Influence of Cow Horn Particles on the Hardness and Impact Properties of the Reinforced Recycled Aluminium Alloy
Adeyemi Gbenga Joshua,
Oguntuase Musa,
Stephen Joseph Temitope
Issue:
Volume 7, Issue 1, January 2022
Pages:
1-6
Received:
9 April 2022
Accepted:
23 April 2022
Published:
7 May 2022
Abstract: Development of low cost metal alloys reinforced with waste materials such as agro- waste and industrial waste has been one of the major innovations in the area of material engineering. This aimed at producing engineering materials with improved properties without additional cost of techniques such as annealing and normalising. In this study, aluminium scraps from automobile parts (secondary aluminium) were used as principal material and reinforced with locally available inexpensive cow horn particulate (ago-wastes) of 3, 6, 9 and 12% by weight to produce an aluminium based composite. Hardness and impact strength of the aluminium alloy reinforced cow horn particulate (CHp) were studied. The results showed that the produced composite exhibits superior hardness value compared to the alloy metal. The hardness increases from 87.7 BHN to 101.4 BHN, 132.4 BHN, 134.4 BHN and 143 BHN with addition of 3%, 6%, 9% and 12%, weight of CHp into the aluminium alloy matrix, respectively. However, the composite displayed lower impact strength than the aluminium alloy and the strength reduces as the weight percentage of CHp in the composite increases. Addition of 3%, 6%, 9% and 12%, weight of CHp into the aluminium alloy reduced the impact value from 49.4 J to 36.76 J, 35.05 J, 33.68 J and 28.53, respectively. The X-ray diffraction analysis of the reinforced aluminium alloy revealed the presence of CHp without the formation of any other intermetallic compounds, good bonding between CHp and aluminium alloy, and absence of agglomeration of CHp in the aluminium alloy matrix.
Abstract: Development of low cost metal alloys reinforced with waste materials such as agro- waste and industrial waste has been one of the major innovations in the area of material engineering. This aimed at producing engineering materials with improved properties without additional cost of techniques such as annealing and normalising. In this study, alumin...
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Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory
Issue:
Volume 7, Issue 1, January 2022
Pages:
7-12
Received:
13 April 2022
Accepted:
29 April 2022
Published:
7 May 2022
Abstract: The article describes the properties and application of the original adaptive multipoint (for each irregularity size) method for predicting the values of track geometric parameters and their changes over time, based on the use of convergence theory. Prediction results are presented in the form of irregularity size distribution function (ISDF). ISDF shows the cumulative length of specific-size track irregularity within an arbitrary length track segment at the end of the prediction interval. The method is based on three main principles: using the ISDF function to describe track condition and changes therein, using only the results of previous measurements for calculations as input information about the condition of the track, using the ISDF convergence process analysis to calculate future values of the track geometric parameters. The method is invariant to the length of the time interval between past measurements. The method also allows to identify a tendency to sudden spontaneous deterioration of the track, which does not follow from a regular trend. For longitudinal level defects, the average prediction error for defect sizes s>|3|mm and prediction intervals of 2 and 6 months does not exceed 0.35%.
Abstract: The article describes the properties and application of the original adaptive multipoint (for each irregularity size) method for predicting the values of track geometric parameters and their changes over time, based on the use of convergence theory. Prediction results are presented in the form of irregularity size distribution function (ISDF). ISDF...
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