Abstract
In this research work, the experimental tests were conducted on a single-cylinder, constant speed, variable compression ratio (VCR) engine fuelled with green diesel. Initially, bio-oil was extracted from waste Trichosanthes cucumerina fruit seeds using the Soxhlet apparatus. The acquired bio-oil is used to make green diesel through the trans-esterification process. The fuel blends were prepared with different proportions of Trichosanthes cucumerina biodiesel (TCB) in diesel fuel (30%, 50%, and 70%) for the experimental test, and their thermo-physical properties were evaluated according to ASTM standards. At full load condition, the TCB30 blend with CR 18:1 gives closer engine performance of brake thermal efficiency (33.52%), brake specific fuel consumption (0.27 kg/kWh), and exhaust gas temperature (389.56 °C) and reduced emission levels of unburned hydrocarbon by 13.51%, carbon monoxide by 10.82%, smoke opacity by 16.87%, and the penalty of nitric oxide by 17.56% equated with neat diesel fuel. The engine performance and emission parameters are predicted using multiple regression artificial neural network (ANN) models. A database generated from the experimental results is used to train the ANN model. The average correlation coefficient (R) of the trained ANN model is 0.99673, which is closer to 1. It indicates that the proposed ANN model can generate the exact correlation between input factors and output responses. As a result, the application of ANN is a better forecasting tool for predicting VCR engine performance and emission characteristics.
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Abbreviations
- ASTM:
-
American Society for Testing and Materials
- ANN:
-
Artificial neural network
- BTE:
-
Brake thermal efficiency
- BSFC:
-
Brake specific fuel consumption
- CO:
-
Carbon monoxide
- CO2 :
-
Carbon dioxide
- EGT:
-
Exhaust gas temperature
- GC-MS:
-
Gas chromatography-mass spectroscopy
- HC:
-
Hydrocarbon
- NO:
-
Nitric oxide
- TCO:
-
Trichosanthes cucumerina Bio-oil
- TCB:
-
Trichosanthes cucumerina Biodiesel
- TCB30:
-
30% Trichosanthes cucumerina Biodiesel + 70% diesel
- TCB50:
-
50% Trichosanthes cucumerina Biodiesel + 50% diesel
- TCB70:
-
70% Trichosanthes cucumerina Biodiesel + 30% diesel
- TCB100:
-
100% Trichosanthes cucumerina Biodiesel
References
Anand BP, Saravanan CG, Srinivasan CA (2010) Performance and exhaust emission of turpentine oil powered direct injection diesel engine. Renew Energy 35(6):1179–1184. https://doi.org/10.1016/j.renene.2009.09.010
Annamalai M, Dhinesh B, Nanthagopal K, SivaramaKrishnan P, Isaac JoshuaRamesh Lalvani J, Parthasarathy M, Annamalai K (2016) An assessment on performance, combustion and emission behavior of a diesel engine powered by ceria nanoparticle blended emulsified biofuel. Energy Convers Manag 123:372–380. https://doi.org/10.1016/j.enconman.2016.06.062
Ashok B, Nanthagopal K, Sakthi Vignesh D (2018) Calophyllum inophyllum methyl ester biodiesel blend as an alternate fuel for diesel engine applications. Alex Eng J 57(3):1239–1247. https://doi.org/10.1016/j.aej.2017.03.042
Ashok B, Nanthagopal K, Saravanan B, Azad K, Patel D, Sudarshan B, Aaditya Ramasamy R (2019) Study on isobutanol and Calophyllum inophyllum biodiesel as a partial replacement in CI engine applications. Fuel 235:984–994. https://doi.org/10.1016/j.fuel.2018.08.087
Aydın M, Uslu S, Bahattin Çelik M (2020) Performance and emission prediction of a compression ignition engine fueled with biodiesel-diesel blends: A combined application of ANN and RSM based optimization. Fuel 269:117472. https://doi.org/10.1016/j.fuel.2020.117472
