Six radiation dosimetry and medical physics problems were analyzed using a beta version of MCNP 5 as part of an international intercomparison of radiation dosimetry computer codes, sponsored by the European Commission committee on the quality assurance of computational tools in radiation dosimetry. Results have been submitted to the committee, which will perform the inter-code comparison and publish the results independently. A comparison of the beta version of MCNP 5 with MCNP 4C2 is made, as well as a comparison of the new Doppler broadening feature. Comparisons are also made between the *F8 and F6 tallies, neutron tally results with and without the use of the S(a,b) cross sections, and analytically derived peak positions with pulse height distributions of a Ge detector obtained using the beta version of MCNP 5. The following problems from the study were examined: Problem 1 was modeled to determine the near-field angular anisotropy and dose distribution from a high dose rate 192Ir brachytherapy source in a surrounding spherical water phantom. Problem 2 was modeled to find radial and axial dose in an artery wall from an intravascular brachytherapy 32P source. Problem 4 was modeled to investigate the response of a four-element TLD-albedo personal dosimeter from neutrons and/or photons. Significant differences in neutron response with S(a,b) cross sections compared to results without these cross sections were found. Problem 5 was modeled to obtain air kerma backscatter profiles for 150 and 200 kVp X-rays upon a water phantom. Air kerma backscatter profiles were determined along the apothem and diagonal of the front face of the phantom. A comparison of experimental results is also made. Problem 6 was modeled to determine indirect spectral and energy fluences upon two neutron detectors within a calibration bunker. The largest indirect contribution was found to come from low energy neutrons with an average angle of 47o where 0o is a plane parallel to the floor. Problem 7 was modeled to obtain pulse height distributions for a germanium detector. Comparison of analytically derived peaks with peak positions in the spectra are made. An examination of the Doppler broadening feature is also included.

Modeling and understanding the doses around the neutron generator provides insightful data in regard to radiation safety and protection precautions. Published data can be used to predict doses, but realistic data for the Nuclear Engineering Teaching Laboratory’s Thermo MP 320 Neutron Generator helps health physicists more accurately predict dose rates and protect experimenters against exposure. The goal was to create a model inclusive of the entire setup and room where the neutron generator is housed. Monte Carlo N-Particle (MCNP) Code reigns as the preferred method for modeling radiation transport and was utilized to model the transport of neutrons within the current configuration of the 14 MeV neutron generator facility. This model took into account all shielding materials and their respective dimensions and locations within the concrete room. By utilizing tallies and tally modifiers, the model predicts dose rates that can be used with experimental factors such as irradiation time and flux to predict a dose in millirem. Validation experiments were performed in the current setup using Landauer Luxel®+ with Neutrak dosimeters placed in strategic locations to record the neutron dose vi received as well as a Ludlum Model 42-41 PRESCILA neutron probe to predict dose rates. The dosimeters and PRESCILA measurement locations matched the positions of the point detector tallies in MCNP. After laboratory analysis, a comparison was performed between the model output and the dosimeter and PRESCILA values to successfully validate the accuracy of the model. / text

Radioactive sources used in brachytherapy must be dosimetrically characterized prior to clinical use as defined the TG-43 protocol. In our previous project, Gafchromic film dosimetry was used to experimentally obtain the anisotropy function for an M-19 iridium-192 brachytherapy seed being developed by Source Production Equipment Corp (St. Rose, LA). In this project, the Monte Carlo N-Particle Transport code (MCNP) was used to computationally obtain the full set of TG-43 parameters including the Dose Rate Constant, the Reference Dose Rate, the Radial Dose Function, and the Anisotropy Constant for the M-19 seed.

