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Ultra-intense laser and plasma interactions with their ability to accelerate particles reaching relativistic speed are exciting from a fundamental high-field physics perspective. Such relativistic laser-plasma interaction (RLPI) offers a plethora of critical applications for energy, space, and defense enterprise. At AFIT’s Extreme Light Laboratory (ELL), we have demonstrated such RLPI employing a table-top ∼10mJ, 40 fs laser pulses at a kHz repetition rate that produce different types of secondary radiations via target normal sheath acceleration (TNSA). With our recent demonstration of laser-driven fusion, the secondary radiations generated are neutrons, x-ray emission, and MeV energy electrons and protons—all at a kHz rate. To achieve the high repetition rate, we developed the enabling kHz-repetition-rate-compatible liquid targets in the form of microjets, droplets, and submicron-thick sheets. These targets, combined with high repetition rate diagnostics, enable a unique, real-time feedback loop between the experimental inputs (laser and target parameters) and generated sources (x-rays, electrons, ions, etc.) to develop machine learning (ML)-based control of mixed radiation. The goal of this paper is to provide an overview of the capabilities of ELL, describe the diagnostics and characteristics of the secondary radiation, data analysis, and quasi-real-time ML functionality of this platform that have been developed over the last decade and a half.
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CFD Modeling of Droplets Heated by an X-ray Free Electron Laser
Material in HED regimes are at very high pressures and temperatures but can often still be modeled in the plasma-fluid approximation. Historically HED regimes were created using large laser/ion- beam drivers heating solid targets. Exciting data was obtained from these single shot experiments. In recent years there has been a shift to obtain HED related data from a large number of shots by using high-repetition-rate drivers. For high-repetition-rate experiments a series of droplet targets are often used to have a fresh target/droplet for each shot. However, one must make sure that target debris from the previous shot does not degrade the target for subsequent shots. This is a challenging CFD problem as one needs to model the initial dynamics of the heated droplet and the subsequent interaction with the following droplets. We use the CFD modeling code PISALE to study this complex problem. We discuss results for liquid hydrogen droplets heated by an x-ray free electron laser (XFEL). We first show 2D results for single heated droplet then 3D results for a heated droplet interacting with two unheated droplets.
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- Award ID(s):
- 2005259
- PAR ID:
- 10420558
- Date Published:
- Journal Name:
- Proceedings of the International Conference on Computational Fluid Dynamics
- ISSN:
- 2330-6580
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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