NERS Project #1: Atombot: Swarm Robotics and Collective Intelligence
Faculty Mentor: Y Z, [email protected]
Prerequisites:
- GPA>3.9; Sophomore and above
- PCB and circuit design (Altium, Eagle, etc.) and fabrication
- Electronics platform, microcontroller, and embedded systems (Arduino, Raspberry Pi, Nvidia Jetson, etc.)
- Sensing technologies (UWB, proximity, accelerometer, gyrometer, etc.) and near-field communication technologies
- Programming with C/C++/Python.
Project Description:
The understanding of collective phenomena is one of the major intellectual challenges in a wide range of fields, from materials science to life science. One fundamentally interesting and technologically impactful system is swarm robotics – a collection of robots that can self-organize and exhibit higher-level collective intelligence. Because of the low cost of individual units of the swarm, swarm robots may have a profound impact on a wide range of disciplines, such as information gathering, cooperative missions, and collective artificial intelligence. This Atombot project develops two robot prototypes: (1) Atombot Hydrogen: a miniature swarm robot system serving as a platform to study the fundamental emergent behavior of many-robot systems; (2) Atombot Helium: an advanced wheel-legged robot unit. While the Atombot system has potential applications across many fields, our immediate focus is on mission-critical applications in extreme environments, such as the energy sector and homeland security and safeguards. The Atombot team seeks students with a broad range of backgrounds and interests to take roles in the technology, science, and commercialization sub-teams. Students can choose a sub-team to work with and have the flexibility to move between different sub-teams. Students will have the opportunity to develop skills in additive manufacturing, electronics, control and optimization, physics, and business development.
Research Mode: In-person
NERS Project #2: Integral-effect test (IET) facility design and construction for advanced gas-cooled reactor
Faculty Mentor: Xiaodong Sun, [email protected]
Prerequisites:
- NERS major
Project Description:
General Atomics Electromagnetic Systems (GA-EMS) is developing a new 100 MWth fast modular reactor (FMR) under the U.S. Department of Energy’s (DOE’s) Advanced Reactor Demonstration Program. To support the FMR design and licensing activities, a research project sponsored was initiated to better understand natural circulation flow phenomena under pressurized loss of forced cooling (P-LOFC) and depressurized loss of forced cooling (D-LOFC) accidents in the FMR and to improve our modeling capabilities for such accidents. One of the important tasks of the project is to design and construct an integral-effect test (IET) facility to simulate those accidents. The undergraduate student is expected to carry out the following tasks: (1) Work with a graduate student and our collaborators to develop an engineering design for the IET facility, including an instrumentation plan and (2) Support the construction of the IET facility, including acquiring key components and instruments, and assembling the facility.
Research Mode: In-person
NERS Project #3: Core Design for Holtec SMR-160
Faculty Mentor: Brendan Kochunas, [email protected]
Prerequisites:
- NERS 211, U.S. Citizen. Ability to write python or shell scripts and use software on the Linux command.
- Basic understanding of pressurized water reactors.
Project Description:
This project is very representative of the work done by core design engineers in industry. Students will use nuclear reactor design tools to calculate core reactivity parameters, power distributions, and depletion characteristics for the Holtec SMR-160 to support core design, loading pattern optimization and uncertainty analysis. It is likely an academic publication can result from this work if successful.
Research Mode: In-Person/Hybrid
NERS Project #4: Modeling and Benchmarking of the Fort St. Vrain High Temperature Gas Reactor
Faculty Mentor: Brendan Kochunas, [email protected]
Prerequisites:
- NERS 211 Ability to write python or shell scripts and use software on the Linux command.
- Ability to acquire a software license to use VERA.
Project Description:
The Fort St. Vrain reactor was one of two commercial high-temperature gas reactors to operate in the U.S. In this project, students will develop and analyze models of the Fort St. Vrain reactor in MPACT to benchmark MPACT against previously developed MCNP models and plant measurement. It is likely an academic publication can result from this work if successful.
Research Mode: In-Person/Hybrid
NERS Project #5: Radiation Transport Analysis Methods for Fusion Energy Systems
Faculty Mentor: Brian Kiedrowski, [email protected]
Prerequisites:
- Programming experience, Python and/or C++ preferred
Project Description:
Nuclear fusion offers the potential of a limitless supply of clean energy. To make these systems a reality, nuclear designers require robust and efficient simulation tools. This project will focus on developing novel schemes for effectively solving the neutron/gamma transport equation to obtain estimates of engineering relevant quantities in fusion energy systems such as nuclear heating, radiation damage, and tritium breeding. The SURE student will work with one or more graduate students with specific objectives determined based on the current status of the research and the skills of the student.
