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1

Effect of graphite nanoparticles on mechanical properties of FSPed aluminum surface composite

Kumar Dinesh, Singh Satnam

Composites Theory and Practice

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2024

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R. 24, nr 1

33--38

EN

Friction stir processing (FSP) is a manufacturing technique that can be employed to produce aluminum 6082 surface composites (ASCs). These ASCs display considerable increases in hardness and tensile strength, which makes them ideal for a wide variety of automotive applications. One example is piston skirts that are used in the cylinder chamber. The primary emphasis of this research is to investigate the accumulative impact that several passes have on Al 6082 surface composites that were filled with graphite nanopowder. The mechanical properties and microstructure of the fabricated composites were studied in order to accomplish this goal. The microstructural investigation showed that the graphite nanopowder particles were evenly distributed throughout the Al-6082 alloy. In addition, better dispersion of the graphite nanopowder was seen throughout the matrix material as the number of passes made during friction stir processing was increased. This may be explained by the reduction in grain size that occurs inside the aluminum metal matrix composites (AMMCs) that are produced as a consequence. According to the results of the research, the microhardness of the material grew to 105.3 HV after the third pass of the tool, and its maximum tensile strength rose to 215±3 MPa. In the ASCs that fabricated after three passes of friction stir processing, the smallest grain size that was measured was 24 micrometers.

2

Characterization of Al 6061/Al2O3/SiC composites with cerium oxide: corrosion analysis and microstructural insights

Sharma Vipin Kumar, Kumar Pardeep, Kumar Dinesh, Chalisgaonkar Rupesh, Akhai Shalom

Composites Theory and Practice

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2024

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R. 24, nr 1

49--56

EN

CeO2) is incorporated, employing electrochemical analysis and scanning electron microscopy (SEM) techniques. This study investigated the impact of cerium oxide on the corrosion behavior and assessed the hydrophobic properties of the composite surface in corrosive environments using contact angle measurements. The experimental methodology comprised several key components, like the selection of specific materials, the production of hybrid composites by the stir casting technique, the analysis of corrosion using the potentiodynamic polarization method, and the characterization of surface wettability. The metallographic analysis of the composites provided insights into the impact of various reinforcements on the microstructural properties. The incorporation of cerium oxide served to mitigate agglomeration and augment grain refinement within the composites. The utilization of potentiodynamic polarization analysis revealed enhanced corrosion resistance in hybrid composites containing cerium oxide in comparison to the Al 6061 alloy. The corrosion current density exhibited a decrease as the content of CeO2 increased. The findings indicate that cerium oxide can effectively prevent corrosion in aluminum hybrid, composites. These composites show potential for use in corrosion-prone applications.

3

Feature map augmentation to improve scale invariance in convolutional neural networks

Kumar Dinesh, Sharma Dharmendra

Journal of Artificial Intelligence and Soft Computing Research

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2023

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Vol. 13, No. 1

51--74

EN

Introducing variation in the training dataset through data augmentation has been a popular technique to make Convolutional Neural Networks (CNNs) spatially invariant but leads to increased dataset volume and computation cost. Instead of data augmentation, augmentation of feature maps is proposed to introduce variations in the features extracted by a CNN. To achieve this, a rotation transformer layer called Rotation Invariance Transformer (RiT) is developed, which applies rotation transformation to augment CNN features. The RiT layer can be used to augment output features from any convolution layer within a CNN. However, its maximum effectiveness is shown when placed at the output end of final convolution layer. We test RiT in the application of scale-invariance where we attempt to classify scaled images from benchmark datasets. Our results show promising improvements in the networks ability to be scale invariant whilst keeping the model computation cost low.

4

Analytical versus experimental investigation of physical and mechanical characteristics of stir cast hybrid aluminium nanocomposite

Kumar Dinesh, Singh Satnam, Angra Surjit

Composites Theory and Practice

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2023

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R. 23, nr 3

136--144

EN

Aluminium alloys have good mechanical and physical properties and are lightweight, easy to cast, and simple to machine. Aluminium alloys are widely used in the aviation industry, auto sector, defence sector, and structural industries because of their promising abilities. The fundamental aim of this study was to investigate the mechanical properties and physical characteristics of a stir cast hybrid aluminium nanocomposite reinforced with 1-3 wt.% cerium oxide (CeO2) and graphene nanoplatelets (GNPs). Utilizing SEM, microstructural analysis was carried out. The existence of the elements of the reinforcement in the manufactured nanocomposite specimens was verified using EDAX. With an increase in the reinforcement wt.%, improvements in the mechanical and physical properties were seen. In the hybrid nanocomposites reinforced with 3 wt.% GNPs and 3 wt.% CeO2, a low porosity of 1.06% was observed. The best results for tensile strength, yield strength, and microhardness were 398 MPa, 247 MPa, and 119.6 HV, respectively. The SEM micrographs of the studied materials showed that the reinforcement particles were uniformly dispersed and refined into ultrafine grains.

