Performance Evaluation Research of Digital Twin Model of Knife Gate Based on Finite Element Analysis Under Temperature Rise
DOI:
https://doi.org/10.13052/ejcm2642-2085.3522Keywords:
Digital twin, finite element analysis, knife gate valve, thermal stress, predictive maintenanceAbstract
Knife gate valves are widely used in industrial systems for regulating the flow of liquids, gases, and slurries under demanding operating conditions. Continuous exposure to elevated temperatures can cause thermal expansion, material degradation, stress accumulation, and structural deformation, reducing valve performance and increasing failure risk. This study proposes a Digital Twin-based thermo-mechanical performance evaluation framework integrated with finite element analysis (FEA) for knife gate valves under progressive thermal loading. Five operating temperature cases of 50∘C, 100∘C, 150∘C, 200∘C, and 250∘C were evaluated to characterize temperature distribution, heat flow, temperature-dependent yield strength, thermal and mechanical stress, deformation, safety factor, actuator torque, and seal pressure. The results demonstrate progressive thermo-mechanical degradation with increasing temperature. At 250∘C, the maximum induced stress reaches 246.45 MPa, exceeding the temperature-dependent yield strength of 235.2 MPa, while the safety factor decreases to 0.95 and deformation increases to 0.80682 mm. The required actuator torque increases to 1414.56 Nm, accompanied by a reduction in seal pressure to 1.069 MPa, a decline in valve health score from 100% to 55%, and a reduction in remaining useful life from 74.57 to 24.14 years. The Digital Twin consequently identifies the highest-temperature condition as a warning state, indicating increased structural and operational risk. The primary contribution of this work is the simultaneous prediction of stress, deformation, safety factor, torque, and remaining useful life within a single unified Digital Twin–FEA model.
Downloads
References
H. Elsherbiny, L. Szamel, M. K. Ahmed, and M. A. Elwany, “High Accuracy Modeling of Permanent Magnet Synchronous Motors Using Finite Element Analysis,” Mathematics, vol. 10, no. 20, p. 3880, 2022, doi: 10.3390/math10203880.
C. Song, H. Chang, D. Zhang, Y. Zhang, M. Shi, and X. Meng, “Biomechanical Evaluation of Oblique Lumbar Interbody Fusion with Various Fixation Options: A Finite Element Analysis,” Orthopedic Surgery, vol. 13, no. 2, pp. 517–529, 2021, doi: 10.1111/os.12877.
L. Comuzzi et al., “Crestal and Subcrestal Placement of Morse Cone Implant–Abutment Connection Implants: An In Vitro Finite Element Analysis (FEA) Study,” Biomedicines, vol. 11, no. 11, p. 3077, 2023, doi: 10.3390/biomedicines11113077.
P. Van Vinh and L. Q. Huy, “Finite Element Analysis of Functionally Graded Sandwich Plates with Porosity via a New Hyperbolic Shear Deformation Theory,” Defence Technology, vol. 18, no. 3, pp. 490–508, 2022, doi: 10.1016/j.dt.2021.03.006.
G. M. Hekal, M. I. Salama, G. Elsamak, and A. H. Almaadawy, “Shear Behavior of RC Beams Strengthened with Ultra-High-Performance Fiber-Reinforced Concrete Using Finite-Element Analysis,” Asian Journal of Civil Engineering, vol. 24, no. 1, pp. 71–91, 2023, doi: 10.1007/s42107-022-00489-x.
A. F. Schrunder, S. Rodriguez, and A. Rusu, “A Finite Element Analysis and Circuit Modelling Methodology for Studying Electrical Impedance Myography of Human Limbs,” IEEE Transactions on Biomedical Engineering, vol. 69, no. 1, pp. 244–255, 2022, doi: 10.1109/TBME.2021.3091884.
S. Chhetri and P. Deb, “Finite Element Analysis of Geogrid-Incorporated Flexible Pavement with Soft Subgrade,” Applied Sciences, vol. 14, no. 13, p. 5798, 2024, doi: 10.3390/app14135798.
B. Deon et al., “Digital Twin and Machine Learning for Decision Support in Thermal Power Plant with Combustion Engines,” Knowl.-Based Syst., vol. 253, p. 109578, Oct. 2022, doi: 10.1016/j.knosys.2022.10 9578.
