<p dir="ltr">There is a growing need to reconstruct high quality tomographic images from sparse view measurements to accommodate time and space constraints as well as patient well-being in medical CT. Analytical methods perform poorly with sub-Nyquist acquisition rates. In extreme cases with 4 or fewer views, effective reconstruction approaches must be able to incorporate side information to constrain the solution space of an otherwise under-determined problem. This thesis presents two sparse view tomography problems that are solved using techniques that exploit. knowledge of the structural and physical properties of the scanned objects.</p><p dir="ltr"><br></p><p dir="ltr">First, we reconstruct four view CT datasets obtained from an in-situ imaging system used to observe Kolsky bar impact experiments. Test subjects are typically 3D-printed out ofhomogeneous materials into shapes with circular cross sections. Two advanced prior modelsare formulated to incorporate these assumptions in a modular fashion into the iterativeradiographic inversion framework. The first is a Multi-Slice Fusion and the latter is TotalVariation regularization that operates in cylindrical coordinates.</p><p dir="ltr"><br></p><p dir="ltr">In the second problem, artificial neural networks (NN) are used to directly invert a temporal sequence of four radiographic images of discontinuities propagating through an imploding steel shell. The NN is fed the radiographic features that are robust to scatter and is trained using density simulations synthesized as solutions to hydrodynamic equations of state. The proposed reconstruction pipeline learns and enforces physics-based assumptions of hydrodynamics and shock physics to constrain the final reconstruction to a space ofphysically admissible solutions.</p>

Power electronics applications in high power are normally large, expensive, spatially distributed systems. These systems are typically complex and have multiple functions. Due to these properties, the control algorithm and its implementation are challenging, and a different approach is needed to avoid customized solutions to every application while still having reliable sensor measurements and converter communication and control. This thesis proposes a synchronous digital control architecture that allows for the communication and control of devices via a fiber optic communication ring using digital technology. The proposed control architecture is a multidisciplinary approach consisting of concepts from several areas of electrical engineering. A review of the state of the art is presented in Chapter 2 in the areas of power electronics, fieldbus control networks, and digital design. A universal controller is proposed as a solution to the hardware independent control of these converters. Chapter 3 discusses how the controller was specified, designed, implemented, and tested. The power level specific hardware is implemented in modules referred to as hardware managers. A design for a hardware manager was previously implemented and tested. Based on these results and experiences, an improved hardware manager is specified in Chapter 4. A fault tolerant communication protocol is specified in Chapter 5. This protocol is an improvement on a previous version of the protocol, adding benefits of improved synchronization, multimaster support, fault tolerant structure with support for hot-swapping, live insertion and removals, a variable ring structure, and a new network based clock concept for greater flexibility and control. Chapter 6 provides a system demonstration, verifying the components work in configurations involving combinations of controllers and hardware managers to form applications. Chapter 7 is the conclusion. VHDL code is included for the controller, the hardware manager, and the protocol. Schematics and manufacturing specifications are included for the controller. / Master of Science