Babu D, Thangarasu V, Ramanathan A (2020) Artificial neural network approach on forecasting diesel engine characteristics fuelled with waste frying oil biodiesel. Appl Energy 263:114612. https://doi.org/10.1016/j.apenergy.2020.114612
Balasubramanian D, Sokkalingam Arumugam SR, Subramani L, Joshua Stephen Chellakumar IJRL, Mani A (2018) A numerical study on the effect of various combustion bowl parameters on the performance, combustion, and emission behavior on a single cylinder diesel engine. Environ Sci Pollut Res 25(3):2273–2284. https://doi.org/10.1007/s11356-017-0565-2
Baranitharan P, Ramesh K, Sakthivel R (2019) Measurement of performance and emission distinctiveness of Aegle marmelos seed cake pyrolysis oil/diesel/TBHQ opus powered in a DI diesel engine using ANN and RSM. Measurement 144:366–380. https://doi.org/10.1016/j.measurement.2019.05.037
Dey S, Reang NM, Majumder A, Deb M, Das PK (2020) A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend. Energy 202:117813. https://doi.org/10.1016/j.energy.2020.117813
Dharma S, Hassan MH, Ong HC, Sebayang AH, Silitonga AS, Kusumo F, Milano J (2017) Experimental study and prediction of the performance and exhaust emissions of mixed Jatropha curcas-Ceiba pentandra biodiesel blends in diesel engine using artificial neural networks. J Clean Prod 164:618–633. https://doi.org/10.1016/j.jclepro.2017.06.065
Dhinesh B, Isaac JoshuaRamesh J, Parthasarathy LM, Annamalai K (2016) An assessment on performance, emission and combustion characteristics of single cylinder diesel engine powered by Cymbopogon flexuosus biofuel. Energy Convers Manag 117:466–474. https://doi.org/10.1016/j.enconman.2016.03.049
Dhingra S, Bhushan G, Dubey KK (2014) Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominated sorting genetic algorithm-II. Front Mech Eng 9(1):81–94. https://doi.org/10.1007/s11465-014-0287-9
Elsanusi OA, Roy MM, Sidhu MS (2017) Experimental investigation on a diesel engine fuelled by diesel-biodiesel blends and their emulsions at various engine operating conditions. Appl Energy 203:582–593. https://doi.org/10.1016/j.apenergy.2017.06.052
Ganesan S, Padmanabhan S, Mahalingam S, Shanjeevi C (2020) Environmental Effects Environmental impact of VCR diesel engine characteristics using blends of cottonseed oil with nano additives. Energy Sources, Part A Recover Util Environ Eff 42(6):761–772. https://doi.org/10.1080/15567036.2019.1602196
Gnanamoorthi V, Devaradjane G (2015) Effect of compression ratio on the performance, combustion and emission of di diesel engine fueled with ethanol-Diesel blend. J Energy Inst 88(1):19–26. https://doi.org/10.1016/j.joei.2014.06.001
Gülüm M, Yesilyurt MK, Bilgin A (2019) The performance assessment of cubic spline interpolation and response surface methodology in the mathematical modeling to optimize biodiesel production from waste cooking oil. Fuel 255:115778. https://doi.org/10.1016/j.fuel.2019.115778
Hawi M, Elwardany A, Ookawara S, Ahmed M (2019) Effect of compression ratio on performance, combustion and emissions characteristics of compression ignition engine fueled with jojoba methyl ester. Renew Energy 141:632–645. https://doi.org/10.1016/j.renene.2019.04.041
Heywood JB (1988) Internal combustion engine fundamentals. McGraw-Hill series in Mechanical Engineering, USA
Hoang AT, Le AT, Pham VV (2019) A core correlation of spray characteristics, deposit formation, and combustion of a high-speed diesel engine fueled with Jatropha oil and diesel fuel. Fuel 244:159–175. https://doi.org/10.1016/j.fuel.2019.02.009
Holman J (2000) Experimental methods for engineers. McGraw Hill Book, New York
Hosamani BR, Katti VV (2018) Experimental analysis of combustion characteristics of CI DI VCR engine using mixture of two biodiesel blend with diesel. Eng Sci Technol an Int J 21:769–777. https://doi.org/10.1016/j.jestch.2018.05.015
