NUMERICAL INVESTIGATION OF PERFORMANCE, COMBUSTION AND EMISSION OF VARIOUS BIOFUELS.pptx

**Numerical Investigation of Performance, Combustion, and Emissions of Various Biofuels**

In recent years, there has been growing interest in biofuels as a sustainable alternative to fossil fuels due to their potential to reduce greenhouse gas emissions and dependence on non-renewable energy sources. Biofuels, derived from organic materials such as plants, algae, and waste, offer promising prospects for improving energy sustainability. To maximize their benefits, a comprehensive understanding of their performance, combustion characteristics, and emission profiles is crucial. This study aims to address these aspects through a numerical investigation.

The investigation begins with a detailed performance analysis of various biofuels. Performance metrics include energy density, fuel efficiency, and power output. Biofuels such as ethanol, biodiesel, and biogas are compared to each other and to traditional fossil fuels. By using numerical simulations, the study evaluates how different biofuels perform under various operational conditions, such as engine types, load levels, and environmental factors. These simulations provide insights into how biofuels can be optimized for specific applications, such as transportation or industrial use.

Combustion characteristics are another key focus of this study. The combustion process of biofuels is influenced by their chemical composition, which varies depending on the feedstock and processing methods. Numerical models simulate the combustion process to analyze factors like flame temperature, combustion efficiency, and reaction kinetics. These models help to understand how different biofuels burn and how their combustion can be controlled to achieve optimal performance. The study also explores the impact of combustion conditions on fuel consumption and engine longevity.

Emission profiles of biofuels are critically examined to assess their environmental impact. Emissions from biofuels include carbon dioxide (CO2), nitrogen oxides (NOx), particulate matter, and unburned hydrocarbons. Numerical simulations are used to predict the emission levels of various biofuels under different operating conditions. By comparing these emissions with those from conventional fossil fuels, the study aims to identify which biofuels offer the most significant reduction in harmful pollutants. The goal is to provide data that supports the development of biofuels with lower environmental impact.

The study employs advanced computational techniques to perform these numerical investigations. Computational Fluid Dynamics (CFD) models, chemical kinetics simulations, and emission prediction algorithms are used to analyze the performance, combustion, and emissions of biofuels. These models are validated against experimental data to ensure accuracy. The results from these simulations are then used to generate recommendations for biofuel usage and development.

1. NUMERICAL INVESTIGATION OF PERFORMANCE, COMBUSTION AND EMISSION OF VARIOUS BIOFUELS DEPARTMENT OF MECHANICAL ENGINEERING NATIONAL INSTITUTE OF TECHNOLOGY MANIPUR Presented by RAJ GAURAV (15UME012) BUDDHA DEV KUMAR (15UME008) B V S SURYA PRASAD (15UME006) 1 Under the supervision of Dr. t.n . Verma

2. Introduction Fuel properties Experimental setup Numerical simulation approach Results & discussion Conclusion List of publication Reference 2

3. FUELS Fuels are any materials that store potential energy in forms that can be practicably released and used as heat energy. Fuels are required for a variety of purposes,but are utilized chiefly for.. 3

4. Power Generation • The generation of electricity is the single largest use of fuel in the world. • More than 60 % of power generated comes from fossil fuels 4

5. Transportation • Globally, transportation accounts for 25% of energy demand and nearly 62% of oil consumed 5

6. Internal combustion engines Engines in which the combustion of fuels takes place inside the cylinder App: automobiles, ships, planes, trains etc,. 6

7. Fossil Fuels will soon be Exhausted BUT • If we had replenish fuel sources, what direction should we go in? • Electric cars • Solar power • Wind power OR 7

8. Biofuels What are biofuels ? Any hydrocarbon fuel that is produced from organic matter (living or once living material) in a short period of time (days, weeks, or even months) is considered a Biofuel . 8

9. Biofuel vs Fossil Fuel Fossil fuels are not renewable, which means they will run out at some point. As our ability to pump fossil fuels from the ground diminishes, the available supply will decrease, which will inevitably lead to an increase in price. Biofuels can be looked upon as a way of energy security which stands as an alternative of fossil fuels that are limited in availability. Today, the use of biofuels has expanded throughout the globe. 9

