Oil Film Thickness - Assignment Example

Literature review Oil film thickness Oil film thickness of a piston is determined by sustained variables such as piston speed the ring face, surface round roughness, lubricants viscosity, ring twist, impacts distortion and density of oil. Once these parameters have been determined an equation is formed which is solved by finite differential. According to Bhatt, Bulsara and Mistry (2009) oil film thickness is important in engines if not properly managed may lead to engine failure. According to He, Lu, Zou, Guo, Li, Huang (2014) oil film thickness determines the durability of an engine. It is true the oil thickness that piston failure is likely to take place. Without proper oil thickness there is likely to be thermomechanical fatigue in the engine which may lead to failure and eventual failure of the machine involved. It is necessary to determine the oil thickness. According to Novotny, Pistek and Drapal oil film pressure is determined by oil thickness that is applied in the piston. Oil thickness affects both dynamical and thermal boundary layers, leading to increased thickness and decreased gradients by injecting some low-momentum low-temperature fluid (Jost Institute for Tribotechnology, 2010). This translates to reduced transfer coefficients, and lower shear stress and convective heat flux, allowing for low viscous drag and an efficient thermal protection when hot surface fluid is in contact and keeping the surface temperature at an appropriate level (He, Lu, Zou, Guo, Li and Huang, 2014). In addition to this, there is an increase in both pressure drag and overall drag (Wolff, 2011). Achieving satisfactory operation of engine that is used in the marine is generally viewed as very essential to consider factors like oil thickness come into play. As such, the requirements can usually be fulfilled through proper oil thickness estimation. However, the estimation part is normally the most crucial of the factors despite the fact that proper pressure also do play a huge role when it comes to observing the dynamic behaviour even among the well established engines (Sreenath and Venkatesh, 1973). 3D-Reynolds equation Reynolds equations use high fine grid resolution for example, the Kolmogorov micro scale. Further, DNS has a problem with the amount of grid points required. It raises three-fold the Reynolds number (Livanos and Kyrtatos, 2007). Consequently, the Reynolds number for fire and smoke movement within a compartment is close to 105, thus; the total number of cells crucial for solving the movements within a room goes up to the value of 1013 (Novotný, P, Píštěk and Drápal, 2011). The current super computers have the capacity to attain the grid resolution of 134,217,728 cells. Thus, the existing computer technology cannot give solutions of such motions( Gudimetal and Gopinath 2006) 3D-Reynolds equations are applied when it comes to oil film thickness between cylinders of an engine. According to Novotný, Píštěk and Drápal (2011) 3D-Reynold equations that are applicable in case of oil film thickness are = ‘Where h stands for oil film thickness, x is distance coordinates; t is change in time, is pressure, is oil density,  is dynamic oil viscosity and U is relative velocity’(Novotný, Píštěk and Drápal, 2011). The Reynolds equation will be solved using Finite Difference Method. Advantages and limitations Reynolds equations Computational models essentially are full-scale representations of the prototype, in contrast to physical models. Thus computational models have certain advantages over physical scaled models and have limitations in their use (Stark, Gamble, Hammond, Gillespie, Smith, Nagatomi, Priest, Taylor, Taylor and Waddington, 2006). The main advantages of computational models are: 1. they are generally less expensive than the equivalent physical scale model; 2. many alternative designs can be readily tested, quickly and cheaply; 3. the models may be stored on electronic media for future use; 4. the models do not suffer from any scaling effects. The main limitations of computational models are: They can only be applied where the main underlying physics of the flow are known and can be included in the model. The minimum amount of topographical data required to obtain accurate results is difficult to quantify. Finite difference methods A more advanced 3D computational method is reported by He, Lu, Zou, Guo, Li and Huang (2014) where 3D-Reynold equations are solved via a finite differential method. The oil film thickness representation must be time-accurate, nonlinear and viscous. The turbulence model must be able to cope with piston separation and re-attachment. The unsteadiness due to the vibration must be included but the structural analysis is not straightforward because of gross mistuning (Stark, Gamble, Hammond, Gillespie, Smith, Nagatomi, Priest, Taylor, Taylor and Waddington, 2006). Finally, it must be stressed that the computational requirement for such