Nuclear Engineering and Radiological Sciences 2022 SURE and SROP Research Projects

NERS Project #1: Radiation Detection Methods for Photon Active Interrogation
Faculty Mentor: Sara Pozzi, pozzisa@umich.edu
Graduate Student Mentor:  Chris Meert, cmeert@umich.edu
Prerequisites: Ability to work independently, inquisitive/questioning attitude. Programming experience (e.g., matlab, python, C++) is preferred
Project Description:  Photon active interrogation techniques improve detection capabilities for shielded special nuclear material (SNM), such as highly enriched uranium. Photon active interrogation can improve detection capabilities because an intense, high-energy photon beam can penetrate shielding materials and induce photonuclear reactions in SNM, greatly increasing radiation emissions. The University of Michigan is developing economical photon active interrogation techniques for homeland security applications using a 9-MeV linear accelerator (linac), and new detection technologies. Students will participate in experiments, develop simulations, analyze data, and learn underlying nuclear engineering concepts.
Research Mode: Hybrid 

NERS Project #2: Neutron Multiplicity Counting for Nuclear Nonproliferation and Safeguards
Faculty Mentor: Sara Pozzi, pozzisa@umich.edu
Graduate Student Mentor:  Flynn Darby, fdarby@umich.edu
Prerequisites: Willingness to learn, experience with coding (MATLAB, Python, or C++) is a bonus
Project Description:  Quantities of special nuclear material (SNM) must be accounted for and verified to prevent State diversion of SNM from civilian to clandestine uses and to prevent loss to terrorist organizations.  Because SNM is typically surrounded by shielding and portions could be replaced by other material, simply weighing samples is insufficient.  Instead, nondestructive assays based on correlated signatures from the SNM are used.  SNM undergoes fission and emits neutrons.  The number or multiplicity of neutrons is random; however, the multiplicity of emitted neutrons follows a distribution over many fissions.  The distribution is unique to each isotope and the rate of the detected multiplicities can be used to calculate the mass of a sample.  In this project, students will work with radiation, perform data analysis, and write simulations.  Students will have the opportunity to analyze data taken from large samples of uranium, plutonium, and neptunium.
Research Mode: Hybrid  

NERS Project #3: Neutron and Gamma-Ray Imaging using Augmented Reality
Faculty Mentor: Sara Pozzi, pozzisa@umich.edu
Graduate Student Mentor: Ricardo Lopez, rlopezle@umich.edu
Prerequisites: Willingness to learn, experience with coding (MATLAB, Python, or C++) is a bonus
Project Description: Radiation imaging systems are used to locate sources in applications such as nuclear nonproliferation, nuclear safeguards, and emergency response. Our handheld dual particle imaging system combines organic and inorganic scintillation detectors with arrays of silicon photomultipliers into a detection system capable of detecting and imaging source of neutrons and gamma rays. This system is compact and produces images and energy spectra of radiation sources in its field of view. In order to improve the interface for future operators, we are developing an augmented reality output to display the radiation images on a real-world overlay. The current version of the system interfaces with the Microsoft HoloLens platform for augmented reality display of pre-acquired radiation imaging data. Students will have the opportunity to collect radiation detection data and develop an improved augmented reality interface to display the results.
Research Mode: Hybrid

NERS Project #4: Investigation of Filament-induced Breakdown Spectroscopy for Remote Sensing
Faculty Mentor: Igor Jovanovic, ijov@umich.edu
Prerequisites: NERS 311
Project Description: Nonlinear propagation of high-power ultrafast laser pulses offers unique opportunities for remote sensing. Filamentation has been shown to extend the propagation distance of energetic femtosecond laser pulses to distances on the order of 1 km. A powerful tool for long-range detection such as filament-induced breakdown spectroscopy (FIBS) has applications in protecting the public from environmental radiation, nuclear accident plume reconstruction, and nuclear weapons treaty verification. This project seeks to understand the underlying physics and determine the experimental conditions that favor the most efficient filament-solid coupling while optimizing emission signals in unique environments. Students will assist with laboratory measurements and analysis of FIBS signals to infer thermodynamic parameters such as excitation temperature and electron density.
Research Mode: In Lab

NERS Project #5: Laser-induced Breakdown Spectroscopy Analysis of Powders
Faculty Mentor: Igor Jovanovic, ijov@umich.edu
Prerequisites: NERS 311
Project Description: Laser-induced breakdown spectroscopy (LIBS) uses laser pulses to excite a microplasma from the material of interest which then emits material-specific light spectrum upon electronic and molecular de-excitation. While this technique has been demonstrated successfully for samples across various states of matter, several difficulties are associated with measuring powders such as particle ejection and turbulent mixing of separate elements within the powder. This project aims to use plasma imaging and spectroscopy measurements to study the underlying physics of laser interactions with powders which may reveal methods which can improve LIBS sensitivity. The student will be involved with setting up and operating an experimental configuration that can support high-fidelity LIBS measurements with powders as well as with processing of data obtained. During this project, the student will  gain familiarity with the basic optics and spectroscopy theory relevant to LIBS experimentation.
Research Mode: In lab