The objectives of this thesis were the validation of G4STORK to use it for the investigation of the SCWR lattice cell. MCNP6 was chosen as the program that the methodology of G4STORK would be validated against. Over multiple steps, the methodology of G4STORK was matched to that of MCNP6 (described here, 3.4). After each step, the output of the two programs were compared, allowing us to pinpoint why and where discrepancies came about. At the end of this process, we were able to show that when G4STORK used the same assumptions as MCNP6, it produced similar results (shown here, 4.1.4). The results of G4STORK simulating the SCWR lattice cell, using its more accurate default methodology, was then compared to those of MCNP6 (shown here, 4.2.1). Large differences in the results were seen to occur, because of the inaccurate assumptions used by MCNP6, during transient cases. We concluded that despite the existence of minor discrepancies between the results of MCNP and G4STORK for some cases, G4STORK is still the theoretically more accurate method for simulating lattice cell cases such as these, due to MCNP’s use of the generational method. / Thesis / Master of Applied Science (MASc)

This research uses an existing innovative fuel design (IFD) that has intrinsic safety features and enhanced economics over the current uranium dioxide (UO2) light water fuel design and evaluates promising methods to improve the waste management and proliferation resistance of the IFD by doping the fresh fuel with select actinides.The most robust approach for proliferation resistance is to denature these materials by adding a uranium or plutonium isotope that hampers the usability of the materials in weapons. The proposed modifications to the IFD use this approach through elevated fractions of 238Pu. 238Pu generates large quantities of heat and neutrons through its radioactive decay and is estimated to make plutonium potentially “proliferation-proof." The IFD this work uses as a foundation is an advanced metallic fuel designed for use in current light water reactors. Due to the high fission density of metallic fuel and the proposed uranium enrichments, the plutonium produced by irradiating this fuel has promising isotopic content for proliferation resistance. This proliferation resistance will be further increased by adding 237Np and/or 241Am to the initial fresh fuel composition that will result in increased 238Pu content. Adding these actinides into the fresh fuel at 0.2 wt.%, the amount of 238Pu produced in the used fuel can be used for proliferation resistance. Increasing the actinide wt.% can potentially produce "proliferation-proof" used fuel. Also, by utilizing neptunium and americium in fresh fuel, many of the challenges with permanent geological disposal of used fuel can be mitigated.

<p>In order to monitor a nuclear boiling water reactor fixed and movable detectors are used, such as the neutron sensitive LPRM (Local Power Range Monitors) detectors and the gamma sensitive TIP (Traversing Incore Probe) detectors. These provide a mean to verify the predictions obtained from core simulators, which are used for planning and following up the reactor operation. The core simulators calculate e.g. the neutron flux and power distribution in the reactor core. The simulators can also simulate the response in the LPRM and TIP detectors. By comparing with measurements the accuracy of the core simulators can be quantified. The core simulators used in this work are PHOENIX4 and POLCA7. Because of the complexity of the calculations, each fuel assembly is divided axially into typically 25 nodes, which are more or less cubic with a side length of about 15 cm. Each axial segment is simulated using a 2D core simulator, in this work PHOENIX4, which provides data to the 3D code, in this case POLCA7, which in turn perform calculations for the whole core. The core simulators currently use both radial pin weights and axial node weights to calculate the gamma TIP detector signal. A need to bring forward new weight factors has now been identified because of the introduction of new fuel designs. Therefore, the gamma TIP detector response has been simulated using a Monte Carlo code called MCNPX for a modern fuel type, SVEA-96 Optima2, which is manufactured by Westinghouse. The new weights showed some significant differences compared to the old weights, which seem to overestimate the radial weight of the closest fuel pins and the axial weight of the node in front of the detector. The new weights were also implemented and tested in the core simulators, but no significant differences could be seen when comparing the simulated detector response using new and old weights to authentic TIP measurements.</p>

Using the computer code Monte Carlo N-Particle (MCNP), doses were calculated for organs of interest such as the large intestine, urinary bladder, testes, and kidneys while patients were undergoing prostate brachytherapy. This research is important because the doses delivered to the prostate are extremely high and the organs near the prostate are potentially at risk for receiving high doses of radiation, leading to increased probabilities of adverse health effects such as cancer. In this research, two MCNP version 4C codes were used to calculate the imparted energies to the organs of interest delivered by 125I and 103Pd. As expected, the organs nearest to the prostate received the highest energy depositions and the organs farthest from the prostate received the lowest energy depositions. Once the energy depositions were calculated, the doses to the organs were calculated using the known volumes and densities of the organs. Finally, the doses to the organs over an infinite time period were calculated.

