CURRENT PROJECTS

Autonomous Aerobraking Technology Development

Sponsor: NASA JPL, University of Illinois

Aerobraking uses drag generated over many passes through the upper atmosphere of a planet to reduce orbital energy and reduce propellant needs. Although performed successfully by recent Mars missions (MRO, Odyssey, MGS), aerobraking campaigns remain operationally intensive and require 24-7 monitoring by ground teams to ensure mission success. The goal of this project is to develop technology, based on recent advances in machine learning techniques, to automate mission planning and operations for aerobraking at the campaign level. This technology will enable detailed mission design studies of aerobraking campaign options and potentially reduce the operational cost and time required to successfully execute aerobraking campaigns.

Deep Space Navigation using X-ray Pulsars

Sponsor: NASA Johnson Space Center, University of Illinois

Current deep space missions are dependent on Earth-based ground stations for navigation state estimates. Pulsars emit stable, predictable X-ray signals that may be used in lieu of ground stations to update spacecraft position and velocity estimates. However, current concept still require initial state knowledge to effectively use the X-ray data. This effort is focused on developing position and velocity state estimates using  X-ray navigation without initial states from the ground, also known as the “cold start” or “lost in space” problem. The ability to solve the cold start problem onboard a spacecraft will improve spacecraft autonomy, reduce mission risk, and help to unload the already oversubscribed Deep Space Network.

Linear Covariance Analysis for Estimating Sensor- and Trajectory-Dependent Navigation Error

Sponsor: Sandia National Laboratory

Linear Covariance Analysis Capability Development for Guided Entry Systems

Partner: NASA Johnson Space Center

Current uncertainty analysis for guided entry systems often use Monte Carlo methods, which can be computationally expensive, especially in early-mission phases. An alternative uncertainty analysis method with heritage in many other phases of spaceflight is linear covariance analysis, which can provide similar statistical information as Monte Carlo methods with a single trajectory integration. This project is focused on extending linear covariance analysis capability to six-degree-of-freedom guided entry systems to complement Monte Carlo methods for early-mission uncertainty analysis. Using linear covariance analysis in this way will also enable a deeper understanding of the performance of guidance algorithms through direct uncertainty analysis of guidance-internal parameters.

Sponsor: NASA Space Technology Mission Directorate

As Mars mission goals develop, larger payloads must be landed on the surface with high precision. Recent advancements in electromagnets have made leveraging magnetohydrodynamic effects a possibility for planetary entry. A magnetic field can interact with the ionized flow to reduce heating, shorten the blackout period, and develop force. This project explores how magnetohydrodynamic forces can be utilized as a control mechanism to enable landing larger payloads and/or increase landing precision.

Sponsor: DARPA

An Approach for Assessing the Entry Performance of Different Direct Force Control Vehicle Configurations During Mars Entry

Sponsor: NASA Space Technology Mission Directorate

PAST PROJECTS

Utilization of Self-Healing Materials in Thermal Protection System Applications

2016-2021

Sponsor: NASA Space Technology Mission Directorate

Current technology for repairing thermal protection systems from micrometeor and orbital debris impact damage has a low Technology Readiness Level (TRL) and there are no repair materials currently available for use. The proposed plan for advancing self-healing TPS consists of four stages: manufacturing, thermal testing, self-healing testing, and thermal testing of healed samples. Placing the material in arc jets with relevant reentry environments will test the thermal response of the material. Impacting or damaging the integrated material will test self-healing properties. After performing this research, self-healing TPS will be ready for testing in relevant space environments by measuring material responses in vacuum and at extreme varying temperatures.

Student Aerothermal Spectrometer Satellite of Illinois and Indiana (SASSI²)

2016-2019

Sponsor: NASA Science Mission Directorate

Partner: Purdue University

SASSI2 will characterize the flow field and radiation generated by the diffuse bow shock formed during high-speed flight through the upper atmosphere. Optical spectrographic measurements of the radiation will provide benchmark data for fundamental flow, radiation, and materials modeling, resulting in improved prediction of the aerothermodynamic environment encountered by bodies entering the atmosphere, including entry vehicles, meteors, and large impactor ejecta. Novel MEMS-based pressure and temperature sensors will characterize the free-stream and help interpret spectrometer data; successful flight of these sensors will space-qualify them for future picosat missions. The goal of this project is to develop industry-critical skills in undergraduate students while pursuing a meaningful science investigation. The undergraduate student team has responsibility for all project roles, with multiple faculty members at each participating university providing mentoring, guidance, and training.

Chariot to the Moons of Mars

Hypersonic Trajectory Control via Moving-Mass Actuation

2015-2016

Sponsor: University of Illinois