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Posts

Future Blog Post

less than 1 minute read

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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Blog Post number 2

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Chaos in the quantum Duffing oscillator in the semiclassical regime under parametrized dissipation

Physical Review E, 2021

We study the quantum dissipative Duffinng oscillator across a range of system sizes and environ- mental couplings under varying semiclassical approximations. Remarkably, we find that a parametrically invariant meta- attractor emerges at a specific length scale and noise-added classical models deviate strongly from quantum dynamics below this scale. Our findings also generalize the previous surprising result that classically regular orbits can have the greatest quantum-classical differences in the semiclassical regime. In particular, we show that the dynamical growth of quantum-classical differences is not determined by the degree of classical chaos.

Recommended citation: Maris, Andrew D., Bibek Pokharel, Sharan Ganjam Seshachallam, Moses ZR Misplon, and Arjendu K. Pattanayak. "Chaos in the quantum Duffing oscillator in the semiclassical regime under parametrized dissipation." Physical Review E 104, no. 2 (2021). https://journals.aps.org/pre/abstract/10.1103/PhysRevE.104.024206

Investigating Boosted Decision Trees as a Guide for Inertial Confinement Fusion Design

Physics of Plasmas, 2023

Inertially confined fusion experiments at the National Ignition Facility have recently entered a new regime approaching ignition. Improved modelling and exploration of the experimental parameter space were essential to deepening our understanding of the mechanisms that degrade and amplify the neutron yield. The growing prevalence of machine learning in fusion studies opens a new avenue for investigation. In this paper, we have applied the Gradient Boosted Decision Tree (GBDT) machine learning architecture to further explore the parameter space and find correlations with the neutron yield, a key performance indicator. We find reasonable agreement between the measured and predicted yield, with a mean absolute percentage error on a randomly assigned test set of 35.5%. This model finds the characteristics of the laser pulse to be the most influential in prediction, as well as the hohlraum laser entrance hole diameter and an enhanced capsule fabrication technique. We used the trained model to scan over the design space of experiments from three different campaigns to evaluate the potential of this technique to provide design changes that could improve the resulting neutron yield. While this data-driven model cannot predict ignition without examples of ignited shots in the training set, it can be used to indicate that an unseen shot design will at least be in the upper range of previously observed neutron yields.

Recommended citation: Maris, Andrew D., Shahab F. Khan, Michael M. Pokornik, J. Luc Peterson, Kelli D. Humbird, and Steven W. Haan. "Investigating boosted decision trees as a guide for inertial confinement fusion design." Physics of Plasmas 30, no. 4 (2023): 042713. https://pubs.aip.org/aip/pop/article/30/4/042713/2882225/Investigating-boosted-decision-trees-as-a-guide

The impact of disruptions on the economics of a tokamak power plant

Fusion Science and Technology, 2023

Tokamaks are often considered to be a leading candidate for near term, cost-effective fusion energy, but these devices are susceptible to sudden loss of confinement events called “disruptions.” The threat of disruptions has garnered serious attention in research for the next generation of burning plasma experiments, such as ITER, but has received little treatment in economic studies of magnetic fusion energy. In this paper, we present a model for quantifying the effect of disruptions on the cost of electricity produced by a tokamak power plant (TPP). We outline the various ways disruptions increase costs and decrease revenues, introduce metrics to quantify these effects, and add them to a Levelized Cost of Electricity (LCOE) model. Additionally, we identify several rate-limiting repair steps and introduce a classification system of disruption types based on the time to return to operations. We demonstrate how the LCOE model can be used to find the cost of electricity and requirements for disruption handling of a TPP, and we further highlight where future research can have a strong impact in neutralizing the “showstopping” potential of disruptions.

Recommended citation: Maris, Andrew D., Allen Wang, Cristina Rea, Robert Granetz, and Earl Marmar. "The impact of disruptions on the economics of a tokamak power plant." Fusion Science and Technology (2023).

talks

The impact of disruptions on the economics of a tokamak power plant

Published:

Tokamaks are often considered a leading candidate for near term, cost-effective fusion energy, but these devices are susceptible to sudden loss of confinement events called “disruptions.” The threat of disruptions has garnered serious attention in research and development for the next generation of burning plasma experiments, such as ITER, but has received little treatment in economic studies of magnetic fusion energy. In this talk, we present a model for quantifying the effect of disruptions on the cost of electricity produced by a tokamak power plant (TPP). We outline the various ways disruptions increase costs and decrease revenues, introduce metrics to quantify these effects, and add them to a Levelized Cost of Electricity (LCOE) model. Additionally, we identify several rate-limiting repair steps and introduce a classification system of disruption types based on the time to return to operations. We demonstrate how the LCOE model can be used to find the cost of electricity and requirements for disruption handling of a TPP, and we further highlight where future research can have a strong impact in neutralizing the “showstopping” potential of disruptions

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.