Making inertial confinement fusion models more predictive
Abstract
Computer models of inertial confinement fusion (ICF) implosions play an essential role in experimental design and interpretation as well as our understanding of fundamental physics under the most extreme conditions that can be reached in the laboratory. Building truly predictive models is a significant challenge, with the potential to greatly accelerate progress to high yield and ignition. One path to more predictive models is to use experimental data to update the underlying physics in a way that can be extrapolated to new experiments and regimes. We describe a statistical framework for the calibration of ICF simulations using data collected at the National Ignition Facility (NIF). We perform Bayesian inferences for a series of laser shots using an approach that is designed to respect the physics simulation as much as possible and then build a second model that links the individual-shot inferences together. We show that this approach is able to match multiple X-ray and neutron diagnostics for a whole series of NIF “BigFoot” shots. Within the context of 2D radiation hydrodynamic simulations, our inference strongly favors a significant reduction in fuel compression over other known degradation mechanisms (namely, hohlraum issues and engineering perturbations). This analysis is expanded using a multifidelitymore »
- Authors:
-
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1597607
- Alternate Identifier(s):
- OSTI ID: 1556809
- Report Number(s):
- LLNL-JRNL-770914
Journal ID: ISSN 1070-664X; 961192
- Grant/Contract Number:
- AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Physics of Plasmas
- Additional Journal Information:
- Journal Volume: 26; Journal Issue: 8; Journal ID: ISSN 1070-664X
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 70 PLASMA PHYSICS AND FUSION TECHNOLOGY; Artificial neural networks; Bayesian inference; Hydrodynamics simulations; Nuclear fusion; Calibration methods; Physics; Mathematics; Computing
Citation Formats
Gaffney, Jim A., Brandon, Scott T., Humbird, Kelli D., Kruse, Michael K. G., Nora, Ryan C., Peterson, J. Luc, and Spears, Brian K. Making inertial confinement fusion models more predictive. United States: N. p., 2019.
Web. doi:10.1063/1.5108667.
Gaffney, Jim A., Brandon, Scott T., Humbird, Kelli D., Kruse, Michael K. G., Nora, Ryan C., Peterson, J. Luc, & Spears, Brian K. Making inertial confinement fusion models more predictive. United States. doi:https://doi.org/10.1063/1.5108667
Gaffney, Jim A., Brandon, Scott T., Humbird, Kelli D., Kruse, Michael K. G., Nora, Ryan C., Peterson, J. Luc, and Spears, Brian K. Mon .
"Making inertial confinement fusion models more predictive". United States. doi:https://doi.org/10.1063/1.5108667. https://www.osti.gov/servlets/purl/1597607.
@article{osti_1597607,
title = {Making inertial confinement fusion models more predictive},
author = {Gaffney, Jim A. and Brandon, Scott T. and Humbird, Kelli D. and Kruse, Michael K. G. and Nora, Ryan C. and Peterson, J. Luc and Spears, Brian K.},
abstractNote = {Computer models of inertial confinement fusion (ICF) implosions play an essential role in experimental design and interpretation as well as our understanding of fundamental physics under the most extreme conditions that can be reached in the laboratory. Building truly predictive models is a significant challenge, with the potential to greatly accelerate progress to high yield and ignition. One path to more predictive models is to use experimental data to update the underlying physics in a way that can be extrapolated to new experiments and regimes. We describe a statistical framework for the calibration of ICF simulations using data collected at the National Ignition Facility (NIF). We perform Bayesian inferences for a series of laser shots using an approach that is designed to respect the physics simulation as much as possible and then build a second model that links the individual-shot inferences together. We show that this approach is able to match multiple X-ray and neutron diagnostics for a whole series of NIF “BigFoot” shots. Within the context of 2D radiation hydrodynamic simulations, our inference strongly favors a significant reduction in fuel compression over other known degradation mechanisms (namely, hohlraum issues and engineering perturbations). This analysis is expanded using a multifidelity technique to pick fuel-ablator mix from several candidate causes of the degraded fuel compression (including X-ray preheat and shock timing errors). Finally, we use our globally calibrated model to investigate the extra laser drive energy that would be required to overcome the inferred fuel compression issues in NIF BigFoot implosions.},
doi = {10.1063/1.5108667},
journal = {Physics of Plasmas},
number = 8,
volume = 26,
place = {United States},
year = {2019},
month = {8}
}
Web of Science
Works referenced in this record:
Deep learning: A guide for practitioners in the physical sciences
journal, August 2018
- Spears, Brian K.; Brase, James; Bremer, Peer-Timo
- Physics of Plasmas, Vol. 25, Issue 8
Modulus prediction of buckypaper based on multi-fidelity analysis involving latent variables
journal, September 2014
- Pourhabib, Arash; Huang, Jianhua Z.; Wang, Kan
- IIE Transactions, Vol. 47, Issue 2
The high velocity, high adiabat, “Bigfoot” campaign and tests of indirect-drive implosion scaling
journal, May 2018
- Casey, D. T.; Thomas, C. A.; Baker, K. L.
