Engineering Research Practice Assignment Sample
Here’s the best sample of Engineering Research Practice Assignment, written by the expert.
Problem Definition – from Assignment 1
What are advantages and limitations of using smart materials (shape memory alloys) in cars?
Literature Review Exercise
According to Janke et al. (2005), the key advantage of shape memory alloys in cars is their bio-compatibility. These alloys have good mechanical properties like strong and corrosion resistance that provides higher strengths in shocks. On the other hand, the study of Jani et al. (2014) focuses on the properties of using smart materials (shape memory alloys). As per this study, SMA retains its original shape and coverts to its pre-deformed shape when it is heated. It has properties like light weight, solid-state alternative to conventional actuators such as hydraulic, pneumatic, and motor-based systems. It has capacity to return to its original geometry after heating or compression. Apart from this, it can be identified from the study of Cho and Ahn (2012) that SMA have highest power-to-weight ratio among light-weight technologies. Such property is beneficial for miniaturization. These types of alloys provide high strengths and power with low weights. In addition, Chu et al. (2012) depicted that using smart materials (shape memory alloys) also makes the mechanism simple because there is no need of dampers that helps to reduce complexity of overall system. In addition it is also beneficial to reduce pollution as it contributes to noiseless operation leading to removal of the vibration disturbances. These materials have also high electrical resistivity that unable to transform the shape by passing an electrical current. Additionally, the use of smart materials provides high energy density excellent bandwidth. As per the study of Hartl and Lagoudas (2007), smart materials have durability and reliability and reduce the production cost. It is crucial to reduce the manufacturing cost car. The reason behind this is that smart materials used in car production reduce the weight of component used in Mechanical operations. On the other hand, the research conducted by Riccardi et al. (2012) reflects that it is easy to monitor structural health of smart materials used in car production. The use of smart materials like SMA in cars helps to repair the damages itself because smart materials are self repaired materials as it can repair itself if damages occur.
However, the research of Grigorie et al. (2012) provides contradictory results by finding that smart materials are very expensive that makes production of vehicles costly. At the same time, the availability of smart materials is low as they are not easily available in the market. Non-availability or lack of availability of these materials causes high purchasing cost due to high bargaining power of the supplies. It is because the suppliers of these materials charge high prices for these materials that cause high cost of purchasing as well as production cost. At the same time, Liu et al. (2014) argue that use of smart materials requires extra care because these materials are very sensible while storing. This requirement raises the need for the firms to appoint more skilled and talented staff which could handle these materials effectively and with care. It may also raise the requirement of the training for the employees for handling these materials that also cause higher cost of training for handling these materials leading to the high cost of production. In addition, Riccardi et al. (2012) find that it is difficult for the automobile companies recognize it among materials. So, it can be stated that the handling of smart materials requires better skills and knowledge. In relation to the pollution aspects, Barbarino et al. (2014) find that the use of SMA caused the high pollution because these materials are not biodegradable that may be harmful for the environment. Nowadays, it is major concerns for the automobile firms to focus on environmental protection by reducing carbon emission of their vehicles. But if these materials are not effective to reduce the environmental pollution that it may cause a significant limitation for the production of cars by using these materials.
Selecting quantitative and/or qualitative approach(s)
2.1 Selecting a quantitative approach
1. Define variable(s) that you need to measure in your research (quantitative source(s) of data).
To determine the advantages and disadvantages of the smart materials alloys, their properties need to be measured in the research. For this, two properties like pseudo-elasticity and shape memory effect should be measured in the study. Pseudo elasticity is related to the flexibility of the material like rubber. At the same time, shape memory effect reflects the ability of the materials to be deformed and then return to their original shape. In addition, the biodegradation inability of these materials will also be checked to determine their contribution to the environmental pollution.
2. Describe the factors that indicate you do not need to work with people directly as subjects to gather quantitative data.
There will be no need to work with people directly as subjects to gather quantitative data.
3. Describe the factors that might dictate a high level of structure in this research.
For this research, there will be need to consider large number of measurements over a considerable amount of time. All the parameters providing the flexibility and reformation of the materials will be graphed, analysed and then any associated with the qualitative aspects.
2.2 Selecting a qualitative approach
1. Describe the qualitative source(s) of data that you need for your research that cannot easily be converted to quantitative information.
There is need to determine qualitative data for this research as for this it will be required to conduct interview with the employee working in production department. It will be needed to interact with a number of subjects both online and in person to gather qualitative data regarding availability of SMA and related costs.
2. Describe the factors that indicate you need to work with people directly as subjects on this problem to gather qualitative data.
There will need to work with subjects to gather qualitative data. Response and time consideration for interview will be factors needed to be considered in gathering qualitative data.
3. Describe factors that might dictate a low level of structure in this research.
As outlined in 2.1, this research will have a high level of structure.
Considering your answers given to the questions in the subsection 2.1 and 2.2, do you think your research topic requires a quantitative or qualitative methodology or both?
The topic of research will require quantitative and qualitative methodology both as it is about fixed measurements and associated financial costs and limitations of materials.
Barbarino, S., Flores, E.S., Ajaj, R.M., Dayyani, I. and Friswell, M.I., 2014. A review on shape memory alloys with applications to morphing aircraft. Smart Materials and Structures, 23(6), p.063001.
Chu, W.S., Lee, K.T., Song, S.H., Han, M.W., Lee, J.Y., Kim, H.S., Kim, M.S., Park, Y.J., Cho, K.J. and Ahn, S.H., 2012. Review of biomimetic underwater robots using smart actuators. International journal of precision engineering and manufacturing, 13(7), pp.1281-1292.
Grigorie, T.L., Botez, R.M., Popov, A.V., Mamou, M. and Mébarki, Y., 2012. A hybrid fuzzy logic proportional-integral-derivative and conventional on-off controller for morphing wing actuation using shape memory alloy Part 1: Morphing system mechanisms and controller architecture design. The Aeronautical Journal, 116(1179), pp.433-449.
Hartl, D.J. and Lagoudas, D.C., 2007. Aerospace applications of shape memory alloys. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 221(4), pp.535-552.
Janke, L., Czaderski, C., Motavalli, M. and Ruth, J., 2005. Applications of shape memory alloys in civil engineering structures—overview, limits and new ideas. Materials and Structures, 38(5), pp.578-592.
Liu, Y., Du, H., Liu, L. and Leng, J., 2014. Shape memory polymers and their composites in aerospace applications: a review. Smart Materials and Structures, 23(2), p.023001.
Riccardi, L., Naso, D., Janocha, H. and Turchiano, B., 2012. A precise positioning actuator based on feedback-controlled magnetic shape memory alloys. Mechatronics, 22(5), pp.568-576.
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