This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.
This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of this exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.
Two classical verification problems from shock hydrodynamics are adapted for verification in the context of ideal magnetohydrodynamics (MHD) by introducing strong transverse magnetic fields, and simulated using the finite element Lagrange-remap MHD code ALEGRA for purposes of rigorous code verification. The concern in these verification tests is that inconsistencies related to energy advection are inherent in Lagrange-remap formulations for MHD, such that conservation of the kinetic and magnetic components of the energy may not be maintained. Hence, total energy conservation may also not be maintained. MHD shock propagation may therefore not be treated consistently in Lagrange-remap schemes, as errors in energy conservation are known to result in unphysical shock wave speeds and post-shock states. That kinetic energy is not conserved in Lagrange-remap schemes is well known, and the correction of DeBar has been shown to eliminate the resulting errors. Here, the consequences of the failure to conserve magnetic energy are revealed using order verification in the two magnetized shock-hydrodynamics problems. Further, a magnetic analog to the DeBar correction is proposed and its accuracy evaluated using this verification testbed. Results indicate that only when the total energy is conserved, by implementing both the kinetic and magnetic components of the DeBar correction, can simulations in Lagrange-remap formulation capture MHD shock propagation accurately. Additional insight is provided by the verification results, regarding the implementation of the DeBar correction and the advection scheme.