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Peter C Young - One of the best experts on this subject based on the ideXlab platform.

  • a data based Mechanistic Approach to nonlinear flood routing and adaptive flood level forecasting
    Advances in Water Resources, 2008
    Co-Authors: Renata J Romanowicz, Peter C Young, Keith Beven, Florian Pappenberger
    Abstract:

    Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed flood inundation models more common. However, problems remain with the application of such models. There are still uncertainties associated with the identifiability of parameters; with the computational burden of calculating distributed estimates of predictive uncertainty; and with the adaptive use of such models for operational, real-time flood inundation forecasting. Moreover, the application of distributed models is complex, costly and requires high degrees of skill. This paper presents an alternative to distributed inundation models for real-time flood forecasting that provides fast and accurate, medium to short-term forecasts. The Data Based Mechanistic (DBM) methodology exploits a State Dependent Parameter (SDP) modelling Approach to derive a nonlinear dependence between the water levels measured at gauging stations along the river. The transformation of water levels depends on the relative geometry of the channel cross-sections, without the need to apply rating curve transformations to the discharge. The relationship obtained is used to transform water levels as an input to a linear, on-line, real-time and adaptive stochastic DBM model. The Approach provides an estimate of the prediction uncertainties, including allowing for heterescadasticity of the multi-step-ahead forecasting errors. The Approach is illustrated using an 80 km reach of the River Severn, in the UK.

  • the data based Mechanistic Approach to the modelling forecasting and control of environmental systems
    Annual Reviews in Control, 2006
    Co-Authors: Peter C Young
    Abstract:

    Abstract The paper presents a unified Approach to the modelling, forecasting and control of natural and man-made environmental systems. The modelling Approach exploits the author’s Data-Based Mechanistic (DBM) modelling philosophy, combined with powerful methods of recursive statistical estimation. These provide the basis for two major stages of model building: first, the critical evaluation of the over-parametrized simulation models that are currently the most common vehicle used in environmental planning and management studies; and second, the adaptive, data-based estimation of parsimonious, ‘top-down’ models that can be used for adaptive forecasting and data assimilation, as well as operational control and management system design. The associated control system design methodology is based on the Non-Minimal State Space (NMSS) Approach to the design of Proportional-Integral-Plus (PIP) control systems, based on the DBM models obtained at the previous modelling stage. The paper includes a case study concerned with the modelling and control of globally averaged levels of CO 2 in the atmosphere.

Kevin S Mccann - One of the best experts on this subject based on the ideXlab platform.

  • a Mechanistic Approach for modeling temperature dependent consumer resource dynamics
    The American Naturalist, 2005
    Co-Authors: David A Vasseur, Kevin S Mccann
    Abstract:

    Abstract: Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer‐resource framework. Our analysis leads to three predictions for the response of consumer‐resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase...

  • a Mechanistic Approach for modeling temperature dependent consumer resource dynamics
    The American Naturalist, 2005
    Co-Authors: David A Vasseur, Kevin S Mccann
    Abstract:

    Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer-resource framework. Our analysis leads to three predictions for the response of consumer-resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase or decrease depending on their proximity to the feasibility (extinction) boundary. Third, consumer biomass density is more sensitive to warming than resource biomass density (with some exceptions). These predictions are in line with many current observations and experiments. The model presented and analyzed here provides an advancement in the testing framework for global change scenarios and hypotheses of latitudinal and elevational species distributions.

David A Vasseur - One of the best experts on this subject based on the ideXlab platform.

  • a Mechanistic Approach for modeling temperature dependent consumer resource dynamics
    The American Naturalist, 2005
    Co-Authors: David A Vasseur, Kevin S Mccann
    Abstract:

    Abstract: Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer‐resource framework. Our analysis leads to three predictions for the response of consumer‐resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase...

  • a Mechanistic Approach for modeling temperature dependent consumer resource dynamics
    The American Naturalist, 2005
    Co-Authors: David A Vasseur, Kevin S Mccann
    Abstract:

    Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer-resource framework. Our analysis leads to three predictions for the response of consumer-resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase or decrease depending on their proximity to the feasibility (extinction) boundary. Third, consumer biomass density is more sensitive to warming than resource biomass density (with some exceptions). These predictions are in line with many current observations and experiments. The model presented and analyzed here provides an advancement in the testing framework for global change scenarios and hypotheses of latitudinal and elevational species distributions.

Simon S Park - One of the best experts on this subject based on the ideXlab platform.

  • a new Mechanistic Approach for micro end milling force modeling
    Journal of Manufacturing Science and Engineering-transactions of The Asme, 2012
    Co-Authors: Martin B G Jun, Mohammad Malekian, Chanseo Goo, Simon S Park
    Abstract:

    This paper investigates the Mechanistic modeling of micro end milling forces, with consideration of the effects of plowing, elastic recovery, effective rake angle, and flank face rubbing. Two different Mechanistic models are developed for shearing- and plowing-dominant regimes. Micro end milling experiments are conducted to validate the model for Aluminum 6061; and, the model appropriately predicts force profiles for a wide range of feed rates, and prediction of the root mean square (RMS) values of the resultant forces is, on average, within a 12% error. The study of the model shows that plowing and rubbing force contributions are significant, especially at low feed rates. The edge radius is found to have a significant effect on plowing and rubbing force components and the effective rake angle, which indicates that it is important to maintain a low edge radius to reduce micro end milling forces.

