# Los Alamos National Laboratory

# Computational Physics Student Summer Workshop

## 2020 Computational Physics Summer Workshop Projects

Please click on each project title for more information about a particular project.

Mentors: Ting Chen & Carene Larmat

Seismic waves are routinely used to discriminate between earthquakes and explosions. Geological structures control the propagation of seismic waves and affect our ability to analyze seismic signal to recover the original source properties. Data collected from explosions show a seismic energy partition between compressive and shear motion unexpectedly close to earthquakes. We will conduct numerical simulations to study the role of complex geologic structures in this phenomenon.

Mentors: Jonathan Regele & Yash Mehta

The objective of this project is to develop an understanding of how particle jetting phenomena occurs after an explosive sends particles away from a high pressure source. Numerical simulations will be performed of 2-D movable cylinders with different initial configurations and analyze how shock wave interactions with these cylinders lead to clustering and jetting. Dr. Regele has a custom made code that uses volume penalization to impose cylinders into a fluid and these cylinders move and collide with other cylinders as typical particles would. Full two-way momentum coupling exists between the particles and gas. These fully resolved 2-D simulations will develop insight into how the jetting phenomena occurs after explosive dispersal of particles.

Mentors: Daniel Sheppard, Daniel Rehn & Ann Mattsson

Many materials exhibit multiple crystalline phases that are stable under different temperatures, pressures, and densities. For example, iron can exist in both a body-centered cubic (BCC) phase and a face-centered cubic (FCC) phase. In this project, we will use a variety of computational techniques to accurately predict the stable phases and phase boundaries of specific materials under different temperatures, pressures, and densities. In particular, we will make use of density functional theory (DFT) software to compute thermodynamic quantities that can be used to construct phase diagrams for these materials. The overarching goal of the project will be to compare the predictions of different DFT-based methods, such as DFT-based molecular dynamics and DFT-based phonon calculations, and assess the differences and similarities in the predicted phase diagrams for these materials.

Mentors: Jeff Leiding, Stephen Andrews & Chris Ticknor

Understanding how matter behaves in extreme conditions is of importance to many areas of study, such as earth science, astrophysics, and weapons physics. The behavior of energetic materials is particularly intriguing. LANL has developed a thermochemical code called MAGPIE, which uses statistical mechanics to describe the behavior of molecular mixtures in extreme conditions. We are interested in studying how uncertainties in the input to MAGPIE (such as molecular properties) affect the resultant behavior of high explosives. Opportunities exist in this project to learn about high explosives, molecular physics, Bayesian techniques, uncertainty quantification, and hydrodynamic simulation of high explosives.

Mentors: Charles Starret, Nathaniel Shaffer & Chris Fontes

Warm dense matter lies at the poorly understood intersection of plasma, condensed matter, and atomic physics. At the atomic level, it is a complex slurry of quantum-mechanical, ionized electrons, and many different types of ions. Some material properties are described well with an atomic physics approach, while others require an accurate account of the state's disordered plasma character. Students will be tasked with coding a theoretical model for photon absorption in warm dense matter that lies at the intersection of these two worldviews. A successful project will result in an accurate, practical computational model of relevance to conditions in the solar interior, and to inertial-fusion plasmas.

Mentors: Matthew Price & Tariq Aslam

High explosive "reactive burn" models consist of an equation of state (EOS) for the unreacted material, an EOS for the detonation products, and a phenomelogical rate law that describes the reaction process. These models are used in simulations of shock initiation and detonation of explosives. Rate parameters in the models are inherently linked to the particular EOSs during the calibration process. While analytic EOSs (e.g. JWL and Davis EOSs) are typically used, they have limitations due to their functional form. We propose investigating a tabular EOS (SESAME) for use with the burn models, and assessing the benefits and challenges therein.

