The National Ignition Facility (NIF), the world’s most energetic laser system and the first to demonstrate fusion ignition, routinely operates at energies that can damage its final optics. To enable sustained operation, NIF recycles optics by ablating fractured material associated with damage, leaving behind a benign, cone-shaped void. These mitigation cones range in depth and diameter and typically are applied using the smallest effective cone for one damage site. However, when multiple damage sites are closely situated, various combinations of larger and smaller cones can be used to repair the region, and the number of options grows exponentially. Standard brute force approaches that iterate through each of these possibilities are thus computationally impractical beyond a relatively low threshold. To overcome these limitations, we introduce Combinatorial Optimization for OPtic Repair (COOPR), a novel combinatorial optimization framework to solve the problem of cone placement given any configuration of damage sites. Using tools from the seemingly unrelated literature on facility location problems in urban planning, we formulate and solve mixed-integer linear programs that identify optimal cone configurations for damage mitigation with respect to a multi-objective cost function. We show that even for optics with hundreds of clustered damage sites, COOPR finds more effective cone placements faster than existing approaches, thus enabling a more efficient optic mitigation cycle with a reduced need for human intervention.
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