The Experts below are selected from a list of 49107 Experts worldwide ranked by ideXlab platform

Gang Wang - One of the best experts on this subject based on the ideXlab platform.

  • Effects of positive interactions, size symmetry of competition and abiotic stress on self-thinning in Simulated Plant populations.
    Annals of botany, 2010
    Co-Authors: Chengjin Chu, Jacob Weiner, Fernando T. Maestre, Youshi Wang, Charles Morris, Xiao, Jianli Yuan, Gang Wang
    Abstract:

    BACKGROUND AND AIMS Competition drives self-thinning (density-dependent mortality) in crowded Plant populations. Facilitative interactions have been shown to affect many processes in Plant populations and communities, but their effects on self-thinning trajectories have not been investigated. METHODS Using an individual-based 'zone-of-influence' model, we studied the potential effects of the size symmetry of competition, abiotic stress and facilitation on self-thinning trajectories in Plant monocultures. In the model, abiotic stress reduced the growth of all individuals and facilitation ameliorated the effects of stress on interacting individuals. KEY RESULTS Abiotic stress made the log biomass-log density relationship during self-thinning steeper, but this effect was reduced by positive interactions among individuals. Size-asymmetric competition also influenced the self-thinning slope. CONCLUSIONS Although competition drives self-thinning, its course can be affected by abiotic stress, facilitation and competitive symmetry.

  • Relationship between the virtual dynamic thinning line and the self-thinning boundary line in Simulated Plant populations.
    Journal of integrative plant biology, 2008
    Co-Authors: Kang Chen, Hong-mei Kang, Juan Bai, Xiangwen Fang, Gang Wang
    Abstract:

    The self-thinning rule defines a straight upper boundary line on log-log scales for all possible combinations of mean individual biomass and density in Plant populations. Recently, the traditional slope of the upper boundary line, -3/2, has been challenged by -4/3 which is deduced from some new mechanical theories, like the metabolic theory. More experimental or field studies should be carried out to identify the more accurate self-thinning exponent. But it's hard to obtain the accurate self-thinning exponent by fitting to data points directly because of the intrinsic problem of subjectivity in data selection. The virtual dynamic thinning line is derived from the competition-density (C-D) effect as the initial density tends to be positive infinity, avoiding the data selection process. The purpose of this study was to study the relationship between the virtual dynamic thinning line and the upper boundary line in Simulated Plant stands. Our research showed that the upper boundary line and the virtual dynamic thinning line were both straight lines on log-log scales. The slopes were almost the same value with only a very little difference of 0.059, and the intercept of the upper boundary line was a little larger than that of the virtual dynamic thinning line. As initial size and spatial distribution patterns became more uniform, the virtual dynamic thinning line was more similar to the upper boundary line. This implies that, given appropriate parameters, the virtual dynamic thinning line may be used as the upper boundary line in Simulated Plant stands.

Kenneth J. Hunt - One of the best experts on this subject based on the ideXlab platform.

  • Neural control of a steel rolling mill
    IEEE Control Systems, 1993
    Co-Authors: D. Sbarbaro-hofer, D. Neumerkel, Kenneth J. Hunt
    Abstract:

    The application of nonlinear neural networks to control of the strip thickness in a steel-rolling mill is described. Different control structures based on neural models of the Simulated Plant are proposed. The results for the neural controllers, among them internal model control and model predictive control, are compared with the performance of a conventional proportional-integral controller. By exploiting the advantage of the nonlinear modeling technique, all neural approaches increase the control precision. In the application considered, the combination of a neural model as a feedforward controller with a feedback controller of integral type gives the best results. >

Joost Sattler - One of the best experts on this subject based on the ideXlab platform.

  • transient simulation of a solar hybrid tower power Plant with open volumetric receiver at the location barstow
    Energy Procedia, 2014
    Co-Authors: Spiros Alexopoulos, Gisbert Breitbach, Markus Latzke, Bernhard Hoffschmidt, Joost Sattler
    Abstract:

    Abstract In this work the transient simulations of four hybrid solar tower power Plant concepts with open-volumetric receiver technology for a location in Barstow-Daggett, USA, are presented. The open-volumetric receiver uses ambient air as heat transfer fluid and the hybridization is realized with a gas turbine. The Rankine cycle is heated by solar-heated air and/or by the gas turbine's flue gases. The Plant can be operated in solar-only, hybrid parallel or combined cycle-only mode as well as in any intermediate load levels where the solar portion can vary between 0 to 100%. The Simulated Plant is based on the configuration of a solar-hybrid power tower project, which is in planning for a site in Northern Algeria. The meteorological data for Barstow-Daggett was taken from the software meteonorm. The solar power tower simulation tool has been developed in the simulation environment MATLAB/Simulink and is validated.

D. Sbarbaro-hofer - One of the best experts on this subject based on the ideXlab platform.

  • Neural control of a steel rolling mill
    IEEE Control Systems, 1993
    Co-Authors: D. Sbarbaro-hofer, D. Neumerkel, Kenneth J. Hunt
    Abstract:

    The application of nonlinear neural networks to control of the strip thickness in a steel-rolling mill is described. Different control structures based on neural models of the Simulated Plant are proposed. The results for the neural controllers, among them internal model control and model predictive control, are compared with the performance of a conventional proportional-integral controller. By exploiting the advantage of the nonlinear modeling technique, all neural approaches increase the control precision. In the application considered, the combination of a neural model as a feedforward controller with a feedback controller of integral type gives the best results. >

  • Neural control of a steel rolling mill
    Proceedings of the 1992 IEEE International Symposium on Intelligent Control, 1992
    Co-Authors: D. Sbarbaro-hofer, D. Neumerkel, K. Hunt
    Abstract:

    The authors apply nonlinear neural control to strip thickness control in a steel rolling mill, Different control structures based on neural models of the Simulated Plant are proposed. The results for the neural controllers, which include internal model control and model predictive control, are compared with the performance of a conventional PI controller. By exploiting the advantage of nonlinear modeling, all neural approaches increase the control precision. The combination of a neural model as a feedforward controller with a feedback controller of the integral type gives the best results.

Spiros Alexopoulos - One of the best experts on this subject based on the ideXlab platform.

  • transient simulation of a solar hybrid tower power Plant with open volumetric receiver at the location barstow
    Energy Procedia, 2014
    Co-Authors: Spiros Alexopoulos, Gisbert Breitbach, Markus Latzke, Bernhard Hoffschmidt, Joost Sattler
    Abstract:

    Abstract In this work the transient simulations of four hybrid solar tower power Plant concepts with open-volumetric receiver technology for a location in Barstow-Daggett, USA, are presented. The open-volumetric receiver uses ambient air as heat transfer fluid and the hybridization is realized with a gas turbine. The Rankine cycle is heated by solar-heated air and/or by the gas turbine's flue gases. The Plant can be operated in solar-only, hybrid parallel or combined cycle-only mode as well as in any intermediate load levels where the solar portion can vary between 0 to 100%. The Simulated Plant is based on the configuration of a solar-hybrid power tower project, which is in planning for a site in Northern Algeria. The meteorological data for Barstow-Daggett was taken from the software meteonorm. The solar power tower simulation tool has been developed in the simulation environment MATLAB/Simulink and is validated.