Efficient buckling constrained topology optimization using reduced order modeling

Reduced Order Constrained Optimization (ROCO):

Purpose: We use reduced-order constrained optimization (ROCO) to create clinically acceptable IMRT plans quickly and automatically for advanced lung cancer patients. Our new ROCO implementation works with the treatment planning system and full dose calculation used at Memorial Sloan-Kettering Cancer Center, and we have implemented mean dose hard-constraints, along with the point-dose and dose-v...

Reduced-order constrained optimization in IMRT planning.

This paper presents a new algorithm for constrained intensity-modulated radiotherapy (IMRT) planning, made tractable by a dimensionality reduction using a set of plans obtained by fast, unconstrained optimizations. The main result is to reduce planning time by an order of magnitude, producing viable five field prostate IMRT plans in about 5 min. Broadly, the algorithm has three steps. First, we...

A Novel Filter Trust-region Algorithm for Constrained Optimization Using Reduced Order Modeling

Reduced order models (ROM) lead to powerful techniques to address computational challenges in PDE-constrained optimization. However, when incorporated within optimization strategies, ROMs are sufficiently accurate only in a restricted zone and thus, need to be systematically updated over the course of the optimization. As an enabling strategy, trust-region methods provide an excellent adaptive ...

Continuum Topology Optimization of Buckling-Sensitive Structures

Two formulations for continuum topology optimization of structures taking buckling considerations into account are developed, implemented, and compared. In the first, the structure undergoing a specified loading is modeled as a hyperelastic continuum at finite deformations, and is optimized to maximize the minimum critical buckling load. In the second, the structure under a similar loading is m...

Reduced-Order Galerkin Approximations in PDE Constrained Optimization