Degree and Student Projects
The projects listed below are possible degree projects (on various levels) within applied nuclear physics.
Several of the projects can be adapted to shorter student projects.
See also our Swedish website for further project ideas.
Design of an upgraded PPAC setup for fission fragment mass determination at the CERN-n_TOF facility
Student project scope
Ideally 30 credits.
Start: upon agreement
Background
The Neutron Time-of-flight (n_TOF) facility at CERN is the unique experimental facility in the world providing with a neutron beam with energies from thermal up to several GeV [Gue13]. The study of neutron-induced fission reactions plays a key role in the experimental activities of the n_TOF international collaboration [Col20]. One of the setups used to study fission reactions at n_TOF is based on Parallel Plate Avalanche Counters (PPACs) and, thanks to the excellent time resolution of the detectors, it has provided the only existing data in nuclear reactions induced with neutrons of 1 GeV [Par10, Par15, Tar11, Tar23].
Although this setup has been initially designed for high-accuracy measurements of fission cross-sections only, it has been found that it can be also used to study the mass distribution of the fission fragments. This will allow to study this observable in the so-called spallation energies (100 MeV and above), providing with new experimental data in an energy region which has not been explored with neutrons before.
To exploit these capabilities, modifications to the experimental setup are required to improve the mass resolution of the fission fragments and to enable measurement of the linear momentum transferred by the neutron to the target nucleus.
Project objective
The student will investigate the dependence of both the mass resolution and the linear momentum transfer on selected characteristics of the setup, such as distance between PPACs and target and time resolution of the detectors. The ultimate goal is to identify the optimal configuration for future experiments at the CERN n_TOF facility.
The student will carry out simulations; therefore, some knowledge of a programming language (e.g., Python, C++) is required. Experience with simulation toolkits such as Geant4 [Gea] and with the data analysis framework ROOT [Roo] will be advantageous.
Further Reading
[Col20] N. Colonna et al. Eur. Phys. J. A 56, 48 (2020) https://doi.org/10.1140/epja/s10050-020-00037-8
[Gea] Geant4. A simulation toolkit. Web: https://geant4.web.cern.ch
[Gue13] C. Guerrero et al. Eur. Phys. J. A 49, 27 (2013) https://doi.org/10.1140/epja/i2013-13027-6
[Par10] C. Paradela et al. Phys. Rev. C, 82:034601 (2010) http://link.aps.org/doi/10.1103/PhysRevC.82.034601
[Par15] C. Paradela et al. Phys. Rev. C, 91:024602 (2015) http://link.aps.org/doi/10.1103/PhysRevC.91.024602
[Roo] ROOT. An Object-Oriented Data Analysis Framework. Web: https://root.cern
[Tar11] D. Tarrío et al. Phys. Rev. C, 83:044620 (2011) http://link.aps.org/doi/10.1103/PhysRevC.83.044620
[Tar23] D. Tarrío et al. Phys. Rev. C, 107:044616 (2023) https://link.aps.org/doi/10.1103/PhysRevC.107.044616
Contact
Diego Tarrío, diego.tarrio@physics.uu.se
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 as 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
Machine learning predictions of BWR fuel properties
Student project scope
Ideally 30 credits
Background and relevance
The majority of commercial nuclear reactors in operation today are light-water reactors (LWRs), such as pressurized water reactors (PWRs) and boiling water reactors (BWRs). These both have enrichment levels below 5%, but the fuel geometries and properties are slightly different due to the different conditions in the reactor.
In order to verify that neither the reactors nor the fuels have been tampered with, nuclear safeguards measures are in place to ensure the peaceful use of commercial nuclear installations. Measurement instruments in use typically rely on detection of emitted gamma and neutron radiation. International nuclear inspectors perform measurements to draw conclusions about the completeness and correctness of fuel declarations based on such measurements.
The UU research group has for decades investigated improved measurement and analysis techniques for such spent fuel verification. An important tool in this context is synthetic fuel data to use in the analysis, since measurement data are scarce. In previous projects we have therefore developed e.g. PWR fuel libraries and explored the use of machine learning tools in the verification of the nuclear fuels. We have for instance explored the prediction capability of different regression techniques to quantify fuel properties such as initial enrichment, burnup and cooling time independent of operator declarations, and based on measurable observables.
Project objective
We are currently developing a BWR fuel library to do similar research as we did using the PWR fuel library. As BWR fuels are less homogeneous than PWR fuels with more varying fuel properties, we expect the fuel library to be more complex than the PWR fuel library with e.g. varying void levels and moderator densities in addition to varying initial enrichment and burnup levels and cooling time. The objective of the project is hence for the student to explore capabilities of different machine learning algorithms to make predictions about safeguards relevant parameters based on simulated fuel properties. If time and scope allow, the student could also generate additional synthetic data to enable classification of for instance fuel type.