- Physics of Plasmas, Vol. 25, Issue 5
A new quotidian equation of state (QEOS) for hot dense matter
journal, January 1988
- More, R. M.; Warren, K. H.; Young, D. A.
- Physics of Fluids, Vol. 31, Issue 10
An electron conductivity model for dense plasmas
journal, January 1984
- Lee, Y. T.; More, R. M.
- Physics of Fluids, Vol. 27, Issue 5
Development of a Bayesian method for the analysis of inertial confinement fusion experiments on the NIF
journal, June 2013
- Gaffney, J. A.; Clark, D.; Sonnad, V.
- Nuclear Fusion, Vol. 53, Issue 7
Deep Neural Network Initialization With Decision Trees
journal, May 2019
- Humbird, Kelli D.; Peterson, J. Luc; Mcclarren, Ryan G.
- IEEE Transactions on Neural Networks and Learning Systems, Vol. 30, Issue 5
Remarks on Some Nonparametric Estimates of a Density Function
journal, September 1956
- Rosenblatt, Murray
- The Annals of Mathematical Statistics, Vol. 27, Issue 3
Computer Model Calibration Using High-Dimensional Output
journal, June 2008
- Higdon, Dave; Gattiker, James; Williams, Brian
- Journal of the American Statistical Association, Vol. 103, Issue 482
Mitigation of X-ray shadow seeding of hydrodynamic instabilities on inertial confinement fusion capsules using a reduced diameter fuel fill-tube
journal, May 2018
- MacPhee, A. G.; Smalyuk, V. A.; Landen, O. L.
- Physics of Plasmas, Vol. 25, Issue 5
An indirect-drive non-cryogenic double-shell path to 1ω Nd-laser hybrid inertial fusion–fission energy
journal, August 2010
- Amendt, Peter; Milovich, Jose; Perkins, L. John
- Nuclear Fusion, Vol. 50, Issue 10
Examples of Adaptive MCMC
journal, January 2009
- Roberts, Gareth O.; Rosenthal, Jeffrey S.
- Journal of Computational and Graphical Statistics, Vol. 18, Issue 2
Zonal flow generation in inertial confinement fusion implosions
journal, March 2017
- Peterson, J. L.; Humbird, K. D.; Field, J. E.
- Physics of Plasmas, Vol. 24, Issue 3
Bayesian inference of inaccuracies in radiation transport physics from inertial confinement fusion experiments
journal, September 2013
- Gaffney, J. A.; Clark, D.; Sonnad, V.
- High Energy Density Physics, Vol. 9, Issue 3
Fusion Energy Output Greater than the Kinetic Energy of an Imploding Shell at the National Ignition Facility
journal, June 2018
- Le Pape, S.; Berzak Hopkins, L. F.; Divol, L.
