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This work presents techniques for characterizing the nuclear and thermal hydraulic performance of liquid-cooled, solid fueled advanced reactors during start-up testing and normal operation. A technique is proposed that uses periodic perturbations to obtain the frequency response characterization of the systems of interest. This characterization provides a description of the dynamic behavior which can then be used for model validation, safety and stability analysis, fault detection, controller design, among other uses.This is done by first reviewing the use of frequency response testing, how tests should be designed, and what information can be obtained from tests. The techniques were then used on a non-nuclear integral effects test facility to characterize the transient heat transfer of the loop for model validation purposes. A new model was developed of the U.C. Berkeley Compact Integral Effects Test primary flow circuit to model the frequency response tests and to study a new frequency domain approach to model validation. The electric heater controls for the facility were updated to utilize simulated reactivity feedback control, allowing for a controlled study of the relationship between the simulated reactivity and heater power using frequency domain techniques. This provides a non-nuclear method for developing techniques that could be used for determining reactor kinetics parameters. Parameters like feedback coefficients and delayed neutron precursor concentrations can be changed easily to study their effects on reactor behavior.While the integral effects test is designed to replicate the behavior of a molten salt cooled reactor, it does not operate at prototypical temperatures, and does not have the added complexity of nuclear fuel. After testing the use of these techniques with the integral effects test, similar techniques are applied to a model of the Molten Salt Reactor Experiment which operated at Oak Ridge National Laboratory from 1965 to 1969. The Molten Salt Reactor Experiment is modeled using the Modelica based modeling library, TRANSFORM. Historical frequency response data were used to validate the model using a frequency domain comparison. From this work, there are several lessons learned that are important to incorporate into the pre-installation testing and testing during initial operation of future advanced reactors. This provides the groundwork for techniques that can be used to characterize the performance of future reactors. This characterization could then be used to validate models of the facility that were used to make the safety case for their licensing. These techniques may also prove to be valuable in detecting changes in the nuclear or thermal hydraulic behavior during operation, as a means by which faults can be detected.

In modern video compression and communication systems, prediction is one of the key schemes to exploit spatial and temporal redundancies. However, current approaches are suboptimal as they do not fully exploit the spatial and temporal correlations within signals. This dissertation focuses on the optimal prediction algorithms that fully utilize the correlations, and the optimal design of predictors that accounts for the rich variety of video statistics as well as the instability due to quantization error propagation in the closed-loop video coding system. Complementary to predictive coding, we also expand the design framework to the general predictive coding system, focusing on the optimal transform design that spatially de-correlates the residual data, leading to better compactness and compression performance.The contributions in this dissertation cover the topics of spatial (intra) prediction, temporal (inter) prediction, the layered prediction in scalable coding and transform design. The contributions have been proposed to or accepted in multiple video coding standardization efforts including the Moving Picture Experts Group (MPEG) and the Alliance for Open Media (AOM), and have provided significant improvements in the video compression performance.

This unit describes the concept and some applications of Map Algebra, in which GIS data layers are used as variables in mathematical expressions. Examples using raster and vector data are presented with many illustrations.