Workshop Overview

Two teams of participants work under the guidance of one or more mentors. A fellowship is awarded to each participant and typically ranges from $9,000 to $17,000, based on academic rank (junior, senior, first-year graduate student). Lectures, teamwork and mentoring help students learn about computational physics and enhance their careers. Shared technical goals help students build future connections. Social events and tours enhance the workshop experience, promoting team-building and creating lasting memories and professional relationships.

Application Guidelines

We invite applications from graduate students and advanced undergraduates (minimum of at least one year of college or university).  Applications must be submitted online.  The application process requires a cover letter, resume, and contact information for a letter of recommendation.  Students will also need to select their top three research project choices.  Descriptions of this years projects will be posted on the application website.

Fellowship Stipend

Participants will receive a fellowship stipend, paid in three installments during the summer. Travel, food, and housing are the participants' responsibilities. Resources to find summer housing, often in short supply, are provided. 

XCP Summer School Projects 2024

Using Simulation to Optimize Pulsed Beam DIagnostic Design and Analyze Data from Pulsed Power Experiments

Christopher Johnson (NEN-2), Kevin Meaney (P-4)

Radiographic pulsed x-ray sources such as the Dual-Axis Radiographic Hydrodynamic Test Facility (DARHT), Cygnus, and the upcoming Scorpius are fundamental tools for the Science-Based Stockpile Stewardship Program. In any beam-on-target experiment where beam-target interaction products are measured to infer properties of the target, enhancing the understanding of the beam characteristics (energy, intensity, and timing) improves the fidelity of the measurement. The goal of this project is to design a system of Cherenkov radiator detectors (of varying densities and signal generation thresholds) to be fielded in the DARHT beam to measure the time-dependent x-ray energy spectrum. This concept places design constraints on the system that require a unique light collection system composed of wavelength shifters, chromatic filters, optical fibers, irises and lenses to harvest light from the detector and transport the signal to a remotely housed light sensor. This project will provide many opportunities for students to contribute by using radiation and optical simulation calculations both in the detector design and characterization phase and upon analysis of experimental data obtained with the detectors when fielded. Students will learn to build applications with the Geant4 simulation toolkit to couple radiation and optical transport, optimize the detector and light transport system design, and simulate parts of the pulsed-power experiments. The ideal candidate would have some experience with physics, radiation detection, C++, and the root data analysis framework.

Sensitivity analyses of simulations of fluid jetting from shocked metal surfaces

Bryan Kaiser (XCP-8), Jesse Canfield (XCP-4)

The students will run 2D simulations of shocked metals with grooves and bumps on the free surface of the metal. As the shock passes, the grooves and bumps eject mass at a much higher rate than the velocity of the free surface. The quantity of the ejecta is a nonlinear function of cavity geometry, shock loading, shock geometry, and other variables. The students will use already existing validated code to generate, run, and post-process large sets of Flag simulations over which the students will vary physical parameters (e.g., strength model parameters, shock loading) and/or numerical parameters (e.g., grid resolution, ALE scheme parameters) to generate sensitivity studies. The simulation sensitivity studies will be plotted against already existing experimental data to provide calibration information for physical parameters or to illuminate the sensitivity of the simulation output to numerical parameter choices. If successful, the sensitivities studies will be included in the section of a publication in which model parameter choices are defended. Students interested in turbulence modeling, baroclinic vorticity, Richtmyer-Meshkov Instability, secondary instabilities, equation of state modeling, and/or ejecta modeling are encouraged to apply.

Modeling optical properties of plasmas and warm dense matter

Joseph Kasper (XCP-5), Charles Starrett (XCP-5)

Understanding the properties of plasmas and materials at high densities and temperatures, such as those in stars or inertial confinement fusion remains an important field of research in atomic physics. Optical properties and equation of state are key physical parameters for physics models. In this project we will develop and apply approaches such as time-dependent density functional theory to model and evaluate these properties for warm dense matter. This will also provide an opportunity to implement or extend models in computer code and write a publication for a peer-reviewed journal.

Materials simulations under high impact

JeeYeon Plohr (XCP-5)

"Material response under extreme conditions is a challenging and interesting topic to explore. Examples include the structural engineering, fusion reactor environment, and astrophysical conditions.  Often the experimental data are not available in the pressure and temperature regimes of interest, and the predictive modeling plays an important role.

In this project, we will calibrate the material model parameters using the Bayesian framework and perform high impact, multi-physics simulations in the LANL's Lagrangian code, FLAG. Various loading scenarios as well as geometry will be studied and investigated.

Investigating the volumetric energy deposition Rayleigh Taylor instability with xRAGE

Brandon Wilson    XCP-8    Filipe Pereira    XCP-8    Ally Leffler    XCP-8

The Rayleigh Taylor instability occurs when an unstable interface between a heavy fluid and a light fluid is subject to gravitational acceleration. In 2023, the volumetric energy deposition (VED) Rayleigh Taylor instability was observed by students in the Los Alamos Dynamic Summer School (LADSS). This was the first time this instability was observed experimentally. In this project, students will develop and perform simulations of the VED Rayleigh Taylor instability. Predictions will be compared to experimental measurements using verification, validation, and uncertainty quantification practices. If a parallel LADSS project is chosen, students will have the chance to work with experimentalists acquiring new measurements and inform experimental design for future VED Rayleigh Taylor experiments.

