MIT researcher Taylor Hampson develops computational models to overcome critical challenges in nuclear thermal propulsion systems, potentially halving Mars transit times compared to conventional rockets.

For interplanetary missions to Mars, conventional chemical propulsion systems face fundamental limitations in efficiency and transit duration. Taylor Hampson, a master's student in MIT's Department of Nuclear Science and Engineering, is addressing this challenge through advanced modeling of nuclear thermal propulsion (NTP) systems. His NASA-sponsored research focuses on overcoming the operational complexities that have hindered practical implementation of this promising technology.
The Efficiency Advantage
NTP systems utilize nuclear reactors to heat propellants like hydrogen to extreme temperatures (~2700°C) before expulsion through a nozzle. This approach fundamentally differs from chemical rockets that rely on combustion. "You can achieve double the specific impulse or more compared to chemical rockets with equivalent thrust," Hampson explains. "For Mars missions, this translates to potentially halving transit times from 6-9 months to just 3-4 months."
Taylor Hampson models nuclear thermal propulsion systems that could revolutionize Mars missions (Credit: Gretchen Ertl)
The reduced transit time addresses critical human factors: prolonged exposure to microgravity causes muscle atrophy and bone density loss at approximately 1-2% per month. Shorter journeys also decrease radiation exposure during transit through unshielded space.
Modeling Complex System Interactions
Hampson's research centers on developing one-dimensional computational models that simulate the entire NTP engine system—including propellant tanks, turbopumps, reactor core, and nozzle. This integrated approach is necessary because:
- Thermal-neutronic coupling: Neutron flux affects heat generation, while temperature changes influence neutron moderation
- Transient behavior: Unlike combustion engines, NTP systems exhibit complex startup/shutdown dynamics due to residual decay heat
- Material constraints: Fuel elements must withstand extreme thermal gradients without structural failure
"The challenge lies in accurately simulating how temperature fluctuations in one component propagate through the entire system during dynamic operations," Hampson notes. His models account for variables like propellant flow rates, control rod positioning, and reactor power levels to predict performance under various mission profiles.
Technical Hurdles and Solutions
Key challenges Hampson's work addresses include:
- Startup sequencing: Rapid power increases risk thermal shock in fuel elements. Models optimize ramp-up procedures
- Decay heat management: Post-shutdown, radioactive decay continues generating 5-7% of full power heat, requiring sustained cooling
- Fuel performance: Testing novel tri-structural isotropic (TRISO) fuels in MIT's research reactor (MIT Nuclear Reactor Laboratory) provides material behavior data
- System efficiency: Balancing hydrogen dissociation losses against temperature gains in the reactor core
MIT's research infrastructure supports advanced nuclear propulsion development (Credit: MIT News)
Implementation Pathways
While NTP offers compelling performance advantages, practical deployment faces regulatory and infrastructure hurdles. Hampson's research informs:
- Ground test facility designs requiring contained exhaust capture
- Mission architecture studies for Mars transit vehicles
- Fuel qualification standards under NASA's Space Nuclear Propulsion program
"The technology readiness is advancing," Hampson observes. "Our models help identify which engineering compromises yield the optimal balance between performance, safety, and cost." With NASA targeting crewed Mars missions in the 2030s, this research provides critical data for mission planners weighing NTP against alternatives like nuclear electric propulsion.
Hampson continues refining his models while preparing for doctoral research, leveraging MIT's unique combination of nuclear and aerospace expertise. His work exemplifies how computational approaches accelerate development of technologies that may transform humanity's capacity for deep space exploration.

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