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DATA-BASED MECHANISTIC MODELLING (DBM) AND CONTROL OF MASS AND ENERGY TRANSFER IN AGRICULTURAL BUILDINGS

机译:农业建筑的基于数据的机械建模(DBM)和质量与能量传递的控制

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This paper discusses the Data-Based Mechanistic (DBM) approach to modelling the micro-climate in agricultural buildings. Here, the imperfect mixing processes that dominate the system behaviour during forced ventilation are first modelled objectively, in purely data-based terms, by continuous-time transfer function relationships. In their equivalent differential equation form, however, these models can be interpreted in terms of the Active Mixing Volume (AMV) concept, developed previously at Lancaster in connection with pollution transport in rivers and soils and, latterly, in modelling the micro- . climate of horticultural glasshouses. The data used in the initial stages of the research project, as described in the paper, have been obtained from a series of planned ventilation experiments carried out in a large instrumented chamber at Leuven. The overall obJectives of this collaborative study are two-fold first, to gain a better understanding of the mass and heat transfer dynamics in the chamber, and second, to develop models that can form the basis for the design of optimal Proportional-lntegral-Plus, Linear Quadratic (PIP-LQ) climate control systems for livestock buildings of a kind used previously for controlling the micro-climate in horticultural glasshouses.
机译:本文讨论了基于数据的机械(DBM)方法对农业建筑的微气候进行建模。在此,首先通过连续时间传递函数关系,以纯粹基于数据的术语客观地对主导通风期间系统行为的不完美混合过程进行建模。然而,这些模型可以用它们的等效微分方程形式来解释,该模型可以用主动混合体积(AMV)概念来解释,该概念是先前在兰开斯特(Lancaster)针对河流和土壤中的污染物迁移以及后来的微观模型建模而开发的。园艺温室的气候。如本文所述,用于研究项目初期的数据是从在鲁汶的大型仪器室中进行的一系列计划通风实验获得的。这项合作研究的总体目标是双重的,首先是为了更好地了解腔室内的质量和传热动力学,其次是开发可以为最优比例-积分-加法设计基础的模型。 ,用于牲畜建筑的线性二次(PIP-LQ)气候控制系统,以前用于控制园艺温室的微气候。

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