A. Koesters, F. Koetz, M. Bock, M. Fett, R. Breimann, and E. Kirchner, “Methodical Development of a Digital Twin for an Industry Valve,” Machines, vol. 12, no. 10, p. 674, Oct. 2024, doi: 10.3390/machines12100674.
R. Cabrera-Escobar et al., “Finite Element Analysis Method Design and Simulation of Fins for Cooling a Monocrystalline Photovoltaic Panel,” Clean Technologies, vol. 6, no. 2, pp. 767–783, 2024, doi: 10.3390/cleantechnol6020039.
B. Jeon, M.-S. Kim, S.-H. Choi, and Y. Jeong, “Finite Element Analysis Using Elasto-Visco-Plastic Self-Consistent Polycrystal Model for E-form Mg Sheet Subjected to Bending,” Journal of Magnesium and Alloys, vol. 11, no. 4, pp. 1393–1407, 2023, doi: 10.1016/j.jma.2022.10.017.
C. Hernandez, J. Lara, M. A. Arjona, and E. Melgoza-Vazquez, “Multi-Objective Electromagnetic Design Optimization of a Power Transformer Using 3D Finite Element Analysis, Response Surface Methodology, and NSGA-III,” Energies, vol. 16, no. 5, p. 2248, 2023, doi: 10.3390/en16052248.
J.-H. Lee, H. Y. Jang, and S. Y. Lee, “Finite Element Analysis of Dental Implants with Zirconia Crown Restorations,” Materials, vol. 14, no. 10, p. 2666, 2021, doi: 10.3390/ma14102666.
H. D. Kweon, J. W. Kim, O. Song, and D. Oh, “Determination of True Stress-Strain Curve of Type 304 and 316 Stainless Steels Using a Typical Tensile Test and Finite Element Analysis,” Nuclear Engineering and Technology, vol. 53, no. 2, pp. 647–656, 2021, doi: 10.1016/j.net.2020.07.014.
R. A. Moga et al., “Cortical and Trabecular Bone Stress Assessment during Periodontal Breakdown,” Medicina, vol. 59, no. 8, p. 1462, 2023, doi: 10.3390/medicina59081462.
A. Sur and M. Kanoria, “Thermoelastic Interaction in a Viscoelastic Functionally Graded Half-Space under Three-Phase-Lag Model,” Eur. J. Comput. Mech., vol. 23, no. 5-6, pp. 179–198, Nov. 2014, doi: 10.1080/17797179.2014.978143.
M. Sharifi Guildennoei et al., “Finite Element Analysis of Shear Reinforcing of Reinforced Concrete Beams,” Buildings, vol. 13, no. 4, p. 1034, 2023, doi: 10.3390/buildings13041034.
K. A. Ahmed, L. N. Lowes, and D. E. Lehman, “Investigation of the Behavior of Slender Reinforced Concrete Walls Using Nonlinear Finite Element Analysis,” Resilient Cities and Structures, vol. 2, no. 1, pp. 120–142, 2023, doi: 10.1016/j.rcns.2023.02.010.
J.-F. Zhang et al., “Biomechanical Analysis of Locking Plates for Fixation of Metacarpal Shaft Fractures,” Orthopaedics & Traumatology: Surgery & Research, vol. 108, no. 8, p. 103340, 2022, doi: 10.1016/j.otsr.2022.103340.
B. H. Mills et al., “Design Evaluation of a Next-Generation High-Temperature Particle Receiver,” Energies, vol. 15, no. 5, p. 1657, 2022, doi: 10.3390/en15051657.
P. Piechota et al., “Experimental Determination Influence of Flow Disturbances Behind the Knife Gate Valve,” Sensors, vol. 23, no. 10, p. 4677, 2023, doi: 10.3390/s23104677.
A. Kösters, M. Bock, M. Fett, and R. Breimann, “Methodical Development of a Digital Twin for an Industry Valve,” Machines, vol. 12, no. 10, p. 674, 2024, doi: 10.3390/machines12100674.
R. Kerkeni, S. Khlif, A. Mhalla, and K. Bouzrara, “Digital Twin Applied to Predictive Maintenance for Industry 4.0,” ASME Journal of Nondestructive Evaluation, vol. 7, no. 4, p. 041008, 2024, doi: 10.1115/1.4065875.
I. Abdullahi, S. Longo, and M. Samie, “Towards a Distributed Digital Twin Framework for Predictive Maintenance in Industrial Internet of Things (IIoT),” Sensors, vol. 24, no. 8, p. 2663, 2024, doi: 10.3390/s24082663.