Further reading
- Zs. Elter et al., Pressurized water reactor spent nuclear fuel data library produced with the Serpent2 code. https://doi.org/10.1016/j.dib.2020.106429
- S. Grape et al., Determination of spent nuclear fuel parameters using modelled signatures from non-destructive assay and Random Forest regression. https://doi.org/10.1016/j.nima.2020.163979
- Mishra et al., Comparison of different supervised machine learning algorithms to predict PWR spent fuel parameters. https://resources.inmm.org/system/files/annual_meeting_proceedings/a287_11_0.pdf
For more information
Contact: Sophie Grape, Sophie.grape@physics.uu.se
Measuring nuclear masses with an MR-TOF system at GSI
Student project scope
Ideally 30 credits
Start: upon agreement
Background and relevance
Multi-reflection time-of-flight (MR-TOF) systems offer a way to measure nuclear masses with high precision.
One such system is installed at GSI in Darmstadt, Germany (link below). The system is connected to the cryogenic stopping cell (CSC) at the FRS and can be run both with beam and offline using internal sources.
One way to obtain and study short-lived nuclei to use (spontaneous) fission resulting in neutron rich nuclei far from the line of nuclear stability.
It is of interest to measure masses, separate nuclear isomers and obtain the isomeric ratio resulting from the fission reaction.
The nuclear reactions group has a strong interest in especially isomeric yield ratios. These can be used to study the complex and interesting process of nuclear fission.
So far we have obtained our data with Penning traps but we are now looking into possibilities to also use MR-TOF systems since they might allow for measuring systems not currently accessible at Penning traps and might allow measuring more short-lived nuclei.
Project objective
- Test and improve the analysis procedure for experimental data from the GSI MR-TOF.
- Participate in experimental campaign to obtain new data.
- Analyse experimental data from spontaneous fission and obtain isomeric yield ratios.
The project will to a large part be conducted at GSI in Darmstadt, Germany. Support for housing etc. is provided by GSI.
Further reading
- The FRS Ion Catcher at GSI: https://www-windows.gsi.de/frs-ion-catcher/setup/
- Samuel Ayet San Andrés et al., “High-resolution, accurate multiple-reflection time-of-flight mass spectrometry for short-lived, exotic nuclei of a few events in their ground and low-lying isomeric states”, Phys. Rev. C 99, 064313
- S. Cannarozzo et al., “Isomeric yield ratios and mass spectrometry of Y and Nb isotopes in the neutron-rich N=60 region: The unusual case of 98Y”, Physics Letters B 871 (2025) 140012
Contact
Stephan Pomp, stephan.pomp@physics.uu.se
Neutron activation analysis of materials
Student project scope
Ideally 30 credits
Start: upon agreement
Background and relevance
Neutron activation analysis (NAA) is a powerful non-destructive technique to determine the elemental composition of materials.
The technique is used in various applications including archeology, geology, medicine, biology, and forensics.
The methods rests on the neutron capture reaction to produce radioisotopes that can then be identified using gamma spectrometry.
The activation is done at the NESSA neutron facility. Gamma spectrometry of the activated material is then done using HPGe detectors at the UGGLA facility, Both NESSA and UGGLA are located at Ångström laboratory.
Project objective
Establish and test in-house capabilities for NAA.
This is done by:
- Using available information on neutron intensity estimate detectable amount of various isotopes.
- Build a neutron moderator around the 14-MeV neutron source to provide thermal neutrons.
- Perform activations of various material at NESSA.
- Obtain gamma-spectra from the activated material and derive information of the elemental content of the sample.
Further reading
IAEA: IAEA - Neutron activation analysis
Wikipedia: Wikipedia - Neutron activation analysis
Contact
Stephan Pomp, stephan.pomp@physics.uu.se
Novel neutron flux monitor
Introduction
The measurement of absolute neutron flux is a core problem in fusion reactors. Traditionally, neutron flux monitoring has relied on fission chambers (FCs), owing to their direct neutron sensitivity, relatively simple response function, and well-established calibration procedures. However, FCs suffer from several intrinsic limitations, including the use of fissile materials, aging and burnup effects, space-charge saturation at high count rates, wall effects and complex calibration procedures. Recent advances in high-rate, high resolution gamma-rays detectors motivate the exploration of an alternative neutron flux monitor based on thermal neutron-capture gamma-ray emission. In such detectors, incident neutrons are moderated and captured in materials (boron or hydrogen), producing characteristic gamma-rays. The gamma-ray count rate can then be related to the neutron flux through accurate modeling of the neutron source and the detector response function coupled to Monte Carlo simulation of neutron moderation, capture and gamma-ray generation and transport.
