Arpan Kumar
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Scopus Publications
- COVID-19: Implications for social sustainability through artificial intelligence - A critical review
Arpan Kumar, Harinadh Vemanaboina, B. Sridhar Babu, Kaushik Kumar
Aip Conference Proceedings, 2023 - Computing strategies towards successful implementation of industry 4.0: A review
Arpan Kumar
Aip Conference Proceedings, 2023 - Heat conduction in an orthotropic material–numerical analysis using python
Arpan Kumar, Apurba Kumar Roy, Kaushik Kumar
International Journal on Interactive Design and Manufacturing, 2023 - Virtual Prediction of Material Properties
Arpan Kumar
Materials Today Proceedings, 2022 - Python assisted numerical analysis of heat conduction for an orthotropic material
Ashutosh Ranjan, Arpan Kumar, Apurba Kumar Roy, Kaushik Kumar
Advances in Materials and Processing Technologies, 2022
While machining materials changes and deformation of grain structure take place. This deformation of the grains affects the thermal properties of the material leading to orthotropic thermo-physical property. Typical materials like Ti-6Al-4 V having high hardness which are extensively used in many critical applications especially medical implants, requires study of such properties for proper fitment, sustainability and longevity. As a large amount of heat is produced during machining hence, in depth idea of the distribution of temperature in the product is highly necessary to design an optimally cooling strategy, to control the thermo-physical property of the material. In this present work, 2D material domain has been modelled to numerically predict the distribution of temperature, aided with Finite Difference scheme using Python. The differential equation governing the heat conduction and the boundary conditions have been are discretized, which are solved using an iterative method. The effect of different orthotropic thermo-physical property on heat conduction for Ti-4Al-4 V alloy have been demonstrated using the temperature distribution plots. The results can be used for deciding both the machining parameters as well as post-machining operations like cooling strategies. - Graphic user interface based implementation of longest common subsequence problem in DNA sequencing
Arpan Kumar, Sarbajit Manna
Aip Conference Proceedings, 2021
One of the oldest problems in computational biology is biological sequences in which similar portion of two DNA sequence is searched. Global alignment is designed for the same and Longest Common Subsequence (LCS), one of the most basic algorithms in the field of computer science, provides the best solution global alignment irrespective of the shape of its input sequences. The Longest common Subsequence problem with a variable number of strings is variable and strictly more than 2 is known as Multiple Longest Common Subsequence problem (MLCS) and it is an NP-hard problem. Dynamic Programming Algorithm can be employed to solve the same within polynomial time provided the number of strings is known. In this work, using python GUI-library tkinter, the GUI has been built with the code of the LCS problem embedded within the GUI application. This would not only help to see how the strings are being matched inside the program but also the way the optimal solution is produced.
