For this reason, performing fatigue reliability analysis was essential to maintain system availability and reliability. Remaining Fatigue Life Assessment using the Crack Growth Model (CGM) has been conducted as an initiative to prevent fatigue failure. The purpose of the study is to estimate the fatigue crack growth over the time period and develop the crack growth model using spreadsheets to help the engineers prevent fatigue damage.
The crack progress depended on the number of working cycles and the year of maintenance. This project work is expected to contribute to assisting engineers in predicting the next possible failure and monitoring the reliability level of the equipment. Praise to Allah Almighty that in His will I successfully completed the Residual Fatigue Life Assessment using the Crack Growth Model Project within the allotted eight months at Universiti Teknologi PETRONAS (UTP).
Kielland oil platform in Norwegian 3 Figure 1.5 Crack initiations on the gasoline engine piston 6 Figure 1.6 Crack initiations on the diesel engine piston 6 Figure 1.7 Typical stress distributions on the engine piston 7. CGM Crack Growth Model 𝐹𝑒 crack shape factor 𝐹𝑠 free surface effect factor 𝐹𝑠 finite width factor 𝐹𝑔 non-uniform stress factor FRA Fatigue reliability analysis G(a) non-dimensional function ΔK stress intensity factor 𝐾𝑡𝑚 stress concentration factor.
INTRODUCTION 1
Background of the Study 1
- History of Fatigue 4
- Crack Growth Model 14
- Monte Carlo Simulation 17
The black mark formed on the cross-sectional area of the crack leg indicates the slow crack growth pattern of crack initiation and propagation. An investigation determined that the main cause of the accident was fatigue cracking (Walter, 2001). The aim of the study is to determine the causes and consequences of fatigue on mechanical equipment, which is specific; engine piston.
A lot of research has been done on geometry, material and manufacturing techniques that contribute to the continuous improvement of pistons. The heat generated by the movement is also responsible for reducing the fatigue resistance of the material. Both approaches have been shown to provide accurate and reliable results for fatigue reliability analysis.
It is important to understand the failure paths and the reliability level of the components. Fatigue damage can occur as previously mentioned, where 90 percent of the mechanical failure was due to fatigue mechanism. This fatigue reliability analysis not only predicts and prevents fatigue damage, it also helps reduce the company's overall maintenance costs.
Once the crack growth model is proven to be accurate and reliable, development of the fatigue analysis tool will begin. The straight line of the plotted graph advocates that the experimental data fit the power law. There are several reasons for choosing crack growth model as the main approach of the studies.
The red circle shows the expected result of the project, which is the graph of crack size versus time. The implementation of Monte Carlo can be seen in the determination of the value of π. The area of the square is 4 cm2 and the area of the circle is π cm2.
To ensure the accuracy of the results, another simulation was performed using MatLab simulator. To measure the accuracy and reliability of the results, the simulation was run for several times.
The Analysis Framework 21
These random points will be subjected to the Paris equation that was inserted in column D. While columns E and F calculate the acceptance and rejection criteria of the points according to the equation. The random point below the curve will be accepted, while the points above the curve will be rejected.
The accepted points show the area under the graph, which indicates the integration value of the Paris equation.
The Project Management Framework 24
Therefore, each simulation will produce only one value of N; the process was repeated with different crack sizes. As the number of cycles applied is gradually increased, the 'speed' of crack propagation increases rapidly. This crack growth pattern is due to the high strength of the material at early onset of fatigue.
To measure the accuracy and consistency of the results, the simulation should be performed using different numbers of sample sizes. As shown in Figures 4.9 and 4.10; both graphs show the result of the MatLab simulation. But due to some limitation the software was not able to generate the crack growth in terms of number of years.
These results were used as a reference in determining the accuracy of the developed CGM. As shown in Figure 4.2 and Figure 4.11(a), both graphs of the crack growth with respect to the number of years graphs show striking similarities. This is because the exposed material had its release strength in line with the increase in applied stress.
This large difference may be due to the disparate approach used from both case studies. When the maintenance action was done just before the failure occurred, the chances of the accident are very low. To further increase the effectiveness of the model, integration of CGM with other elements, such as material properties, physical geometry and design specifications, should be included in future work.
7] Dong, W., Moan, T., and Gao, Z., 2012, “Fatigue Reliability Analysis of the jacket support structure for offshore wind turbines, considering the effect of corrosion and inspection”, Journal of Reliability Engineering and System Safety European Directorate General Commission's Joint Research Centre,. Some of the deterministic parameters were taken from the nondestructive test, while other random variables were from the lognormal probability density function (PDF). The purpose of this analysis is to determine the number of applied cycles with respect to the crack size.
Build the range of the system by setting the maximum and minimum value of crack size and cycle number.