Triggering Kinetic Magnetic Reconnection

Ari Le (XCP-6), Adam Stanier (T-5), Fan Guo (T-2)

In space and astrophysical plasmas, energy may slowly be stored in the magnetic fields and plasma currents, and this energy is then explosively released when magnetic reconnection is triggered. Reconnection rearranges the magnetic field line topology and energizes the plasma in solar and astrophysical flares, geomagnetic storms in Earth’s magnetic tail, and disruptions in magnetic fusion devices. While reconnection releases the global stored energy of space plasmas, its trigger or onset typically depends on small kinetic-scale plasma physics dynamics. This project will use kinetic and hybrid (kinetic ion/fluid electron) versions of LANL’s high-performance particle-in-cell code VPIC to study the global-to-kinetic coupling of reconnection onset in multi-ion species plasmas.

Sub-grid modeling of reactive burn in high explosive materials

Josh McConnell (XCP-2), CJ Solomon (XCP-2)

Resolving the reaction zone of a detonation front is important for predicting the behavior of detonating high explosive (HE). The practicality of running high explosives calculations with a reactive burn model is limited by the resolution requirements of the chosen burn model.  A potential work-around for the restrictive resolution requirements typical of reactive burn models is to presume the form of the joint probability density function (PDF) of a reaction model’s input variables (e.g. pressure, burn fraction, temperature) and computing the expected burn rate by convolving the rate law with the joint PDF conditioned on one or more scalar variances. 

The  goal of this summer project is to apply a presumed PDF approach to a reactive burn model, such as the Wescott-Stewart-Davis model, and determine the efficacy of this approach. The first part of this project will consist of running fully-resolved simulations of a detonating HE and using the resulting data to form an appropriate form of the presumed PDF for the burn model’s input variables. After a form of the PDF is determined, the presumed PDF approach will be applied to the target burn model and tested by running computations on a coarsened mesh and comparing to fully-resolved simulations.

Reduced order modeling for RANS verification

Daniel Israel (XCP-4), Arvind Mohan (CCS-2)

Conventionally, RANS models are calibrated using a self-similar solution.  However, much of the available data is not taken at the asymptotic self-similar state, nor is this the regime in which the models are primarily used.  We have developed a new method of creating a reduced-order surrogate model to use for model calibration and validation.  This model takes the form of a dynamical system.  Students will post-process data to obtain trajectories for this system, and use advanced optimization tools to calibrate and validate RANS models.

Kinetic Simulations of Magnetic Mirror Fusion Devices

Blake Wetherton (XCP-6), Scott Luedtke (XCP-6), Alex Seaton (XCP-6)

Magnetic mirrors are the simplest geometry magnetic fusion concept, and new devices are being built inspired by the advent of high temperature superconducting coils and some promising stability results in recent experiments. Students will run simulations of magnetic mirrors in the fully-kinetic VPIC code and/or its fluid electron/kinetic ion counterpart, Hybrid VPIC, with a focus on the physics of sloshing ions. Sloshing ions are energetic (tens of keV) fusion fuel ions injected as a beam, and they are believed to increase fusion efficiency and to help stabilize the mirror. Both the effects of the sloshing ions on mirror stability and the evolution of the sloshing ion distribution will be investigated.

Material Modeling for Dynamic Experiments

Kendra Van Buren (XCP-8), Sean Smith (XCP-8), Saryu Fensin (MPA-CINT)

This project will explore modeling choices used to simulate the deformation of metal samples undergoing planar shocks. These experiments, known as the "Lens" experiments to describe how the plane-wave shock is generated, were performed at LANL's Proton-Radiography (pRad) facility. The simulations will be performed with FLAG, a lagrangian hydrodynamics code developed at LANL. Of particular interest is to gain a better understanding of how metal samples with defects deform under shock-loading, and how our computational tools capture these effects. Some of the modeling choices that could be explored are: material strength parameters, material spall parameters, and defect sizes in the sample. Details and scope of the computational study may be adjusted based on student's research interests.

Application of Machine Learning in Nuclear Data Evaluation

Hirokazu Sasaki (T-2)

Nuclear Data libraries, which contain information about the interaction of particles with nuclei, are carefully curated from experimental data and theoretical predictions. This data includes details about nuclear reactions, such as their reaction probability (cross section), decay yields, spectra of the outgoing particles etc. and are used to understand/predict the behavior of particles in nuclear systems, such as nuclear reactors, astrophysical processes, radiography, gamma-based interrogation techniques etc. As such, any inaccuracies and imprecision in the nuclear data gets propagated to the uncertainties in the application of interest. Until recently, most general purpose nuclear data libraries have utilized Bayesian approach to tune the theory model input parameters to fit the experimental data. In this project, the student(s) will explore machine learning based approach to combine the theoretical models with experimental data to come up with evaluated nuclear data for specific reaction channels and physics observables. Upon the successful completion of this work, the work will be published in peer reviewed journals.