The Experts below are selected from a list of 222525 Experts worldwide ranked by ideXlab platform
Øyvind Skreiberg - One of the best experts on this subject based on the ideXlab platform.
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Drying of Thermally Thick Wood Particles: A Study of the Numerical Efficiency, Accuracy, and Stability of Common Drying Models
Energy & Fuels, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:The primary focus of this paper is on studying different Numerical models for drying of wet wood particles. More specifically, the advantages and disadvantages of the models, with respect to Numerical Efficiency, stability, and accuracy, are investigated. The two basic models that are studied in detail are the thermal drying model and the kinetic rate drying model. The drying models have been implemented in an in-house simulation tool that solves for drying and devolatilization of a one-dimensional cylindrical wood log. It is found that the choice of drying model can significantly influence the computational time associated with the thermal conversion. Furthermore, the occurrence of Numerical pressure oscillations in the thermal drying model has been found and investigated. The Numerical oscillations are reduced by introducing an evaporation fraction, fevap. When the thermal drying model is applied, the drying zone is very thin, commonly only including one grid point, which can result in Numerical instabi...
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Comparison of Numerical Efficiency of the thermal and the kinetic rate drying model applied to a thermally thick wood particle
Energy Procedia, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:Abstract In this work, the drying and devolatilization of a thermally thick wood particle were modeled. The work was validated against experiments and good agreement was found. The work compared the Numerical Efficiency and accuracy of the thermal drying model and the kinetic rate drying model. The thermal drying model was used with a fixed boiling temperature (373 K). The kinetic data for the kinetic rate drying model was taken from an earlier work by Di Blasi [1] and additionally one set of kinetic data that was also tested, was assumed by the authors, with the main purpose of reducing the stiffness of the evaporation equation. The Numerical Efficiency was compared by comparing the CPU times associated with the different drying models. It was found that the thermal drying model is the most efficient drying model at both high and low moisture contents. Soft drying kinetics resulted in intermediate CPU times, while very stiff kinetics yielded the lowest Numerical Efficiency. No trend was observed regarding how CPU times of the different drying models behave with respect to increasing or decreasing moisture contents.
Zhang Chun - One of the best experts on this subject based on the ideXlab platform.
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A Numerical Comparison between Two Classes of Non-monotone Trust Region Algorithms
Journal of Nanjing Xiaozhuang University, 2011Co-Authors: Zhang ChunAbstract:This paper is aimed at the comparison between two typical non-monotone trust region algorithms for unconstrained optimization.In theory,they both have good convergence properties.The Numerical Efficiency of the two non-monotone algorithms is the focus of the comparison.Extensive Numerical experiments were conducted,making use of the well-known test problems package by J.J.More et al..Then the two algorithms were compared by the performance profiles based on the data obtained from the Numerical experiments.The analysis indicates that the Numerical Efficiency of the algorithm NATR is superior to that of the traditional non-monotone trust region algorithm to a certain extent.
Inge Haberle - One of the best experts on this subject based on the ideXlab platform.
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Drying of Thermally Thick Wood Particles: A Study of the Numerical Efficiency, Accuracy, and Stability of Common Drying Models
Energy & Fuels, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:The primary focus of this paper is on studying different Numerical models for drying of wet wood particles. More specifically, the advantages and disadvantages of the models, with respect to Numerical Efficiency, stability, and accuracy, are investigated. The two basic models that are studied in detail are the thermal drying model and the kinetic rate drying model. The drying models have been implemented in an in-house simulation tool that solves for drying and devolatilization of a one-dimensional cylindrical wood log. It is found that the choice of drying model can significantly influence the computational time associated with the thermal conversion. Furthermore, the occurrence of Numerical pressure oscillations in the thermal drying model has been found and investigated. The Numerical oscillations are reduced by introducing an evaporation fraction, fevap. When the thermal drying model is applied, the drying zone is very thin, commonly only including one grid point, which can result in Numerical instabi...