5

Simulation of strong ground motions of 1991 Uttarkashi (M 7) and 1999 Chamoli (M 6.6) earthquakes using modified hybrid technique

Sharma Anjali, Kumar Dinesh, Paul Ajay, Teotia Satybir Singh

Acta Geophysica

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2023

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Vol. 71, no. 6

2573--2602

EN

In the present study, 1991 Uttarkashi (M 7) and 1999 Chamoli (M 6.6) earthquakes that occurred on October 19, 1991, at 21:23:14 h and March 28, 1999, at 19:05:11 h, respectively, have been simulated using the modified hybrid technique. Hybrid technique is the combination of two existing techniques, i.e., envelope technique and composite source model technique. In the present modified technique, site amplification functions and kappa factor have also been incorporated. The simulated waveforms and their corresponding response and Fourier spectra for each site have been generated. In this study, simulation has been done at 11 and 9 recorded stations of Uttarkashi and Chamoli earthquakes, respectively. Important frequency - and time-domain parameters, i.e., Fourier spectra, response spectra, peak ground acceleration (PGA) and duration at stations, have been estimated and compared with the observed accelerograms. It has been observed that the simulated PGA (231 cm/s2) at the closest distance Bhatwari (22 km) matched with the observed one (248 cm/s2) for the Uttarkashi earthquake. The same has been observed at the nearest most station Gopeshwar (19 km) of the Chamoli earthquake. The simulated PGA (347 cm/s2) for this station has been found well matched with the observed PGA value (352 cm/s2). Similar matching has been observed for other stations also. The present technique is independent of velocity-Q structure of earth’s layered model and past events data of small earthquakes. This study brings light on the site effect and high-frequency decay parameter. This study can be very helpful in the estimation of seismic hazard in a specific region and designing earthquake-resistant buildings.

6

Hospital selection under Insured Public Health Schemes in the multi-criteria group decision-making environment

Dev Manimay, Kumar Dinesh, Mor Rahul S.

Production Engineering Archives

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2022

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Vol. 28, Iss. 1

1--11

EN

A thriving healthcare system perfectly reflects economic development and contentment amongst the people of any region. With increasing anxiety concering health and growing medical needs, hospitals worldwide face substantial challenge to provide patients with adequate medical facilities under one roof. With a fragile state of the health industry in a developing country like India, there is a need for the hospitals to opt for international standards and comply with other premier health centers of the country. This paper aims to select the hospitals based on incongruous and conflicting criteria involving group decision-making using the Intuitionistic Fuzzy (IF) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The criteria used are concomitant to an insured public health scheme named Ayushman Bharat-National Health Protection Scheme (AB-NHPS) of the Government of India. For each alternative Euclidean distance has been used to calculate the positive and negative separation measure from the ideal solution. The relative closeness to the ideal solution has been used to rank the hospitals. The result is a list of hospitals ranked from best to worst based on the laid criteria. It can aid governing bodies in decision-making under an uncertain environment with multiple complex criteria to analyze.

7

Dual-modality synthetic mammogram construction for breast lesion detection using U-DARTS

Rautela Kamakshi, Kumar Dinesh, Kumar Vijay

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 3

1041--1050

EN

Multimodal image fusion is an emergent research area for cancer detection. It provides a wide variety of visual qualities for the accurate medical diagnosis. However, this process requires accurate registration of each image modality for its efficient and effective use. To address the aforementioned issue, a novel synthetic mammogram construction model is proposed. An image enhancement approach is applied to enhance the image quality. Dual-modality structural feature (DMSF) based mapping function is designed to transform a mammogram from a thermal image segment. This paper also proposes modified Differentiable ARchiTecture Search (DARTS) named as (U-DARTS) to detect and classify the breast lesion. In U-DARTS, a stochastic gradient descent optimizer is used. The proposed approach is tested over DMR and INbreast datasets. The results exhibit a significant improvement in the performance of the proposed model over the existing techniques. The validation and testing accuracies of 98% and 91%, respectively, are achieved. Overall, the proposed approach establishes supremacy in so far as the mammogram construction and further lesion detection are concerned.

