SOLVING INVERSE TRANSPORT PROBLEMS USING DIFFERENTIABLE SIMULATIONS
Access to this document is restricted. Some items have been embargoed at the request of the author, but will be made publicly available after the "No Access Until" date.
During the embargo period, you may request access to the item by clicking the link to the restricted file(s) and completing the request form. If we have contact information for a Cornell author, we will contact the author and request permission to provide access. If we do not have contact information for a Cornell author, or the author denies or does not respond to our inquiry, we will not be able to provide access. For more information, review our policies for restricted content.
The reconstruction of real-world phenomena represents a crucial and challenging problem with broad relevance to both entertainment and scientific applications. This thesis addresses this by studying inverse problems within transport theory, which includes both radiative transfer and neutron transport, where the field's energy distribution is described by transport equations. A central challenge involves accurately determining the parameters of these equations from empirical or target radiation data, such as reflectance and transmittance. My thesis details three distinct works that contribute to the inversion of transport theory and its applications in reconstruction and design optimization across various disciplines. The initial work introduced a software pipeline designed to reconstruct the geometry and optical properties of semi-translucent objects from photographic input. Building upon this, the second work proposed the integration of hardware and software to facilitate the reconstruction of translucent thin-layered objects from photographs. The third work develops a theoretical framework and a gradient-based method for the shielding design of nuclear reactors using differentiable neutron transport simulation.