Akshansh Mishra

Akshansh MishraAkshansh MishraAkshansh Mishra

Akshansh Mishra

Akshansh MishraAkshansh MishraAkshansh Mishra
  • Home
  • Publications
  • Masters Thesis
  • Ongoing Research
  • Machine Learning
  • Architected Metamaterials
  • Additive Manufacturing
  • Composite Materials
  • Science Preachings
  • Developed APPS
  • STL Gallery
  • AUGMENTED REALITY
  • Altro
    • Home
    • Publications
    • Masters Thesis
    • Ongoing Research
    • Machine Learning
    • Architected Metamaterials
    • Additive Manufacturing
    • Composite Materials
    • Science Preachings
    • Developed APPS
    • STL Gallery
    • AUGMENTED REALITY
  • Home
  • Publications
  • Masters Thesis
  • Ongoing Research
  • Machine Learning
  • Architected Metamaterials
  • Additive Manufacturing
  • Composite Materials
  • Science Preachings
  • Developed APPS
  • STL Gallery
  • AUGMENTED REALITY

Research Activities

Deep learning based porosity detection in additive manufactured samples

In the present work, deep learning based approach is being used for porosity segmentation in additive manufactured samples. 


STATUS: Ongoing

COLLABORATIVE WORK WITH: Professor Shivraman Thapliyal

Data driven prediction of effective properties of TPMS based architected unit cells

The objective of this work will be to collect the data from a simulation-driven approach and further develop algorithms to predict the effective properties of TPMS-based bio-inspired structures and further validate the algorithm on unseen data. 


STATUS: Ongoing

Predictive Modeling and Optimization of Additive Friction Stir Deposition (AFSD)

Predictive Modeling and Optimization of Additive Friction Stir Deposition (AFSD)

This research aims to integrate Machine Learning (ML) techniques with the thermal-mechanical simulation of the Additive Friction Stir Deposition (AFSD) process to predict and optimize process parameters for improved material properties and deposition quality.  


STATUS:  Completed

Structural integrity analysis of TPMS based architected structures

Structural integrity analysis of TPMS based architected structures

Predictive Modeling and Optimization of Additive Friction Stir Deposition (AFSD)

In this work, a data-driven approach will be developed for evaluating the mechanical performance of TPMS-based lattice structures.


STATUS: Ongoing

Homogenization of Graph Unit Cell based architected metamaterial

Structural integrity analysis of TPMS based architected structures

Homogenization of Graph Unit Cell based architected metamaterial

Homogenization refers to the process of replacing a heterogeneous material with an equivalent homogeneous material in finite element analysis. Heterogeneous materials have non-uniform properties that vary spatially across the material. This spatial variation makes analysis complex. 


STATUS: Completed

TALK TO LATTICE: Tailored LLM for Architected Materials

Structural integrity analysis of TPMS based architected structures

Homogenization of Graph Unit Cell based architected metamaterial

The main goal of this research project is to develop a customized LLM retrieval AI agent that is more accurate in terms of answering user queries. 


STATUS: Completed

Machine learning-based structural integrity assessment of AlSi10Mg parts fabricated by L-PBF Process

Machine learning-based structural integrity assessment of AlSi10Mg parts fabricated by L-PBF Process

In this ongoing research work, the main objective is to evaluate the mechanical properties of the AlSi10Mg parts fabricated by the laser powder bed fusion process by developing new machine-learning algorithms. 


STATUS: Completed

COLLABORATIVE WORK WITH: Dr. Vijaykumar S Jatti

Evaluation of Tensile Properties of the Inconel based cellular material specimens

Machine learning-based structural integrity assessment of AlSi10Mg parts fabricated by L-PBF Process

In this research work, structure-property relationship of the architected material based tensile specimens will be evaluated. 


STATUS: Completed

COLLABORATIVE WORK WITH: Dr. Vijaykumar S Jatti

Friction Stir Additive Manufacturing of AA6061 Plates

Friction Stir Additive Manufacturing of AA6061 Plates

In this research, a data-driven approach will be employed to model the mechanical properties of double-layered friction stir additive manufactured AA6061 plates. 


STATUS: Ongoing

COLLABORATIVE WORK WITH: Dr. Vijaykumar S Jatti

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