- Physical Review Letters, Vol. 120, Issue 24
Bayesian calibration of computer models
journal, August 2001
- Kennedy, Marc C.; O'Hagan, Anthony
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, Issue 3
Detailed implosion modeling of deuterium-tritium layered experiments on the National Ignition Facility
journal, May 2013
- Clark, D. S.; Hinkel, D. E.; Eder, D. C.
- Physics of Plasmas, Vol. 20, Issue 5
The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
journal, January 2002
- Xiu, Dongbin; Karniadakis, George Em
- SIAM Journal on Scientific Computing, Vol. 24, Issue 2
Ensemble simulations of inertial confinement fusion implosions
journal, May 2017
- Nora, Ryan; Peterson, Jayson Luc; Spears, Brian Keith
- Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 10, Issue 4
Laser Compression of Matter to Super-High Densities: Thermonuclear (CTR) Applications
journal, September 1972
- Nuckolls, John; Wood, Lowell; Thiessen, Albert
- Nature, Vol. 239, Issue 5368, p. 139-142
Comparison of plastic, high density carbon, and beryllium as indirect drive NIF ablators
journal, May 2018
- Kritcher, A. L.; Clark, D.; Haan, S.
- Physics of Plasmas, Vol. 25, Issue 5
On Estimation of a Probability Density Function and Mode
journal, September 1962
- Parzen, Emanuel
- The Annals of Mathematical Statistics, Vol. 33, Issue 3
Point design targets, specifications, and requirements for the 2010 ignition campaign on the National Ignition Facility
journal, May 2011
- Haan, S. W.; Lindl, J. D.; Callahan, D. A.
- Physics of Plasmas, Vol. 18, Issue 5
Combining Field Data and Computer Simulations for Calibration and Prediction
journal, January 2004
- Higdon, Dave; Kennedy, Marc; Cavendish, James C.
- SIAM Journal on Scientific Computing, Vol. 26, Issue 2
Maximum entropy sampling
journal, January 1987
- Shewry, M. C.; Wynn, H. P.
- Journal of Applied Statistics, Vol. 14, Issue 2
Hydrodynamic instabilities seeded by the X-ray shadow of ICF capsule fill-tubes
journal, August 2018
- MacPhee, A. G.; Smalyuk, V. A.; Landen, O. L.
- Physics of Plasmas, Vol. 25, Issue 8
High-Performance Indirect-Drive Cryogenic Implosions at High Adiabat on the National Ignition Facility
journal, September 2018
- Baker, K. L.; Thomas, C. A.; Casey, D. T.
- Physical Review Letters, Vol. 121, Issue 13
Equation of State Calculations by Fast Computing Machines
journal, June 1953
- Metropolis, Nicholas; Rosenbluth, Arianna W.; Rosenbluth, Marshall N.
- The Journal of Chemical Physics, Vol. 21, Issue 6
Three-dimensional modeling and hydrodynamic scaling of National Ignition Facility implosions
journal, May 2019
- Clark, D. S.; Weber, C. R.; Milovich, J. L.
- Physics of Plasmas, Vol. 26, Issue 5
Capsule physics comparison of National Ignition Facility implosion designs using plastic, high density carbon, and beryllium ablators
journal, March 2018
- Clark, D. S.; Kritcher, A. L.; Yi, S. A.
- Physics of Plasmas, Vol. 25, Issue 3
Bayesian Experimental Design: A Review
journal, August 1995
- Chaloner, Kathryn; Verdinelli, Isabella
- Statistical Science, Vol. 10, Issue 3
Monte Carlo sampling methods using Markov chains and their applications
journal, April 1970
- Hastings, W. K.
- Biometrika, Vol. 57, Issue 1
Three-dimensional HYDRA simulations of National Ignition Facility targets
journal, May 2001
- Marinak, M. M.; Kerbel, G. D.; Gentile, N. A.
- Physics of Plasmas, Vol. 8, Issue 5
Works referencing / citing this record:
Analysis of NIF scaling using physics informed machine learning
journal, January 2020
- Hsu, Abigail; Cheng, Baolian; Bradley, Paul A.
- Physics of Plasmas, Vol. 27, Issue 1