Degree and Student Projects
Analysis of nuclear experiments for detector characterization
Uppsala University is part of a research project to develop a large silicon detector array at the Joint Research Centre of the European Commission in Belgium. The state-of-the-art nuclear instrument (VERDI) stands for “VElocity foR Direct particle Identification”. When a fission event occurs, both fission fragments escape back-to-back and are detected in each Time-Of-Flight (TOF) arm. By measuring the velocities and energies of both particles, one can reconstruct the masses of the particles using the kinematics of the reaction. In order to obtain precise mass measurements, both fragment velocities must be determined in great precision.
One main challenge currently is to deduce the correct time-of-flight from the Si detector signals. The so-called Plasma delay time (PDT) in Si detectors give rise to time delays which deteriorate the mass resolution. To mitigate this problem we recently performed dedicated PDT measurements at the TANDEM accelerator facility of Ångström laboratory in Uppsala (see fig. 2). By measuring the “true” time-of-flight with the aid of 2 Micro Channel Plates we could compare the PDT-affected time-of-flight to the true one. The data were performed with digital data acquisition systems.
Fission is a fascinating topic in nuclear physics, in where the interplay between the fundamental forces of nature give rise to exciting quantum phenomena. Fission fragment mass distributions, neutron evaporation and γ-ray emission may help to understand how exotic nuclei are formed and how their internal structures are. In order to study the properties of fission fragments, one needs accurate and well-characterized detectors. In this work, you will gain general knowledge about fission physics, nuclear de-excitation and learn more about solid-state silicon detectors.
The purpose of this master project is to analyse the data which were done both on α particles and on bromine and iodine ions of 44 MeV, scattering on gold samples. The analysis involves:
- Learn and perform data signal processing.
- Correct for energy losses and Pulse Height defects.
- Calibrate and validate the spectra.
- Investigate the time delay and compare with literature values.
- Correlate the measured times with the energies measured in the Si detector.
- Study and evaluate the uncertainties in these measurement.
This is a unique opportunity to participate in a nuclear experiment analysis, improve the detection capabilities and to ultimately help pushing the limits of nuclear sciences. The analysis will be based on the existing codes in ROOT language developed at CERN, which requires programming in C++.
Contact
Development of a detector system for commissioning of the NFS neutron facility and studies of neutron-induced fission
The Division of Applied Nuclear Physics is involved in a VR project aimed at commissioning of the NFS neutron facility and studies of neutron-induced fission.
NFS (Neutrons For Science), which is currently being constructed at GANIL, France, will be a unique facility for high-precision experiments in neutron nuclear data for science and technology. The data to be measured (cross sections and angular distributions for fission and light-ion production) are of importance for neutron standards, energy applications, nuclear reaction theory, radiation effects in electronics, spallation neutron sources, crew dosimetry for aviation and spaceflight, and more.
Our group will contribute to the NFS facility with a large nuclear reaction chamber (Medley) equipped with detectors of three different types: parallel plate avalanche counters (PPAC), surface-barrier silicon detectors, and scintillators. The setup and/or its elements may also be employed at other neutron facilities in the future, both in Sweden and abroad.
There are currently a few sub-tasks that can be transformed into master diploma works, in particular:
- Participation in development of new PPACs
- Optimisation of PPAC performance with regard to working gas parameters, electronics, and data acquisition system
- Characterisation of the PPAC and surface-barrier silicon detectors in terms of time and energy resolution as well as of effective area
The study has a potential for publication in a peer-reviewed scientific journal.
We are constantly looking for students who are interested to learn and work “hands-on” in a small group of research scientists and engineers at laboratory environment. Our concepts are “learning by doing” and supervision in the group. It is advantageous for interested students having attended courses in nuclear physics and especially nuclear laboratory courses. The group is international and both English and Swedish languages are spoken.
Interested? Book an interview with us and/or attend one of our exercises at the laboratory.