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11. Properties PD JME [29] SME [36] RME [36] PSBD [39] LME [42] CSOBD [43] EEFO [44] MAOME [45] Density (kg/m 3 ) 830 881 885 874 880 865 864 885 864 Viscosity at 40 °C (cst) 3.2 4.12 5.2 7.9 – 4.2 4.14 4.741 4.41 Cetane number 48 48.13 51.3 54.4 60 48 52 52.6 – Low heating value of fuel (MJ/kg) 42.5 39.5 36.22 39.45 34.45 40.75 36.8 40.05 39.1 Flash point (°C) 56 165 – 244 – 161 – 114 115 Fire point (°C) 63 – – – – – – 125 – Oxygen (%) 0.4 9.6 10.81 10.9 11.5 11.72 10 – – Carbon content (%) 87.0 – 77.31 77.0 77.0 78.14 – – – Hydrogen content (%) 12.6 – 11.88 12.1 11.5 9.98 – – – Sulfur content (%) – 0.5 0.15 – 0.05 – – FUEL PROPERTIES Table 1 Physical and chemical properties of test fuels. 11

12. Properties PD   SME20   SME30 SME40 SME100 [36]   Density (kg/m 3 ) 830 841 847 852 885 Viscosity at 40 °C ( cst ) 2.6 2.918 3.091 3.275 4.630 Cetane number 48 48.694 49.035 49.371 51.30 Low heating value of fuel (MJ/kg) 42.5 41.178 40.530 39.890 36.22 Flash point (°C) 50 64 71 78 120 Oxygen (%) 0.6 2.748 3.802 4.842 10.81 Carbon content (%) 86.2 84.328 83.411 82.506 77.31 Hydrogen content (%) 13.2 12.922 12.785 12.651 11.88 Table 2 Physical and chemical properties of Soybean methyl ester at various blend ratio .

13. Properties PD B20 B30 B40 B100 [45]   Density (kg/m 3 ) 830 836.172 839.225 842.256 860 Viscosity at 40 °C ( cst ) 2.6 3.037 3.283 3.549 5.66 Cetane number 48 48.841 49.254 49.661 52 Low heating value of fuel (MJ/kg) 42.5 42.260 42.142 42.026 41.360 Flash point (°C) 50 --- --- --- --- Oxygen (%) 0.6 2.477 3.357 4.306 2.520 Carbon content (%) 86.2 233.145 305.186 376.297 784.400 Hydrogen content (%) 13.2 12.955 12.836 12.718 12.040 Table 3 Physical and chemical properties of microalgae oil methyl ester at various blend ratio. 13

14. Properties PD FB20   FB30   FB40 FB100   Density (kg/m 3 ) 830 136.172 839.225 842.256 860 Viscosity at 40 °C ( cst ) 2.6 2.861 3.0023 8.149 4.2 Cetane number 48 48.968 49.442 49.911 52.6 Low heating value of fuel (MJ/kg) 42.5 41.984 41.731 41.482 40.05 Flash point (°C) 50 --- --- --- --- Oxygen (%) 0.6 2.767 3.830 4.879 10.9 Carbon content (%) 86.2 84.263 83.314 82.377 77 Hydrogen content (%) 13.2 12.968 12.854 12.742 12.1 Table 4 Physical and chemical properties of Ethyl ester Fish oil at various blend ratio. 14

15. Properties PD WCO10   WCO20   WCO30   WCO40     WCO100     Density (kg/m 3 ) 830 834 838 842 846 871 Viscosity at 40 °C ( cst ) 2.6 2.8 3 3.2 3.4 4.6 Cetane number 48 50.1 50.2 50.3 50.4 51 Low heating value of fuel (MJ/kg) 42.5 --- ---- --- --- --- Flash point (°C) 50 90.3 130.6 170.9 211.2 453 Oxygen (%) 0.6 1.62 2.64 3.66 4.68 10.8 Carbon content (%) 86.2 85.29 84.38 83.47 82.56 77.1 Hydrogen content (%) 13.2 13.09 12.98 12.87 12.76 12.1 Table 5 Physical and chemical properties of Waste coocking oil at various blend ratio. 15

