Air Compressor Testing and Applications in Engineering Assignmnet Sample

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In this above-given figure, the graph depicts the result of testing of tensile of the air compressor (Renet al. 2022). In this testing, there are two different models one is AI and the other one is CU. in this part the analysis is made based on the AI analysis and the figure is the output of the test. In this above-given figure, there is specimen 1. According to the test, the incensement in the load is noticed in the first part of the test. With respect to the time, there are noticed some decrement in the graph. That means the load is high at the beginning but rest to the time the load is reduced. The graph is made between the load and the extension of the specimen.

 Figure 2: The result of the Cu Tensile test

The above figure will depict the test of tensile. This test is done based on the Cu analysis and the given graph will depict the construction of the output. This graph can be considered as the output result of the test(Bashaet al. 2020). After analyzing the testing the result comes. In this output graph that can be noticed that at the beginning the level of load is higher than the level of load in the AI test. That means in the cu test the level of load is higher than in the AI test. According to the time the load gets a break at a time. This is the main point that has to be considered as the assumption of the test.

Bending Testing

1. Testing Procedure

Utilizing a cylinder with a radius of approximately four times that material's density is necessary for the flexure test. Installed in a vice with the made pursuant additional option, the experiment is twisted over the spindle until its joints are equal(Cui et al. 2018). Continuously stretch the object back and forward across a 180 ° position. The stretching need to go on unless the basic metal breaks. All through the procedure, the material must remain in touch only with the mandrel's surface. When folding, tension must be applied gradually and steadily. Under 4X examination, check the pattern's distorted region to determine if the covering is chipping or peeling away from the substrate. If the covering fractures or blisters, it can be lifted off with a dagger or other pointed object. Except if the covering can be easily ripped away, cracks by themselves may not always indicate a lack of adherence. When excessively hard or fragile materials are put through adherence testing, shattering is not uncommon. In this form of custodial bending, the test can define the flexibility of the given material(Liu et al. 2020). All the process of this test is done on a simple machine that is made for this kind of bending test.

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2. Theory and Results

Figure 3: The result of the AI bending test

The above figure depicts the result of the test. In this part, the test is based on the flexibility or bending test of the given component. In this case of the test, there are also two parts one is AI and the other one is Cu(Wang et al. 2019). in the given test the graph can be easily depicted the output of the test. In the output graph, the outline denotes that in the beginning the flexibility going well, but at a time the flexibility will pause and remain the same according to the time. At the end of the test, a little number of decrements are noticed n the graph which will help to understand that at the end the bending efficiency is reduced.

Figure 4: The result of the Cu bending test

The above figure depicts the result of the test. In this part, the test is based on the flexibility or bending test of the given component. In this case of the test, the test is done depending on the Cu analysis. in the given test the graph can be easily depicted the output of the test. In the output graph, the outline denotes that in the beginning the flexibility going well, but at a time the flexibility will pause and remain the same according to the time. The flexibility level gets higher to a significant height and then continues the height and moves towards the right. This nature of the graph is describing that the test of bending goes well and no reduction is noticed. In this figure there are two lines in the graph one line is for the load and the other line is for the Flexure of the graph according to the topic of the assignment.

Figure 5: Graph of Load & Extension

In the excel sheet, there is the data provided that is based on the extension and the load data. The data will gather from the lab experiments. The values of extension and load are according to the time. This depicts that the load and the extension give different values based on different times(Lin et al. 2019). The above graph is the result of the excel sheet. By performing a disting analysis the graph is made according to the data of the extension and the data of the load. In the graph, there are three lines. The three lines are time, extension, and load. The graph of extension is quite similar to the graph of the time. From the beginning to the end of the test there is a linear form of the graph made by the extension element. But the load graph is quite different. In the beginning, the graph of load increases more than the extension and at a level, the graph of load stops increasing rapidly. A little level of increment is noticed in the graph of load.

The above graphs are the results of the material testing, depending on the results it can be easily said that the result is replied to the testing, and depending on the testing the effectiveness and durability of the given air compressor can be easily calculated.

Conclusion

According to the test results and the graphs, the material testing is very effective and gives the actual output result. After performing the test it can easily be concluded that the component, that means the air compressor is highly efficient and the durability of the compressor is high. With respect to time, the compressor stays and works according to time. The loading efficiency is high and the extension of the compressor is also at the upper level. The testing of the material is effective because of the output graph and the analysis made depending on the true value explanation.

References

Journals

• Basha, N., Kovacevic, A., Stosic, N. and Smith, I., 2018, September. Effect of oil-injection on twin screw compressor performance. In IOP Conference Series: Materials Science and Engineering (Vol. 425, No. 1, p. 012009). IOP Publishing.
• Cui, Y., He, D., Wu, H., Ying, W. and Huang, H., 2018. Numerical Simulation of Aerodynamic Noise of Soundproof Enclosure of Air Compressor Unit.
• Duan, Q., Lu, R., Xie, H., Ping, J., Lu, C., Zhou, X., Gao, J. and Li, J., 2020. Fault diagnosis of air compressor in nuclear power plant based on vibration observation window. IEEE Access, 8, pp.222274-222284.
• Hwang, S.H., Moon, C.G., Kim, T.H., Lee, J., Cho, K.S., Ha, K.K. and Lee, C.H., 2019. Rotordynamic Performance Measurements and Predictions of a FCEV Air Compressor Supported on Gas Foil Bearings. Tribology and Lubricants, 35(1), pp.44-51.
• Lin, A.Q., Zheng, Q., Yang, L. and Zhang, H., 2019. Effect of inlet air pre-cooling of water injection on compressor performance at high flight Mach. Journal of Applied Fluid Mechanics, 12(2), pp.421-431.
• Liu, E., Guo, B., Lv, L., Qiao, W. and Azimi, M., 2020. Numerical simulation and simplified calculation method for heat exchange performance of dry air cooler in natural gas pipeline compressor station. Energy Science & Engineering, 8(6), pp.2256-2270.
• Nugraha, I.H., 2020. RANCANG BANGUN SISTEM MAINTENANCE AIR COMPRESSOR (STUDI KASUS: PETRONAS CARIGALI INDONESIA) (Doctoral dissertation, Institut Teknologi Indonesia).
• Ren, X., Feng, M. and Liu, J., 2022. Design and Electromagnetic Loss Analysis of High Speed Permanent Magnet Synchronous Motor for an Air Compressor. Progress In Electromagnetics Research C, 120, pp.265-274.
• Vukelic, G., Vizentin, G., Bozic, Z. and Rukavina, L., 2021. Failure analysis of a ruptured compressor pressure vessel. Procedia Structural Integrity, 31, pp.28-32.
• Wang, S., Liu, Z., Cordtz, R., Imran, M. and Fu, Z., 2019. Performance prediction of the combined cycle power plant with inlet air heating under part load conditions. Energy Conversion and Management, 200, p.112063.
• Wu, D.C., Asl, B.B., Razban, A. and Chen, J., 2021. Air compressor load forecasting using artificial neural network. Expert Systems with Applications, 168, p.114209.
• Zhou, J., Liu, J., Su, Q., Feng, C., Wang, X., Hu, D., Yi, F., Jia, C., Fan, Z. and Jiang, S., 2022. Heat dissipation enhancement structure design of two-stage electric air compressor for fuel cell vehicles considering efficiency improvement. Sustainabilit