Research Mode: Hybrid
NERS Project #6: High repetition rate liquid target development for the 3 PW ZEUS laser facility
Mentor: Karl Krushelnick, [email protected]
Prerequisites:
- none
Project Description:
The ZEUS laser facility at Michigan is an NSF funded user facility operating on North Campus. It is presently the highest power laser in the US and will soon operate at 3 PetaWatts peak power. This SURE project involves development of liquid droplet and liquid jet targets to be used as high repetition rate targets for experiments in the ZEUS laser facility. These experiments will address compact particle acceleration techniques, neutron generation as well as the production of x-ray radiation.
Research Mode: In-Person
NERS Project #7: Laser-driven x-pinches on the ZEUS laser
Faculty Mentor: Dr. Heath LeFevre (postdoc for Prof. Kuranz)
Prerequisites:
- Classes at the level of Engin 101 and Phys 240 would be helpful.
- Additional programming or electricity and magnetism background would be useful, but not necessary.
Project Description:
This project will use current produced when the ZEUS laser hits a metal foil to magnetically compress an x-pinch to create an x-ray source with a short duration and small spatial size. An x-pinch is a current-driven plasma where the current travels through an “x”-shaped structure to concentrate the magnetic pressure in a small region. The purpose of this work is to demonstrate and characterize an x-ray source that can operate at a high-repetition rate (~1/second) for future measurements of extreme plasmas. The student working on this project will be involved in setting up, collecting, and analyzing data from an x-ray pinhole camera that images the emission from the x-pinch. The exact distribution of these tasks will depend on timing and some scheduling. There are options to explore other areas of this project, depending on the interests of the student and available time.
Research Mode: In-person
NERS Project #8: Energy System and Fuel Cycle Modeling for Rural and Tribal Communities
Faculty Mentor: Aditi Verma, [email protected], Additional mentor: Riley Fisher, [email protected]
Prerequisites:
- Interest in solving social/technical problems and interdisciplinary research
- Familiarity with programming and statistical analysis
Project Description:
As nuclear technology becomes more diversified in the near future, communities are becoming increasingly interested in siting nuclear facilities. For some communities, especially those that are non-urban, a future that includes nuclear technologies remains uncertain. To this, there is often a lack of resources and tools to help decide whether nuclear technology would truly be a good fit. The goal of this project is to create a computational model that describes the effects of introducing nuclear fuel cycle systems to rural and Tribal communities. The systems of interest include uranium recovery facilities, power generation, and waste disposal. The model will help determine the logistic, economic, and environmental effects brought onto a community by combinations of these facilities. At the start of the program, students will conduct a brief literature review to become familiar with the contexts (economic, political, cultural) that make rural and Tribal communities particularly unique in this analysis. Students will then help plan, develop, and test a model that is sensitive to a wide array of input and output variables. This model will then be made available to communities to aid in energy planning, and students will complete the project with the ability to analyze and plan small-scale energy infrastructure.
Research Mode: Remote or hybrid
NERS Project #9: AI-Driven Analysis of Public Feedback on Nuclear Waste Facility Siting
Faculty Mentor: Aditi Verma, [email protected] and Md Rafiul Abdussami, [email protected]
Project Description:
Consent-based siting of nuclear waste facilities is critical for advancing sustainable and equitable nuclear energy deployment. The U.S. Department of Energy’s (DOE) Request for Information (RFI) on Consent-Based Siting collected diverse community and organizational perspectives on approaching interim storage facility siting. These responses offer valuable insights into public concerns, aspirations, and conditions for participation, but the volume and complexity of the data require innovative tools for effective analysis.
The student will work as part of a research team to analyze these RFI responses using advanced tools, including Large Language Models (LLMs). Our goal is to extract key themes, identify patterns, and propose a community-centered pathway for siting nuclear waste repositories. By leveraging LLM, the project aims to create a replicable framework that ensures inclusivity, fairness, and transparency in decision-making.
Students will:
- Pre-process and analyze qualitative and quantitative data from the RFI responses.
- Use LLMs to identify trends, sentiments, and underrepresented voices in the responses.
- Develop actionable insights and policy recommendations that promote justice and inclusivity in consent-based siting.
