emulationmodelling is an effective way of overcoming the large computational burden associated with the process-based models traditionally adopted by the environmental modelling community. An emulator is a low-order,...
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emulationmodelling is an effective way of overcoming the large computational burden associated with the process-based models traditionally adopted by the environmental modelling community. An emulator is a low-order, computationally efficient model identified from the original large model and then used to replace it for computationally intensive applications. As the number and forms of the problem that benefit from the identification and subsequent use of an emulator is very large, emulationmodelling has emerged in different sectors of science, engineering and social science. For this reason, a variety of different strategies and techniques have been proposed in the last few years. The main aim of the paper is to provide an introduction to emulationmodelling, together with a unified strategy for its application, so that modellers from different disciplines can better appreciate how it may be applied in their area of expertise. Particular emphasis is devoted to dynamic emulation modelling (DEMo), a methodological approach that preserves the dynamic nature of the original process-based model, with consequent advantages in a wide variety of problem areas. The different techniques and approaches to DEMo are considered in two macro categories: structure-based methods, where the mathematical structure of the original model is manipulated to a simpler, more computationally efficient form;and data-based approaches, where the emulator is identified and estimated from a data-set generated from planned experiments conducted on the large simulation model. The main contribution of the paper is a unified, six-step procedure that can be applied to most kinds of dynamicemulation problem. (C) 2012 Elsevier Ltd. All rights reserved.
emulationmodelling has been successfully applied in many environmental applications to reduce large, computationally demanding, process-based models to low order surrogates to be used in place of the original model i...
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ISBN:
(纸本)9780987214331
emulationmodelling has been successfully applied in many environmental applications to reduce large, computationally demanding, process-based models to low order surrogates to be used in place of the original model in problems involving hundreds or thousands of model simulations. Typical examples include optimal planning and management, data assimilation, and sensitivity analysis. In this study, we describe the identification of a dynamic emulator of a 3D hydrodynamic reservoir model and its subsequent use within a real-time control framework for dam operation. In particular, we adopt a novel data-driven approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is particularly effective in designing the controller. The approach is demonstrated on Marina Reservoir, Singapore, which was recently reclaimed to the sea and transformed into a freshwater storage by constructing a barrage. A dynamic emulator of the salinity evolution in a control point near the dam was identified and then used in combination with Model Predictive Control to design the real-time operation of the barrage. Results show that the salinity levels, due to saline intrusion through groundwater seepage, can be dropped to drinking water standards by embedding the emulator in the real-time controller.
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