Hosseini SH, Taghizadeh-Alisaraei A, Ghobadian B, Abbaszadeh-Mayvan A (2020) Artificial neural network modeling of performance, emission, and vibration of a CI engine using alumina nano-catalyst added to diesel-biodiesel blends. Renew Energy 149:951–961. https://doi.org/10.1016/j.renene.2019.10.080
Ibrahim S, Choong CE, El-Shafie A (2019) Sensitivity analysis of artificial neural networks for just-suspension speed prediction in solid-liquid mixing systems: Performance comparison of MLPNN and RBFNN. Adv Eng Inform 39:278–291. https://doi.org/10.1016/j.aei.2019.02.004
Işcan B (2020) ANN modeling for justification of thermodynamic analysis of experimental applications on combustion parameters of a diesel engine using diesel and safflower biodiesel fuels. Fuel 279:118391. https://doi.org/10.1016/j.fuel.2020.118391
Javed S, Murthy YVVS, Ulla R, Rao DP (2015) Development of ANN model for prediction of performance and emission characteristics of hydrogen dual fueled diesel engine with Jatropha Methyl Ester biodiesel blends. J Nat Gas Sci Eng 26:549–557. https://doi.org/10.1016/j.jngse.2015.06.041
Karthic SV, Masimalai SK (2020) Predicting the performance and emission characteristics of a Mahua oil-hydrogen dual fuel engine using artificial neural networks. Energy Sour, Part A Recov Util Environ Eff 42(23):2891–2910. https://doi.org/10.1080/15567036.2019.1618997
Karthickeyan V, Balamurugan P, Rohith G, Senthil R (2017) Developing of ANN model for prediction of performance and emission characteristics of VCR engine with orange oil biodiesel blends. J Braz Soc Mech Sci Eng 39(7):2877–2888. https://doi.org/10.1007/s40430-017-0768-y
Koten H (2018) Hydrogen effects on the diesel engine performance and emissions. Int J Hydrogen Energy 43(22):105–119. https://doi.org/10.1016/j.ijhydene.2018.04.146
Krishnamoorthi M, Malayalamurthi R, Sakthivel R (2019) Optimization of compression ignition engine fueled with diesel - chaulmoogra oil - diethyl ether blend with engine parameters and exhaust gas recirculation. Renew Energy 134:579–602. https://doi.org/10.1016/j.renene.2018.11.062
Lahane S, Subramanian KA (2014) Impact of nozzle holes configuration on fuel spray, wall impingement and NOx emission of a diesel engine for biodiesel-diesel blend (B20). Appl Therm Eng 64(1–2):307–314. https://doi.org/10.1016/j.applthermaleng.2013.12.048
Manimaran R, Murugu Mohan Kumar K, Hari Shankar V (2019) Study on novel nano mahua methyl ester powered DI diesel engine preheated with a thermoelectric waste heat recovery system. Energy Sources, Part A Recov Util Environ Eff. https://doi.org/10.1080/15567036.2019.1587100
Manimaran R, Murugu Mohan Kumar K, Sathiya Narayanan N (2020) Synthesis of bio-oil from waste Trichosanthes cucumerina seeds: a substitute for conventional fuel. Scientific Reports 10(1):1–12. https://doi.org/10.1038/s41598-020-74130-9
Maurya RK, Saxena MR, Rai P, Bhardwaj A (2018) Effect of compression ratio, nozzle opening pressure, engine load, and butanol addition on nanoparticle emissions from a non-road diesel engine. Environ Sci Pollut Res 25:14674–14689. https://doi.org/10.1007/s11356-018-1644-8
Mehra RK, Duan H, Luo S, Rao A, Ma F (2018) Experimental and artificial neural network (ANN) study of hydrogen enriched compressed natural gas (HCNG) engine under various ignition timings and excess air ratios. Appl Energy 228:736–754. https://doi.org/10.1016/j.apenergy.2018.06.085
Mohan B, Yang W, Raman V, Vedharai S, Chou SK (2014) Optimization of biodiesel fuelled engine to meet emission standards through varying nozzle opening pressure and static injection timing. Appl Energy 130:450–457. https://doi.org/10.1016/j.apenergy.2014.02.033