Research Mode: Remote or hybrid
NERS Project #10: Examining the connections between reactor design choices and cost outcomes
Faculty Mentor: Aditi Verma, [email protected], Additional mentor: Rowan Marchie, [email protected]
Prerequisites:
- none
Project Description:
There has been a renewed push for nuclear power to serve as a baseload energy to supplant coal and other fossil fuel energies as a net zero-emission energy source. This motivation has led to an increase in research on existing and new nuclear energy systems. However, one area of research that is relatively underdeveloped is the economics of nuclear energy systems and the relationship between design decisions and the costs of nuclear reactors. For nuclear energy to become one of the primary energy sources for net zero emissions, the economic implications of cost from design decisions must be better understood.
The current iteration of our research was the creation of a survey meant to ask nuclear researchers and designers how they consider and use economics in connection to nuclear design. The purpose of the survey is to get a more direct understanding of the role of economics in the nuclear design process. Currently, the research survey has been created, revised, and published; the next step will involve the tabulation and analysis of the survey data to see what conclusions can be drawn from the connections between design and economics in nuclear systems.
Following these analyses there will be interviews conducted with designs on nuclear energy projects about how reactor economics are considered in the design project to get a more in-depth perspective than from the research survey. Research work related to the interviews will include writing interview questions based on findings from the literature review and survey research, the identification and background checks of potential designers to interview, and the analysis of the interview data itself. This project will conclude by identifying trends and correlations between how economics and costs are treated in the analyzed papers and by nuclear designers and how the papers connect economics to designs of nuclear energy systems.
The results of this project are intended to be included in a larger paper focusing on the connection between design and cost in nuclear energy systems as well as on the development of a computational tool used to predict and mitigate cost overruns for nuclear energy projects.
Research Mode: Remote or hybrid
NERS Project #11: Public perspectives on the design of microreactors
Faculty Mentor: Aditi Verma, [email protected], Additional mentor: Katie Snyder, [email protected]
Prerequisites:
- none
Project Description:
As all energy technologies, including nuclear, become smaller and distributed, it has become vital that technology designers engage with potential host communities during the technology design and development process. Across the country, communities in Alaska, at sites of present and former nuclear research facilities, and coal sites are expressing an interest in nuclear energy and calling for a seat at the table as key decisions about technology and facility design are made. Failure to incorporate these perspectives in the design of nuclear as well as other energy technologies could significantly slow down the transition to a low-carbon energy system. In Fall 2024, with our ENGR100 course, we carried out a novel socially engaged process for designing microreactors, making use of several tools, including generative AI, virtual reality models of reactor systems, and interactive workshops to support socially engaged design.
Students working on this SURE project will analyze the qualitative and quantitative data collected during Fall 2024, carry out interviews and surveys, refine and test socially engaged design tools, and work with the faculty mentors to write up the research findings. Students working on this project will have the opportunity to continue working with us in Fall 2025 semester as peer mentors for our ENGR100 course where we will again run a socially engaged design process for a different nuclear technology.
Research Mode: In-Person, Remote, or Hybrid – though in-person is strongly encouraged as the primary mode
NERS Project #12: Assessing the potential for using generative AI in prototyping energy system designs
Faculty Mentor: Aditi Verma, [email protected], Additional mentor: [email protected]
Prerequisites:
- none
Project Description:
AI image generators are rapidly evolving tools that may be helpful in facilitating conversation about and development of nuclear energy systems in participatory design contexts – giving host communities of energy facilities the ability to visualize and prototype their own energy infrastructure. In this project, we aim to test the capacity of Generative AI to create images of a variety of energy systems and assess their accuracy, creativity, and variety across prompts and system types. This work will involve carrying out hundreds of design experiments with a wide range of generative AI models, coding the images, developing metrics for assessing the energy system prototyping capabilities of the Generative AI models, as well as recommendations for the use and future development of Generative AI models for energy system visualization and prototyping.
Research Mode: Remote or hybrid
NERS Project #13: A framework for responsible AI integration in the nuclear sector
Faculty Mentor: Aditi Verma, [email protected]
Prerequisites:
- none
Project Description:
The rapid development and integration of AI in nuclear plant design, operation, and regulation pose serious questions about the potential tradeoffs – including the potential risks, harms, and benefits of using AI in nuclear contexts, particularly where safety and security are a primary concern. To date, no overarching framework or set of principles exists for informing when, how, and to what extent AI should be used across the nuclear sector, how much human agency should be ceded to AI, how AI uses should be verified, and how failures of AI can be planned for in the overall system design and operation. This project will involve developing a framework for AI applications in nuclear contexts through document analysis, expert interviews, surveys, and a review of current and evolving applications of AI across the nuclear sector. This project is part of a collaboration with the Australian National University.
Research Mode: Remote or Hybrid rid