64 citations · 105 across the 17 of their papers we have counts for
20 papers
Moving Mesh Simulations of Pitting Corrosion
Abu Naser Sarker, Ronald D. Haynes, Michael Robertson
Damages due to pitting corrosion of metals cost industry billions of dollars per year and can put human lives at risk. The design and implementation of an adaptive moving mesh meth…
A positivity-preserving unigrid method for elliptic PDEs
Ronald D. Haynes, Scott MacLachlan, Dawei Wang
While constraints arise naturally in many physical models, their treatment in mathematical and numerical models varies widely, depending on the nature of the constraint and the ava…
A closest point method library for PDEs on surfaces with parallel domain decomposition solvers and preconditioners
Ian C. T. May, Ronald D. Haynes, Steven J. Ruuth
The DD-CPM software library provides a set of tools for the discretization and solution of problems arising from the closest point method (CPM) for partial differential equations o…
A Convergence Analysis of the Parallel Schwarz Solution of the Continuous Closest Point Method
Alireza Yazdani, Ronald D. Haynes, Steven J. Ruuth
The discretization of surface intrinsic PDEs has challenges that one might not face in the flat space. The closest point method (CPM) is an embedding method that represents surface…
Domain Decomposition Parabolic Monge-Ampère Approach for Fast Generation of Adaptive Moving Meshes
Mohamed Sulman, Truong Nguyen, Ronald Haynes +1
A fast method is presented for adaptive moving mesh generation in multi-dimensions using a domain decomposition parabolic Monge-Ampère approach. The domain decomposition procedure…
Schwarz solvers and preconditioners for the closest point method
Ian May, Ronald Haynes, Steven Ruuth
The discretization of surface intrinsic elliptic partial differential equations (PDEs) poses interesting challenges not seen in flat space. The discretization of these PDEs typical…
Domain Decomposition for the Closest Point Method
Ian May, Ronald D. Haynes, Steven J. Ruuth
The discretization of elliptic PDEs leads to large coupled systems of equations. Domain decomposition methods (DDMs) are one approach to the solution of these systems, and can spli…
A Schwarz Method for the Magnetotelluric Approximation of Maxwell's equations
Fabrizio Donzelli, Martin J. Gander, Ronald D. Haynes
The magnetotelluric approximation of the Maxwell's equations is used to model the propagation of low frequency electro-magnetic waves in the Earth's subsurface, with the purpose of…
Moving Mesh simulation of contact sets in two dimensional models of elastic-electrostatic deflection problems
Kelsey L. DiPietro, Ronald D. Haynes, Weizhang Huang +2
Numerical and analytical methods are developed for the investigation of contact sets in electrostatic-elastic deflections modeling micro-electro mechanical systems. The model for t…
Stochastic domain decomposition for the solution of the two-dimensional magnetotelluric problem
Alexander Bihlo, Colin G. Farquharson, Ronald D. Haynes +1
Stochastic domain decomposition is proposed as a novel method for solving the two-dimensional Maxwell's equations as used in the magnetotelluric method. The stochastic form of the…
A Multilevel Coordinate Search Algorithm for Well Placement, Control and Joint Optimization
Xiang Wang, Ronald D. Haynes, Qihong Feng
Determining optimal well placements and controls are two important tasks in oil field development. These problems are computationally expensive, nonconvex, and contain multiple opt…
Well Control Optimization using Derivative-Free Algorithms and a Multiscale Approach
Xiang Wang, Ronald D. Haynes, Qihong Feng
In this paper, we use numerical optimization algorithms and a multiscale approach in order to find an optimal well management strategy over the life of the reservoir. The large num…
A Closer Look At Differential Evolution For The Optimal Well Placement Problem
Grazieli L. C. Carosio, Thomas D. Humphries, Ronald D. Haynes +1
Energy demand has increased considerably with the growth of world population, increasing the interest in the hydrocarbon reservoir management problem. Companies are concerned with…
Stochastic domain decomposition for time dependent adaptive mesh generation
Alexander Bihlo, Ronald D. Haynes, Emily J. Walsh
The efficient generation of meshes is an important component in the numerical solution of problems in physics and engineering. Of interest are situations where global mesh quality…
Joint optimization of well placement and control for nonconventional well types
Thomas D. Humphries, Ronald D. Haynes
Optimal well placement and optimal well control are two important areas of study in oilfield development. Although the two problems differ in several respects, both are important c…
Algorithm xxx: RIDC Methods -- A Family of Parallel Time-Integrators
Benjamin Ong, Ronald Haynes, Kyle Ladd
Revisionist integral deferred correction (RIDC) methods are a family of parallel--in--time methods to solve systems of initial values problems. The approach is able to bootstrap lo…
A stochastic domain decomposition method for time dependent mesh generation
Alexander Bihlo, Ronald D. Haynes
We use a time-relaxed linear grid generator of Winslow type to propose a new deterministic-stochastic domain decomposition approach to the generation of adaptive moving meshes. The…
Generating Equidistributed Meshes in 2D via Domain Decomposition
Ronald D. Haynes, Alexander J. M. Howse
In this paper we consider Schwarz domain decomposition applied to the generation of 2D spatial meshes by a local equidistribution principle. We briefly review the derivation of the…
Parallel stochastic methods for PDE based grid generation
Alexander Bihlo, Ronald D. Haynes
The efficient generation of meshes is an important step in the numerical solution of various problems in physics and engineering. We are interested in situations where global mesh…
A Computationally Stable Approach to Gaussian Process Interpolation of Deterministic Computer Simulation Data
Pritam Ranjan, Ronald Haynes, Richard Karsten
For many expensive deterministic computer simulators, the outputs do not have replication error and the desired metamodel (or statistical emulator) is an interpolator of the observ…