NERS Project #6: Delayed Neutron Spectral Signatures for the Measurement of K-effective
Faculty Mentor: Igor Jovanovic, ijov@umich.edu
Prerequisites: NERS 315, some coding/data analysis experience.
Project Description: Detection of the multiplication of neutrons is highly indicative of significant quantities of special nuclear material (SNM), but is difficult to accomplish and quantify when an external source of neutrons is used. When SNM is actively interrogated with high-energy neutrons and undergoes fission, a small fraction of the fission neutrons are delayed, as they are emitted in the radioactive decay of several fission fragments. These neutrons have a distinct, lower energy spectrum from fission neutrons, additionally, in multiplying assemblies, they can induce additional fission. Therefore, the ratio of primary delayed neutrons to secondary fission neutrons is indicative of the multiplication of the assembly, k-effective. A novel He-4 scintillation detector is more sensitive to neutrons in the 200-1000 keV range than traditional PSD-capable organic scintillators, and can be used to measure this ratio of low- to high-energy neutrons. The student will prepare simulations to characterize the detector response to delayed neutrons emitted in assemblies of various multiplication, and perform experiments with the He-4 detector using a range of neutron sources to validate their simulations.
Research Mode: Hybrid or fully in-lab. Experiments will be performed in lab, computational work can be done on campus or remote.

NERS Project #7: Nuclear Microreactor Control System Modelling with Machine Learning
Faculty Mentor: Brendan Kochunas, bkochuna@umich.edu
Prerequisites: basic Python programming experience, linear algebra math course, basic knowledge of statistics (normal distribution, mean, variance, correlation)
Project Description: Nuclear microreactors are an innovation in the nuclear engineering field which features small-scale designs for electricity generation. These reactors often have unconventional strategies for operation which lead to opportunities for innovation. In this project, existing large-cost calculation methods for modeling reactor control systems will be made to run orders of magnitude faster using machine learning techniques. Students can expect to gain experience in machine learning, data management and statistical analysis.  This project will be co-advised by a graduate student and has the potential for ongoing research.
Research Mode: Remote/Online

NERS Project #8: CPU and GPU Computational Kernels for 0D/1D Pointwise Slowing Down Calculations
Faculty Mentor: Brendan Kochunas, bkochuna@umich.edu
Prerequisites: experienced with high level programming languages (C/C++/Fortran); GPU programming experience (desired)
Project Description: Accurate calculation of resonance integrals and resonance interference effects from microscopic cross section data for the slowing down of neutrons is essential to nuclear reactor analysis. Exact treatment of this problem is extremely computationally intensive due to the magnitude of data as a result of numerous isotopes and temperature distributions. This project is about implementing a high performance computational kernel in a high-level language (C/C++/Fortran) for a CPU as a baseline and a GPU (most likely with CUDA) to test the limits of performance. Highly performant code minimizes data movement, therefore a multipole formalism–rather than pointwise–is desired. The desired outcome is a prototype mini-app that can be used to evaluate performance on various architectures. Students can expect to learn the physics of neutron slowing down, using evaluated nuclear data, program performance analysis, and programming GPUs.
Research Mode: Hybrid

NERS Project #9: Modeling of Critical Experiments with MPACT
Faculty Mentor: Brendan Kochunas, bkochuna@umich.edu
Prerequisites: US Citizenship or Citizenship of a generally allowed country; experience working in Linux
Project Description: The validation of reactor simulation tools is a perpetual activity. This is because new data continually becomes available, and the methods of simulation tools are updated and extended to new reactor types. In this project the students will develop MPACT inputs for models of critical nuclear reactor experiments (or possibly other reactor experiments). The exact experiments to be simulated will be determined at the beginning of the project. Students should expect to gain experience in nuclear reactor analysis and tools for reactor analysis
Research Mode: Hybrid

NERS Project #10: Nuclear Reactor Dynamics System Component Modeling and Control
Faculty Mentor: Brendan Kochunas, bkochuna@umich.edu
Prerequisites: courses in thermodynamics and heat transfer; familiarity with Simulink or Modelica (desired)
Project Description: An initiative within the Department of Energy is the design and analysis of integrated energy systems that include nuclear reactors with other applications besides electricity generation. To support this initiative there are two open source Modelica libraries: TRANSFORM and HYBRID that contain component models and subsystem models. This project is about developing new components or models to contribute to these libraries. Additionally, applying control engineering to these systems will be a stretch goal. Tools for control frameworks of Modelica systems are few, while MATLAB has several toolboxes for this. Therefore, investigating ways to integrate these libraries with tools for system control is another targeted task. Students should expect to learn about reactor systems, power conversion systems, modelica, system dynamics
Research Mode: Hybrid

