D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mechanical and Aerospace Engineering D-index 41 Citations 5,652 195 World Ranking 1048 National Ranking 11

Overview

What is he best known for?

The fields of study he is best known for:

  • Composite material
  • Mechanical engineering
  • Aluminium

His primary areas of study are Welding, Metallurgy, Composite material, Artificial neural network and Engineering drawing. When carried out as part of a general Welding research project, his work on Friction stir welding is frequently linked to work in Quality, therefore connecting diverse disciplines of study. His research investigates the connection with Friction stir welding and areas like Torque which intersect with concerns in Butt welding, Rotational speed, Finite element method and Conical surface.

His Composite material research is multidisciplinary, relying on both Force analysis and Pulmonary surfactant. His biological study deals with issues like Drill, which deal with fields such as Drilling, Structural engineering, Thrust and Work. His studies deal with areas such as Tool wear and Machining as well as Engineering drawing.

His most cited work include:

  • Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II (211 citations)
  • Application of digital image processing in tool condition monitoring: A review (113 citations)
  • Flank wear prediction in drilling using back propagation neural network and radial basis function network (102 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Welding, Composite material, Friction stir welding, Metallurgy and Mechanical engineering. His work deals with themes such as Ultimate tensile strength and Inert gas, which intersect with Welding. His work in Composite material tackles topics such as Heat transfer which are related to areas like Coolant and Thermal conductivity.

His study in Friction stir welding is interdisciplinary in nature, drawing from both Joint, Finite element method and Rotational speed. The study incorporates disciplines such as Boiling and Current in addition to Metallurgy. His Mechanical engineering research includes elements of Artificial neural network, Genetic algorithm and Torque.

He most often published in these fields:

  • Welding (34.69%)
  • Composite material (29.08%)
  • Friction stir welding (26.53%)

What were the highlights of his more recent work (between 2018-2021)?

  • Friction stir welding (26.53%)
  • Welding (34.69%)
  • Composite material (29.08%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Friction stir welding, Welding, Composite material, Microstructure and Metallurgy. His Friction stir welding study combines topics in areas such as Manufacturing process, Fusion welding and Automotive industry. His studies deal with areas such as Porosity, Rotational speed, Alloy, Signal processing and Joint as well as Welding.

His study looks at the relationship between Composite material and fields such as Copper, as well as how they intersect with chemical problems. The various areas that he examines in his Metallurgy study include Work, Texture and Current. As part of one scientific family, Surjya K. Pal deals mainly with the area of Thermal conductivity, narrowing it down to issues related to the Coolant, and often Heat transfer.

Between 2018 and 2021, his most popular works were:

  • Bactericidal effect of graphene oxide and reduced graphene oxide: Influence of shape of bacteria (37 citations)
  • Effect of multiple micro channel reinforcement filling strategy on Al6061-graphene nanocomposite fabricated through friction stir processing (28 citations)
  • Investigation on effect of pin shapes on temperature, material flow and forces during friction stir welding: A simulation study: (18 citations)

In his most recent research, the most cited papers focused on:

  • Composite material
  • Mechanical engineering
  • Aluminium

Surjya K. Pal spends much of his time researching Friction stir welding, Welding, Composite material, Microstructure and Aluminium. His study deals with a combination of Friction stir welding and Material flow. His Welding study introduces a deeper knowledge of Metallurgy.

His Metallurgy research includes elements of Thermoplastic, Thermoplastic materials and Polymer. His Microstructure research incorporates elements of Ultimate tensile strength, Residual stress, Nanocomposite and Grain size. His Rotational speed study incorporates themes from Discrete wavelet transform, Continuous wavelet transform, Structural engineering and Feature.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II

Debabrata Mandal;Surjya K. Pal;Partha Saha.
Journal of Materials Processing Technology (2007)

334 Citations

Application of digital image processing in tool condition monitoring: A review

S. Dutta;S.K. Pal;S. Mukhopadhyay;R. Sen.
Cirp Journal of Manufacturing Science and Technology (2013)

227 Citations

Artificial neural network modeling of weld joint strength prediction of a pulsed metal inert gas welding process using arc signals

Sukhomay Pal;Surjya K. Pal;Arun K. Samantaray.
Journal of Materials Processing Technology (2008)

159 Citations

Flank wear prediction in drilling using back propagation neural network and radial basis function network

S. S. Panda;D. Chakraborty;S. K. Pal.
soft computing (2008)

137 Citations

Soft computing models based prediction of cutting speed and surface roughness in wire electro-discharge machining of tungsten carbide cobalt composite

Probir Saha;Abhijit Singha;Surjya K. Pal;Partha Saha.
The International Journal of Advanced Manufacturing Technology (2008)

136 Citations

Effect of Pulse Parameters on Weld Quality in Pulsed Gas Metal Arc Welding: A Review

Kamal Pal;Surjya K. Pal.
Journal of Materials Engineering and Performance (2011)

128 Citations

Detection of tool condition from the turned surface images using an accurate grey level co-occurrence technique

S. Dutta;A. Datta;N. Das Chakladar;S.K. Pal.
Precision Engineering-journal of The International Societies for Precision Engineering and Nanotechnology (2012)

116 Citations

Influence of plate position, tool offset and tool rotational speed on mechanical properties and microstructures of dissimilar Al/Cu friction stir welding joints

Prakash Kumar Sahu;Sukhomay Pal;Surjya K. Pal;Rahul Jain.
Journal of Materials Processing Technology (2016)

112 Citations

Thermal reduction of graphene oxide: How temperature influences purity

Iman Sengupta;Samarshi Chakraborty;Monikangkana Talukdar;Surjya K. Pal.
Journal of Materials Research (2018)

108 Citations

Drill wear monitoring using back propagation neural network

S.S. Panda;A.K. Singh;D. Chakraborty;S.K. Pal.
Journal of Materials Processing Technology (2006)

100 Citations

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