LA-UR-19-29974
FPY workshop
Thursday Oct. 3$^{rd}$ 2019
Nuclear Data Team
Theoretical Division
Fission yields are needed for a variety of applications
Industrial applications: simulation of reactors, fuel cycles, waste management
Experiments: backgrounds, isotope production with radioactive ion beams (fragmentation)
Science applications: nucleosynthesis, light curve observations
Other Applications: national security, nonproliferation, nuclear forensics
An evaluation combines experimental and theoretical knowledge consistent with physical laws
to produce a quantity (in this case fission yields) with verifiable quality.
Should be distributed in an easily accessible form that all case use (e.g. ENDF or GNDS)
for a variety of applications
Theory is limited in accuracy & measured data is limited in scope
The last update to ENDF fission yield evaluation was in the 1990's
Other evaluations exists such as (JEFF, JENDL, etc.)
We want to improve several key areas:
Purpose: to provide a modern evaluation of fission yields
With a focus on consistency between yields, n's & $\gamma$'s, and decay data
This includes:
We also seek to expand continuous energy dependent information
Auxiliary information:
primary yield (before any prompt particle emission)
Particle spectra and multiplicities (n's & $\gamma$'s)
Our current workflow is a combination of many distinct codes
woven together by a Python3 framework called NEXUS.
MicMac [C++/Python]: nuclear potential energy surface generation
Theoretical calculation of fissioning system based off Finite-Range Liquid-Drop Model
DRW / DPS [C++/Fortran/Python]: primary yield event generators
Theoretical calculation of fission dynamics based off stochastic random walk
BeOH / CGMF [C++]: de-excitation modeling both deterministically and via Monte Carlo
Follows the statistical decay of excited fragments; IY, CY, isomer ratios
KALMAN [Fortran]: Bayesian parameter optimizer
Linear first-order parameter optimzation scheme
DeCE [C++]: evaluation file interaction
Parsing and generation of evaluation files
PRISM [Fortran/Python]: time-ordered information using nuclear reaction network
Generation of cumulative yield; decay heat
We could try to build our model from the ground up using quantum mechanics - this is hard
Energy-density functional theory (DFT) calculations are built on this approach
Can give key physical insight into system of interest
Drawbacks stem from uncertainty in choice of functionals and high computational costs
View the nucleus as a liquid drop composed of macroscopic and microscopic terms - less hard
Macroscopic-microscopic methods are based on this approach
Fast and scalable; good for performing global calculations
Drawbacks: these models are not self-consistent; dependent on fine-tuned parameters
Follow progression of the nucleus from compact to highly elongated shapes
Many possible shape degrees of freedom - but we have to isolate the most important
Projected potential energy surface from 5 canonical shape parameters of FRLDM
Path to sission is dependent on the trajectory through this complex surface
Nuclear potential energy surface of 236-U
Change in nuclear shape acts as a driving force for bulk rearrangement of material
Amounts to random walk across potential energy surface
Ensemble of fission events leads to the cumulation of the yield curve ($^{235}$U + n$_{\rm{therm}}$)
Relies on geometric splitting argument for the scission configuration
We have further enhanced these calculations; moving beyond the geometric picture
First theoretical prediction of odd-even staggering using a particle number projection technique for $^{235}$U + n$_{\rm{therm}}$
Even more improvement when larger quantum basis is used (recall Marc Verriere's talk)
Assume Bohr indepdence hypothesis of compound nucleus formation
Can study n, $\gamma$ and fission competition with $\beta$-decay
Used to study $\beta$-delayed neutron emission and multi-chance $\beta$-delayed fission (new decay mode)
Recently has been applied to statistical de-excitation of nascent fission fragments
Fit data: Hambsch for $^{235}$U + n thermal fission
Primary yield (PY): using 5D Gaussian fitting procedure; charge systematics from Wahl
Independent yield (IY): after prompt neutron and $\gamma$-ray emission using BeOH / HF$^3$D
Average prompt neutrons emitted as a function of fragment mass number
Critical inputs: yield; total kinetic energy as a function of mass number and excitation energy sharing
Increasing confidence of using these models for our evaluation efforts
Consistently calculated with the independent yield
Prompt neutron spectrum; prompt gamma spectrum
Particle multiplicities: P($\nu$), P($N_\gamma$)
Statistical & systematic uncertainties from experiment
Propagation of parameter uncertainties
Model defects
The Nuclear Data Team @ LANL
P. Jaffke, T. Kawano, A. Lovell, I. Stetcu, P. Talou, M. Verriere
& many more...
▣ Postdoc ▣ T-2 Staff ▣ XCP-5 Staff
Current fission evaluations have not been updated in years
and are further lacking for modern applications
An effort to produce an improved fission yield evaluation is underway
We have made major advances in:
Nuclear potential energy surfaces ▴ fission yield calculations ▴ statistical de-excitation
We seek to:
We are planning to include this new fission yield evaluation in the next ENDF release