Musthafa MM, Kumar TA, Mohanraj T, Chandramouli R (2018) A comparative study on performance, combustion and emission characteristics of diesel engine fuelled by biodiesel blends with and without an additive. Fuel 225:343–348. https://doi.org/10.1016/j.fuel.2018.03.147
Nanthagopal K, Ashok B, Saravanan B, Ramesh Pathy M, Sahil G, Ramesh A, Nurun Nabi M, Golam Rasul M (2019) Study on decanol and Calophyllum Inophyllum biodiesel as ternary blends in CI engine. Fuel 239:862–873. https://doi.org/10.1016/j.fuel.2018.11.037
Parida MK, Joardar H, Rout AK, Routaray I, Mishra BP (2019) Multiple response optimizations to improve performance and reduce emissions of Argemone Mexicana biodiesel-diesel blends in a VCR engine. Appl Therm Eng 148:1454–1466. https://doi.org/10.1016/j.applthermaleng.2018.11.061
Prabakaran S, Mohanraj T, Arumugam A (2021) Azolla pinnata methyl ester production and process optimization using a novel heterogeneous catalyst. Renew Energy 180:353–371. https://doi.org/10.1016/j.renene.2021.08.073
Pradhan D, Bendu H, Singh RK, Murugan S (2017) Mahua seed pyrolysis oil blends as an alternative fuel for light-duty diesel engines. Energy 118:600–612. https://doi.org/10.1016/j.energy.2016.10.091
Prasada Rao K, Victor Babu T, Anuradha G, Appa Rao BV, BV, (2017) IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN). Egypt J Pet 26(3):593–600. https://doi.org/10.1016/j.ejpe.2016.08.006
Raghuvaran S, Ashok B, Veluchamy B, Ganesh N (2020) Evaluation of performance and exhaust emission of C.I diesel engine fuel with palm oil biodiesel using an artificial neural network. Mater Today: Proc 37(2):1107–1111. https://doi.org/10.1016/j.matpr.2020.06.344
Ramalingam K, Kandasamy A, Balasubramanian D, Palani M, Subramanian T, Varuvel EG, Viswanathan K (2020a) Forcasting of an ANN model for predicting behaviour of diesel engine energised by a combination of two low viscous biofuels. Environ Sci Pollut Res 27(20):24702–24722. https://doi.org/10.1007/s11356-019-06222-7
Ramalingam K, Balasubramanian D, Chellakumar PJTJS, Padmanaban J, Murugesan P, Xuan T (2020b) An assessment on production and engine characterization of a novel environment-friendly fuel. Fuel 279:118558. https://doi.org/10.1016/j.fuel.2020.118558
Ramesh A, Ashok B, Nanthagopal K, Ramesh Pathy M, Tambare A, Mali P, Phuke P, Patil S, Subbarao R (2019) Influence of hexanol as additive with Calophyllum Inophyllum biodiesel for CI engine applications. Fuel 249:472–485. https://doi.org/10.1016/j.fuel.2019.03.072
Rashed MM, Kalam MA, Masjuki HH, Habibullah M, Imdadul HK, Shahin MM, Rahman MM (2016) Improving oxidation stability and NOx reduction of biodiesel blends using aromatic and synthetic antioxidant in a light duty diesel engine. Ind Crops Prod 89(X):273–284. https://doi.org/10.1016/j.indcrop.2016.05.008
Sathiyamoorthi R, Sankaranarayanan G (2016) Effect of antioxidant additives on the performance and emission charjjm acteristics of a DICI engine using neat lemongrass oil-diesel blend. Fuel 174:89–96. https://doi.org/10.1016/j.fuel.2016.01.076
Senthil Kumar M, Arul K, Sasikumar N (2019) Impact of oxygen enrichment on the engine’s performance, emission and combustion behavior of a biofuel based reactivity controlled compression ignition engine. J Energy Inst 92(1):51–61. https://doi.org/10.1016/j.joei.2017.12.001
Sevinc H, Hazar H (2020) Investigation of exhaust emissions of an isolated diesel engine blended with ethylhexyl nitrate using experimental and ANN approach. Environ Sci Pollut Res 27(27):33753–33772. https://doi.org/10.1007/s11356-020-09373-0
