student will be assigned two operating conditions at which they will perform. a calculation. The excel outputs will be pooled in a google drive. You will perform. your analysis individually on this cumulative data collection.

Logistics

You are requested to download python (PyCharm [4] recommended), anaconda [5] and then install Cantera. The python scripts are available for download from the google drive here:  

https://drive.google.com/drive/folders/10CIN6T0ZYkL7DLmY_npu-FekcTSyVtRb?usp=sharing

Computational Task Assignment


References & Further Reading

[1] Cantera https://cantera.org/.

[2] Chemkin Manual - R.J. Kee, F.M. Rupley, J.A. Miller, M.E. Coltrin, J.F. Grcar, E. Meeks, H.K. Moffat,  A.E. Lutz, G. Dixon-Lewis, M.D. Smooke, J. Warnatz, G.H. Evans, R.S. Larson, R.E.,  Mitchell, L.R. Petzold, W.C. Reynolds, M. Caracotsios, W.E. Stewart, P. Glarborg, C. Wang, O. Adigun, W.G. Houf, C.P. Chou, S.F. Miller.

[3] PyCharm https://www.jetbrains.com/pycharm/download/#section=windows 

[4] Anaconda https://docs.anaconda.com/anaconda/install/windows/ 

[5] Glassman I, Yetter RA, Glumac NG, editors. Combustion (Fifth Edition). Boston: Academic Press; 2015. Chapters 1-4.

[6] Dooley S, Won SH, Chaos M, Heyne J, Ju Y, Dryer FL, et al. A jet fuel surrogate formulated by real fuel properties. Combustion and Flame. 2010 (157) 2333-2339.

[7] Dooley S, Uddi M, Won SH, Dryer FL, Ju Y, Methyl butanoate inhibition of n-heptane diffusion flames through an evaluation of transport and chemical kinetics, Combustion and Flame 159 (4) 1371-1384.

 

 

 

 


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