Global ETD Search

31	Safeguards for Uranium Extraction (UREX) +1a Process Feener, Jessica S. 2010 May 1900 (has links) As nuclear energy grows in the United States and around the world, the expansion of the nuclear fuel cycle is inevitable. All currently deployed commercial reprocessing plants are based on the Plutonium - Uranium Extraction (PUREX) process. However, this process is not implemented in the U.S. for a variety of reasons, one being that it is considered by some as a proliferation risk. The 2001 Nuclear Energy Policy report recommended that the U.S. "develop reprocessing and treatment technologies that are cleaner, more efficient, less waste-intensive, and more proliferation-resistant." The Uranium Extraction (UREX+) reprocessing technique has been developed to reach these goals. However, in order for UREX+ to be considered for commercial implementation, a safeguards approach is needed to show that a commercially sized UREX+ facility can be safeguarded to current international standards. A detailed safeguards approach for a UREX+1a reprocessing facility has been developed. The approach includes the use of nuclear material accountancy (MA), containment and surveillance (C/S) and solution monitoring (SM). Facility information was developed for a hypothesized UREX+1a plant with a throughput of 1000 Metric Tons Heavy Metal (MTHM) per year. Safeguard goals and safeguard measures to be implemented were established. Diversion and acquisition pathways were considered; however, the analysis focuses mainly on diversion paths. The detection systems used in the design have the ability to provide near real-time measurement of special fissionable material in feed, process and product streams. Advanced front-end techniques for the quantification of fissile material in spent nuclear fuel were also considered. The economic and operator costs of these systems were not considered. The analysis shows that the implementation of these techniques result in significant improvements in the ability of the safeguards system to achieve the objective of timely detection of the diversion of a significant quantity of nuclear material from the UREX+1a reprocessing facility and to provide deterrence against such diversion by early detection. nuclear material safeguards UREX UREX+1a Uranium Extraction proliferation resistant proliferation resistance reprocessing PUREX Plutonium Uranium IAEA TMFD Tension Metastable Fluid Detector detection probability nondetection probability non-detection probability nuclear material accountancy containment and surveillance solution monitoring process monitoring false alarm probability real-time measurement material balance area material balance period key measurement point significant quantity timely detection defense in depth detector non-destructive assay NDA front-end measurement material unaccounted for CCD-PEG TRUEX TALSPEAK
32	Evaluation of FMCW Radar Jamming Sensitivity Snihs, Ludvig January 2023 (has links) In this work, the interference sensitivity of an FMCW radar has been evaluated by studying the impact on a simulated detection chain. A commercially available FMCW radar was first characterized and its properties then laid the foundation for a simulation model implemented in Matlab. Different interference methods have been studied and a selection was made based on the results of previous research. One method aims to inject a sufficiently large amount of energy in the form of pulsed noise into the receiver. The second method aims to deceive the radar into seeing targets that do not actually exist by repeating the transmitted signal and thus giving the radar a false picture of its surroundings. The results show that if it is possible to synchronize with the transmitted signal then repeater jamming can be effective in misleading the radar. In one scenario the false target even succeeded in hiding the real target by exploiting the Cell-Averaging CFAR detection algorithm. The results suggests that without some smart countermeasures the radar has no way of distinguishing a coherent repeater signal, but just how successful the repeater is in creating a deceptive environment is highly dependent on the detection algorithm used. Pulsed noise also managed to disrupt the radar and with a sufficiently high pulse repetition frequency the detector could not find any targets despite a simulated object in front of the radar. On the other hand, a rather significant effective radiated power level was required for the pulse train to achieve any meaningful effect on the radar, which may be due to an undersampled signal in the simulation. It is therefore difficult based on this work to draw any conclusions about how suitable pulsed noise is in a non-simulated interference context and what parameter values to use. FMCW FMCW radar radar frequency-modulated radar noise jamming FMCW Jamming Jamming Pulse Train Pulse Jamming Spoofing Attack Spoofing Deception Repeater Jamming Repeater Automotive Radar CFAR sensor jamming constant false alarm rate electronic warfare EW FMCW FMCW radar frekvensmodulerad dopplerradar dopplerradar radar brusstörning radarstörning pulsstörning pulståg falskmål vilseledning repeterstörning bilradar sensorstörning CFAR Annan elektroteknik och elektronik
33	Channel Probing for an Indoor Wireless Communications Channel Hunter, Brandon 13 March 2003 (has links) (PDF) The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of this parameter allows spatial diversity at the transmitter along with the receiver to be simulated. The process of going from raw measurement data to discrete arrivals and then to clustered arrivals is analyzed. Many possible errors associated with discrete arrival processing are discussed along with possible solutions. Four clustering methods are compared and their relative strengths and weaknesses are pointed out. The effects that errors in the clustering process have on parameter estimation and model performance are also simulated. multipath multipath propagation propagation environment indoor propagation indoor multipath indoor multipath propagation channel probing channel probing indoor wireless communications channel indoor wireless communications indoor wireless communications wireless communications wireless communications channel MIMO SISO multiple input multiple output single input single output antenna diversity antenna diversity antenna array channel modeling modeling model wireless propagation clustering methods clustering algorithms clustering parameter estimation parameter channel matrix h matrix ray tracing point spread function psf deconvolution clean algorithm clean algorithm antenna pattern network analyzer temporal pattern 2.4 ghz system 6 ghz system channel capacity capacity estimate channel capacity estimate propagation environment scattering transfer matrix matrix water filling solution water filling method water filling Saleh Valenzuela Saleh and Valenzuela Model arrival time of arrival angle of arrival direction of arrival arrival amplitude arrivals antenna positioner data simulations measurements angle of departure direction of departure correlation convolution errors error CFA CFAD constant false alarm constant false alarm detection signal signal dependent clutter clutter returns transmitter transmit receive receiver transmit antenna receive antenna spatial correlation system PSF system point spread function mapping fuzzy c-means clustering fuzzy clustering c-means clustering c-means fuzzy k-means euclidean distance time amplitude delay performance prediction performance prediction errors fuzzy weighted distance method rectangular method weighted rectangular method statistics statistical statistical model Electrical and Computer Engineering

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