a calculation is very considerable since a time-accurate, nonlinear viscous analysis must be undertaken for a whole assembly because of the loss of symmetry in the flow of oil. Novotný, Píštěk and Drápal, (2011) used a time-domain, nonlinear finite element method coupled with an idealised bird model and contact algorithm to analyse small fan blades. Experimental and predicted results were quoted over a wide range of impact thickness of oil on engines (Chu, Chang and Yang, 2008). The finite differential methods are critical in designing a 3D model for the oil filling the oil film thickness between the piston film and the cylinder of a marine diesels engine. The model is calculated using finite differential method since it is able to perform thermomechanical coupled analysis (Gudimetal and Gopinath, 2006). In designing for finite differential method variables for the piston pin hole and the piston pin are determined then variables relating to the skirt, bolt, pin and push are determined, that means boundary conditions are calculated in order to be able to use the method well. The finite differential method takes the form the system of 2N − 2 continuity and momentum equations for h and p in finite difference form. It has set up the two boundary conditions and solve the system of 2N equations using matrix methods and using current values of parameters initial estimates of at the next time step (Bhatt, Bulsara and Mistry, 2009). A major limitation in the use of finite differential methods for the numerical approximation of partial differential equations is the onset of instability (Cheng and Chang, 2004). This restricts the magnitudes of the time (t)and coordinates(x), and means that quite large numbers of calculations may be involved (Wolff, 2012). Solutions to finite difference equations can overcome this. Stability analysis of implicit models shows that provided the ‘weighting coefficients’ used in the equations are within specified ranges, the models are stable for any value of the commonly used condition number, the Courant number (Chu, Chang and Yang, 2008). Turning next to the validity of the numerical schemes used in the model, it is not normally possible for a model user to adjust them. Thus it is very important to choose a computational model with an established track record and pedigree. The well-established commercial computational models do have robust numerical schemes which perform very well under most circumstances (Jost Institute for Tribotechnology, 2010). References Bhatt, D., Bulsara, M A & Mistry, K. 2009. Prediction of Oil Film Thickness in Piston Ring -Cylinder Assembly in an I C Engine: A Review. Proceedings of the World Congress on Engineering 2009 Vol II. Cheng, C. & Chang, M., 2004. “Profile Design for Surface of a Slider by Inverse Method,” ASME J. of Tribology, Chu,L., Chang, Y., & Yang, J.,2008. Profile Design of Piston Ring Using Inverse Method. Journal of Marine Science and Technology. Gudimetal, P. & Gopinath, C., 2006. “Finite element analysis of reverse engineered internal combustion engine piston,” Asian International Journal of Science and Technology in Production and Manufacturing Engineering. He, T., Lu, X., Zou, D., Guo, Y., Li, W. & Huang, M., 2014.Thermomechanical Fatigue Life Prediction for a Marine Diesel Engine Piston considering Ring Dynamics. Hindawi Publishing Corporation Advances in Mechanical Engineering Jost Institute for Tribotechnology, 2010. Oil film thickness measurement: a contribution to the understanding and control of lubrication in the piston-ring packs of IC engines. Journal of engineering tribology Livanos, G. & Kyrtatos, N., 2007. “Friction model of a marine diesel engine piston assembly”. Tribol. Intl, Lu, X., Li, Q., Zhang, W., Guo, Y., He, T. & Zou, D., 2013. “Thermal analysis on piston of marine diesel engine,” Applied Thermal Engineering. Lu, X., Li, Q., Zhang, W., Guo, Y., He, T. & Zou, D., 2012. “Thermal analysis of composite piston in marine diesel engine based on inverse evaluation method of heat transfer coefficient,” ChineseInternal Combustion Engine Engineering. Novotný, P, Píštěk, V & Drápal, L., 2011. Dynamic Simulation of Piston Ring Pack. International Scientific Conference of Czech and Slovak University Departments and Institutions Dealing With the Research of Combustion Engines. Sreenath, A. & Venkatesh, S.1973. Analysis and computation of the oil film thickness between the piston ring and cylinder liner of an internal combustion engine.” Int. J. Mech. Stark, M., Gamble, R., Hammond, C., Gillespie, H., Smith, J., Nagatomi, E., Priest, M, Taylor, C., Taylor, R. & Waddington D. 2006. Measurement of Lubricant Flow in a Gasoline Engine Wolff, A., 2012. Influence of Engine Load on Piston Ring Pack Operation of a Marine Two-Stroke Engine. Journal of KONES Powertrain and Transport, Vol. 19, No. 2 2012 Wolff, A., 2011. Numerical analysis of piston ring pack operation of a marine two-stroke engine, Combustion Engines. Read More