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Application of multi-core and cluster computing to the Transmission Line Matrix method

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posted on 23.06.2014, 15:38 by Daniel R. Browne
The Transmission Line Matrix (TLM) method is an existing and established mathematical method for conducting computational electromagnetic (CEM) simulations. TLM models Maxwell s equations by discretising the contiguous nature of an environment and its contents into individual small-scale elements and it is a computationally intensive process. This thesis focusses on parallel processing optimisations to the TLM method when considering the opposing ends of the contemporary computing hardware spectrum, namely large-scale computing systems versus small-scale mobile computing devices. Theoretical aspects covered in this thesis are: The historical development and derivation of the TLM method. A discrete random variable (DRV) for rain-drop diameter,allowing generation of a rain-field with raindrops adhering to a Gaussian size distribution, as a case study for a 3-D TLM implementation. Investigations into parallel computing strategies for accelerating TLM on large and small-scale computing platforms. Implementation aspects covered in this thesis are: A script for modelling rain-fields using free-to-use modelling software. The first known implementation of 2-D TLM on mobile computing devices. A 3-D TLM implementation designed for simulating the effects of rain-fields on extremely high frequency (EHF) band signals. By optimising both TLM solver implementations for their respective platforms, new opportunities present themselves. Rain-field simulations containing individual rain-drop geometry can be simulated, which was previously impractical due to the lengthy computation times required. Also, computationally time-intensive methods such as TLM were previously impractical on mobile computing devices. Contemporary hardware features on these devices now provide the opportunity for CEM simulations at speeds that are acceptable to end users, as well as providing a new avenue for educating relevant user cohorts via dynamic presentations of EM phenomena.





  • Mechanical, Electrical and Manufacturing Engineering


© Daniel R. Browne

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A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.

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