Development of MURR flux trap model for simulation and prediction of sample loading reactivity worth and isotope production

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on September 27, 2007)Vita.Ph. D. University of Missouri--Columbia 2007.University of Missouri Research Reactor (MURR) is the highest power university research reactor in America. It has been supplying various radioisotopes for more than 20 years. The flux trap, locating in the center island tube, has the highest flux for sample irradiating with an ability of 6x1014 n/cm2/s. It is very important for the MURR to be able to predict the reactivity worth of sample loading in the flux trap, as well as the production of specific isotopes. The research develops MURR Flux Trap Model (MFTM) which simulates the reactor core and flux trap area, solves the neutron transport equation and calculates the loading worth based on the Monte Carol method, proceeds with burnup and decay calculation, and predicts the requested isotope production. MCNP part of the MFTM model carries out neutron transport calculations and predicts the reactivity worth of sample loading in the flux trap while MonteBurns part of the model calculates isotope production from the target sample irradiated in the flux trap by solving the general nuclide depletion equation. Different sample loadings and their measurement data have been provided by the MURR for benchmarking the model during the developing period. The discrepancy between the model and the corresponding experimental data has been analyzed. Over-prediction of the negative worth of KCl samples was determined to be the cause of most of the deviation between the model and experimentally measured results.The original MCNP model has been refined with the consideration of the self-shielding effect and burnup effect. The modified model has yielded better predictions approaching the experimental values. The MCNP and MonteBurns models were integrated into an automatic analytic tool with Visual Basic language for efficient usage by the MURR. The automated package has been successfully run on the MURR MCNP Server.Includes bibliographical references

WHEN MODEL MEETS REALITY – A REVIEW OF SPAR LEVEL 2 MODEL AGAINST FUKUSHIMA ACCIDENT

The Standardized Plant Analysis Risk (SPAR) models are a set of probabilistic risk assessment (PRA) models used by the Nuclear Regulatory Commission (NRC) to evaluate the risk of operations at U.S. nuclear power plants and provide inputs to risk informed regulatory process. A small number of SPAR Level 2 models have been developed mostly for feasibility study purpose. They extend the Level 1 models to include containment systems, group plant damage states, and model containment phenomenology and accident progression in containment event trees. A severe earthquake and tsunami hit the eastern coast of Japan in March 2011 and caused significant damages on the reactors in Fukushima Daiichi site. Station blackout (SBO), core damage, containment damage, hydrogen explosion, and intensive radioactivity release, which have been previous analyzed and assumed as postulated accident progression in PRA models, now occurred with various degrees in the multi-units Fukushima Daiichi site. This paper reviews and compares a typical BWR SPAR Level 2 model with the “real” accident progressions and sequences occurred in Fukushima Daiichi Units 1, 2, and 3. It shows that the SPAR Level 2 model is a robust PRA model that could very reasonably describe the accident progression for a real and complicated nuclear accident in the world. On the other hand, the comparison shows that the SPAR model could be enhanced by incorporating some accident characteristics for better representation of severe accident progression

A mechanistic model of a PWR-based nuclear power plant in response to external hazard-induced station blackout accidents

Natural hazard-induced nuclear accidents, such as the Fukushima Daiichi Accident that occurred in Japan in 2011, have significantly increased reactor safety studies in understanding nuclear power plant (NPP) responses to external hazard events such as earthquakes and floods. Natural hazards could cause the loss of offsite power in nuclear power plants, potentially leading to a Station Blackout (SBO) accident that significantly contributes to the overall risk of nuclear power plant accidents. Despite the fact that extensive research has been conducted on the station blackout accident for nuclear power plant, further understanding of these events is needed, particularly in the context of the dynamic nature of external hazards such as external flooding. This paper estimates the progression of station blackout events for a generic pressurized water reactor (PWR) in response to external flooding events. The original RELAP5-3D model of the Westinghouse four-loop design pressurized water reactor was adopted and modified to simulate the external flood-induced station blackout accident, including the short-term and long-term station blackout scenarios. A sensitivity analysis of long-term station blackout, examining reactor operation times and analyzing key parameters over time, was also conducted in this work. The results of the analyses, especially the critical timing parameters of key event sequences, provide useful insights about the time during the external flooding event, which is important for plant operators to make timely decisions to prevent potential core damage. This paper represents significant progress toward developing an integrated risk assessment framework for further identifying and assessing the effects of the critical sources of uncertainties of nuclear power plant under external hazard-induced events

A New Approach to Quantify Level 2 SPAR Models in SAPHIRE 8

The U.S. Nuclear Regulatory Commission’s (USNRC) Standardized Plant Analysis Risk (SPAR) Level 2 models for U.S. commercial nuclear power plants has historically used a partitioning approach for plant damage state (PDS) binning and model quantification since late 1990s [1]. While this approach has the advantage to be able to identify the details of the severe accident sequences with one or more individual PDS vector characters, the Level 2 model quantification process is tedious and error-prone with multiple steps involved. A new approach to quantify Level 2 SPAR models was recently developed and implemented in the latest SAPHIRE Version 8 [2]. The new approach removes the partition rules and greatly simplifies the quantification process

Controlled Helicity of the Rigid-Flexible Molecular Assembly Triggered by Water Addition: From Nanocrystal to Liquid Crystal Gel and Aqueous Nanofibers

Despite recent advances in synthetic nanometer-scale helical assembly, control of supramolecular chirality remains a challenge. Here, we describe the fine-tuning of the shape and morphology transitions of twisted and helical assembly from dumbbell-shaped rigid-flexible amphiphile triggered by concentration. The amphiphile <b>2</b> self-assembles into nonchiral 3D columnar crystals with alternative packing of aromatic segment in solid state. Remarkably, with the addition of water into the solid, the achiral crystal transforms into 2D hexagonally ordered liquid crystal gel with supramolecular chirality due to increased entropy of flexible coil in aqueous environment. Notably, the helical liquid crystal gel was observed to dissolve into optically active aqueous nanofibers caused by a conformational change of hydrophobic aromatic rods and enhanced hydro-volume of the ethylene oxide chains