The designer's preoccupation to reduce the energy needs and get a better thermal quality of ambiances helped in the development of several packages simulating the dynamic behaviour of buildings. This paper shows the adaptation of a method of thermal analysis, the nodal analysis, linked to the case of building's thermal behaviour. We take successively an interest in the case of conduction into a wall, in the coupling with superficial exchanges and finally in the constitution of thermal state models of the building. Big variations existing from one building to another, it's necessary to build the thermal model from the building description. This article shows the chosen method in the case of our thermal simulation program for buildings, CODYRUN.
Abstract:The first and maybe the most important step in designing a model-based predictive controller is to develop a model that is as accurate as possible and that is valid under a wide range of operating conditions. The sugar boiling process is a strongly nonlinear and nonstationary process. The main process nonlinearities are represented by the crystal growth rate. This paper addresses the development of the crystal growth rate model according to two approaches. The first approach is classical and consists of determining the parameters of the empirical expressions of the growth rate through the use of a nonlinear programming optimization technique. The second is a novel modeling strategy that combines an artificial neural network (ANN) as an approximator of the growth rate with prior knowledge represented by the mass balance of sucrose crystals. The first results show that the first type of model performs local fitting while the second offers a greater flexibility. The two models were developed with industrial data collected from a 60 m 3 batch evaporative crystallizer.
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