Browsing by Subject "Nuclear engineering"

Now showing 1 - 9 of 9

Advancements to the non-destructive evaluation of strategic components
(2021-12-02) Thompson, Cole Joseph; Charlton, William S.; Clarno, Kevin; Landsberger, Sheldon; Trahan, Alexis; O'Neil, Brian
This dissertation studies the nexus of nuclear engineering, machine learning, and computer vision. This is realized in two ways. The first is through the design of a neutron multiplicity counter and the application of shallow machine learning methods to the multiplicity counter data collected to estimate different parameters with high accuracy. As an extension of this work, other shallow machine learning methods are used to improve the estimation of item leakage multiplication, yielding doubles rate estimates approximately three times better than with traditional methods. The second way is through the application of deep learning models in the form of convolutional neural nets and transformers to the pixel-wise segmentation of welding defects from radiographic images of welds. The results from this application show that a novel transformer network proposed in this work surpasses the performance of other models when compared using a standard candle by at least one percent. All together this work represents a contribution towards leveraging the vast computing and data capabilities of machine learning within nuclear engineering.
Automating X-ray and neutron imaging applications with flexible automation
(2015-12) Hashem, Joseph Anthony; Landsberger, Sheldon; Pryor, Mitchell Wayne; Biegalski, Steven; Schneider, Erich; Janecky, David
This dissertation advances the capability of autonomous manipulation systems for non-destructive testing applications, specifically computed tomography and radiography. Non-destructive testing is the inspection of a part that does not affect its future usefulness. Radiography and tomography technologies are used to detect material faults inaccessible to direct observation. An industrial 7 degree-of-freedom manipulator has been installed in various x-ray and neutron imaging facilities, including the Nuclear Engineering Teaching Laboratory and Los Alamos National Laboratory, for imaging purposes. Inspection of numerous components manually is laborious and time consuming, and there is the risk of high radiation dose to the operator. As Low As Reasonably Achievable exposure can be significantly reduced by installing a robot in an x-ray or neutron imaging facility to perform part placement in the beam for radioactive parts and nuclear facilities. Automation has the additional potential benefit of improving part throughput by obviating the need for human personnel to move or exchange parts to be imaged and allowing for flexible orientation of the imaged object with respect to the x-ray or neutron beam. When the process is fully automated, it eliminates the need for a human to enter the beam area. The robot needs to meet certain performance requirements, including high repeatability, precision, stability, and accuracy. The robotic system must be able to precisely position and align parts, and parts need to be held still while the image is taken. Any movement of the specimen during exposure causes image blurring. Robotics and remote systems are an integral part of the ALARA approach to radiation safety. Robots increase the distance between workers and hazards and reduce time that workers must be exposed. Research performed aims to expand the role of automation at nuclear facilities by reducing the burden on human operators. The robot’s control system must manage collision detection, grasping, and motion planning to reduce the amount of time that an operator spends micro-managing such a system via tele-operation. The subject of this work includes modeling (in MCNP) and measuring flux, dose rates, and DPA rates of neutron imaging facilities to develop predictions of radiation flux, dose profiles, and radiation damage by examining neutron and gamma fields during operation. Dose and flux predictions provide users the means to simulate geometrical and material changes and additions to a facility, thus saving time, money, and energy in determining the optimal setup for the robotic system.
Determination of fission product yields of 235U using gamma ray spectroscopy
(2012-12) Lu, Christopher Hing; Biegalski, Steven R.; Landsberger, Sheldon
It is important to have a method of experimentally calculating fission product yields. Statistical calculations and simulations produce very large uncertainties. Experimental calculations, depending on the methods used, tend to produce lower uncertainties. This work set up a method to calculate fission product yields using gamma ray spectroscopy. In order to produce a method that was theoretically sound, a simulation was set up using OrigenArp to calculate theoretical concentrations of fission products from the irradiation of natural uranium. From these concentrations, the fission product yields were calculated to verify that they would agree with expected values. Moving forward in the work, the total flux at the point of irradiation, in the pneumatic transfer system, was calculated and determined to be 3.9070E+11 ± 6.9570E+10 n/cm^2/s at 100 kW. Once the flux was calculated, the method for calculating fission product yields was implemented and yields were calculated for 10 fission products. The yields calculated were in very good agreement (within 10.04%) with expected values taken from the ENDF-349 library. This method has strong potential in nuclear forensics as it can provide a means for developing a library of experimentally-determined fission product yields, as well as rapid post-nuclear detonation analysis.
Development of a fully automated rapid irradiated sample transport system for neutron activation analysis
(2014-12) Copple, Blake Robert; Biegalski, Steven R.; Landsberger, Sheldon
The need for trace, minor and main element analysis becomes more prevalent each year with an every expanding variety of applications. Neutron Activation Analysis (NAA) is an attractive non-destructive analysis tool that can be utilized on small samples regardless of what physical state the material is in. The analysis process however, typically requires researchers to physically handle a radioactive sample in order to transport the sample to detection systems for data gathering. The purpose of this project was to design a Fully Automated Rapid Irradiated Sample Transit (FARIST) system that could deliver samples into a reactor core and then transfer them to a detector for analysis with zero human interaction. The system would be designed to hold up to 30 samples prior to analysis with the irradiation, decay, and counting times programmed in initially so that once analysis was initiated, no user interaction was required for the next 29 samples. The last requirement of the system was that it supports cyclic NAA. This work discusses the science and history behind NAA as well as the design, construction, installation, and testing of the new FARIST system.
