Early Stage Innovations (ESI) 2023

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Advancing Radiation-Hardened Photon Counting Sensor Technologies

• Karl Berggren
  Massachusetts Institute of Technology
  Radiation hardness study of superconducting detectors and electronics
• Donald Figer
  Rochester Institute of Technology
  Advancing Radiation-Hardened CMOS Detectors for NASA Missions

Advancements in Predicting Plume-Surface Interaction Environments During Propulsive Landings

• Laura Villafane
  Auburn University
  Integrating Data-Driven and Physics-Based Models for Plume-Surface Interaction Predictions
• David Scarborough
  University of Illinois at Urbana-Champaign
  Physics-based Modeling and Tool Development for the Characterization and Uncertainty Quantification of Crater Formation and Ejecta Dynamics due to Plume-surface Interaction

Advancing the Performance of Refrigeration Systems Based on the Elastocaloric Effect

• Patrick Shamberger
  Texas A&M University
  Advancing Elastocaloric Refrigeration through Co-design of Materials and Systems
• Nenad Miljkovic
  University of Illinois at Urbana-Champaign
  Continuous Bending-mode Elastocaloric Composite Refrigeration System for Compact, Lightweight, High-Efficiency Cooling

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Loura Hall

Continuous Bending-mode Elastocaloric Composite Refrigeration System for Compact, Lightweight, High-Efficiency Cooling

Nenad Miljkovic
University of Illinois at Urbana-Champaign

Traditional elastocaloric refrigeration systems are based on uniaxial compression of the elastocaloric material which makes them highly constrained by actuator requirements, the physics of column buckling, and limited surface area for heat transfer. Professor Miljkovic will investigate a novel elastocaloric system based on bending of the elastocaloric material, which removes these constraints. The design requires less energy for equivalent performance and can be run in a continuous loop further increasing efficiency. The team will also investigate methods like heat treatment to tune the elastocaloric material to their application.

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Loura Hall

Advancing Elastocaloric Refrigeration through Co-design of Materials and Systems

Patrick Shamberger
Texas A&M University

Elastocaloric materials heat up or cool down when stress is applied to them or removed. The objective of this grant is to develop improved elastocaloric effect materials that are capable of performing more cooling work per cycle, more efficiently converting mechanical work to cooling work with minimal dissipation, and cycling at a faster rate. Professor Shamberger will use machine learning methods to design new elastocaloric materials, produce them, and characterize their performance. The group will then design and develop a full elastocaloric refrigerator architecture using their new materials to validate system level performance.

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Physics-based Modeling and Tool Development for the Characterization and Uncertainty Quantification of Crater Formation and Ejecta Dynamics due to Plume-surface Interaction

David Scarborough
Auburn University

Professor Scarborough will develop and implement tools to extract critical data from experimental measurements of plume surface interaction (PSI) to identify and classify dominant regimes, develop physics-based, semi-empirical models to predict the PSI phenomena, and quantify the uncertainties. The team will adapt and apply state-of-the-art image processing techniques such as edge detection, 3D-stereo reconstruction to extract the cratering dynamics, and particle tracking velocimetry to extract ejecta dynamics and use supervised Machine Learning algorithms to identify patterns. The models developed will establish a relationship between crater geometry and ejecta dynamics, including quantified uncertainties.

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Integrating Data-Driven and Physics-Based Models for Plume-Surface Interaction Predictions

Laura Villafane
University of Illinois at Urbana-Champaign

Rocket engine exhaust during lunar landings can blow away a large amount of lunar regolith causing damage to nearby hardware and the landing spacecraft itself. The complex physics governing this behavior is not well understood making it hard to predict and mitigate its effects. Professor Villafane’s team will use a multi-stage approach to address this issue, in which advanced image and data processing tools, statistical models, and modern machine learning algorithms are combined. The team will extract the most relevant quantities of interest for cratering, erosion, and ejecta from the large volume of parametric experimental data, and to use them to derive simple closed-form models of rocket plume – surface interaction phenomena.

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Loura Hall