Publications

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Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, and latent-variable modeling, have been proposed to address the limitations of the classical BO framework. In this work, we propose a novel multi-objective BO formalism, called srMO-BO-3GP, to solve multi-objective optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GPs is assigned with a different task. The first GP is used to approximate a single-objective computed from the multi-objective definition, the second GP is used to learn the unknown constraints, and the third one is used to learn the uncertain Pareto frontier. At each iteration, a multi-objective augmented Tchebycheff function is adopted to convert multi-objective to single-objective, where the regularization with a regularized ridge term is also introduced to smooth the single-objective function. Finally, we couple the third GP along with the classical BO framework to explore the convergence and diversity of the Pareto frontier by the acquisition function for exploitation and exploration. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization.

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A cohesive phase-field model of ductile fracture in a finite-deformation setting is presented. The model is based on a free-energy function in which both elastic and plastic work contributions are coupled to damage. Using a strictly variational framework, the field evolution equations, damage kinetics, and flow rule are jointly derived from a scalar least-action principle. Particular emphasis is placed on the use of a rational function for the stress degradation that maintains a fixed effective strength with decreasing regularization length. The model is employed to examine crack growth in pure mode-I problems through the generation of crack growth resistance (J-R) curves. In contrast to alternative models, the current formulation gives rise to J-R curves that are insensitive to the regularization length. Numerical evidence suggests convergence of local fields with respect to diminishing regularization length as well.

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A key objective of the United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal. A study has been initiated to examine the potential consequences, with respect to long-term repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. The first phase (a scoping phase) consisted of developing an approach to creating the modeling tools and techniques that may eventually be needed to either include or exclude criticality from a performance assessment (PA) as appropriate; this scoping phase is documented in Price et al. (2019a). In the second phase, that modeling approach was implemented and future work was identified, as documented in Price et al. (2019b). This report gives the results of a repository-scale PA examining the potential consequences of postclosure criticality, as well as the information, modeling tools, and techniques needed to incorporate the effects of postclosure criticality in the PA.

Brittle materials, such as cement, compose major portions of built infrastructure and are vulnerable to degradation and fracture from chemo-mechanical effects. Currently, methods of modeling infrastructure do not account for the presence of a reactive environment, such as water, on the acceleration of failure. Here, we have developed methodologies and models of concrete and cement fracture that account for varying material properties, such as strength, shrinkage, and fracture toughness due to degradation or hydration. The models have been incorporated into peridynamics, non-local continuum mechanics methodology, that can model intersecting and branching brittle fracture that occurs in multicomponent brittle materials, such as concrete. Through development of new peridynamic capabilities, decalcification of cement and differential shrinkage in clay-cement composites have been evaluated, along with exemplar problems in nuclear waste cannisters and wellbores. We have developed methods to simulate multiphase phenomena in cement and cement-composite materials for energy and infrastructure applications.

Relativistic weakly collisional plasmas describe a variety of astrophysical and terrestrial plasmas, ranging from relativistic outflows from active galactic nuclei to high power microwave and magnetically insulated transmission lines. In many such systems, high fidelity kinetic models are computationally infeasible due large dynamical scales and long dynamical times. Conversely, most fluid based models such as magnetohydrodynamics (MHD) miss many relevant aspects of plasma behavior. Between these two models, two fluid methods - where the electrons and ions are evolved as separate, coupled fluids - capture many of the plasma physics of a kinetic code while remaining computational tractable for large systems.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy, Office of Spent Fuel and Waste Disposition (SFWD), has been conducting research and development on generic deep geologic disposal systems (i.e., geologic repositories). This report describes specific activities in the Fiscal Year (FY) 2021 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package within the SFWST Campaign. The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and system performance assessment (PA) models in several host-rock environments, and to simulate and analyze these generic repository concepts and models using the GDSA Framework toolkit, and other tools as needed.