Journals / Yenilikçi Mühendislik ve Doğa Bilimleri / 2026 / Volume: 6 Issue: 2

Digital twin of waste cooking oil biodiesel: optimizing n-Butanol blends via mixture-process design

Mehmet Selman Gökmen(Necmettin Erbakan Üniversitesi)0000-0001-5943-7504
Pages
—
Publication Date
2026-07-30
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Overall, the findings suggest that n-butanol acts as a highly effective solvent in reducing the internal friction and surface tension of waste oil biodiesels characterized by heavy ester profiles.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Although waste cooking oil (WCO)-based biodiesel represents a sustainable alternative within the context of the circular economy, its direct application remains constrained by drawbacks such as high density, high kinematic viscosity, and elevated surface tension.
📊
Key Findings & Data:This study aims to improve the weak thermophysical properties of WCO biodiesel through the addition of n-butanol, while simultaneously tailoring its density and kinematic viscosity to fall within the EN 590 diesel standard limits.
💡
Conclusion & Impact:Overall, the findings suggest that n-butanol acts as a highly effective solvent in reducing the internal friction and surface tension of waste oil biodiesels characterized by heavy ester profiles.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Digital Twin · Waste Cooking Oil Biodiesel · n-Butanol Blends

Abstract

Although waste cooking oil (WCO)-based biodiesel represents a sustainable alternative within the context of the circular economy, its direct application remains constrained by drawbacks such as high density, high kinematic viscosity, and elevated surface tension. This study aims to improve the weak thermophysical properties of WCO biodiesel through the addition of n-butanol, while simultaneously tailoring its density and kinematic viscosity to fall within the EN 590 diesel standard limits. To this end, rather than relying on costly and time-consuming trial-and-error approaches, this research introduces an innovative methodology based on the integration of the DWSIM process simulator and Mixture-Process Design. The chemical structure of the WCO biodiesel was defined as a surrogate model in the DWSIM environment using the mass fractions of its primary Fatty Acid Methyl Ester (FAME) components (methyl oleate, methyl linoleate, methyl palmitate, and methyl stearate). The fundamental thermophysical properties of the model were then validated against reference experimental data. To statistically model the constrained mixture space, a 15-run experimental matrix was generated utilizing the D-Optimal Extreme Vertices algorithm. The developed regression models accounted for the variations in kinematic viscosity, density, and surface tension with high statistical accuracy (R2 > 96.5%, p < 0.05). In the final stage, Multiple Response Optimization was performed using Derringer's Desirability Function to reconcile the conflicting targets of density and viscosity into a unified metric. The analysis indicated a maximum desirability score (D = 0.835) for a blend comprising 72.8 wt.% WCO and 27.2 wt.% n-butanol (WCO72.8/NB27.2) at an operating temperature of 30 °C. At this global optimum point, the density and kinematic viscosity of the fuel were determined as 840.0 kg/m3 and 2.72 mm2/s, respectively. Overall, the findings suggest that n-butanol acts as a highly effective solvent in reducing the internal friction and surface tension of waste oil biodiesels characterized by heavy ester profiles. Furthermore, the results indicate that the DWSIM-RSM digital integration can be utilized with high reliability in alternative fuel blending optimizations.

🔖

Cite This Article

Gökmen, M. S. (2026). Digital twin of waste cooking oil biodiesel: optimizing n-Butanol blends via mixture-process design. Yenilikçi Mühendislik ve Doğa Bilimleri, Volume: 6 Issue: 2. https://doi.org/10.61112/jiens.1907318

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (30)