Start date
Upon agreement
Contact
Development of an automatic system to characterize Silicon detectors using light ions and fission fragments
Goal
Determine the sensitive area of one or several thin Si-detectors and determine if and in which way this depends on the incoming particle.
Project
At the Department of Applied Nuclear Physics, we conduct several research projects where we study different types of nuclear reactions at international research facilities (for example, GANIL in Caen, France). These nuclear reactions create, among others, light ions and fission products. To register these particles, we use Si detectors. One goal of these studies is to measure reaction cross-sections, i.e., the probabilities of different types of nuclear reactions. The exact size of the sensitive surface of the detector is therefore important to know. This may differ from the nominal value and, for design reasons, would also depend on the particle type.
The active area of the detector can be determined in our lab by using radiation sources and, with the help of radiation shielding, irradiating only a small part of the detector surface. By moving the irradiated part, the entire detector is scanned and the sensitive area can be determined.
As a radiation source, a Cf-252 source is used, which emits both alpha particles and fission products. The latter have a significantly higher mass and the sensitive surface of the detector could therefore differ from that of the relatively light alpha particles. Since the Si detector measures energy of the incoming particles, one can easily distinguish between these different particle types. The measurement takes place in a vacuum chamber located here at Ångström laboratory.
An important part of the project is to build a computer-controlled device that moves the radiation source step by step to irradiate different parts of the detector without having to break a vacuum for each individual measurement.
Thereafter, a series of measurement series will be performed and the collected measurement data will be analyzed to finally determine the detector's response to these different particle types.
Contact
Gen IV reactors and the transmutation of nuclear waste
Nuclear data (ND) underpin all nuclear physics and engineering, and modelling has become increasingly important in these fields. Uncertainty quantification (UQ) in modelling combines two difficult tasks, scientific modelling of advanced systems, and application of novel statistical methods. ND UQ is of particular importance in nuclear engineering for Gen IV reactors due to safety implications.
This project concerns improving novel methods in the field of modelling and ND UQ in the realm of Gen IV reactors.
The Generation IV International Forum (GIF) has pointed out six future reactor concepts which could produce sustainable nuclear energy at a competitive cost, enhance nuclear safety, minimize generation of nuclear waste, and further reduce the risk of weapons materials proliferation. Only about one percent of the mined uranium is used for electricity production in today’s Light Water Reactors (LWR). Recycling the spent fuel currently stored at the Swedish interim storage CLAB in future fast spectrum Generation IV (Gen-IV) systems could fulfil the electricity needs of Sweden for a several hundred years.
Systems with a fast neutron spectrum have the option to close the fuel cycle. The reference technology is the sodium-cooled fast reactor ASTRID which is to be built in France during the next decade. LFR and gas-cooled fast reactors (GFR) compete to be adopted for construction of a demonstrator as alternative technology (ALFRED, ALLEGRO).
In your diploma-work you will study how nuclear data uncertainties affect the operation of Fast Spectrum Reactors to increase the safety of the next generation nuclear reactor fleet.
Contact
Hydrogen incorporation in silicon crystals studied by ion beams
Background
Model calibration and inverse uncertainty quantification (UQ) is essential in all aspects of science and technology. This project is performed in collaboration with SSM (Strålsäkerhetsmyndigheten). However, the significance is not limited to the area of nuclear technology.
An important part of establishing a safety case in an industry is based on model calculations. In many cases, experiments and measured data can only be used to verify and validate the used models and not be used directly to infer the full information of vital engineering parameters. Hence modeling is paramount. [Hessling17]
The models used are generally calibrated with experiments, and methods are available also to quantify model uncertainties. This is referred to inverse uncertainty quantification (IUQ). IUQ can, in many cases, be computationally heavy, and there is a need to find more efficient methods to determine the uncertainty.
Deterministic sampling (DS) has previously been used for propagation of uncertainties [Hessling13] [Sahlberg16] [Sahlberg18]. DS is significantly more computationally efficient than traditional random sampling. The aim of this work is to explore if deterministic sampling can be used for IUQ, and to compare its performance to other IUQ methods.
