Deepak V. Kulkarni

A Domain Decomposition Based Two-Level Newton Scheme for Nonlinear Problems

We present two non-overlapping domain decomposition based two-level Newton schemes for solving nonlinear problems and demonstrate their effectiveness by analyzing systems with balanced and unbalanced nonlinearities. They both have been implemented in parallel and show good scalability. The implementations accommodate non-symmetric matrices and unstructured meshes.

A Discontinuous Galerkin Formulation for Solution of Parabolic Equations on Nonconforming Meshes

Non-conforming meshes are frequently employed in multi-component simulations and adaptive refinement. In this work we develop a discontinuous Galerkin framework capable of accommodating non-conforming meshes and apply our approach to analyzing the transient heat conduction problem.

IC Substrate Package Yield Prediction Model and Layer Level Risk Assessment by Design Analysis

We present a method for quantifying a risk for killer defects at layer level and estimating yield for substrate packages using information from design files. To calculate risk ranks and predicted yield, we define a risk distance that is a key parameter extracted from designs using image processing techniques. In order to validate our model, we analyze two different designs, each having multiple layers, and compare with data from baseline lots. It is shown that there is an inverse correlation between risk layer ranks and yield. Estimated yield based on our model is compared with baseline yield for four layers of the second design. The model-to-baseline yield difference is less than 1% for three layers we tested.