Dr Brendan Harding
Research Associate
Pro Vice-Chancellor (Student Learning)
Division of Academic and Student Engagement
My current research is focused towards understanding how inertial lift force and secondary flow motion interact to cause particles to focus towards different locations within the cross-section of a curved microfluidic duct depending on their size. I'm also interested in iterated function systems and their associated dynamical systems, sparse grid methods for high dimensional approximation, hyperbolic partial differential equations and algorithm based fault tolerance in high performance computing.
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Journals
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Book Chapters
Year Citation 2015 Barnsley, M., & Harding, B. (2015). Three-dimensional fractal homeomorphisms. In M. Frame, & N. Cohen (Eds.), Benoit Mandelbrot A Life in Many Dimensions (pp. 117-142). Singapore: World Scientific Publishing Company Pty. Ltd..
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Conference Papers
Year Citation 2018 Harding, B. (2018). A study of inertial particle focusing in curved microfluidic ducts with large bend radius and low flow rate. In T. Lau, & R. Kelso (Eds.), Proceedings of the 21st Australasian Fluid Mechanics Conference (AFMC 2018) (pp. 1-4). Adelaide, Australia: Australasian Fluid Mechanics Society.
Scopus22016 Harding, T. (2016). Combination technique coefficients via error splittings. In ANZIAM Journal: Proceedings of the 17th Computational Techniques and Applications Conference Vol. 56 (pp. C355-C368). Australian National University, Canberra, Australia: Australian Mathematical Society.
2016 Strazdins, P., Harding, B., Lee, C., Mayo, J., Ray, J., & Armstrong, R. (2016). A robust technique to make a 2D advection solver tolerant to soft faults. In Procedia Computer Science Vol. 80 (pp. 1917-1926). Online: Elsevier.
Scopus22016 Parra Hinojosa, A., Harding, B., Hegland, M., & Bungartz, H. (2016). Handling silent data corruption with the sparse grid combination technique. In Lecture Notes in Computational Science and Engineering Vol. 113 (pp. 165-186). Online: Springer Verlag.
Scopus22016 Hegland, M., Harding, B., Kowitz, C., & Pflüger, D. (2016). Recent developments in the theory and application of the sparse grid combination technique. In Lecture Notes in Computational Science and Engineering Vol. 113 (pp. 143-163). Online: Springer Verlag.
Scopus12016 Harding, B. (2016). Adaptive sparse grids and extrapolation techniques. In Lecture Notes in Computational Science and Engineering Vol. 109 (pp. 79-102). Online: Springer Verlag.
Scopus5 WoS32015 Strazdins, P., Ali, M., & Harding, B. (2015). Highly Scalable Algorithms for the Sparse Grid Combination Technique. In Proceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015 (pp. 941-950). Online: IEEE.
Scopus7 WoS42015 Ali, M., Strazdins, P., Harding, B., Hegland, M., & Larson, J. (2015). A fault-tolerant gyrokinetic plasma application using the sparse grid combination technique. In Proceedings of the 2015 International Conference on High Performance Computing and Simulation, HPCS 2015 (pp. 499-507). Online: IEEE.
Scopus11 WoS72015 de Baar, J., Harding, B., Hegland, M., & Oehmigara, C. (2015). Reduced Basis Model Reduction for Statistical Inverse Problems with applications in Tsunami Modelling. In T. Weber, M. McPhee, & R. Anderssen (Eds.), Proceedings of 21st International Congress on Modelling and Simulation (MODSIM) held jointly with the 23rd National Conference of the Australian-Society-for-Operations-Research / DSTO led Defence Operations Research Symposium (DORS (pp. 112-118). Online: MODELLING & SIMULATION SOC AUSTRALIA & NEW ZEALAND INC. 2014 Harding, B., & Hegland, M. (2014). Robust solutions to PDEs with multiple grids. In Lecture Notes in Computational Science and Engineering. 2nd Workshop on Sparse Grids and Applications, SGA 2012 Vol. 97 (pp. 171-193). Online: Springer.
Scopus52014 Ali, M., Southern, J., Strazdins, P., & Harding, B. (2014). Application level fault recovery: Using fault-tolerant open MPI in a PDE solver. In Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS (pp. 1169-1178). Online: IEEE.
Scopus182014 Barnsley, M., Harding, B., & Rypka, M. (2014). Measure preserving fractal homeomorphisms. In Springer Proceedings in Mathematics and Statistics Vol. 92 (pp. 79-102). Online: Springer.
Scopus12014 Larson, J., Strazdins, P., Hegland, M., Harding, B., Roberts, S., Stals, L., . . . Southern, J. (2014). Managing complexity in the parallel sparse grid combination technique. In Parallel Computing: Accelerating Computational Science and Engineering (CSE) Vol. 25 (pp. 593-602). Amsterdam: IOS Press.
Scopus4 WoS42014 Harding, B., & Hegland, M. (2014). A parallel fault tolerant combination technique. In M. Bader, A. Bode, H. -J. Bungartz, M. Gerndt, G. R. Joubert, & F. Peters (Eds.), Parallel Computing: Accelerating Computational Science and Engineering (CSE) Vol. 25 (pp. 584-592). Amsterdam: IOS Press.
Scopus8 WoS22013 Larson, J., Hegland, M., Harding, B., Roberts, S., Stals, L., Rendell, A., . . . Oishi, Y. (2013). Fault-tolerant grid-based solvers: Combining concepts from sparse grids and MapReduce. In V. Alexandrov, M. Lees, V. Krzhizhanovskaya, J. Dongarra, & P. Sloot (Eds.), Procedia Computer Science Vol. 18 (pp. 130-139). Barcelona, Spain: Elsevier.
Scopus14 WoS142012 Harding, B., & Hegland, M. (2012). A robust combination technique. In ANZIAM Journal Vol. 54.
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