Modeling capture rate changes as a function of hydrogen content in epithermal neutron activation analysis samples using an absorbent polymer
(2020-06-24) McLaughlin, Kevin Ross; Landsberger, Sheldon
Neutron activation analysis measurements are known to be affected by the presence of hydrogen within the sample in question. However, the mechanism of this phenomenon, particularly in epithermal neutron activation analysis, has not been fully studied and quantified. Using MCNP6 models of the University of Texas at Austin epithermal pneumatic tube irradiation location within the Nuclear Engineering Teaching Laboratory’s TRIGA reactor, the effects of the presence of hydrogen in samples are measured. Mixtures of water and sodium acrylate, a polymer with strong water absorption and retention properties, are modeled in varying ratios and densities, creating a distribution of sample materials with varying hydrogen contents. These models provide insight into the neutron capture rate changes that take place within hydrogenous epithermal neutron activation analysis samples. The results show a quadratic relationship between capture rates and hydrogen mass within the samples.
Object recognition and pose estimation for nuclear manipulation in nuclear materials handling applications
(2013-05) O'Neil, Brian Erick; Landsberger, Sheldon; Pryor, Mitchell Wayne
This dissertation advances the capability of autonomous or semiautonomous robotic manipulation systems by providing the tools required to turn depth sensor measurements into a meaningful representation of the objects present in the robot's environment. This process happens in two steps. First, the points from depth imagery are separated into clusters representing individual objects by a Euclidean clustering scheme. Each cluster is then passed to a recognition algorithm that determines what it is, and where it is. This information allows the robot to determine a pose of the object for grasp planning or obstacle avoidance. To accomplish this, the recognition system must extract mathematical representation of each point cluster. To this end, this dissertation presents a new feature descriptor, the Cylindrical Projection Histogram which captures the shape, size, and viewpoint of the object while maintaining invariance to image scale. These features are used to train a classifier which can then determine the label and pose of each cluster identified in a scene. The results are used to inform a probabilistic model of the object, that quantifies uncertainty and allows Bayesian update of the object's label and position. Experimental results on live data show a 97.2% correct recognition rate for a classifier based on the Cylindrical Projection Histogram. This is a significant improvement over another state-of-the art feature that gives an 89.6% recognition rate on the same object set. With statistical filtering over 10 frames, the raw recognition rate improve to 100% and 92.3% respectively. For pose estimation, both features offe rrotational pose estimation performance from 12° to 30°, and pose errors below 1 cm. This work supports deployment of robotic manipulation systems in unstructured glovebox environments in US Department of Energy facilities. The recognition performance of the CPH classifier is adequate for this purpose. The pose estimation performance is sufficient for gross pick-and-place tasks of simple objects, but not sufficient for dexterous manipulation. However, the pose estimation, along with the probabilistic model, support post-recognition pose refinement techniques.
Quantifying the fidelity of a novel methodology for in-core experiment prototyping at the advanced test reactor
(2011-12) Parks, Brian David; Schneider, Erich A.; Deinert, Mark
We have recently developed and tested a new computational method for experiment prototyping at the Advanced Test Reactor (ATR). The method significantly reduces neutronic computation time while maintaining computational accuracy. In this thesis, we present the method and describe the techniques that we used to implement it. We then qualitatively and quantitatively analyze its performance for absorptive and multiplicative experiment perturbations over a single region and across multiple regions of the ATR. We conclude with a discussion of future research that might be conducted on the method.
Three technical challenges facing advanced fuel cycle closure
(2009-12) Van der Hoeven, Christopher Ainslie; Schneider, Erich A.; Biegalski, Steven R.
Many technical hurdles remain to be overcome before an advanced fuel cycle in which minor actinides from spent nuclear fuel are used to generate power. Three such issues were addressed: criticality safety of minor actinides as compared to currently used fissile isotopes; accuracy of evaluated nuclear data for selected minor actinide high energy fission cross-sections; and the preliminary design optimization of a minor actinide burning/breeding fission blanket in a fission fusion hybrid reactor concept. For minor actinide compositions found in spent fuel, current safety measures for actinide solutions were found to be adequate, though concerns may remain for unmoderated transuranic materials. Additionally, computational results indicated a 5-10% error in the fission cross-section of some minor actinides above the fast fission threshold. Finally, a relatively tall annular fission blanket was found to be the most ideal configuration for the UT fission- fusion hybrid reactor concept, satisfying criticality and power output criteria.
Transport of nobel gases under pressure in geological materials
(2021-07-25) Lumpkin, Samantha Katharine; Haas, Derek Anderson, 1981-
This report intends to elucidate the ways in which noble gases transport through geological materials, and how pressure plays a role in this process. The role of sand is explored, and future experiments with salt are discussed. These experiments give an idea of how noble gases would behave if released underground into geological materials which contain these substances. This is of particular interest for nuclear monitoring purposes. Radioisotopes of xenon, krypton and argon are all of interest due to their long half-lives, low background levels and non-reactive nature. We have chosen to test xenon-132, krypton-84, and argon-40 in our experiments. These are stable isotopes of key gases, which closely mimic the behavior of their radioactive counterparts while being cheaper and safer alternatives. Our results examined how pressure affects the transport of noble gases through geological material and delve into troubleshooting with the Gas Chromatography Mass Spectrometer (GCMS). Evidence was found showing equilibrium times at pressure are much longer than anticipated, however we also learned the GCMS was not well suited for high pressure work in its current configuration and did not yield the anticipated results.