16. Parameter Value Make Legion Brothers Engine type 1/4 Bore (mm) 80 Stroke (mm) 110 Connecting rod length (mm) 235 Compression ration 17.5 Maximum Power (KW) 3.7 Dynamometer Eddy current Method of cooling Water cooled Nozzle type Multi hole 3. Experimental setup 16

17. S. No. Working System Function 1. Eddy current dynamometer Torque & Power 2. Flywheel Store rotation energy 3. Exhaust gas calorimeter Energy lost to exhaust or heat content of exhaust 4. Crank angle encoder Crank angle 5. Pressure sensor Combustion cylinder pressure 6. Temperature sensors Temperature measurement different points in setup 7. Rota meter Flow measurement 8. Load cell Force measurement 3.1 Function of working setup 17

18. 3.2 Uncertainties of experimental setup Table 7 Uncertainty of instruments Instrument Uncertainty (%) Temperature Sensor ±0.15 Speed Sensor ±1.0 Load indicator ±0.2 Pressure Sensor ±0.5 Crank Angle encoder ±0.2 Smoke ±1.0 Flue gas analyzer CO 2 NO X   ± 1% ± 0.5%   Total percentage of uncertainty = square root of [(0.15)2+ (1.0)2+ (0.2)2+ (0.5)2+ (0.2)2+ (1.0)2+ (0.15)2+ (1.0)2+ (0.5)2] = ±1.92%. 18

19. 3.4 Validation of Diesel RK tool To validate the results from the Diesel-RK model simulation tool proposed herewith, experimental results were compared, as shown in Fig. (1&2) Table 6 Comparison of input parameters Parameter Gnanasekaran S, et al. (2016) Authors work CR 17.5 17.5 FIP 180 bar 220 bar Speed 1500 rpm 1500 rpm Load 100% 100% Injection timing 24.0° b TDC 23.0° b TDC Cooling system Air water Fuel Diesel diesel Inlet valve open 5° before TDC 4.5° before TDC Inlet valve closed 35° BDC 35.5° after BDC Outlet valve open 35° before BDC 35.5° before BDC Outlet valve closed 5° after TDC 4.5° after TDC 19

20. Fig. 1. Variation of crank angle versus cylinder pressure 20

21. Fig. 2. Variation of crank angle versus heat release rate 21

22. Parameter Validation 1 (Author) Validation 2 [9]   Experimental Numerical ED (%) Experimental Numerical ED (%) CP (bar) 86.62 87.71 1.24 73.6 73.82 0.29 HRR (J/CA) 57.4 55.3 3.6 60.0 58.1 3.1 Table 7 Comparison of experimental and numerical results at full load condition 22

23. Diesel RK Model The software Diesel-RK is based on the first law of thermodynamics and is used for the calculation of combustion, engine performance and ecological analysis parameters. The Diesel-RK model analyses mixture formation and combustion in a diesel engine. Governing equations The above equation gives the conservation of energy, frictional mean effective pressure (FMEP), brake specific fuel consumption respectively in equation (1-3). 1 2 3 23

24. Model of NO X formation The thermal NO is calculated using chain Zeldovich mechanism , which is given as follows in equation. The volume concentration of NO in combustion products is calculated using equations (4-6). 4 5 6 24

25. Result and Discussion The effect of physical and chemical composition of various alter native fuels on the combustion, performance and emission of a C.I en gine with single cylinder, four stroke, DI, water cooled, naturally as pirated, is discussed here. 25

26. PARAMETERS OF EFFICIENCY AND POWER Specific Fuel Consumption, kg/kWh Efficiency of piston engine ( Eta_f ) Indicated Efficiency ( Eta_i ) Volumetric Efficiency Average Exhaust Manifold Gas Temperature, K EMISSION ANALYSIS Bosch Smoke Number Specific Particulate Matter, (g/kWh) Specific Carbon dioxide emission, (g/kWh) Fraction of wet NOx in exh . gas,(ppm) Summary emission of PM and Nox Specific SO2 emission, g/kWh 26