Project description
The object of this project is to develop the conceptual design of a neutron flux monitor based on thermal neutron-capture gamma-ray detection using Monte Carlo simulations. In particular, the project will focus on the design and optimization of a moderated neutron-to-gamma converter coupled to a gamma-ray spectrometer. The detector geometry, moderator composition, boron concentration and shielding configuration arrangement will be systematically investigated using the radiation transport simulation codes OpenMC and Geant4. The simulations will evaluate candidate gamma-ray detectors including LaBr3:Ce and LaCl3:Ce under realistic mixed radiation fields. Sensitivity studies will quantify the impact of uncertainties in geometry and material composition on the inferred neutron flux. Different neutron-capture gamma-rays emission, including both boron and hydrogen capture lines, will be compared to identify optimal operating configurations. The expected outcome of the project is an optimized and validated detector design for a high-rate neutron flux monitor capable of achieving uncertainty levels competitive with conventional FCs. This project can be extended into a 30 HP diploma work by performing benchmarks of the simulated detector response to experimental measurements using the NESSA facility. NESSA is a deuterium-tritium 14 MeV neutron generator located at the Ånsgtröm Laboratory and operated by the Division of Applied Nuclear Physics. This part of the project will include the construction of a proof-of-principle detector set-up, participation in the irradiation experiments, data acquisition and data analysis. An assessment of the performance of the proof-of-principle system against the model will conclude the work.
Whom are we looking for?
- Someone from the physics or engineering physics programme who:
is planning a 15 HP/30 HP project or master thesis in nuclear physics; - is interested in learning how to program in Python, Octave and C/C++
(or in advancing their expertise) and using advanced Monte Carlo methods for the simulation of radiation transport; - basic knowledge of radiation measurement techniques would be advantageous.
Contact
Please send a mail to schedule a meeting to discuss further details in person.
Marco Cecconello, marco.cecconello@physics.uu.se
Nuclear reactions modeling in light-ion production
Student project scope
Ideally 30 credits
Start: upon agreement
Goal
To investigate the nuclear reaction models implemented in the TALYS software and determine the best set of parameters that describe experimental data obtained by our group at the NFS facility at GANIL, France.
Background
The Division of Applied Nuclear Physics is developing a long-term project in experimental measurements of neutron-induced reactions at the neutron facility GANIL-NFS in France. In particular, we perform experiments to study the production of light-ions in reactions induced by neutrons of energies up to 40 MeV.
The computer code TALYS is a very powerful and versatile software for simulating and predicting properties of nuclear reactions over a wide range of projectiles (photons, neutrons, protons, deuterons…) and energies up to 200 MeV. To do that, different theoretical models are used to describe the nuclear reactions, thus providing results on reaction cross-sections, energy distributions of the outgoing particles, spin distributions, etc. However, those theoretical models include free parameters which have to constrain by experimental data.
Project objective
The goal of this project is to investigate the physical principles of the neutron-induced emission of light-ions. Depending on the initial energy of the neutron, different reaction mechanisms will be possible (compound-nucleus, pre-equilibrium emission, or direct reaction), and will lead to different energy spectra and angular distributions of the emitted light-ions.
By comparing the results from TALYS with experimental data, the student will study which choice of model and set of free parameters better describes the experimental data. Apart from the data available in the literature, it is also possible to use results from our recent experiments at GANIL-NFS.
Further reading
- A. Koning, S. Hilaire and S. Goriely, TALYS: modeling of nuclear reactions, Eur. Phys. J. A, 59 6 (2023) 131. DOI: https://doi.org/10.1140/epja/s10050-023-01034-3
- TALYS web page: https://nds.iaea.org/talys/
- X. Ledoux et al, First beams at neutrons for science. Eur. Phys. J. A 57, 257 (2021) https://doi.org/10.1140/epja/s10050-021-00565-x
Contact
Diego Tarrío, diego.tarrio@physics.uu.se
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
Safeguards verification of TRISO pebble bed fuel
Student project scope
Student project scope: 10-30 hp
Background and relevance
Currently a multitude of Small Modular Reactor (SMR) designs are under development, several which use nuclear fuel forms not frequently encountered today. One such class of fuel is for pebble bed reactors containing TRISO microparticles. These fuels are currently considered for High Temperature Gas-cooled Reactors and for Molten Salt Reactors. The TRISO particles has a kernel of enriched uranium, and is surrounded by multiple layers of carbon and silicon carbide, to ensure an extra barrier preventing the release of radioactive nuclei. Several thousand TRISO particles are then put into a pebble, a roughly tennis ball sized structure containing the fuel, structural material, and in some designs, a graphite moderator.
