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OSTP memo guides space nuclear plan
A White House Office of Science and Technology Policy (OSTP) memorandum released on Tuesday guides NASA, the Department of Energy, and the Department of Defense on their roles in deploying near-term space nuclear power.
This follows a series of NASA announcements last month—driven by the executive order “Ensuring American Space Superiority,” issued by Trump in December—including an ambitious timeline for establishing a moon base, which would rely on fission surface power (FSP) to survive the long lunar night at the moon’s south pole, and plans for a nuclear electric propulsion (NEP) rocket to be launched in 2028.
Colin A. Weaver, Christopher M. Perfetti, Michael E. Rising
Nuclear Science and Engineering | Volume 199 | Number 1 | April 2025 | Pages S797-S807
Research Article | doi.org/10.1080/00295639.2024.2380607
Articles are hosted by Taylor and Francis Online.
A numerical code library was developed for the radiation transport code MCNP6.3 to calculate generalized response sensitivity coefficients for fixed source neutron transport problems with applications to inertial confinement fusion (ICF) experiments. The new MCNP6.3 dependency is used to generate a novel time convolution response that represents a neutron time-of-flight (nToF) signal. The traditional suite of macroscopic cross-section sensitivities and constrained fixed source probability distribution sensitivities are available for both the standard and the new response tallies in this library. However, novel sensitivity coefficients for the constrained hyperparameters of analytic fixed source probability distributions are emphasized in this work for their connection to ICF neutron transport models. Particularly, advanced Monte Carlo methods are developed for calculating the sensitivity of a nToF signal to perturbations in an ICF plasma’s ion temperature and burn history as well as perturbations in the target liner mass density and the shape parameters of the nToF detector’s impulse response function. Together, these capabilities form an advanced suite of computational tools that can be used to analyze and extract information from any ICF experimental platform.