Candidate
We are looking for a candidate with an interest in mathematics, statistics, and computational methods. The project will involve programming.
With the growing need for expertise in advanced mathematical modeling and data handling in society, particularly coupled to the onset of Machine Learning and Artificial Intelligence in many fields, we believe that this project will provide the student with a valuable skill set for the future. The project can be completed by one or more students.
References
[Hessling13] P. Hessling, “Deterministic Sampling for Propagating Model Covariance,” SIAM/ASA J. Uncertainty Quantification, vol. 1, no. 1, pp. 297–318, Jan. 2013, doi: 10.1137/120899133.
[Hessling17] P. Hessling, “Kalibrering för bestämning av optimal beräkningsmode,” 2017:23, p. 72, 2017.
[Sahlberg16] A. Sahlberg, “Ensemble for Deterministic Sampling with positive weights,” Master Thesis, Uppsala University, 2016.
[Sahlberg18] A. Sahlberg, C. Hellesen, J. Eriksson, S. Conroy, G. Ericsson, and D. King, “Propagating transport-code input parameter uncertainties with deterministic sampling,” Plasma Phys. Control. Fusion, vol. 60, no. 12, p. 125010, Nov. 2018, doi: 10.1088/1361-6587/aae80b.
Contact
Penning trap experiment for the development of nuclear clocks
The SPECTRAP experiment is located at HITRAP, a unique facility for high precision experiments with cold highly-charged ions, located at GSI, Darmstadt, Germany. SPECTRAP uses a Penning trap at liquid-helium temperature of 4 K inside a superconducting magnet to store highly charged ions and perform precision laser spectroscopy with them. The experiment is currently being upgraded with a better superconducting magnet, and is being prepared for upcoming measurements with Th89+ and similar ions that could serve as a nuclear clock for metrology. During the present upgrade and commissioning phase, we offer student projects at all levels in which one can do design-, simulation- and/or hands-on work in the fields of cryogenics, electronics, cryo-electronics, Penning trap technology and XHV vacuum, as well as data taking systems and experiment control.
Start date
Upon agreement
Contact
Production of medical radionuclides with nuclear power plants
Background
The global demand for radionuclides used in medical treatment and diagnostics is growing. The radionuclides are usually produced in dedicated research reactors, either by extraction of fission products (such as technetium-99m) or through neutron activation of inserted elements (such as cobolt-60). Some radionuclides can be produced with accelerator beams that irradiate suitable elements and produce the radionuclides through nuclear reactions (such as fluorine-18). In a few cases commercial nuclear reactors used for electricity production are producing radionuclides for medicine.
In the Nordic countries the production of radionuclides occurs at low energy accelerators for a limited set of nuclides, while a the large volume of needed radionuclides are imported from other countries. Production of radionuclides for medical purposes in Nordic countries with the use of commercial reactors would bring a clear benefit to society.
Purpose and goal of the project (why?)
The purpose of the project is to investigate if radionuclides for medical purposes could be produced using experimental pipes in existing nuclear power plants without any major reconstructions.
Scope and deliverable of the project (what and how?)
- The study is expected to cover the following topics:
The potential need for medical radionuclides from Nordic reactors (which nuclides, for what purposes, and how much?). - An overview of production of medical radionuclides in international nuclear power plants (which nuclides, for what purposes, how much, and how are they produced?).
- Investigation of what would be needed for the existing Nordic nuclear power plants to start producing medical radionuclides using the existing experimental pipes in the reactors.
- Obstacles that exist, and what would be needed in order to overcome them. The obstacles may be of technical (for instance material issues, reduced power production, risk for radiation exposure to staff, other system effects, etc.), financial or regulatory nature.
The scope is restricted to the Nordic nuclear power plants that exist today (not eventual new-build). The deliverable will be a report covering the issues above as well as analysis and conclusions.
The level of depth and focus of the project may vary depending on which engineering programme that the student is following. While the main focus is on general considerations the work may include calculations with model codes for nuclear interactions and reactor physical aspects, material or thermodynamic properties in order to estimate production rates of the relevant nuclides, and the potential related issues that may be of relevance for the assessment. But the work can also include financial or societal aspects.
