Wear behaviour analysis on aluminium alloy 7050 with reinforced SiC through taguchi approach

Sathish, T.; Karthick, S.

doi:10.1016/j.jmrt.2020.01.085

Cited by 425 publications

(88 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An other screening technique that can be used for COVID-19 screening is radiography assessment, where chest radiography imaging is led and broke down by radiologists to investigate for visual markers related with SARS-CoV-2 viral defilement [9] , [10] , [11] , [12] . Most of chest radiology imaging of COVID-19 patients indicated coordinating component like ground-glass opacities, adjusted morphology, fringe lung appropriation and aspiratory consolidation [13] , [14] , [15] , [16] , [17] . Notwithstanding the way that chest radiology imaging may offer help with early screening of suspected cases, the highlights of various major viral pneumonia are comparative [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] .…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Convolutional neural network use chest radiography images for identification of COVID-19

Murali¹,

Bhuvaneswari²,

Parvathi

et al. 2020

Materials Today: Proceedings

View full text Add to dashboard Cite

The epic Covid sickness 2019 (COVID-19) has turned into the significant danger to humankind in year 2020. The pandemic COVID-19 flare-up has influenced more than 2.7 million individuals and caused around 187 thousand fatalities worldwide [1] inside scarcely any months of its first appearance in Wuhan city of China and the number is developing quickly in various pieces of world. As researcher everywhere on the world are battling to discover the fix and treatment for COVID-19, the urgent advance fighting against COVID-19 is the screening of immense number of associated cases for disconnection and isolate with the patients. One of the key methodologies in screening of COVID-19 can be chest radiological imaging. The early investigations on the patients influenced by COVID-19 shows the attributes variations from the norm in chest radiography pictures. This introduced a chance to utilize distinctive counterfeit clever (AI) frameworks dependent on profound picking up utilizing chest radiology pictures for the recognition of COVID-19 and numerous such framework were proposed indicating promising outcomes. In this paper, we proposed a profound learning based convolution neural organization to characterize COVID-19, Pneumonia and Normal cases from chest radiology pictures. The proposed convolution neural organization (CNN) grouping model had the option to accomplish exactness of 94.85% on test dataset. The trial was completed utilizing the subset of information accessible in GitHub and Kaggle.

show abstract

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Convolutional neural network use chest radiography images for identification of COVID-19

Murali¹,

Bhuvaneswari²,

Parvathi

et al. 2020

Materials Today: Proceedings

View full text Add to dashboard Cite

show abstract

“…Wear acts in the surfaces that occur when the material is moved or torn off, as it usually involves progressive weight loss and resizing over a period of time. An in‐depth study is required for the dry sliding wear characteristic which influences the volume‐fraction reinforcements and its size, applied load, sliding distance, sliding speed, phase, and hardness of the surface of the work [11, 12]. The study has been reported that different wear parameters affect sliding speed and wear characteristics [13–16].…”

Section: Introductionmentioning

confidence: 99%

Investigations into dry‐sliding wear behaviour of a novel composite (aluminium‐magnesium‐silicon‐copper‐silicon carbide) produced by powder metallurgy route

Behera

Samal

Panigrahi

2021

Materialwissenschaft Werkst

View full text Add to dashboard Cite

Metal-matrix aluminium composites are satisfactory successor not only for steels, but also for aluminium-alloys in several automotive units and components. There are various paths to get lightweight materials without compromising their toughness, strength and safety demands. Tests on dry-sliding or un-lubricated pin-ondisc tests can be performed to obtain the wear-characteristics of metal-matrix composites built on aluminum. In the present study, we studied the behavior of wear resistance during sliding of metal matrix aluminium composites (AMMC) at sliding speeds of 1.5 m/s and loads of 20 N and 40 N in a normal environment, and experiments have been conducted using pin-on-disk tribometer (Make: DU-COM tribometer). The composites were manufactured by powder treatment and presented a number of problems, such as defective bonds and inter-facial product reactions, which alter the tribological and mechanical properties. The results have shown that wear-rates of the prepared composites are much lesser than those of matrix-alloy and decreased further with increasing silicon carbide content. As the normal loads increases, the cracks and combination of abrasions, delimitation and wear of the adhesives of silicon carbide particles were observed. The composite samples were studied using a scanning electron microscope before and after the wear tests and systematically analysed.

show abstract

“…S. Samuel et al, 2019;S. R. Samuel et al, 2020;Sathish & Karthick, 2020;Sharma et al, 2019;Varghese et al, 2019;Vignesh et al, 2019;Vijayakumar Jain et al, 2019). Now the growing trend in this area motivated us to pursue this project.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on MATLAB based JPEG Image Size Reduction Using Discrete Cosine Transform and Shearlet Transform for Mammogram Images with Potential Hospital Data Storage Applications

Srinivasan¹

2021

revistageintec

View full text Add to dashboard Cite

Aim: The aim of this study was to compare Discrete cosine transform and Shearlet transform for mammographic image compression and determine better transform among them. Materials and methods: Sample mammographic images were collected- DCT (30) and Shearlet (30) for compression. Compression ratio was calculated by comparing the original and compressed image size. The significance of the data were calculated using SPSS software. Result: There was a statistical significance between DCT and shearlet based compression ratio data (p=0.035) deviation independent sample t test). Conclusion: DCT based compression ratio was higher (2.41) than the shearlet transforms (0.73). Hence, proving to be a better compression transform than its counterpart (shearlet).

show abstract

Wear behaviour analysis on aluminium alloy 7050 with reinforced SiC through taguchi approach

Cited by 425 publications

References 11 publications

WITHDRAWN: Convolutional neural network use chest radiography images for identification of COVID-19

WITHDRAWN: Convolutional neural network use chest radiography images for identification of COVID-19

Investigations into dry‐sliding wear behaviour of a novel composite (aluminium‐magnesium‐silicon‐copper‐silicon carbide) produced by powder metallurgy route

Comparative Study on MATLAB based JPEG Image Size Reduction Using Discrete Cosine Transform and Shearlet Transform for Mammogram Images with Potential Hospital Data Storage Applications

Contact Info

Product

Resources

About