  • a new Mechanistic Approach for micro end milling force modeling
    ASME 2010 International Mechanical Engineering Congress and Exposition, 2010
    Co-Authors: Mohammad Malekian, Simon S Park
    Abstract:

    This paper investigates the Mechanistic modeling of micro end milling forces, with consideration of the effects of plowing, elastic recovery, effective rake angle, and flank face rubbing. Two different Mechanistic models are developed for shearing- and plowing-dominant regimes. Micro end milling experiments are conducted to validate the model for Aluminum 6061; and, the model appropriately predicts force profiles for a wide range of feed rates, and prediction of the root mean square (RMS) values of the resultant forces is, on average, within a 12% error. The study of the model shows that plowing and rubbing force contributions are significant, especially at low feed rates. The edge radius is found to have a significant effect on plowing and rubbing force components and the effective rake angle, which indicates that it is important to maintain a low edge radius to reduce micro end milling forces.Copyright © 2010 by ASME

Robert L Lytton - One of the best experts on this subject based on the ideXlab platform.

  • energy based Mechanistic Approach for damage characterization of pre flawed visco elasto plastic materials
    Mechanics of Materials, 2014
    Co-Authors: Xue Luo, Rong Luo, Robert L Lytton
    Abstract:

    Abstract Damage characterization plays a significant role in producing durable and high performance structural materials. However, it is somewhat complicated because of the particular characteristics of many materials, such as pre-existing flaws, time-dependent behaviors, and coexistence of cracking and permanent deformation. This kind of materials is pre-flawed visco-elasto-plastic material. In order to characterize damage in such materials, this paper proposes an energy-based Mechanistic (EBM) Approach that provides a complete solution to these problems. As typical pre-flawed visco-elasto-plastic materials, asphalt mixtures are selected to demonstrate the principles and applications of the EBM Approach. When an asphalt mixture is not damaged, the pre-existing flaws are air voids, characterized by the average air voids size and number of air voids calculated by the EBM Approach. The calculated values are more accurate than those measured by the X-ray Computed Tomography system. Due to the increased accuracy, it is discovered that the air voids becomes smaller when the mixture is aged, which serves as an evidence of the change of the internal structure of the material due to aging. When an asphalt mixture is damaged, the damage includes cracking and permanent deformation. The cracking damage is a multitude of randomly distributed cracks. A new concept, distributed continuum fracture (DCF), is introduced to model the distributed cracks in the EBM Approach. Development of cracking damage is quantified by the evolution of damage density, average crack size and number of cracks. The damage densities of eight different mixtures are proven to correctly reflect the effect of mixture composition and aging. New features of number of cracks discovered lead to new definitions of cracking history in pre-flawed materials. The energy for permanent deformation is separated from that expended for cracking in the same asphalt mixture. Such a separation acknowledges the fact that cracking and permanent deformation always occur simultaneously. The separated energy for cracking is used to define a cracking energy dissipation rate, a direct indicator of cracking susceptibility of asphalt mixtures. In a word, the EBM Approach is able to characterize damage in asphalt mixtures under various conditions using one type of test on one specimen. It requires simple inputs: stress, strain, and time, and all the calculations are performed automatically by the Excel. Using this Approach to analyze the test data is more efficient than some alternative methods because of less testing effort and more informative results with improved accuracy.

  • energy based Mechanistic Approach to characterize crack growth of asphalt mixtures
    Journal of Materials in Civil Engineering, 2013
    Co-Authors: Xue Luo, Rong Luo, Robert L Lytton
    Abstract:

    Fatigue cracking is a common distress in asphalt pavements, but most existing models to predict its growth are generally empirical or phenomenological in nature. To fill this gap, this paper aims at developing an energy-based Mechanistic Approach to model the fatigue crack growth in asphalt mixtures. The core of this Approach is establishing the energy balance equations between the apparent energy of the bulk specimen and the true energy of the intact material. A controlled-strain repeated direct tension (RDT) test is used to generate fatigue cracking damage in asphalt mixtures. The true stresses, true strains, and true pseudostrains are simulated through the force equilibrium and energy balance equations. The true stress in a damaged asphalt mixture is found to be the driving force for crack growth; the crack growth in turn aggravates the localization of the true stress/true strain. The ratio of the true stress and the apparent stress in a damaged asphalt mixture is used to calculate the damage density. The evolution of the damage density with repeated loading demonstrates the development of fatigue cracking in the asphalt mixture. In addition to modeling fatigue cracking in asphalt mixtures, the energy-based Mechanistic Approach developed in this paper can be used with a wide range of tests to predict crack growth of different types of materials because of its mechanical nature.