Academic Projects (2015-On going)



(1)  Improving Environmental Sustainibility of Non-linear Systems.

Collaborators:

1) Dr. Liang Gao (Professor, HUST, China)

2) Dr. Ankit (Assistant Professor, IIT Guwahati)

3) Dr. Monica Mahesh Savalani (Assistant Professor, Hongkong Polytechnic University, Hongkong)



(2)  Modelling of Green Supply chain networks by Non-linear programming and Evolutionary approach.

Collaborators:

1) Dr. Liang Gao (Professor, HUST, China)

1) Dr. Jasmine Siu Lee Lam (Assistant Professor, NTU Singapore)



(3)  System Identification of Microbial fuel cells.

Collaborators:

1) Mr. Biranchi Panda (IST Lisbon, Portugal)



Academic Projects (2010-2014 (Completed))



(1)  Optimization of 3-D Printing process by development of ensemble based genetic programming variants.

Collaborators:

1) Dr. M C Tsai (Chair Professor, NCKU Taiwan)

2) Dr. Kang Tai (Associate Professor, NTU)

3) Dr. Leehter Yao (President, Professor, NTUT Taiwan)

4) Dr. K.S Sangwan (Professor, BITS Pilani Campus)

5) Dr. Monica Mahesh Savalani (Assistant Professor, Hongkong Polytechnic University, Hongkong)



1.1New genetic programming approach is developed for evaluating the characteristics (density, strength, surface roughness) of 3-D printing fabricated prototype.

1.1 Sensitivity and parametric analysis is further conducted to evaluate the robustness of the model.



(2)  Evaluation of properties of nanomaterials by simulation methods of Molecular dynamics and Genetic Programming.

Collaborators:

1) Dr. S.S. Mahapatra (Professorand HOD, NIT Rourkela)

2) Dr. Wong Chee How (Associate Professor, NTU Singapore)

3) Dr. Kang Tai (Associate Professor, NTU)

4) Dr. Liang Gao (Professor, HUST, China)

5) Dr. K Sumithra (Professor, BITS Hyderabad)

6) Dr. Pravin M Singru (Professor,BITS Goa Campus)



2.1 A hybrid artificial intelligence model based on MD simulation was developed to simulate and analyze the drilling process of graphene sheet.

2.2 Multi-gene GP was incorporated to train and test process variables obtained using MD simulation and best process parameters were obtained for optimal drilling performance.



(3)  Formulation of structural risk minimization integrated evolutionary approach in optimizing hydraulic properties of soil.

Collaborators:

1) Dr. Sreedeep S (Associate Professor, IIT Guwahati)

2) Dr. Kang Tai (Associate Professor, NTU)

3) Dr. M.C. Deo (Professor, IIT Bombay)

4) Dr. Alexia Stokes (INRA , France)

5) Dr. Stefano Barontini (UniversitÓ degli Studi di Brescia DICATAM, Italy)

6) Prof. Wan-Hannah Zhou (University of Macao)



3.1We developed an integrated multi-gene genetic programming approach by introducing new complexity measure, structural risk minimization, in the fitness function.

3.2 Proposed approach is applied for modelling hydraulic, mechanical, and thermal properties of soil.



(4)  Development of mathematical model for incorporating DSA regime of ASS 304 Steel.

Collaborators:

1) Dr. Amit Kumar Gupta (Associate Professor, BITS Hyderabad Campus)

2) Dr. Kang Tai (Associate Professor, NTU)



4.1 We modified the multi-gene genetic programming approach by inducting the stepwise regression for combining the relevant genes in the evolutionary stage.

4.2 Parametric and Sensitivity analysis is conducted to validate the modified multi-gene genetic programming approach and the important non-linear and hidden relationships of the ASS 304 behaviour is evaluated.



(5)  Robust Optimization of finishing process by simulation based GA approach.

Collaborators:

1) Dr. Lily Rachmawati (Advance Technologist, Rolls Royce)

2) Dr. Kang Tai (Associate Professor, NTU)



5.1 Developed graphical user interface (GUI) for implementing genetic programming in a user friendly manner.

5.2 The project aims at eliminating vital issues such as generalization in the field of genetic programming so as to evolve the optimal models for the robust optimization of the process.

5.3 The important process parameter settings of the machine that enables time and cost optimization are obtained.



(6)  Fuzzy-Taguchi based approach for improving the dimensional accuracy of Fused Deposition Modeling (FDM) built specimen.

Collaborators:

1) Dr. S.S. Mahapatra (Professor and HOD, NIT Rourkela)



6.1 A Hybrid Fuzzy-Taguchi approach is proposed to predict the dimensional accuracy of FDM part specimen in terms of % change in length, width and thickness of the specimen.

6.2 Rules generated using Taguchi parameter design from Fuzzy inference system is used to learn the behavior of FDM process.





(7)  Parameter optimization of Rapid prototyping (RP) part subjected to the dynamic loading

Collaborators:

1) Dr. S.S. Mahapatra (Professor and HOD, NIT Rourkela)

2) Dr. Monica Mahesh Savalani (Assistant Professor, Hongkong Polytechnic University, Hongkong)



7.1 Research report highlights the most significant unresolved issues in the field of rapid prototyping (RP).

7.2 The RP fabricated parts are subjected to the dynamic loading and the experimental investigation based on this realistic fact has not been done yet.





(8)  Modelling of FDM Printed hexagonal honeycomb structures for Resin transfer Moulding Applications

Collaborators:

1) Mr. Biranchi Panda