Domain Decomposition Based Hybrid Methods of Finite Element and Finite Difference and Applications in Biomolecule Simulations

The dielectric continuum models, such as Poisson Boltzmann equation (PBE), size modified PBE (SMPBE), and nonlocal modified PBE (NMPBE), are important models in predicting the electrostatics of a biomolecule in an ionic solvent. To solve these dielectric continuum models efficiently, in this dissertation, new finite element and finite difference hybrid methods are constructed by Schwartz domain decomposition techniques based on a special seven-box partition of a cubic domain. As one important part of these methods, a finite difference optimal solver --- the preconditioned conjugate gradient method using a multigrid V-cycle preconditioner --- is described in details and proved to have a convergence rate independent of mesh size in solving a symmetric positive definite linear system. These new hybrid algorithms are programmed in Fortran, C, and Python based on the efficient finite element library DOLFIN from the FEniCS project, and are well validated by test models with known analytical solutions. Comparison numerical tests between the new hybrid solvers and the corresponding finite element solvers are done to show the improvement in efficiency. Finally, as applications, solvation free energy and binding free energy calculations are done and then compared to the experiment data

Application of general semi-infinite Programming to Lapidary Cutting Problems

We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of container constraints, which is necessary to make the subproblems practically tractable. An iterative process consisting of GSIP optimization and adaptive refinement steps is then employed to obtain an optimal solution which is also feasible for the original problem. Some numerical results based on realworld data are also presented

Atomic radius and charge parameter uncertainty in biomolecular solvation energy calculations

Atomic radii and charges are two major parameters used in implicit solvent electrostatics and energy calculations. The optimization problem for charges and radii is under-determined, leading to uncertainty in the values of these parameters and in the results of solvation energy calculations using these parameters. This paper presents a new method for quantifying this uncertainty in implicit solvation calculations of small molecules using surrogate models based on generalized polynomial chaos (gPC) expansions. There are relatively few atom types used to specify radii parameters in implicit solvation calculations; therefore, surrogate models for these low-dimensional spaces could be constructed using least-squares fitting. However, there are many more types of atomic charges; therefore, construction of surrogate models for the charge parameter space requires compressed sensing combined with an iterative rotation method to enhance problem sparsity. We demonstrate the application of the method by presenting results for the uncertainties in small molecule solvation energies based on these approaches. The method presented in this paper is a promising approach for efficiently quantifying uncertainty in a wide range of force field parameterization problems, including those beyond continuum solvation calculations.The intent of this study is to provide a way for developers of implicit solvent model parameter sets to understand the sensitivity of their target properties (solvation energy) on underlying choices for solute radius and charge parameters

Teaching and Learning of Fluid Mechanics

This book contains research on the pedagogical aspects of fluid mechanics and includes case studies, lesson plans, articles on historical aspects of fluid mechanics, and novel and interesting experiments and theoretical calculations that convey complex ideas in creative ways. The current volume showcases the teaching practices of fluid dynamicists from different disciplines, ranging from mathematics, physics, mechanical engineering, and environmental engineering to chemical engineering. The suitability of these articles ranges from early undergraduate to graduate level courses and can be read by faculty and students alike. We hope this collection will encourage cross-disciplinary pedagogical practices and give students a glimpse of the wide range of applications of fluid dynamics