N. Abd Wahab et al., “Systematic Review of Predictive Maintenance and Digital Twin Technologies: Challenges, Opportunities, and Best Practices,” PeerJ Computer Science, 2024, doi: 10.7717/peerj-cs.1943.
A. Marra, S. Gerbino, A. Greco, and G. Fabbrocino, “Combining Integrated Informative System and Historical Digital Twin,” Sensors, vol. 21, no. 17, p. 5956, 2021, doi: 10.3390/s21175956.
J. I. Rojas-Sola and J. C. Barranco-Molina, “Study of the Mechanical Behavior of a Single-Cylinder Horizontal Steam Engine,” Applied Sciences, vol. 14, no. 13, p. 5878, 2024, doi: 10.3390/app14135878.
R. Zhang et al., “A Fast Spatio-Temporal Temperature Predictor for Vacuum Assisted Resin Infusion Molding Process,” Journal of Intelligent Manufacturing, vol. 35, no. 4, pp. 1737–1764, 2024, doi: 10.1007/s10845-023-02113-4.
J. Kang, Z. Yuan, and J. Li, “Mechanism Analysis and Evaluation of Thermal Effects on the Operating Point Drift of Servo Valves,” Journal of Zhejiang University-SCIENCE A, vol. 23, no. 4, pp. 286–302, 2022, doi: 10.1631/jzus.A2100464.
J. I. Rojas-Sola and J. C. Barranco-Molina, “Technical Feasibility of a Two-Cylinder Entablature Steam Engine,” Applied Sciences, vol. 14, no. 15, p. 6597, 2024, doi: 10.3390/app14156597.
D. R. Gonzalez-Morales et al., “Mathematical and Physical Modelling of Transient Multi-Phase Flows in a Ladle Shroud during Start-Up,” Processes, vol. 11, no. 6, p. 1628, 2023, doi: 10.3390/pr11061628.
Y. Wang, C. Wang, G. Liu, C. Zhang, and J. Li, “An Assessment Method of Sealing Performance and Stress Intensity Factors at Crack Tip of Subsea Connector Metal Sealing Rings,” Energies, vol. 15, no. 13, p. 4680, 2022, doi: 10.3390/en15134680.
G. S. Lewis, D. Mischler, H. Wee, J. S. Reid, and P. Varga, “Finite Element Analysis of Fracture Fixation,” Current Osteoporosis Reports, vol. 19, no. 4, pp. 403–416, 2021, doi: 10.1007/s11914-021-00690-y.
N. Kardani, A. Zhou, M. Nazem, and S.-L. Shen, “Improved Prediction of Slope Stability Using a Hybrid Stacking Ensemble Method,” Journal of Rock Mechanics and Geotechnical Engineering, vol. 13, no. 1, pp. 188–201, 2021, doi: 10.1016/j.jrmge.2020.05.011.
K. Wang, A. Wang, L. Wu, and G. Xie, “Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion,” Sensors, vol. 24, no. 8, p. 2652, 2024, doi: 10.3390/s24082652.
J. I. Rojas-Sola and J. F. Gutiérrez-Antúnez, “Analysis of the Design of Henry Muncaster’s Two-Cylinder Compound Vertical Steam Engine with Speed Control,” Applied Sciences, vol. 13, no. 16, p. 9150, 2023, doi: 10.3390/app13169150.
M. Marin, A. Hobiny, and I. Abbas, “Finite Element Analysis of Nonlinear Bioheat Model in Skin Tissue Due to External Thermal Sources,” Mathematics, vol. 9, no. 13, p. 1459, 2021, doi: 10.3390/math9131459.
K. Gholami, F. Ege, and R. Barzegar, “Prediction of Composite Mechanical Properties: Integration of Deep Neural Network Methods and Finite Element Analysis,” Journal of Composites Science, vol. 7, no. 2, p. 54, 2023, doi: 10.3390/jcs7020054.
Béné Inox, 458481-80 Knife Gate Valve (CF8M Stainless Steel Body, 316 Stainless Steel Gate, EPDM Seat). Accessed: Dec. 27, 2025. [Online]. Available: https://www.3dfindit.com/en/digitaltwin/knife-gate-valvecf8m-stainless-steel-body316-stainless-steel-gateepdm-seat?path=bene_inox_raccords%2Findustrie%2F58_robinetterie%2F03_vannes_guillotine%2F58481.prj.
