student profile: Mr Aditya Vishwanathan


Map

Thesis work

Thesis title: Transient Topology and Shape Optimization Problems using Evolutionary Algorithms

Supervisors: Gareth VIO , Dries VERSTRAETE

Selected publications

Download citations: PDF RTF Endnote

Journals

  • Vishwanathan, A., Vio, G. (2019). Efficient quantification of material uncertainties in reliability-based topology optimization using random matrices [Forthcoming]. Computer Methods in Applied Mechanics and Engineering, 351, 5478-570. [More Information]
  • Vishwanathan, A., Vio, G. (2019). Numerical and experimental assessment of random matrix theory to quantify uncertainty in aerospace structures. Mechanical Systems and Signal Processing, 118, 408-422. [More Information]

Conferences

  • Vishwanathan, A., Munk, D., Vio, G. (2019). Experimental and Parametric Study on Uncertainty Quantification within Topology Optimization utilizing Non-Intrusive Polynomial Chaos Theory. 2019 AIAA Scitech Forum, Reston, VA,: American Institute of Aeronautics and Astronautics (AIAA).
  • Vishwanathan, A., Vio, G. (2018). Experimental application of random matrix theory to quantify modal uncertainty in aircraft t-tails. 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018, Leuven: KU Leuven - Departement Werktuigkunde.
  • Vishwanathan, A., Vio, G. (2018). On the efficacy of random matrix theory to quantify uncertainty in topology optimisation. 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018, Leuven: KU Leuven - Departement Werktuigkunde.
  • Vishwanathan, A., Munk, D., Vio, G. (2017). Frequency Response Characteristics of 2D Wings in Uncertain Environments: A Random Matrix Theory Approach. 12th World Congress of Structural and Multidisciplinary Optimisation (ISSMO), Cham: Springer. [More Information]
  • Vishwanathan, A., Cheema, P., Vio, G. (2017). Multiple-Particle Swarm Optimization used to study material degradation in aeroelastic composites including probabalistic uncertainties. IEEE Congress on Evolutionary Computation 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2019

  • Vishwanathan, A., Vio, G. (2019). Efficient quantification of material uncertainties in reliability-based topology optimization using random matrices [Forthcoming]. Computer Methods in Applied Mechanics and Engineering, 351, 5478-570. [More Information]
  • Vishwanathan, A., Munk, D., Vio, G. (2019). Experimental and Parametric Study on Uncertainty Quantification within Topology Optimization utilizing Non-Intrusive Polynomial Chaos Theory. 2019 AIAA Scitech Forum, Reston, VA,: American Institute of Aeronautics and Astronautics (AIAA).
  • Vishwanathan, A., Vio, G. (2019). Numerical and experimental assessment of random matrix theory to quantify uncertainty in aerospace structures. Mechanical Systems and Signal Processing, 118, 408-422. [More Information]

2018

  • Vishwanathan, A., Vio, G. (2018). Experimental application of random matrix theory to quantify modal uncertainty in aircraft t-tails. 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018, Leuven: KU Leuven - Departement Werktuigkunde.
  • Vishwanathan, A., Vio, G. (2018). On the efficacy of random matrix theory to quantify uncertainty in topology optimisation. 28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018, Leuven: KU Leuven - Departement Werktuigkunde.

2017

  • Vishwanathan, A., Munk, D., Vio, G. (2017). Frequency Response Characteristics of 2D Wings in Uncertain Environments: A Random Matrix Theory Approach. 12th World Congress of Structural and Multidisciplinary Optimisation (ISSMO), Cham: Springer. [More Information]
  • Vishwanathan, A., Cheema, P., Vio, G. (2017). Multiple-Particle Swarm Optimization used to study material degradation in aeroelastic composites including probabalistic uncertainties. IEEE Congress on Evolutionary Computation 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.