Mentors: Derek Armstrong, Eric Nelson & Garry Maskaly

For an electromagnetic pulse (EMP) application, the MCNP code is used for photon and neutron transport in air and to compute the energy deposition rate and photocurrent density. MCNP estimates these quantities as a function of space and time. The MCNP calculations are time consuming and can take weeks to complete. This project seeks to build and train deep neural networks to estimate the energy deposition rate and photocurrent density as a function of space, time, source particle type (neutron or photon), and source particle energy. The neural networks will be trained on MCNP results for photon and neutron transport in the atmosphere. The students will focus on building and training the neural networks and not on running MCNP to construct the training and testing data set. However, the students will be introduced to the topics of MCNP and EMP, and will learn to run MCNP for a few problems.

Mentors: Amy Lovell & Ionel Stetcu

The consistent calculation of prompt fission observables requires various inputs, many of which are parameterized. Sometimes, these inputs can be fit to experimental data before they are used within the full calculation, but to consistently constrain all of the inputs, a full optimization from all input model parameters to all fission observables should be performed. For this to be feasible, an emulator of the fission code must be constructed. In this project, the students will learn to run the LANL-developed fission code, CGMF, perform sensitivity studies with respect to the input parameters, and use these studies to construct an emulator for CGMF. This emulator will then be used to optimize the input models simultaneously to various prompt observables and propagate uncertainties through the model calculations.

Mentors: Jerawan Armstrong & Jim Ferguson

MCNP (**M**onte **C**arlo **N**-**P**article) is a general-purpose, continuous-energy, generalized-geometry, time-dependent, particle transport code. Complex nuclear systems that cannot be modeled by computer codes that implement deterministic methods are typically studied via Monte Carlo simulations. In order to run MCNP simulations, nuclear systems of interest must be modeled by using constructive solid geometries (CSG) and/or unstructured mesh geometries (UMG). The UMG model is the collection of finite elements and nodes generated by meshing tools, such as Abaqus or Cubit. The MCNP UMG capability is mostly used to model complex 3-dimensional nuclear systems. The CSG and UMG particle tracking algorithms are implemented differently in MCNP. Unlike the CSG feature, the MCNP UMG feature is not well verified. This project proposes to study some selected equivalent CSG and UMG models. For example, the benchmarks of the Godiva critical assembly of HEU and Oktavian 14 MeV neutron source will be modeled and analyzed. The simulation results from these two different models will be compared to verify the MCNP UMG code implementations. Students will learn how to model and simulate the selected nuclear systems in MCNP and analyze the simulation results.

Mentors: Pete Maginot & Andrew Till

There exists a long standing assumption in radiation hydrodynamics calculations that the thermal radiative transfer (TRT) equations must be solved on the same mesh as the hydrodynamics equations. However, the standard spatial discretizations employed in deterministic TRT simulations, discontinuous finite element methods, have multiple spatial degrees of freedom per mesh cell as compared to the single spatial degree of freedom of current finite volume hydrodynamics codes, e.g. xRAGE. Given the significantly higher (relative) computational cost of solving the TRT equations versus the hydrodynamics equations, we seek to answer, “Can one solve the TRT equations on a coarser grid than the hydrodynamics equations?”. We seek students interested in Eulerian hydrodynamics, discrete-ordinates thermal radiative transfer, the coupling of the two, or those eager to learn about how these two separate single physics interact in a multi-physics environment, to assist in our investigation of this paradigm shifting idea.

Mentors: Matt Hudspeth & Mike Prime

Students will be asked to calibrate a constitutive model based on numerical simulation of a Richtmyer-Meshkov instability in solid media driven via shock loading. Using recently captured data sets, students will probe the effect of strain-rate, drive pressure, and temperature on the resulting material strength, and will then be asked to fit this within a constitutive model framework (e.g. Preston-Tonks-Wallace). Finally, students will be asked to determine required drive conditions (explosive or flyer-plate) to further calibrate their proposed constitutive model, and to assess viability of such conditions within the confines of experimental limitations.

Mentor: Baolian Cheng

Plasma jets are ubiquitous in nature, from astrophysics to high energy density (HED) plasmas. Particularly, it has been observed in inertial confinement fusion capsules at the National Ignition Facility that jets formed during the implosion of capsules can degrade the thermonuclear burn of DT fuel. In this study, we propose to study and simulate the jet dynamics and its interactions with surrounding hot plasmas using code FLAG.