27. COMBUSTION Maximum Cylinder Pressure, bar Maximum Cylinder Temperature, K Max. Rate of Pressure Rise, bar/deg. Max. Injection Pres. (before nozzles), bar Sauter Mean Diameter of Drops, microns Ignition Delay Period, deg. Combustion duration, deg. 27

28. Fig. 3 . Variation of average exhaust manifold gas temperature versus load . The exhaust gas temperature (EGT) is the temperature obtained at the end of expansion stroke. The EGT of an engine increases with increase in loading due to more fuel delivery inside the engine cylinder. The EGT also depends on the amount of oxygen present in the fuel and high cetane number in the fuel decrease the premixed duration time. This in turn continued the burning of the fuel till late combustion phase during the expansion stroke and hence more heat is released [43] . 28

29. Fig. 4 . Variation of bosch smoke number versus load . The smoke decreases with high content of oxygen in the alternative fuel, contributing to complete combustion of the fuel even in rich zones [33]. The BSN of PD at full load was found to be 3.0272. 29

30. Fig. 5 . Variation of brake thermal efficiency versus load . The brake thermal e ffi ciency (BTE) de fi nes the ability of an engine in converting chemical energy of the fuel to mechanical output. The BTE of an engine increases with increase in engine load thereby, the brake power and fl ow rate also increases [1,43,50] . 30

31. Fig. 7 . Variation of fraction of wet NOx in exhaust gas versus load . The NO x emission of all fuels increases with increase in load. 31

32. Fig. 8 . Variation of indicated efficiency versus load . I ndicated efficiency (IE) is the efficiency of the engine with respect to the power obtained inside the cylinder before transferring to the piston and cylinder. With increase in load of the engine, the IE decreases gradually. 32

33. Fig. 9 . Variation of sp. Carbon dioxide emission versus load . The rate of CO 2 emission decreases gradually with increase in engine load, leading to more fuel injection in the chamber. It can be observed that the CO 2 emission of PD is lower than all other tested fuels 33

34. Fig. 1 . Variation of specific SO2 emission versus load . The rate of Specific SO 2 emission decreases gradually with increase in engine load. The rate of Specific SO 2 emission of PD is almost 0. 34

35. Fig. 1 1 . Variation of summery emission of PM and NOx versus load . Emission of PM and Nox increases gradually with increase in engine load 35

36. Fig. 12. Variation of volumetric efficiency versus load . The volumetric effi ciency of an engine depends on inlet pressure and temperature. Since the inlet conditions are same for all fuels, there is steep decrease in volumetric efficiency of all fuels. 36

37. Fig. 1 3 . Variation of specific fuel consumption versus load . It can be observed that the SFC of the engine decreases with increase in loading of the engine. With increase in density and viscosity of biodiesels, there is increase in amount of injected fuel and hence SFC increases as compared to PD. But with increase in load, the SFC decreases due to reduction of engine speed and tends to stabilize for all biodiesels at higher load. 37

38. Fig. 1 4 . Variation o f maximum cylinder pressure versus load . The pressure of the cylinder gradually increases with increase in engine load. The greater the ignition delay, the higher the fuel consump tion thereby resulting in high peak pressure of the combustion [50] . 38

39. Fig. 1 5 . Variation of maximum cylinder temperature versus load . The cylinder peak temperature of the tested fuels increases with increase in load. 39

40. Fig. 1 6 . Variation o f maximum rate of pressure rise versus load . The maximum rate of pressure rise is an important parameter in determining the knocking tendency of an internal combustion engine [19] . The variation in maximum rate of pressure rise with various loading is shown . The maximum rate of pressure rise in creases with increase in engine load. The rate of pressure rise (maximum) was found to be highest for PD at maximum load. 40

41. Fig. 1 7 . Variation of maximum injection pressure versus load . Maximum injection pressure increases with increases in load. 41

