Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 85-92). Also available via the Internet.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 159-165). Also available via the Internet.

Thesis--University of Florida. / Manuscript copy. Vita. Includes bibliographical references (leaves 154-167).

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science, Joannesburg, 2014. / An investigation was performed to look at a method to develop easy to use field survey measurements to assist decision makers in the process of deriving public protective actions. This method could be used at a nuclear power plant if certain accident conditions are known. International values for operational intervention levels (OIL’s) do exist and are recommended to be employed if station specific data has not been derived. No values exist specific to Koeberg Nuclear Power Station and as a result, this became an ideal opportunity to derive station specific values. It was firstly necessary to decide on a specific accident type and hence an applicable accident release fraction. A suitable accident software dispersion code was applied to calculate the organ doses for the selected accident type. It was also decided to use two different wind dispersion criteria to further refine the results. Due to the complexities of dose distribution within the body it was also necessary to look at the gamma dose in isolation as this would be the measurement radiation type utilised as a limit in the field either using installed radiation monitors or by physical measurement performed by station Radiation Protection staff. Comparisons were done with thyroid and lung dose versus gamma dose to arrive at ratios for this specific accident type. This would then be indicative of the total dose to each organ as a result of a single field measurement. Conclusions were drawn on the results obtained and recommendations were made for when this type of data may be suitable for use in the unlikely event of a nuclear accident.

One of the essential duties of the State of California Department of Civil Defense in times of nuclear weapon attack will be radiological monitoring. The workers in this field will operate from a mobile laboratory truck, equipped with radiation counters and meters, but containing only the simplest of chemical equipment. One of their main problems will be the determination of the total amount of radioactive material, especially fallout of fission products, in a water sample. As yet no method of analysis both simple and rapid enough for application to mobile operation has been developed. It was the purpose of this research to develop and refine a simple, rapid, quantitative procedure for the detection and estimation of the total amount of radioactive material contained in a water sample, using only readily available and preferably inexpensive apparatus. However, no attempt has been made to either qualitatively or quantitatively determine any of the possible individual constituents.

A system intended to detect, classify, and track radioactive sources in moving vehicle traffic is under development at Lawrence Livermore National Laboratory (LLNL). This system will fuse information from a network of sensor suites to provide real time tracking of the location of vehicles emitting gamma and/or neutron radiation. This work examined aspects of the source terms of interest and applicable gamma detection technologies for passive detection of emitted gamma radiation. The severe restriction placed on the length of count due to motion of the source is presented. Legitimate gamma sources expected in traffic are discussed. The requirement to accurately classify and discriminate against these "nuisance" sources and cost restraints dictate the choice of NaI(Tl) detectors for this application. The development of a capability to automatically analyze short duration, low signal-to-noise NaI(Tl) spectra collected from vehicles passing a large, stationary detector is reported. The analysis must reliably discriminate between sources commonly transported in motor vehicles and alert on the presence of sources of interest. A library of NaI(Tl) spectra for 33 gamma emitting sources was generated with MCNP4B Monte Carlo modeling. These simulated spectra were used as parent distributions, from which multiple realizations of short duration spectra were sampled. Principal component analysis (PCA) of this data set yielded eigenvectors that enable the conversion of unknown spectra into principal component space (PCS). An algorithm using least squares fitting of the positions of library sources in PCS as basis functions, capable of identifying library nuclides in unidentified spectra, is reported. Analysis results for experimental spectra are compared against those achieved using simulated spectra. A valuable characteristic of this method is its ability to identify sources despite unknown shielding geometries. The successful identification of radionuclides and false identification rates found were excellent for the signal levels involved. For many of the sources, identification performance against experimental spectra was somewhat poorer than found using simulated spectra. The results demonstrate that the PCA-based algorithm is capable of high success rates in identifying sources in short duration, low signal-to-noise NaI(Tl) spectra. / Graduation date: 2001

Thesis (Ph.D)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Hertel, Nolan; Committee Member: Kulp, William David; Committee Member: Lee, Eva; Committee Member: Pagh, Richard; Committee Member: Petrovic, Bojan; Committee Member: Rahnema, Farzad; Committee Member: Smith, Eric; Committee Member: Wang, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.

published_or_final_version / Radioisotope / Master / Master of Philosophy

No description available.

Thesis (M.S.)--University of Nevada, Reno, 2006. / "May, 2006." Includes bibliographical references (leaves 33-35). Online version available on the World Wide Web.