Andrew Seagar’s research while affiliated with Griffith University and other places

Hydrologists delineate surface water path (SWP) from digital elevation model (DEM) images to gain insights into catchment characteristics. Currently, high-resolution DEM can be obtained to improve the SWP delineation accuracy. It was found that accuracy is still the same for the popular existing grid-based algorithms, but is much higher for the physically-based and contour-based algorithms. Unfortunately, the contour-based algorithms suffer complexity at high resolution. Accordingly, we develop the algorithm to decrease the error with high-resolution DEMs by enhancing an existing contour-based algorithm, constructed with a physically-based concept, derived from the semi-analytical solution of Laplace’s partial differential equation through the boundary element method (BEM). To reduce the complexity, we propose the framework integrating the enhanced algorithm with pre-processing that reduces the input data size from very long contours by transforming those contours into the closed paths, exploited by the enhanced algorithm to delineate SWPs with numerical BEM-based solution. The results show the framework’s ability to successfully delineate the forward SWPs from hilltops to reservoirs over a real-world large-terrain DEM image and to depict the drainage networks flowing into real rivers. Analyzing the catchment boundary at the outlet along the real river, the framework successfully delineates the reverse SWPs from the outlet to hilltops and accurately demarcates the catchment boundary, consistent with the results from a popular GIS software. These findings indicate that the framework can reduce the complexity of the physically-based and contour-based algorithm in delineating the SWPs over a real-world large-terrain DEM image while maintaining robustness in problematic regions.

This paper presents a novel structure of Integrated SiC MOSFETs with a high-frequency transformer (I-SiC-HFT) for various high-power isolated DC–DC converters. Several resonant converters are considered for integration in this paper, including the phase-shift full-bridge (PSFB) converter, inductor–inductor–capacitor (LLC) resonant converter, bidirectional PSFB converter, and capacitor–inductor–inductor–capacitor (CLLC) resonant converter. The applications of I-SiC-HFT are focused on V2G EV battery charging systems, energy storage in DC and AC microgrids, and renewable energy systems. SiC devices, including MOSFETs, Schottky diodes, and MOSFET modules, are used in this novel structure of I-SiC-HFT. The high-frequency magnetic structure uses distributed ferrite cores to form a large central space to accommodate SiC devices. The optimized architecture of I-SiC-HFT and heatsink structure is proposed for thermal management of SiC devices. To prove the concept, a small-scale 1.5 kW prototype I-SiC-HFT is used to demonstrate the basic structure and various performance indicators through the FEM based electromagnetic simulation and DC–DC converter experiments.

Hydrologists usually gain insights into topographic variability by using a high-performance algorithm to estimate the catchment area from a digital elevation model (DEM) image. In the literature, the grid-based algorithms are more popular than the contour-based algorithms; however, the existing ones cannot reduce the error when higher resolution DEM is available. This paper introduces a new contour-based algorithm, formulated with the physically-based concept, to estimate catchment from contour-based DEM data. The formulation was derived from the semi-analytical solution of Laplace’s partial differential equation based on the boundary element method (BEM). With this approach, the algorithm can estimate the catchment area along the smooth surface water paths (SWPs), which are delineated from the physically-based algorithm in [1]. The proposed algorithm was validated with the standard synthetic surfaces, where the theoretical specific catchment areas (SCAs) for error assessment are exactly known. When estimating the SCAs with ordinary resolution, the average error of the estimated SCAs is between 14.19 and 2.32%, but the average error from the popular grid-based algorithms is between 77.8 and 17.0 %. With higher resolutions, between 12.5 and 0.88 meters, the proposed algorithm significantly reduces the average error from 15 to 0.8%.

This paper presents a novel and compact structure which integrates silicon-carbide (SiC) Schottky diodes with a high-frequency (HF) transformer. A prototype HF transformer in the shape that is similar to a torus is designed for the integration with SiC Schottky diodes. The modular-based unique structure of the HF transformer can be designed and optimised for integration with various SiC devices. SiC devices integrated within an HF transformer with the proposed structure would reduce the volume of a power converter and in turn to reduce the volume of the system to which it is applied. The three-dimensional (3-D) finite element method (FEM) simulation technique is used to design and analyse the magnetic structure of HF transformer taking into account the space for SiC devices. The experimental results including the HF transformer itself and SiC Schottky diodes integrated with the transformer are presented.

This paper presents a novel and compact structure which integrates silicon-carbide (SiC) Schottky diodes within a high-frequency transformer (HFT). The proposed structure would reduce the volume of a power converter and in turn the system to which it is applied. It would also greatly reduce the leakage inductances of an HFT as well as the inductive electromagnetic interference (EMI) to surrounding components and devices. A prototype HFT shaped much like a torus is designed for integration with SiC Schottky diodes. The three-dimensional (3D) finite element method (FEM) simulation technique is used to design and analyze the magnetic structure of the HFT including the space reserved for the SiC Schottky diodes. Experimental results are presented for both the HFT as a separate component and as a system integrated with SiC Schottky diodes.

It is well-known that the delineated surface water paths (SWP) from a DEM image are essential in hydrology. Both grid-based and contour-based algorithms were proposed in the literature to improve the delineated SWP position’s accuracy. Compared to the grid-based algorithm, the contour-based algorithms usually give more accurate results but require higher computation resources, especially in case of the wide catchment. This paper introduces a new contour-based algorithm which is formulated with the semi-analytical solution of Laplace’s partial differential equation with boundary element method. This approach allows the algorithm to determine the SWP in any direction in order to keep the delineated SWP smooth. The proposed algorithm was validated with the standard synthetic surfaces, where theoretical SWPs are known for accuracy evaluation. The obtained SWPs are more accurate than that of the popular grid-based algorithms. Moreover, the proposed algorithm requires less computation resources when considering very long contour lines. In experimentation with a real DEM image, all delineated SWPs are absolute (no broken part) when the contour interval is equal to or less than 20 meters, and the spacing between adjacent discrete elevation data is 20 meters or narrower. This algorithm helps the hydrologists estimate the catchment area, which is useful for water management in flood and drought prevention.

Solving boundary value problems with boundary element methods requires specific Green functions suited to the boundary conditions of the problem. Using vector algebra, one often needs to use a Green function for the Helmholtz equation whereas it is a solution of the perturbed Dirac equation that is required for solving electromagnetic problems using Clifford algebra. A wealth of different Green functions of the Helmholtz equation are already documented in the literature. However, perturbed Dirac equation is only solved for the generic case and only its fundamental solution is reported. In this paper, we present a simple framework to use known Green functions of Helmholtz equation to construct the corresponding Green functions of perturbed Dirac equation which are essential in finding the appropriate kernels for integral equations of electromagnetic problems. The procedure is further demonstrated in a few examples.

The relationship between Maxwell’s equations and the wave equation is exploited to show how problems involving the latter can be converted from a second order differential equation into one of the first order. As an immediate consequence it becomes possible to solve the wave equation without resorting to double differentiation or integration. An example of application is given utilising the Maxwellian equations to solve both an electromagnetic and an equivalent acoustic wave problem.