NERS Project #11: Derivation of Arbitrarily High Order Sources for the Method of Characteristics
Faculty Mentor: Brendan Kochunas, bkochuna@umich.edu
Prerequisites: multivariate calculus
Project Description: The method of characteristics is a “work horse” method for neutron transport calculations for reactors. Recent work has derived newer linear and quadratic source representations. This project is about extending those formulations to arbitrarily high-order. Additionally, we wish to investigate non-polynomial expansions of the source. The main activity will be mathematical derivation of the resulting discretized equations. If sufficient progress is made here, than it is desired for the student to develop numerical implementations to confirm estimates of order of convergence, and computational cost. Students should expect to develop skills in the applied mathematics field of numerical analysis, and discretization of the transport equation. 
Research Mode: Hybrid

NERS Project #12: Radiation Weather Station (RWS)
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students work as part of a team; a student’s specific assignment will depend upon the background and interests of each student
Project Description: Knowing changes in the presence of radionuclides in the environment is important for the detection and response to nuclear power plant accidents and radiological terrorist events. The Radiation Weather Station is a facility consisting of sensors located at several stations on University of Michigan’s North Campus, with auxiliary stations planned elsewhere. Sensors are available for temperature, pressure, humidity, rainfall, wind speed and direction, solar radiation, solar flares, soil moisture, radon, and gamma rays. Naturally-occurring, medical and nuclear power plant radionuclides may be detected, with information collected about the energy of their gamma rays. Monitoring is designed to identify radionuclides from natural, planned, and accidental releases, while tracking indoor and outdoor environmental conditions. All data are shared through a continuously-updated website. A variety of projects are available involving the development and improvement of the data base, deployment of new sensors, analysis of large data sets, website development, addition of mobile phone-based radiation detectors, and the preparation of educational materials for the public and K-12 audiences. A small, affordable RWS featuring a smaller collection of more affordable sensors controlled by a Raspberry Pi computer is also undergoing development. Tasks and specific work are tailored to the student, depending upon their interests and capabilities. This may involve one (or possibly multiple) of the following: software usage, statistical analysis, coding, hardware interfacing, analysis of temporal data sets, machine learning, design and 3-D printing of mechanical parts and cases, design of circuits and printed circuit boards, historical research, and technical writing for the public. 
Note: This project is *not* about climate change or weather prediction. It is about detecting and characterizing the type and source of ionizing radiation as it changes as a function of time at different locations.
Research Mode: remote, hybrid (some in-person may be possible/needed for certain tasks but not required of all participants). Example in-person tasks could include installation, modification, calibration, or testing of new sensors.

NERS Project #13: Smart Radiation Detectors and Adaptive Navigation for Radiation Surveys
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students work as part of a team; a student’s specific assignment will depend upon the background and interests of each student
Project Description: Several software and hardware development projects are relating to the improvement and testing of a smart radiation detector. The current design is a Geiger-Muller (GM) ionizing radiation detector controlled by Raspberry Pi computer. Enhanced designs may ultimately be possible using spectroscopic detectors.  Smart radiation detectors could be used by individuals performing radiation surveys on smaller spaces such as individual laboratories. They could also be transported larger distances using ground-base or aerial platforms, ranging from firetrucks to automatically piloted drones. Software involving auditory or visual communications could alert surveyors of spots which have been missed in performing detailed surveys, such as lab benches when searching for contamination. More complex software could be used to construct the distribution of the sources of radiation in an environment from limited measurements. That approximation could then be used to inform the best locations for addition measurements and optimize a measurement path to further improve knowledge of the sources. Such approaches would be invaluable for first responders to radiological events as well as those involved in the cleanup of legacy radioactive wastes or the decommissioning of nuclear facilities. Experienced students are sought to develop computer programs and mobile device Apps to fully enable their appropriate functioning, display of data, and intelligent navigation of such detectors. Students should provide clear information about their experience and proficiency in software, hardware, radiation detection, and mechanical design so that their role on a diverse team working on this project could be identified.
Note: The algorithms in this project may also be applied to the location of WiFi emitters and other sources of radiation (such as radio waves) which are non-ionizing. Some projects are available concerned with the usage of these, which are “substitutes” for ionizing radiation.
Research Mode: remote, hybrid (some in-person may be possible/needed for certain tasks but not required of all participants). Dry benchwork (such as soldering involved in the making of a smart detector) may be completed at student’s homes and tested using readily available radioactive materials. Example in-person tasks could include experiments testing the performance of the smart detectors or algorithms for using them.  Some experiments may be performed outside.