Due to the large number of pebbles in a reactor, and the low amounts of nuclear material per pebble, there is a significant safeguards challenge in verifying these pebbles, to ensure that no nuclear material is diverted for non-peaceful applications. The pebbles are in general not considered to be unique items due to their abundance, hence there is no trackable fuel-ID or parameters which is typically relied on in today’s safeguards verification. If verification is done on a per-pebble basis, the verification must be quick, due to the number of pebbles, as well as accurate, due to the low uranium contents.
Project objective
For a 10-30 hp credit project, the aim is to study possible Non-Destructive Assay (NDA) methods for verifying pebbles, typically relying on gamma and neutron emissions from the spent fuel, to determine that its parameters are in accordance with declarations. This will require simulating how the pebble is used in the reactor, simulating detector responses for a variety of pebble parameters and detectors, to investigate what detector setup is capable of obtaining the safeguards-relevant data required.
For more information
Contact Erik Branger, erik.branger@physics.uu.se
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
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
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
Total Monte Carlo Studies of Fission Fragment De-excitation with GEF
Master Project in Nuclear Physics: Total Monte Carlo Studies of Fission Fragment De-excitation with GEF
Nuclear fission is one of the most complex quantum many-body processes in physics. During fission, the nucleus splits into two highly excited fragments whose subsequent de-excitation through neutron and γ-ray emission is governed by the interplay between collective motion, shell effects, angular momentum generation, and energy sharing between the fragments. Understanding these processes is essential both for fundamental nuclear physics and for applications in reactor technology, nuclear safeguards, and nuclear data evaluations.
Modern fission event generators such as GEF provide powerful frameworks for modeling the complete fission process on an event-by-event basis. Based on some input parameters, GEF models the subsequent de-excitation of the fragments, including neutron and γ-ray emission. However, several aspects of the de-excitation process remain insufficiently constrained, particularly the angular momentum population of the fragments and the sharing of excitation energy between them.
The aim of this project is to investigate how uncertainties and variations in the physical parameters governing angular momentum generation and energy sharing influence fission observables. A methodology inspired by the Total Monte Carlo approach will be used, where model parameters are randomly modified within physically reasonable ranges to study correlations, sensitivities, and uncertainties in the predicted observables. The project will focus on benchmark systems such as 235U(n,f), 239Pu(n,f), 252Cf(sf).
The project goals are:
- Learn how to run and modify GEF and understand their treatment of fission fragment formation and de-excitation.
- Identify and vary key model parameters related to, Fragment angular momentum population, excitation energy sharing, neutron evaporation, γ-ray emission
- Develop a Total Monte Carlo framework to generate ensembles of randomized fission events with modified model parameters.
- Investigate how the modified parameter sets affect observables such as Prompt fission neutron multiplicity and spectra, Prompt fission γ-ray multiplicity and spectra, Angular momentum distributions, Fragment excitation energy distributions, Correlations as a function of fragment mass and total kinetic energy
- Compare the calculated observables with available experimental data and evaluate the sensitivity of different observables to specific model assumptions.
The project combines nuclear theory, Monte Carlo simulations, and data analysis. Programming experience in C++, Python, Fortran or ROOT is highly beneficial, together with an interest in computational physics and nuclear reactions.
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
Using surrogate models for fuel power history reconstruction
Accurate knowledge of the irradiation history (power history) of spent nuclear fuel is critical for nuclear safeguards, spent fuel management, and repository safety. Traditional methods of reconstructing this history rely on computationally expensive inverse depletion calculations. Recent advancements in Machine Learning (ML) offer a promising alternative: training surrogate models to quickly and accurately predict the operating history of a fuel assembly based on its End-Of-Life (EOL) isotopic inventory. This project explores the feasibility of using deep neural networks to reconstruct the power history of Pressurized Water Reactor (PWR) fuels, using data generated by the high-fidelity Serpent Monte Carlo code.
Start date
As soon as possible, upon agreement.
Student project scope
Credits: need to be discussed
Contact
Vaibhav Mishra, vaibhav.mishra@physics.uu.se
Contact
- Programme Professor
- Stephan Pomp
- Head of Division
- Henrik Sjöstrand
- Visiting adress: Ångströmlaboratoriet, house 9, floor 4, Regementsvägen 10, Uppsala