8

Achieving cost efficiency through increased inventory leanness: Evidence from manufacturing industry

Mor Rahul S., Kumar Dinesh, Yadav Sarika, Jaiswal Swatantra K.

Production Engineering Archives

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2021

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Vol. 27, Iss. 1

42--49

EN

Inventory management’s fundamental problem starts with maintaining equilibrium among the operating efficiency, cost of investment, and other allied costs with extensive inventories to keep the actual conflicts at the minimum while optimizing the inventory holding levels. But, inventory management practices have not been well exploited in various manufacturing industries yet. In this study, inventory management tools, i.e., ABC and VED analysis, have been applied in the manufacturing industry, considering 146 items as raw material for an assembly. A total of 15 items under ‘AV’ class have been identified that consume 82.05 % of the total cost, and these items need strict control and frequent ordering. Sigma level of suppliers is also calculated, which comes out to be 2.36, and it must be improved to reduce the overall inventory cost.

9

Spatial distribution of high frequency spectral decay factor kappa (κ) for Delhi, India

Mittal Himanshu, Sharma Babita, Sandhu Manisha, Kumar Dinesh

Acta Geophysica

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2021

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Vol. 69, no. 6

2113--2127

EN

The recorded strong motion data in the Delhi region provide an excellent opportunity to study high-frequency decay parameter, kappa (κ) for the National Capital (Delhi) region and to further understand its implications to study the site effects characterized by different stations within the vicinity of the study region. The kappa values are estimated at 30 locations from 99 accelerograms of 19 earthquakes recorded in the Delhi region and are found to vary from place to place depending upon the controlling parameters, primarily the site characterization. The estimated average values of ‘κ’ lie in the range 0.0118–0.0537 s for the various locations of the region depending upon the source, path, and site characteristics of earthquakes considered in the present study. The distance dependence is found insignificant, while there is a scatter in the variation of κ values with that of magnitude which indicates that κ is more related to the site characteristic for the entire Delhi region which in turn reveals the fact of the basic criterion of the κ parameter. To affirm the total attenuation on the instruments, the site effects demonstrate the behavior of amplification to the geological exposure. It has been found that the various sites under consideration for the study area amplify between 0.6 and 7.0 Hz predominant frequency ( fpeak) and agree with the geological arrangements of the region. Based on the present study, the most vulnerable areas are the northeastern region of Delhi which lies in proximity to the food plains of Yamuna river and alluvial deposits of younger origins of the foreland basin along with the southwestern part of Delhi capital which is comprised of the water-saturated alluvial deposits. The estimated ‘κ’ values are found to be correlated with those of the estimated site amplification and are useful in strong ground motions simulation for the proper evaluation of seismic hazard to build a seismic risk resilient society.

10

A novel multi-class approach for early-stage prediction of sudden cardiac death

Devi Reeta, Tyagi Hitender Kumar, Kumar Dinesh

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

586--598

EN

Sudden cardiac death (SCD) is a complex issue that may occur in population groups with either known or unknown cardiovascular disease (CVD). Given the complex nature of SCD, the discovery of a suitable biomarker will prove essential in identifying individuals at risk of SCD, while discriminating it from patients with other cardiac pathologies as well as healthy individuals. Thus, this study aimed to develop an efficient approach to support a better comprehension of heart rate variability (HRV) as a predictive biomarker to identify SCD patients at an early stage. The present study proposed a novel multi-class classification approach using signal processing methods of HRV to predict SCD 10 min before its occurrence. The developed algorithm was qualitatively and quantitatively analyzed in terms of discriminating SCD patients from patients of heart failure and normal people. A total of 51 HRV signals of all three classes obtained from PhysioBank were processed to extract 32 features in each subject. The optimal feature selection was performed by a hybrid approach of sequential feature selection-random under sampling boosting algorithms. Multi-class classifiers, namely decision tree, support vector machine, and k-nearest neighbors were used for classification. An average classification accuracy of SCD prediction 10 min before occurrence was obtained as 83.33%. Therefore, this study suggests a new efficient approach for the early-stage prediction of SCD that is considerably different from that reported in the literature to date. However, to generalize the findings, the algorithm needs to be tested for a larger population group.