Liquid Biofuels. Группа авторов

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СКАЧАТЬ href="#ulink_bfcccf23-1739-520d-92c3-91b903561858">Figure 2.3 Contours of the absolute acoustic pressure field based on COMSOL simu...Figure 2.4 Grid sensitivity analysis of the CFD simulations [112].

      3 Chapter 3Figure 3.1 Steps involved in biodiesel production using vegetable oil and hetero...Figure 3.2 Reaction mechanism of transesterification using CaO catalyst [9].Figure 3.3 SEM image of CaO calcined at 600°C.Figure 3.4 XRD spectrum of CaO obtained from limestone [16].Figure 3.5 FTIR spectrum of CaO obtained from limestone [16].Figure 3.6 Overall reaction and products of the pyrolysis process.

      4 Chapter 4Figure 4.1 Various steps adopted for obtaining biofuel from microalgal biomass.Figure 4.2 Microalgal biomass conversion methods for biofuel production.Figure 4.3 Chemical conversion of triglycerides into biodiesel via transesterifi...

      5 Chapter 5Figure 5.1 Hydrothermal degradation pathways for lignin decomposition [17].Figure 5.2 Procedure for product separation [20–22].Figure 5.3 Variation of oil yield with biomass concentration [37].Figure 5.4 Hydrothermal degradation pathway of glycerol [62].Figure 5.5 Carbohydrate, protein and lipid hydrothermal degradation pathway [10]...

      6 Chapter 6Figure 6.1 Global jet fuel consumption for the past two decades.Figure 6.2 Evolution of feedstock and mechanisms for the successful conversion o...Figure 6.3 The possible mechanism adopted by aviation giants and the airlines op...

      7 Chapter 7Figure 7.1 Global total energy supply scenario. Source: IEA World Energy Balance...Figure 7.2 Glycolysis pathway.Figure 7.3 Raw FT-MIR (Mid infra-red) spectra acquired for aqueous solutions of ...

      8 Chapter 8Figure 8.1 The general layout of the conversion of biomass into energy.Figure 8.2 Development of pyrolytic oil up-gradation techniques over the years.Figure 8.3 Variation of liquid yield against the temperature with a varying mois...Figure 8.4 Schematic layout of bubbling fluidized bed reactor (adopted from [129...Figure 8.5 The schematic layout of the circulating fluidized bed reactors (adopt...Figure 8.6 The schematic layout of the vacuum pyrolysis reactor (adopted from [1...Figure 8.7 Schematic layout of the rotating cone reactor (adopted from [133]).Figure 8.8 Pyrolysis process scheme in a single-auger reactor.

      9 Chapter 9Figure 9.1 Examples of fatty acids.Figure 9.2 Examples of monoterpenes.Figure 9.3 Examples of diterpenes.Figure 9.4 Detailed procedure of Hydrothermal Liquefaction of lignocellulose bio...Figure 9.5 Detailed procedure of Hydrothermal Liquefaction of wet/algal biomass.Figure 9.6 Flow diagram of pyrolysis unit for different product production.

      10 Chapter 10Figure 10.1 TG and DTG curves of (a) sesame, (b) neem, (c) mustard, (d) mahua, a...Figure 10.2 Variation of pyrolysis products with temperature at (a) 400 °C, (b) ...Figure 10.3 FTIR spectra of sesame, neem, mustard, mahua, and polonga oil seed r...Figure 10.4 The product distribution of bio-oils obtained from sesame, neem, mus...Figure 10.5 The variation of (a) brake thermal efficiency, (b) brake specific fu...

      11 Chapter 11Figure 11.1 Pyrolysis of biomass for production of biofuels and bio-char.Figure 11.2 Fixed bed bioreactor for extraction of bio-oils by catalytic pyrolys...Figure 11.3 Fluidised bed bioreactor for catalytic pyrolysis of biomass.Figure 11.4 Summary of co-pyrolysis of lignocellulosic biomass for production of...Figure 11.5 Removal of contaminants from bio-oil.

      12 Chapter 12Figure 12.1 Fluidized bed reactor [16].Figure 12.2 Fixed bed reactor [13].Figure 12.3 Auger reactor [5].Figure 12.4 Rotating cone pyrolysis reactor [17].Figure 12.5 Tubular reactor for conversion of Caryota ures seeds to bio oil: 1. ...Figure 12.6 FTIR of bio oil.Figure 12.7 GCMS analysis of caryota oil.Figure 12.8 TGA of Caryota urens.Figure 12.9 DTG of Caryota urens.Figure 12.10 Kissinger method.Figure 12.11 KAS method.Figure 12.12 OFW method.