In order to monitor a nuclear boiling water reactor fixed and movable detectors are used, such as the neutron sensitive LPRM (Local Power Range Monitors) detectors and the gamma sensitive TIP (Traversing Incore Probe) detectors. These provide a mean to verify the predictions obtained from core simulators, which are used for planning and following up the reactor operation. The core simulators calculate e.g. the neutron flux and power distribution in the reactor core. The simulators can also simulate the response in the LPRM and TIP detectors. By comparing with measurements the accuracy of the core simulators can be quantified. The core simulators used in this work are PHOENIX4 and POLCA7. Because of the complexity of the calculations, each fuel assembly is divided axially into typically 25 nodes, which are more or less cubic with a side length of about 15 cm. Each axial segment is simulated using a 2D core simulator, in this work PHOENIX4, which provides data to the 3D code, in this case POLCA7, which in turn perform calculations for the whole core. The core simulators currently use both radial pin weights and axial node weights to calculate the gamma TIP detector signal. A need to bring forward new weight factors has now been identified because of the introduction of new fuel designs. Therefore, the gamma TIP detector response has been simulated using a Monte Carlo code called MCNPX for a modern fuel type, SVEA-96 Optima2, which is manufactured by Westinghouse. The new weights showed some significant differences compared to the old weights, which seem to overestimate the radial weight of the closest fuel pins and the axial weight of the node in front of the detector. The new weights were also implemented and tested in the core simulators, but no significant differences could be seen when comparing the simulated detector response using new and old weights to authentic TIP measurements.

A special work evolution was performed at Los Alamos National Laboratory (LANL) with a particular 73As/74As source but the worker’s extremity dosimeter did not appear to provide appropriate dosimetric information for the tasks performed. This prompted a reconstruction of the dose to the worker’s hands. The computer code MCNP was chosen to model the tasks that the worker performed to evaluate the potential nonuniform hand dose distribution. A model was constructed similar to the worker’s hands to represent the performed handling tasks. The model included the thumb, index finger, middle finger, and the palm. The dose was calculated at the 7 mg cm-2 skin depth. To comply with the Code of Federal Regulations, 10 CFR 835, the 100 cm2 area that received the highest dose must be calculated. It could be determined if the dose received by the worker exceeded any regulatory limit. The computer code VARSKIN was also used to provide results to compare with those from MCNP where applicable. The results from the MCNP calculations showed that the dose to the worker’s hands did not exceed the regulatory limit of 0.5 Sv (50 rem). The equivalent nonuniform dose was 0.126 Sv (12.6 rem) to the right hand and 0.082 Sv (8.2 rem) to the left hand.

The rising desire for individualized medical physics models has sparked a transition from the use of tangible phantoms toward the employment of computational software for medical physics applications. One such computational software for radiation transport modeling is the Monte Carlo N-Particle (MCNP) radiation transport code. However, no comprehensive document has been written to introduce the use of the MCNP code for simulating medical physics applications. This document, a primer, addresses this need by leading the medical physics user through the basic use of MCNP and its particular application to the medical physics field. This primer is designed to teach by example, with the aim that each example will illustrate a practical use of particular features in MCNP that are useful in medical physics applications. These examples along with the instructions for reproducing them are the results of this thesis research. These results include simulations of: dose from Tc-99m diagnostic therapy, calculation of Medical Internal Radiation Dose (MIRD) specific absorbed fraction (SAF) values using the ORNL MIRD phantom, x-ray phototherapy effectiveness, prostate brachytherapy lifetime dose calculations, and a radiograph of the head using the Zubal head phantom. Also included are a set of appendices that include useful reference data, code syntax, and a database of input decks including the examples in the primer. The sections in conjunction with the appendices should provide a foundation of knowledge regarding the MCNP commands and their uses as well as enable users to utilize the MCNP manual effectively for situations not specifically addressed by the primer.