The results will be published as a report at Energiforsk.
Contact details:
Contact person at UU: Mattias Lantz, Applied nuclear physics, Uppsala university mattias.lantz@physics.uu.se
Contact person at Energiforsk: Karin Westling, Energiforsk karin.westling@energiforsk.se
Images from Wikipedia under Creative Commons licenses 3.0 och 4.0
Safety in spent nuclear fuel storage
Nuclear data (ND) underpin all nuclear physics and engineering, and modelling has become increasingly important in these fields. Uncertainty quantification (UQ) in modelling combines two difficult tasks, scientific modelling of advanced systems, and application of novel statistical methods. ND UQ is of particular importance in nuclear engineering for nuclear engineering applications due to safety implications.
Present nuclear data libraries contain uncertainties due to uncertainties in the underlying nuclear physics model parameters and their covariance’s. Today, reactor codes do not request information about the uncertainty range for different nuclear data input and hence have the output data from these codes unknown uncertainties. The consequence of this is that important reactor safety parameters such as keff, and void coefficient have unknown uncertainties that might influence the reactor safety margins. The manner to handle the uncertainty in underlying nuclear physics data and their correlation is essential in order to have a safe energy production from nuclear power.
Since the Fukushima accident, more emphasis has been put in also studying the safety in the nuclear fuel storage. This work concerns investigating the uncertainty in decay-heat and criticality due to uncertainties in nuclear data to insure safe handling of spent nuclear fuel.
Contact
Serpent simulations of boiling water reactor (BWR) nuclear fuel
Scope
We are announcing a project work that can be tailored to fit a bachelor work of 15 credits, or a master work of 30 credits.
Objective
This project is a first step to creating a BWR fuel library that will be used in nuclear safeguards research to study the future verification of nuclear fuel before encapsulation and final storage. However, before creating the fuel library, it is necessary to select the prevailing conditions under which the simulations of the fuel irradiation will be performed. The objective of this project is to study the connection between different irradiation circumstances in the reactor and the resulting radionuclide inventory in the irradiated nuclear fuel.
Methodology
The Monte Carlo code Serpent2 will be used to simulate different models of BWR fuel, and different irradiation conditions. Of particular interest is to simulate different BWR geometries (a single-pin models versus a fuel assembly model, and potentially different fuel rod dimensions), and to study to what degree irradiation conditions such as void profile, void level, presence of control rods and burnable absorbers influence the radionuclide inventory at the end of irradiation and at certain cooling times.
Prerequisites
It is good if you have knowledge of nuclear power operation. Experience of Serpent simulations are beneficial but not necessary, as it analyses using Python/Matlab.
Starting time
As soon as possible.
Contact
Erik Branger, erik.branger@physics.uu.se
Sophie Grape, Sophie.grape@physics.uu.se
Simulating hydrogen concentration profiles of energy materials from resonant nuclear reactions
HITRAP is a unique facility for high precision experiments with cold highly-charged ions (HCI) of heavy elements currently being constructed at the research facility GSI in Germany. Later HITRAP will become an integrated part of the new international accelerator facility FAIR, one of the largest research projects worldwide.
At HITRAP HCI of all elements and charge states, up to U92+, can be delivered by the accelerator complex. These will be decelerated and captured in a Cooling Penning trap and, after cooling to sub-meV energy, the ions will be extracted to the experimental area. One of the first experiments to be constructed is the ARTEMIS Penning trap for measurement of the g-factor of heavy hydrogen like systems like U91+. This measurement will serve as a benchmark of theoretical predictions for g-factors calculated in the framework of bound state quantum electrodynamics (QED). The measurement of the atomic gF factors of two hyperfine structure levels on the ppb level of accuracy will allow the extraction of nuclear magnetic moments without diamagnetic corrections as well as the quantification of diamagnetic shielding effects.
