Automated Netlist Generation for 3D Electrothermal and Electromagnetic Field Problems

We present a method for the automatic generation of netlists describing general three-dimensional electrothermal and electromagnetic field problems. Using a pair of structured orthogonal grids as spatial discretisation, a one-to-one correspondence between grid objects and circuit elements is obtained by employing the finite integration technique. The resulting circuit can then be solved with any standard available circuit simulator, alleviating the need for the implementation of a custom time integrator. Additionally, the approach straightforwardly allows for field-circuit coupling simulations by appropriately stamping the circuit description of lumped devices. As the computational domain in wave propagation problems must be finite, stamps representing absorbing boundary conditions are developed as well. Representative numerical examples are used to validate the approach. The results obtained by circuit simulation on the generated netlists are compared with appropriate reference solutions.Comment: This is a pre-print of an article published in the Journal of Computational Electronics. The final authenticated version is available online at: https://dx.doi.org/10.1007/s10825-019-01368-6. All numerical results can be reproduced by the Matlab code openly available at https://github.com/tc88/ANTHE

Overview of Large-Scale Computing: The Past, the Present, and the Future

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Derivation of the bidomain equations for a beating heart with a general microstructure

A novel multiple scales method is formulated that can be applied to problems which have an almost\ud periodic microstructure not in Cartesian coordinates but in a general curvilinear coordinate system.\ud The method is applied to a model of the electrical activity of cardiac myocytes and used to derive a\ud version of the bidomain equations describing the macroscopic electrical activity of cardiac tissue. The\ud treatment systematically accounts for the non-uniform orientation of the cells within the tissue and for\ud deformations of the tissue occurring as a result of the heart beat

Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks

The Partial Elements Equivalent Circuit Method: The State Of The Art

This year marks about half a century since the birth of the technique known as the partial element equivalent circuit modeling approach. This method was initially conceived to model the behavior of interconnect-type problems for computer-integrated circuits. An important industrial requirement was the computation of general inductances in integrated circuits and packages. Since then, the advances in methods and applications made it suitable for modeling a large class of electromagnetic problems, especially in the electromagnetic compatibility (EMC)/signal and power integrity (SI/PI) areas. The purpose of this article is to present an overview of all aspects of the method, from its beginning to the present day, with special attention to the developments that have made it suitable for EMC/SI/PI problems

Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition

Hierarchical uncertainty quantification can reduce the computational cost of stochastic circuit simulation by employing spectral methods at different levels. This paper presents an efficient framework to simulate hierarchically some challenging stochastic circuits/systems that include high-dimensional subsystems. Due to the high parameter dimensionality, it is challenging to both extract surrogate models at the low level of the design hierarchy and to handle them in the high-level simulation. In this paper, we develop an efficient ANOVA-based stochastic circuit/MEMS simulator to extract efficiently the surrogate models at the low level. In order to avoid the curse of dimensionality, we employ tensor-train decomposition at the high level to construct the basis functions and Gauss quadrature points. As a demonstration, we verify our algorithm on a stochastic oscillator with four MEMS capacitors and 184 random parameters. This challenging example is simulated efficiently by our simulator at the cost of only 10 minutes in MATLAB on a regular personal computer.Comment: 14 pages (IEEE double column), 11 figure, accepted by IEEE Trans CAD of Integrated Circuits and System

Fast methods for full-wave electromagnetic simulations of integrated circuit package modules

Fast methods for the electromagnetic simulation of integrated circuit (IC) package modules through model order reduction are demonstrated. The 3D integration of multiple functional IC chip/package modules on a single platform gives rise to geometrically complex structures with strong electromagnetic phenomena. This motivates our work on a fast full-wave solution for the analysis of such modules, thus contributing to the reduction in design cycle time without loss of accuracy. Traditionally, fast design approaches consider only approximate electromagnetic effects, giving rise to lumped-circuit models, and therefore may fail to accurately capture the signal integrity, power integrity, and electromagnetic interference effects. As part of this research, a second order frequency domain full-wave susceptance element equivalent circuit (SEEC) model will be extracted from a given structural layout. The model so obtained is suitably reduced using model order reduction techniques. As part of this effort, algorithms are developed to produce stable and passive reduced models of the original system, enabling fast frequency sweep analysis. Two distinct projection-based second order model reduction approaches will be considered: 1) matching moments, and 2) matching Laguerre coefficients, of the original system's transfer function. Further, the selection of multiple frequency shifts in these schemes to produce a globally representative model is also studied. Use of a second level preconditioned Krylov subspace process allows for a memory-efficient way to address large size problems.Ph.D.Committee Chair: Swaminathan Madhavan; Committee Member: Papapolymerou John; Committee Member: Chatterjee Abhijit; Committee Member: Peterson Andrew; Committee Member: Sitaraman Sures