      13 Chapter 15Figure 15.1 Photographic representation of production process of bioethanol.Figure 15.2 Flow diagram of experimental set up: 1. Engine, 2. Air box, 3. U-tub...Figure 15.3 Schematic presentation of working principle of an AAS.Figure 15.4 Decrease in weight of piston rings due to wear.Figure 15.5 (a), (b), (c), and (d) Image of different components of pump.Figure 15.6 Reduction in weight due to wear.Figure 15.7 Comparison of change in clearance.Figure 15.8 Pictorial view of the (a) cylinder head, (b) piston crown, and (c) i...Figure 15.9 Analysis of lubricating oil viscosity at 40°C.Figure 15.10 Variation of flash point with engine operation.Figure 15.11 Variation in density of oil sample.Figure 15.12 Variation of carbon percentage as per usage of oil.Figure 15.13 (a) Concentration of zinc, iron and copper in oil after the long-te...

      14 Chapter 16Figure 16.1 Rancimat apparatus.Figure 16.2 Rancimat Method.Figure 16.3 Schematic diagram of an engine test setup.Figure 16.4 Simple neural network.Figure 16.5 Induction period for biodiesel dosed with 1000 ppm TBHQ.Figure 16.6 BSFC vs. Load for CIME diesel blend.Figure 16.7 BTE vs. Load for biodiesel blend.Figure 16.8 CO vs. Load for biodiesel blend.Figure 16.9 HC vs. Load for biodiesel blend.Figure 16.10 NO_x vs. Load for biodiesel blend.Figure 16.11 CO₂ vs. Load for biodiesel blend.Figure 16.12 BSFC vs. Load for CIME diesel blend + TBHQ.Figure 16.13 BTE vs. Load for biodiesel blend + TBHQ.Figure 16.14 CO vs. Load for biodiesel blend.Figure 16.15 HC vs. Load for biodiesel blend.Figure 16.16 NO_x vs. Load for biodiesel blend.Figure 16.17 CO₂ vs. Load for biodiesel blend.Figure 16.18 Response surface plot for BSFC.Figure 16.19 Contour plot for BSFC.Figure 16.20 Response surface plot for BTE.Figure 16.21 Contour plot for BTE.Figure 16.22 Response surface plot for CO.Figure 16.23 Contour plot for CO.Figure 16.24 Response surface plot for HC.Figure 16.25 Contour plot for HC.Figure 16.26 Response surface plot for NOx.Figure 16.27 Contour plot for NO_x.Figure 16.28 Response surface plot for CO₂.Figure 16.29 Contour plot for CO₂.Figure 16.30 Artificial neural network model.Figure 16.31 Correlation coefficient of 2-7-2 neural network for performance par...Figure 16.32 Variation of RMSE, MRE and R with respect to the different neural n...Figure 16.33 Correlation coefficient of 2-7-4 neural network for emission parame...Figure 16.34 Variation of RMSE, MRE and R² with respect to the different neural ...Figure 16.35 Comparison of the predicted and experimental performance parameter ...Figure 16.36 Comparison of the predicted and experimental CO and HC parameter va...Figure 16.37 Comparison of the predicted and experimental NO_x and CO₂ parameter ...Figure 16.38 Comparison of the predicted and experimental performance parameter ...Figure 16.39 Comparison of the predicted and experimental CO and HC parameter va...Figure 16.40 Comparison of the predicted and experimental NO_x and CO₂ parameter ...

      15 Chapter 17Figure 17.1 Energy flow.Figure 17.2 (a) Mango tree, (b) Mangos, (c) Mango seeds and (d) Mango seed oil.Figure 17.3 Transesterification chemical reaction mechanisms.Figure 17.4 Mango seed biodiesel blends.Figure 17.5 Experimental test setup.Figure 17.6 SEM and XRD pattern of Al₂O₃ nanoparticles.Figure 17.7 BTE variations with engine load.Figure 17.8 Variation of BSFC with engine load.Figure 17.9 Deviation of in-cylinder pressure with different crank angles.Figure 17.10 Variation of HRR with different crank angles.Figure 17.11 Deviation of CO emissions with engine load.Figure 17.12 Variation of CO₂ with engine load.Figure 17.13 Variation of HC with engine load.Figure 17.14 Variation of nitrogen oxide emissions with load.Figure 17.15 Deviation of smoke emissions with load.

      16 Chapter 18Figure 18.1 Global energy consumption (by fuels) for 2019 by BP [5].Figure 18.2 Global biofuel production (in Mtoe) by BP 2019 [5].Figure 18.3 Flowchart representing prediction techniques.Figure 18.4 Flowchart representing optimization techniques.Figure 18.5 Engine parameter optimization.Figure 18.6 Schematic representation of test rig for combustion performance of d...Figure 18.7 Multi-response optimization using RSM.Figure 18.8 Schematic of backpropagation network.Figure 18.9 Typical regression model of an output response.Figure 18.10 СКАЧАТЬ