We are constantly looking for students who want to spend time at the research facility working with the development of the setup. There are currently many sub-task that can easily be transformed into suitable diploma works.
Start date
Upon agreement
Contact
Andreas Solders (Supervisor)
Nuclear Reaction Group
Division of Applied Nuclear Physics
018-471 2631
Temporal Convolutional Neural Nets as a Surrogate for Fuel Performance Codes
Westinghouse Electric Sweden AB and other nuclear fuel vendors use fuel performance codes [1] to demonstrate that fuel rods sustain regular operation and transient events without damage. However, the execution time of a typical fuel rod simulation ranges from tens of seconds to minutes which can be impractical in certain applications. One such application is when it is desirable to quickly forecast the behavior of all rods in an entire core.
A surrogate model can be applied to speed up such applications and must predict various time-dependent outputs (e.g., temperature, pressure, strain, and stresses, etc.) as a function of a time-dependent heat generation rate. Several different classes of artificial neural networks for temporal sequence modeling exist for this purpose. For example, ref. [2] presents the use of Recurrent Neural Networks (RNNs) for predicting clad strain and stress, but with moderate success in performance. Reference [3] offers temporal convolutional networks (TCNs) as an alternative to RNNs and concludes that TCNs are “a natural starting point for sequence modeling”. In addition, a recently conducted study [4] presents TCNs as a promising candidate to predict cladding oxidation. Based on this, we offer a Master’s Thesis proposal to evaluate TCNs as surrogate models for a complete fuel performance code.
The student will conduct this diploma work at the Department of Physics and Astronomy, Division of Applied Nuclear Physics, collaborating with Westinghouse Electric Sweden AB.
For more information, contact:
gustav.robertson@physics.uu.se
For more information about Westinghouse Electric Sweden AB, visit:
https://www.westinghousenuclear.com/sweden/
References
[1] P. Van Uffelen, J. Hales, W. Li, G. Rossiter, and R. Williamson, “A review of fuel performance modelling”, J. Nucl. Mater., vol. 516, pp. 373–412, 2019.
[2] O. Gärdin, “Development of a Clad Stress Predictor for PCI Surveillance using Neural Networks”, p. 75.
[3] S. Bai, J. Z. Kolter, and V. Koltun, “An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling”, ArXiv180301271 Cs, Apr. 2018, Accessed: Aug. 05, 2021. [Online]. Available: http://arxiv.org/abs/1803.01271
[4] V. Nerlander, “Temporal Convolutional Networks in Lieu of Fuel Performance Codes: Conceptual Study Using a Cladding Oxidation Model”, Advanced Project Work in Energy Systems Engineering, 2021. Accessed: Oct. 16, 2021. [Online]. Available: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-455904
Temporal Convolutional Neural Nets as a Surrogate for Fuel Performance Codes
Westinghouse Electric Sweden AB and other nuclear fuel vendors use fuel performance codes [1] to demonstrate that fuel rods sustain regular operation and transient events without damage. However, the execution time of a typical fuel rod simulation ranges from tens of seconds to minutes which can be impractical in certain applications. One such application is when it is desirable to quickly forecast the behavior of all rods in an entire core.
A surrogate model can be applied to speed up such applications and must predict various time-dependent outputs (e.g., temperature, pressure, strain, and stresses, etc.) as a function of a time-dependent heat generation rate. Several different classes of artificial neural networks for temporal sequence modeling exist for this purpose. For example, ref. [2] presents the use of Recurrent Neural Networks (RNNs) for predicting clad strain and stress, but with moderate success in performance. Reference [3] offers temporal convolutional networks (TCNs) as an alternative to RNNs and concludes that TCNs are “a natural starting point for sequence modeling”. In addition, a recently conducted study [4] presents TCNs as a promising candidate to predict cladding oxidation. Based on this, we offer a Master’s Thesis proposal to evaluate TCNs as surrogate models for a complete fuel performance code.
The student will conduct this diploma work at the Department of Physics and Astronomy, Division of Applied Nuclear Physics, collaborating with Westinghouse Electric Sweden AB.