  1. Goh BHH, Chong CT, Ge Y, Ong HC, Ng J-H, Tian B, Ashokkumar V, Lim S, Seljak T, Józsa V (2020) Progress in utilisation of waste cooking oil for sustainable biodiesel and biojet fuel production. Energy Convers Manag 223:113296. https://doi.org/10.1016/j.enconman.2020.113296
  2. Rahman A, Oktaufik MAM, Sasongko TW, Guntoro I, Soedjati D, Abbas N, Rahman A, Ulfah F, Widiarto A, Siswanto, Dharmawan, Trihadi SEY, Kusrestuwardani, Prihatin AL, Hadi A, Indrijarso S, Rahardjo P, Barkah A, Febijanto I, Sasongko NA (2025) Current scenario and potential of waste cooking oil as a feedstock for biodiesel production in Indonesia: Life cycle sustainability assessment (LCSA) review. Case Stud Chem Environ Eng 11:101067. https://doi.org/10.1016/j.cscee.2024.101067
  3. Manikandan G, Kanna PR, Taler D, Sobota T (2023) Review of Waste Cooking Oil (WCO) as a Feedstock for Biofuel—Indian Perspective. Energies (Basel) 16:1739. https://doi.org/10.3390/en16041739
  4. Idris M, Abdul Rasid AF, Mohd Zamberi M, Zhang Y (2024) Biodiesel Production from Waste Cooking Oil: A Review of Prospects and Challenges. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 124:28-52. https://doi.org/10.37934/arfmts.124.1.2852
  5. Yaqoob H, Teoh YH, Sher F, Farooq MU, Jamil MA, Kausar Z, Sabah NU, Shah MF, Rehman HZU, Rehman AU (2021) Potential of Waste Cooking Oil Biodiesel as Renewable Fuel in Combustion Engines: A Review. Energies (Basel) 14:2565. https://doi.org/10.3390/en14092565
  6. Soares de Carvalho Freitas E, Xavier LH, Oliveira LB, Guarieiro LLN (2022) System dynamics applied to second generation biofuel in Brazil: A circular economy approach. Sustainable Energy Technol Assess 52:102288. https://doi.org/10.1016/j.seta.2022.102288
  7. Gad MS, EL-Seesy AI, Radwan A, He Z (2020) Enhancing the combustion and emission parameters of a diesel engine fueled by waste cooking oil biodiesel and gasoline additives. Fuel 269:117466. https://doi.org/10.1016/j.fuel.2020.117466
  8. Kuti OA, Nishida K (2025) An investigation into spray combustion processes of waste cooking oil biodiesel fuel under diesel engine conditions using the LIF-PIV, shadowgraph, and chemiluminescence techniques. Int J Thermofluids 26:101066. https://doi.org/10.1016/j.ijft.2025.101066
  9. Suherman S, Abdullah I, Sabri M, Turmuzi M, Silitonga AS, Dharma S, Yusfiani M (2023) A Review of Properties, Engine Performance, Emission Characteristics and Material Compatibility Biodiesel From Waste Cooking Oil (WCO). Automotive Experiences 6:624-651. https://doi.org/10.31603/ae.10128
  10. Razzaq L, Imran S, Anwar Z, Farooq M, Abbas MM, Mehmood Khan H, Asif T, Amjad M, Soudagar MEM, Shaukat N, Rizwanul Fattah IM, Rahman SMA (2020) Maximising Yield and Engine Efficiency Using Optimised Waste Cooking Oil Biodiesel. Energies (Basel) 13:5941. https://doi.org/10.3390/en13225941
  11. Konjević L, Racar M, Ilinčić P, Faraguna F (2023) A comprehensive study on application properties of diesel blends with propanol, butanol, isobutanol, pentanol, hexanol, octanol and dodecanol. Energy 262:125430. https://doi.org/10.1016/j.energy.2022.125430
  12. Obergruber M, Hönig V, Jenčík J, Hájek J, Schlehöfer D, Herink T (2021) Lignocellulosic Bioethanol and Biobutanol as a Biocomponent for Diesel Fuel. Materials 14:5597. https://doi.org/10.3390/ma14195597
  13. Ait Belale R, M’hamdi Alaoui FE, Chhiti Y, Sahibeddine A, Munoz Rujas N, Aguilar F (2021) Study on the thermophysical properties of waste cooking oil biodiesel fuel blends with 1-butanol. Fuel 287:119540. https://doi.org/10.1016/j.fuel.2020.119540
  14. Csemány D, DarAli O, Rizvi SAH, Józsa V (2022) Comparison of volatility characteristics and temperature-dependent density, surface tension, and kinematic viscosity of n-butanol-diesel and ABE-diesel fuel blends. Fuel 312:122909. https://doi.org/10.1016/j.fuel.2021.122909