NERS Project #14: Radon Gas—An Indoor Radioactive Hazard Useful for the Detection of Nuclear Weapons and Earthquakes
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students work as part of a team; a student’s specific assignment will depend upon the background and interests of each student
Project Description: Radon gas is a ubiquitous naturally occurring radioactive material that occurs throughout the environment and in all buildings, at least in small amounts. It can be readily detected but presents health hazards when in high concentrations. Radon gas levels change as a function of local weather conditions, as well as the heating or cooling situation within a building. Radon has also been observed to change many days in advance of major earthquakes. This project involves the study of radon gas as a function of time both indoors and outside. State-of-the-art equipment is deployed both to measure radon gas as well as to track local weather and other conditions such as solar and background radiation from other sources. Students may participate in both experimental data collection as well as analysis of large data sets. Discrimination of airborne transuranics from naturally occurring radon gas is particularly important for worker protection during commercial nuclear power plant outages and dose control during emergencies. Topic is especially suitable for students ultimately interested in homeland security/treaty verification, nuclear power plant operations, and/or radiation protection. Students should have motivation to learn, basic programming skills, and solid mathematics and physics backgrounds. Student with appropriate background may be able to apply machine learning techniques to analyze existing data sets.
Research Mode: remote, hybrid (some in-person may be possible/needed for certain tasks but not required of all participants). In-person tasks for some participants could include counting charcoal canisters or reading out electrets on existing laboratory equipment or setting up experiments to collect data.

NERS Project #15: Thermoluminescent and Optically Stimulated Luminescent Dosimetry–Radiation Dose Measurements for Workers, Patients, and Environmental Monitoring
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students work as part of a team; a student’s specific assignment will depend upon the background and interests of each student
Project Description: Dosimeters are passive, integrating materials used to monitor the radiation exposure of workers in nuclear facilities. Although all workers receive dosimeters, there are different types and they have different performance characteristics. New dosimeter types and ways of calibrating and deploying them are being developed in the laboratory. Dosimetry systems are also used for medical applications including radiation therapy, diagnostic radiology and nuclear medicine. The limitations of different types of dosimeters are being actively compared and characterized for medical applications. Advanced software is also being developed to automatically analyze thermoluminescent dosimeter glow curves for research projects as well as routine analysis. A dosimetry calibration source is also being carefully characterized using a quality control experiments undergoing development. Students may be engaged in in performing experiments, data analysis, and/or software design. This project is especially suitable for students ultimately interested in homeland security/treaty verification, medical physics, nuclear power plant operations, and/or radiation protection. Students should have motivation to learn, basic programming skills, and solid mathematics and physics or computer programming backgrounds.
Research Mode: remote, hybrid (some in-person may be possible/needed for certain tasks but not required of all participants). Example in-person tasks could include performing quality control of a radiation source, calibration of detectors, processing of dosimeters, or performance of experiments involving phantoms.

NERS Project #16: Radiation Spectroscopy for the Identification of Radionuclides
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students should have strong skills, experience, or interest in computer programming or radiation detection 
Project Description:  The applications of this project are protection of the public from environmental radiation, nuclear accident dose reconstruction, and nuclear weapons treaty verification. Energy spectroscopy involves the determination of the energy of particular types of radiation, which are characteristic of the source of radiation. Alpha, gamma, and neutron spectroscopic devices are calibrated and deployed to solve real-world problems involving radiation sources. Students may become involved in nuanced calibrations, data interpretation, and specific measurement campaigns involving a variety of both state-of-the-art and newly developed instruments used for radiation spectroscopy. Applications of an imaging spectrometer to the medical environment as well as for naturally occurring radioactivity may also be explored. Topic is especially suitable for students ultimately interested in homeland security/treaty verification, medical physics, nuclear power plant operations, and/or radiation protection. 
Research Mode: remote, hybrid (some in-person may be possible/needed for certain tasks but not required of all participants). Example in-person tasks could include data collection and instrument calibration.

NERS Project #17: Extended Reality and Virtual Reality Games for Radiation Protection
Faculty Mentor: Professor Kim Kearfott, kearfott@umich.edu
Prerequisites: Students work as part of a team; a student’s specific assignment will depend upon the background and interests of each student
Project Description: Work with a team producing a game or other extended reality experience to teach the principles of radiation protection or attracting interest in the nuclear sciences. Unity, Unreal, Uptail, or other 3D software may be used.  Students may become involved in overall game or experience design, artwork, rendering of nuclear-specific objects (Blender or Solidworks), implementation of realistic radiation source and detector physics, or creation of competitive aspects to the software. Three-dimensional video cameras and Oculus 
Research Mode: remote. Software, 3D cameras, and virtual reality display systems will be made available to students for the performance of the project at locations of their choosing.