References
[1] P. Van Uffelen, J. Hales, W. Li, G. Rossiter, and R. Williamson, “A review of fuel performance modelling”, J. Nucl. Mater., vol. 516, pp. 373–412, 2019.
[2] O. Gärdin, “Development of a Clad Stress Predictor for PCI Surveillance using Neural Networks”, p. 75.
[3] S. Bai, J. Z. Kolter, and V. Koltun, “An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling”, ArXiv180301271 Cs, Apr. 2018, Accessed: Aug. 05, 2021. [Online]. Available: http://arxiv.org/abs/1803.01271
[4] V. Nerlander, “Temporal Convolutional Networks in Lieu of Fuel Performance Codes: Conceptual Study Using a Cladding Oxidation Model”, Advanced Project Work in Energy Systems Engineering, 2021. Accessed: Oct. 16, 2021. [Online]. Available: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-455904
Links
Westinghouse Electric Sweden AB
Contact
To investigate the fission products in an electric field using GEANT4
Master work in applied nuclear physics, 20 weeks with 30 credits (also could be a course project with 15 credits in 10 weeks).
Introduction
In order to measure fission yield of neutron-induced fission, we have developed an ion guide in which the fission products are collected. In addition, a GEANT4 model has been constructed to simulate the fission products in the ion guide. Fission products are generated isotopically in neutron-induced fissions. When fission products are thermalized by the helium gas in the ion guide, the charge states of most products are changed to 1+. However, stopping efficiency of the Helium gas is presently not sufficient. One solution to this would be to use a larger stopping volume but this would require static and radio frequent electric fields to guide the fission products. Before adding electric fields in the GEANT4 model, we want to know how the charged particles behave in an electric field and how to design an electric field to confine and drive the ions. A literature study of the GEANT4 manual will be necessary to learn how static and oscillating electric fields are implemented in GEANT4. The second step is to test this in a simple model of the ion guide to optimize the collection and transportation of fission products.
Assignment
Build a simple GEANT4 model including electric fields and investigate ion trajectories in these fields. Design an electric field to guide the ions.
Requirements
Basic knowledge of C++ and nuclear physics. Communication in English.
Start date
As soon as possible, upon agreement.
Contacts
Uncertainty Propagation in Nuclear Data for Enhanced Safety of Generation IV Reactors
Nuclear data (ND) underpin all nuclear physics and engineering, and modelling has become increasingly important in these fields. Uncertainty quantification (UQ) in modelling combines two difficult tasks, scientific modelling of advanced systems, and application of novel statistical methods. ND UQ is of particular importance in nuclear engineering for Gen IV reactors due to safety implications.
This project concerns improving novel methods in the field of modelling and ND UQ in the realm of Gen IV reactors.
The Generation IV International Forum (GIF) has pointed out six future reactor concepts which could produce sustainable nuclear energy at a competitive cost, enhance nuclear safety, minimize generation of nuclear waste, and further reduce the risk of weapons materials proliferation. Only about one percent of the mined uranium is used for electricity production in today’s Light Water Reactors (LWR). Recycling the spent fuel currently stored at the Swedish interim storage CLAB in future fast spectrum Generation IV (Gen-IV) systems could fulfil the electricity needs of Sweden for a several hundred years.
Systems with a fast neutron spectrum have the option to close the fuel cycle. The reference technology is the sodium-cooled fast reactor ASTRID which is to be built in France during the next decade. LFR and gas-cooled fast reactors (GFR) compete to be adopted for construction of a demonstrator as alternative technology (ALFRED, ALLEGRO).
In your diploma-work you will study how nuclear data uncertainties affect the operation of Fast Spectrum Reactors to increase the safety of the next generation nuclear reactor fleet.
Contact
Contact
- Programme Professor
- Stephan Pomp
- Head of Division
- Henrik Sjöstrand
- Visiting adress: Ångströmlaboratoriet, house 9, floor 4, Lägerhyddsvägen 1, Uppsala