  15. Singh R, Kumar R (2022) Insights into the influence of n-butanol with neat biodiesel and biodiesel-diesel blends on diesel engine characteristics: Review. Int J Energy Res 46:5441-5466. https://doi.org/10.1002/er.7550
  16. Asaad SM, Inayat A, Ghenai C, Shanableh A (2024) Response Surface Methodology in Biodiesel Production and Engine Performance Assessment. Int J Thermofluids 21:100551. https://doi.org/10.1016/j.ijft.2023.100551
  17. Elkelawy M, Bastawissi HA-E, Esmaeil KK, Radwan AM, Panchal H, Sadasivuni KK, Suresh M, Israr M (2020) Maximization of biodiesel production from sunflower and soybean oils and prediction of diesel engine performance and emission characteristics through response surface methodology. Fuel 266:117072. https://doi.org/10.1016/j.fuel.2020.117072
  18. Ullah K, Asaad SM, Inayat A (2025) Process modelling and optimization of hydrogen production from biogas by integrating DWSIM with response surface methodology. Digital Chem Eng 14:100205. https://doi.org/10.1016/j.dche.2024.100205
  19. Chen C, Mira D, Xing Z, Jiang X (2022) Thermophysical property prediction of biodiesel mixtures at extreme conditions using molecular dynamics simulation. J Mol Liq 367:120423. https://doi.org/10.1016/j.molliq.2022.120423
  20. Yeşilova K, Yücel Ö, Ergan BT (2025) Modeling Prediction of Physical Properties in Sustainable Biodiesel-Diesel-Alcohol Blends via Experimental Methods and Machine Learning. Processes 13:2310. https://doi.org/10.3390/pr13072310
  21. Mohammad SI, Owida HA, Vasudevan A, Menon SV, Al-Hasnaawei S, Ray S, Talniya NC, Sinha A, Jain V, Ranjbar F (2025) Thermophysical properties of used frying oil biodiesels blended with alcohols: Robust machine learning frameworks for density prediction. Ind Crops Prod 236:121916. https://doi.org/10.1016/j.indcrop.2025.121916
  22. Hussein RZK, Attia NK, Fouad MK, ElSheltawy ST (2021) Experimental investigation and process simulation of biolubricant production from waste cooking oil. Biomass Bioenergy 144:105850. https://doi.org/10.1016/j.biombioe.2020.105850
  23. Kuti OA, Sarathy SM, Nishida K (2020) Spray combustion simulation study of waste cooking oil biodiesel and diesel under direct injection diesel engine conditions. Fuel 267:117240. https://doi.org/10.1016/j.fuel.2020.117240
  24. Hidegh GT, Csemány D, DarAli O, Rizvi SAH, Ng JH, Chong CT, Józsa V (2023) Comparison of thermophysical properties and combustion characteristics of various biodiesels in a non-MILD ultra-low emission swirl burner. Fuel 334. https://doi.org/10.1016/j.fuel.2022.126583
  25. Florido PM, Visioli PCF, Pinto CN, Gonçalves CB (2020) Study of FAME model systems: Database and evaluation of predicting models for biodiesel physical properties. Renew Energy 151:837-845. https://doi.org/10.1016/j.renene.2019.11.083
  26. Kuhnt S, Becker-Emden E, Schade T, Eden W, Middendorf B (2021) Use of optimal mixture-process designs and response-surface models to study properties of calcium silicate units. Qual Reliab Eng Int 37:391-408. https://doi.org/10.1002/qre.2758
  27. Derringer G, Suich R (1980) Simultaneous Optimization of Several Response Variables. J Qual Technol 12:214-219. https://doi.org/10.1080/00224065.1980.11980968
  28. Ijaz Malik MA, Usman M, Akhtar M, Farooq M, Saleem Iqbal HM, Irshad M, Shah MH (2023) Response surface methodology application on lubricant oil degradation, performance, and emissions in SI engine: A novel optimization of alcoholic fuel blends. Sci Prog 106. https://doi.org/10.1177/00368504221148342
  29. Simsek S, Uslu S (2020) Experimental study of the performance and emissions characteristics of fusel oil/gasoline blends in spark ignited engine using response surface methodology. Fuel 277:118182. https://doi.org/10.1016/j.fuel.2020.118182
  30. Joshipura MH, Saxena P, Shah N, Dwivedi A, Pillai S, Aggrawal M (2023) Determining and modeling of density and viscosity of biodiesel-diesel and biodiesel-diesel-butanol blends. Int J Chem Reactor Eng 21:1561-1569. https://doi.org/10.1515/ijcre-2023-0004