We describe a Newton-based nonlinear solver for immiscible two-phase transport in the presence of significant viscous, buoyancy, and capillary forces. The evolution of CO2 plumes in heterogeneous saline aquifers, especially during the post-injection period, is an important example of this class of problem. The flux (fractional flow) function, which is strongly nonlinear function of saturation, ...

A Newton–Krylov method is an implementation of Newton’s method in which a Krylov subspace method is used to solve approximately the linear subproblems that determine Newton steps. To enhance robustness when good initial approximate solutions are not available, these methods are usually globalized, i.e., augmented with auxiliary procedures (globalizations) that improve the likelihood of converge...

This document gives an overview of the Next Steps in Signaling (NSIS) framework and protocol suite created by the NSIS Working Group during the period of 2001-2010. It also includes suggestions on how the industry can make use of the new protocols and how the community can exploit the extensibility of both the framework and existing protocols to address future signaling needs.

We study the numerical performance of a limited memory quasi Newton method for large scale optimization which we call the L BFGS method We compare its performance with that of the method developed by Buckley and LeNir which combines cyles of BFGS steps and conjugate direction steps Our numerical tests indicate that the L BFGS method is faster than the method of Buckley and LeNir and is better a...

There are a variety of methods in the literature which seek to make iterative estimation algorithms more manageable by breaking the iterations into a greater number of simpler or faster steps. Those algorithms which deal at each step with a proper subset of the parameters are called in this paper partitioned algorithms. Partitioned algorithms in effect replace the original estimation problem wi...

We study the numerical performance of a limited memory quasi-Newton method for large scale optimization, which we call the L-BFGS method. We compare its performance with that of the method developed by Buckley and LeNir (1985), which combines cyles of BFGS steps and conjugate direction steps. Our numerical tests indicate that the L-BFGS method is faster than the method of Buckley and LeNir, and...

To exploit Hessian information in full-waveform inversion (FWI), the matrix-free truncated Newton method can be used. In such a method, Hessian-vector product computation is one of major concerns due to huge memory requirements and demanding computational cost. Using adjoint-state estimated by zero-lag crosscorrelation first-/second-order incident wavefields second-/first-order adjoint wavefiel...

This document gives an overview of the Next Steps in Signaling (NSIS) framework and protocol suite created by the NSIS Working Group during the period of 2001-2010. It also includes suggestions on how the industry can make use of the new protocols and how the community can exploit the extensibility of both the framework and existing protocols to address future signaling needs.

This threats document provides a detailed analysis of the security threats relevant to the Next Steps in Signaling (NSIS) protocol suite. It calls attention to, and helps with the understanding of, various security considerations in the NSIS Requirements, Framework, and Protocol proposals. This document does not describe vulnerabilities of specific parts of the NSIS protocol suite.

This research consider the problem of efficiently estimating a parameter of interest when the model is complicated by a vector of nuisance parameters. If the model is nonadaptive we must often resort to full information estimation to gain an efficient estimator for the parameter of interest. In certain cases full information estimation can be computationally intensive and lead to poor finite sa...