In this paper, we propose a novel design-for-manufacture strategy for integrated photonics which specifically addresses the commonly encountered scenario in which probability distributions of the manufacturing variations are not available, however their bounds are known. The best design point for the device, in the presence of these uncertainties, can be found by applying robust optimization. This is performed by minimizing the maximum realizable value of the objective with respect to the uncertainty set so that an optimum is found whose performance is relatively immune to fabrication variations. Instead of applying robust optimization directly on a computationally expensive simulation model of the integrated photonic device, we construct a cheap surrogate model by uniformly sampling the simulated device at different values of the design variables and interpolating the resulting objective using a Kriging metamodel. By applying robust optimization on the constructed surrogate, the global robust optimum can be found at low computational cost. As an illustration of the method's general applicability, we apply the robust optimization approach on a 2x2 multimode interference (MMI) coupler. We robustly minimize the imbalance in the presence of uncertainties arising from variations in the fabricated design geometry. For this example device, we also study the influence of the number of sample points on the quality of the metamodel and on the robust optimization process.
In this paper we present an algorithm that maps a reference diffracting structure along an arbitrarily curved boundary. The proposed algorithm produces deformed photonic crystal lattice patches with minimal angular distortion of its unit cells, thus realizing a discrete quasi-conformal transformation of the dielectric map. We then investigate the field confinement characteristics of some curved waveguide devices realized by such structures.
This article illustrates the opportunities that combining computational modeling and systematic design optimization
techniques offer to facilitate the design process of shape memory alloy (SMA) structures. Focus is on
shape memory behavior due to the R-phase transformation in Ni-Ti, for which a dedicated constitutive model is
formulated. In this paper, efficient topology and shape optimization procedures for the design of SMA devices are
described. In order to achieve fast convergence to optimized designs, sensitivity information is computed to allow
the use of gradient-based optimization algorithms. The effectiveness of the various optimization procedures is
illustrated by numerical examples, including the design of a miniature SMA gripper and a steerable SMA active
catheter. It is shown that design optimization enables designers of SMA structures to systematically enhance
the performance of SMA devices for a variety of applications.