42. 6.Conclusion In the combustion characteristics, the biodiesels have shown closeness in terms of cylinder pressure, temperature, cylinder peak pressure with PD. The biodiesels have lesser ignition delay, as compared with PD. Also in performance characteristics, the speci fi c fuel consumption decrease for all fuels with increase in load of the engine. While the brake thermal e ffi ciency increased for all tested fuels, the volumetric e ffi ciency decreases with increase in load. The values of indicated and mechanical e ffi ciency for all tested biofuels were close to PD. The soot and smoke formation was highest in PD and lesser for biodiesels. NO emission increased for all fuels during increment in engine load. Among all types of blend B20 are more preferable. 42

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46. SD standard deviation RME rapeseed methyl ester SFC speci fi c fuel consumption (g/kWh) SME soybean methyl ester SOI start of injection (degree) SFC speci fi c fuel consumption (kg/kWh) SFR soot formation rate (1/deg) SS speed sensor STP spray tip penetration (mm) V p mean piston velocity (m/s) S ̇ g net generation rate of the ith species (kg/s) T temperature (K) TDC top dead centre TIS temperature indicator sensor T b temperature in a burnt gas zone (K) TME tallow methyl ester V volume of cylinder (cm 3 ) V 1 current velocity of the EFM (m/s) V initial velocity of the EFM at the nozzle of the injector (m/ s) V m fuel spray evaluation process in a medium speed diesel engine (m/s) V k swept volume (cm 3 ) V i & V c cylinder volumes at injection timing and top dead centre (cm 3 ) x fraction of fuel burnt X fraction of burnt fuel during ignition delay Y i mass fraction [N 2 ] e equilibrium concentrations of an molecular nitrogen [NO] e equilibrium concentrations of an oxide of nitrogen [O] e equilibrium concentrations of molecular oxygen [O 2 ] e equilibrium concentrations of atomic oxygen r H 2 O volume fraction of water vapor in a combustion chamber stoichiometric coe ffi cients on the reactant side i stoichiometric coe ffi cients on the product side α , β , λ constants α 1 air-fuel equivalence ratio τ time (second) τ k travel time for the EFM to reach a distance l from the in- jector ’ s nozzle ρ density (kg/m 3 ) ν speci fi c volume (m 3 /kg) ϕ crank angle (degree) ω angular crank velocity (rpm) ε compression ratio ξ b cylinder air charge usage e ffi ciency σ ud , σ u fuel fractions evaporated during ignition delay period and up molar rate of production (mol/s) heat release rate (J/deg) variable compression ratio volumetric e ffi ciency (%) A/F air/fuel BMEP brake mean e ff ective pressure (bar) BN Bosch number BSN Bosch smoke number BT brake power (kW) BTE brake thermal e ffi ciency (%) b m depth of the spray forward front (m) CA crank angle (degrees) CAE crank angle encoder CI compression ignition CN cetane number of fuel CPP cylinder peak pressure (bar) CR compression ratio CPT cylinder peak temperature (K) CSOBD cotton seed oil biodiesel DI direct injection ED error deviation (%) EGR exhaust gas recirculation EGT exhaust gas temperature (K) EEFO ethyl ester fi sh oil E a apparent activation energy for the auto ignition process (kJ/kmole) FMEP friction mean e ff ective pressure (bar) HSL Hartridge Smoke Level h wfr height of the NWF forward front JME jatropha methyl ester K T evaporation constant l current distance between the injector ’ s nozzle and the lo- cation of the EFM (m) total mass (kg) m f fuel mass per cycle (kg/h) NOP nozzle opening pressure (bar) NWF near wall fl ow engine speed (rpm) P pressure (bar) PD pure diesel PM particular matter (g/kWh) POU percentage of uncertainty (%) PSBD palm stearin biodiesel PTS pressure transducer sensor P max maximum cylinder pressure (bar) P b brake power (kW) q c cycle fuel mass (kg) R gas constant (J/(mol·k)) SE standard error NOMENCLATURE 46

47. Thank you 47