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Comparison of Numerical Efficiency of the thermal and the kinetic rate drying model applied to a thermally thick wood particle
Energy Procedia, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:Abstract In this work, the drying and devolatilization of a thermally thick wood particle were modeled. The work was validated against experiments and good agreement was found. The work compared the Numerical Efficiency and accuracy of the thermal drying model and the kinetic rate drying model. The thermal drying model was used with a fixed boiling temperature (373 K). The kinetic data for the kinetic rate drying model was taken from an earlier work by Di Blasi [1] and additionally one set of kinetic data that was also tested, was assumed by the authors, with the main purpose of reducing the stiffness of the evaporation equation. The Numerical Efficiency was compared by comparing the CPU times associated with the different drying models. It was found that the thermal drying model is the most efficient drying model at both high and low moisture contents. Soft drying kinetics resulted in intermediate CPU times, while very stiff kinetics yielded the lowest Numerical Efficiency. No trend was observed regarding how CPU times of the different drying models behave with respect to increasing or decreasing moisture contents.
David Sirl - One of the best experts on this subject based on the ideXlab platform.
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how big is an outbreak likely to be methods for epidemic final size calculation
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2013Co-Authors: Thomas A House, Joshua V Ross, David SirlAbstract:Epidemic models have become a routinely used tool to inform policy on infectious disease. A particular interest at the moment is the use of computationally intensive inference to parametrize these models. In this context, Numerical Efficiency is critically important. We consider methods for evaluating the probability mass function of the total number of infections over the course of a stochastic epidemic, with a focus on homogeneous finite populations, but also considering heterogeneous and large populations. Relevant methods are reviewed critically, with existing and novel extensions also presented. We provide code in MATLAB and a systematic comparison of Numerical Efficiency.
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How big is an outbreak likely to be? Methods for epidemic final-size calculation
Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, 2013Co-Authors: Thomas House, Joshua V Ross, David SirlAbstract:Epidemic models have become a routinely used tool to inform policy on infectious disease. A particular interest at the moment is the use of computationally intensive inference to parametrize these models. In this context, Numerical Efficiency is critically important. We consider methods for evaluating the probability mass function of the total number of infections over the course of a stochastic epidemic, with a focus on homogeneous finite populations, but also considering heterogeneous and large populations. Relevant methods are reviewed critically, with existing and novel extensions also presented. We provide code in MATLAB and a systematic comparison of Numerical Efficiency.
Nils Erland L. Haugen - One of the best experts on this subject based on the ideXlab platform.
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Drying of Thermally Thick Wood Particles: A Study of the Numerical Efficiency, Accuracy, and Stability of Common Drying Models
Energy & Fuels, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:The primary focus of this paper is on studying different Numerical models for drying of wet wood particles. More specifically, the advantages and disadvantages of the models, with respect to Numerical Efficiency, stability, and accuracy, are investigated. The two basic models that are studied in detail are the thermal drying model and the kinetic rate drying model. The drying models have been implemented in an in-house simulation tool that solves for drying and devolatilization of a one-dimensional cylindrical wood log. It is found that the choice of drying model can significantly influence the computational time associated with the thermal conversion. Furthermore, the occurrence of Numerical pressure oscillations in the thermal drying model has been found and investigated. The Numerical oscillations are reduced by introducing an evaporation fraction, fevap. When the thermal drying model is applied, the drying zone is very thin, commonly only including one grid point, which can result in Numerical instabi...
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Comparison of Numerical Efficiency of the thermal and the kinetic rate drying model applied to a thermally thick wood particle
Energy Procedia, 2017Co-Authors: Inge Haberle, Nils Erland L. Haugen, Øyvind SkreibergAbstract:Abstract In this work, the drying and devolatilization of a thermally thick wood particle were modeled. The work was validated against experiments and good agreement was found. The work compared the Numerical Efficiency and accuracy of the thermal drying model and the kinetic rate drying model. The thermal drying model was used with a fixed boiling temperature (373 K). The kinetic data for the kinetic rate drying model was taken from an earlier work by Di Blasi [1] and additionally one set of kinetic data that was also tested, was assumed by the authors, with the main purpose of reducing the stiffness of the evaporation equation. The Numerical Efficiency was compared by comparing the CPU times associated with the different drying models. It was found that the thermal drying model is the most efficient drying model at both high and low moisture contents. Soft drying kinetics resulted in intermediate CPU times, while very stiff kinetics yielded the lowest Numerical Efficiency. No trend was observed regarding how CPU times of the different drying models behave with respect to increasing or decreasing moisture contents.
