Digital Twin in Modelling Citronella Grass Essential Oil Distillation Process with Computational Fluid Dynamics Approach
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Abstract
This study aims to investigate distillation process of Citronella Grass (Cymbopogon nardus) essential oil and determine the effect of heating temperature on oil quality, which significantly influences the market value. The study procedures were carried out by developing a virtual model of distillation apparatus using Digital Twin (DT) approach, integrating Computational Fluid Dynamics (CFD) to stimulate fluid behavior as it transitioned from vapor to liquid during distillation. The core of DT is in the virtual model development and three-dimensional (3D) geometric representations of system. The methodology comprised creating 3D geometric model of distillation setup, followed by mesh generation as well as setting of boundary conditions and computational parameters. In addition, numerical iterations were used to refine the process, leading to the analysis of CFD visualizations. The convergent result showed that the developed model was accurate at 300 iterations. Observations confirmed the occurrence of vapor to liquid phase change in the spiral pipe, with vapor density below 1 kg/m3 and liquid density between 800-1000 kg/ m3. Temperature monitoring showed a reduction from 120◦C in distillation tank to 24-26◦C post-condenser, which was similar to the observed range of 25-30◦C. Further temperature exchange in the reservoir was stimulated and observed in 36-38◦C. The result also showed that DT model created using CFD was capable of reflecting the real conditions observed.
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References
- Alighiri D, Eden WT, Supardi KI, Masturi, Purwinarko A. Potential Development Essential Oil Production of Central Java, Indonesia. J Phys Conf Ser 2017;824. https://doi.org/10.1088/1742-6596/824/1/012021.
- Julianto TS. Minyak Atsiri Bunga Indonesia. Yogyakarta: deepublish; 2016.
- Sastrohamidjojo H. Kimia Minyak Atsiri. Yogyakarta: Gadjah Mada University; 2020.
- Golmohammadi M, Borghei A, Zenouzi A, Ashrafi N, Taherzadeh MJ. Optimization of essential oil extraction from orange peels using steam explosion. Heliyon 2018;4:1–18. https://doi.org/10.1016/j.heliyon.2018.e00893.
- Mohamed AL, Sedik A, Mosaad MM, Othman HA. Imparting the mosquito-repellent and fragrance properties to linen fabric using different natural plants oils without or via silica encapsulation technique. Results Chem 2023;5:100742. https://doi.org/10.1016/j.rechem.2022.100742.
- Teshale F, Narendiran K, Beyan SM, Srinivasan NR. Extraction of essential oil from rosemary leaves: optimization by response surface methodology and mathematical modeling. Applied Food Research 2022;2. https://doi.org/10.1016/j.afres.2022.100133.
- Kashyap N, Kumari A, Raina N, Zakir F, Gupta M. Prospects of essential oil loaded nanosystems for skincare. Phytomedicine Plus 2022;2:100198. https://doi.org/10.1016/j.phyplu.2021.100198.
- Kim IK, Kim B, Song BW, Kim SW, Kim D, Kang JH, et al. Borneol facilitates the whitening and anti-wrinkle effect of the essential oil extracted from Abies koreana needles. J King Saud Univ Sci 2023;35:102886. https://doi.org/10.1016/j.jksus.2023.102886.
- Ibrahim MA, Cantrell CL, Jeliazkova EA, Astatkie T, Zheljazkov VD. Utilization of Nutmeg (Myristica fragrans Houtt.) Seed Hydrodistillation Time to Produce Essential Oil Fractions with Varied Compositions and Pharmacological Effect. Molecules 2020;25:565–75. https://doi.org/10.3390/molecules25030565.
- Mustiadi L, Astuti S, Purkuncoro AE. Distilasi Uap dan Bahan Bakar Pelet Arang Sampah Organik. vol. 6. Malang: CV IRDH; 2020.
- Wei C, Wan C, Huang F, Guo T. Extraction of Cinnamomum longepaniculatum deciduous leaves essential oil using solvent-free microwave extraction: Process optimization and quality evaluation. Oil Crop Science 2023;8:7–15. https://doi.org/10.1016/j.ocsci.2023.02.004.
- Mo F, Rehman HU, Monetti FM, Chaplin JC, Sanderson D, Popov A, et al. A framework for manufacturing system reconfiguration and optimisation utilising digital twin and modular artificial intelligence. Robot Comput Integr Manuf 2023;82:102524. https://doi.org/10.1016/j.rcim.2022.102524.
- Roy RB, Mishra D, Pal SK, Chakravarty T, Panda S, Chandra MG, et al. Digital twin: current scenario and a case study on a manufacturing process. International Journal of Advanced Manufacturing Technology 2020;107:3691–714. https://doi.org/10.1007/s00170-020-05306-w.
- Segovia M, Garcia-Alfaro J. Design, Modeling and Implementation of Digital Twin. Sensors 2022;22:1–30. https://doi.org/10.3390/s22145396.
- Onaji I, Tiwari D, Soulatiantork P, Song B, Tiwari A. Digital twin in manufacturing: conceptual framework and case studies. Int J Comput Integr Manuf 2022;35:831–58. https://doi.org/10.1080/0951192X.2022.2027014.