Shameer PM, Ramesh K (2017) Influence of antioxidants on fuel stability of Calophyllum inophyllum biodiesel and RSM-based optimization of engine characteristics at varying injection timing and compression ratio. J Braz Soc Mech Sci Eng 39(11):4251–4273. https://doi.org/10.1007/s40430-017-0884-8
Shivakumar, Srinivasa Pai P, Shrinivasa Rao BR (2011) Artificial Neural Network based prediction of performance and emission characteristics of a variable compression ratio CI engine using WCO as a biodiesel at different injection timings. Appl Energy 88(7):2344–2354. https://doi.org/10.1016/j.apenergy.2010.12.030
Subramani S, Govindasamy R, Rao GLN (2020) Predictive correlations for NOx and smoke emission of DI CI engine fuelled with diesel-biodiesel-higher alcohol blends-response surface methodology approach. Fuel 269:117304. https://doi.org/10.1016/j.fuel.2020.117304
Thiruvenkatachari S, Saravanan CG, Geo VE, Vikneswaran M, Udayakumar R, Aloui F (2021) Experimental investigations on the production and testing of azolla methyl esters from Azolla microphylla in a compression ignition engine. Fuel 287:119448. https://doi.org/10.1016/j.fuel.2020.119448
Uslu S, Celik MB (2018) Prediction of engine emissions and performance with artificial neural networks in a single cylinder diesel engine using diethyl ether. Eng Sci and Technol Int J 21(6):1194–1201. https://doi.org/10.1016/j.jestch.2018.08.017
Uslu S, Celik MB (2020) Performance and Exhaust Emission Prediction of a SI Engine Fueled with I-amyl Alcohol-Gasoline Blends: An ANN Coupled RSM Based Optimization. Fuel 265:116922. https://doi.org/10.1016/j.fuel.2019.116922
Vellaiyan S (2020) Enhancement in combustion, performance, and emission characteristics of a biodiesel-fueled diesel engine by using water emulsion and nanoadditive. Renew Energy 145:2108–2120. https://doi.org/10.1016/j.renene.2019.07.140
Venugopal P, Kasimani R, Chinnasamy S (2018) Prediction and optimization of CI engine performance fuelled with Calophyllum inophyllum diesel blend using response surface methodology (RSM). Environ Sci Pollut Res 25(25):24829–24844. https://doi.org/10.1007/s11356-018-2519-8
Vigneswaran R, Annamalai K, Dhinesh B, Krishnamoorthy R (2018) Experimental investigation of unmodified diesel engine performance, combustion and emission with multipurpose additive along with water-in-diesel emulsion fuel. Energy Convers Manag 172:370–380. https://doi.org/10.1016/j.enconman.2018.07.039
Wamankar AK, Satapathy AK, Murugan S (2015) Experimental investigation of the effect of compression ratio, injection timing & pressure in a DI (direct injection) diesel engine running on carbon black-water-diesel emulsion. Energy 93:511–520. https://doi.org/10.1016/j.energy.2015.09.068
Yang F, Cho H, Zhang H, Zhang J, Wu Y (2018) Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery. Energy Convers Manag 164:15–26. https://doi.org/10.1016/j.enconman.2018.02.062
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The authors wish to convey their thanks to the School of Mechanical Engineering, SASTRA Deemed University, which provides laboratory facilities for carrying out the engine tests.
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Rajayokkiam Manimaran: conceptualization, methodology, writing—original draft, review and editing. Thangavelu Mohanraj: supervision, investigation. Moorthy Venkatesan: software, resources.
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Manimaran, R., Mohanraj, T. & Venkatesan, M. ANN modeling for forecasting of VCR engine performance and emission parameters fuelled with green diesel extracted from waste biomass resources. Environ Sci Pollut Res 29, 51183–51210 (2022). https://doi.org/10.1007/s11356-022-19500-8
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DOI: https://doi.org/10.1007/s11356-022-19500-8