Double decomposition : decomposing the variance in subcomponents of male extra-pair reproductive success

Peer reviewed

Double decomposition : decomposing the variance in subcomponents of male extra-pair reproductive success

Peer reviewed

Double decomposition : decomposing the variance in subcomponents of male extra-pair reproductive success

Peer reviewed

Polarimetric sensitivity to hydrostatic pressure and temperature in birefringent dual-core microstructured polymer fiber

We experimentally characterized a birefringent microstructured polymer fiber of specific construction, which allows for single mode propagation in two cores separated by a pair of large holes. The fiber exhibits high birefringence in each of the cores as well as relatively weak coupling between the cores. Spectral dependence of the group and the phase modal birefringence was measured using an interferometric method. We have also measured the sensing characteristics of the fiber such as the polarimetric sensitivity to hydrostatic pressure and temperature. © 2010 SPIE.

Preparation of Boron by Pyrolytic Decomposition of Boron Tribromide

The national shortage of helium-3 has made it critical to develop an alternative to helium-3 neutron detectors. Boron-10, if it could be produced in macroscopic alpha-rhombohedral crystalline form, would be a viable alternative to helium-3. This work has determined the critical parameters needed for the preparation of alpha-rhombohedral boron by the pyrolytic decomposition of boron tribromide on tantalum wire. The primary parameters that must be met are wire temperature and feedstock purity. The minimum purity level for boron tribromide was determined to be 99.999% and it has been found that alpha-rhombohedral boron cannot be produced using 99.99% boron tribromide. The decomposition temperature was experimentally tested between 830°C and 1000°C. Alpha-rhombohedral boron was found at temperatures between 950°C and 1000°C using 99.999% pure boron tribromide.

Nicole Poret retrieving decomposition bags to measure mangrove fine root decomposition rates, Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Left to right: Robert Twilley and Nicole Poret. Washing mangrove fine roots to set up a decomposition experiment, Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Nicole Poret weighing mangrove fine roots to set up a decomposition experiment, Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Left to right: Nicole Poret and Carlos Coronado-Molina deploying bags to determine decomposition rates of mangrove fine roots, Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Parallel nonconvex generalized Benders decomposition for natural gas production network planning under uncertainty

A scenario-based two-stage stochastic programming model for gas production network planning under uncertainty is usually a large-scale nonconvex mixed-integer nonlinear programme (MINLP), which can be efficiently solved to global optimality with nonconvex generalized Benders decomposition (NGBD). This paper is concerned with the parallelization of NGBD to exploit multiple available computing resources. Three parallelization strategies are proposed, namely, naive scenario parallelization, adaptive scenario parallelization, and adaptive scenario and bounding parallelization. Case study of two industrial natural gas production network planning problems shows that, while the NGBD without parallelization is already faster than a state-of-the-art global optimization solver by an order of magnitude, the parallelization can improve the efficiency by several times on computers with multicore processors. The adaptive scenario and bounding parallelization achieves the best overall performance among the three proposed parallelization strategies.

Hierarchical Demand Response for Peak Minimization Using Dantzig-Wolfe Decomposition

Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.