- Polini W, Corrado A. Digital twin of composite assembly manufacturing process. Int J Prod Res 2020;58:5238–52. https://doi.org/10.1080/00207543.2020.1714091.
- Aversano G, Ferrarotti M, Parente A. Digital twin of a combustion furnace operating in flameless conditions: Reduced-order model development from CFD simulations. Proceedings of the Combustion Institute 2021;38:5373–81. https://doi.org/10.1016/j.proci.2020.06.045.
- Haag S, Anderl R. Automated Generation of as-manufactures geometric representations for Digital Twin using STEP. CIRP Design 2019 2019:1082–7. https://doi.org/10.1016/j.procir.2019.04.305.
- Oyama H, Nieman K, Tran A, Keville B, Wu Y, Durand H. Computational fluid dynamics modeling of a wafer etch temperature control system. Digital Chemical Engineering 2023;8:100102. https://doi.org/10.1016/j.dche.2023.100102.
- Doroshenko Y, Doroshenko J, Zapukhliak V, Poberezhny L, Maruschak P. Modeling computational fluid dynamics of multiphase flows in elbow and T-junction of the main gas pipeline. Transport 2019;34:19–29. https://doi.org/10.3846/transport.2019.7441.
- Versteeg HK, Malalasekera W. An Introduction to Computational Fluid Dynamics: The Finite Volume Method. vol. 6. London: Pearson Education; 2007. https://doi.org/10.1109/mcc.1998.736434.
- Brozovsky J, Simonsen A, Gaitani N. Validation of a CFD model for the evaluation of urban microclimate at high latitudes: A case study in Trondheim, Norway. Build Environ 2021;205:108175. https://doi.org/10.1016/j.buildenv.2021.108175.
- Band SS, Al-Shourbaji I, Karami H, Karimi S, Esfandiari J, Mosavi A. Combination of group method of data handling (GMDH) and computational fluid dynamics (CFD) for prediction of velocity in channel intake. Applied Sciences (Switzerland) 2020;10:1–15. https://doi.org/10.3390/app10217521.
- Zawadzki D, Blatkiewicz M, Jaskulski M, Piątkowski M, Koop J, Loll R, et al. Design and Optimisation of Structural Packings for Rotating Bed Absorbers Using Computational Fluid Dynamics Simulation. Chemical Engineering Research and Design 2022;195:508–25. https://doi.org/10.1016/j.cherd.2023.06.002.
- Tu J, Yeoh G-H, Liu C. Computational Fluid Dynamics A Practical Approach. Oxford: Butterworth-Heinemann; 2019. https://doi.org/10.1016/C2015-0-06135-4.
- Frungieri G, Boccardo G, Buffo A, Karimi–Varzaneh HA, Vanni M. CFD-DEM characterization and population balance modelling of a dispersive mixing process. Chem Eng Sci 2022;260:117859. https://doi.org/10.1016/j.ces.2022.117859.
- Aláez D, Olaz X, Prieto M, Villadangos J, Astrain JJ. VTOL UAV digital twin for take-off, hovering and landing in different wind conditions. Simul Model Pract Theory 2023;123:102703. https://doi.org/10.1016/j.simpat.2022.102703.
- Cai S, Erfle P, Dietzel A. A Digital Twin of the Coaxial Lamination Mixer for the Systematic Study of Mixing Performance and the Prediction of Precipitated Nanoparticle Properties. Micromachines (Basel) 2022;13. https://doi.org/10.3390/mi13122076.
- Myrvang T, Khawaja H. Validation of air ventilation in tunnels, using experiments and computational fluid dynamics. International Journal of Multiphysics 2018;12:295–311. https://doi.org/10.21152/1750-9548.12.3.295.
- AIAA. Guide for the verification and validation of computational fluid dynamics simulations. vol. 1998. Reston: American Institute of Aeronautics and Astronautics; 1998. https://doi.org/10.2514/4.472855.001.
- Assiddiqie Z, Bunga NT. Analisis Perpindahan Panas pada Sirkulasi Air Penyulingan Nilam dengan Tangki Bervolume 150 Liter. Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi 2023;5:1–10.
- Turmizi, Hamdani. Permodelan alat distilasi untuk penyulingan minyak nilam. Jurnal Inovtek Polbeng 2018;8:10–4.
- Simbolon S, Setia Y. Simulasi Distribusi Suhu Tekanan dan Kecepatan Gas Dalam Pipa Pirolisis Pada Reaktor - Kondensor. Journal of Mechanical Engineering Manufactures Materials and Energy 2022;6:155–65. https://doi.org/10.31289/jmemme.v6i2.7186.
- Rubianto B, Winarso R, Wibowo R. Rancang Bangun Kondensor Pada Destilator Bioetanol Kapasitas 5 Liter/Jam Dengan Skala Umkm. Jurnal Crankshaft 2018;1:29–36. https://doi.org/10.24176/crankshaft.v1i1.2587.