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Recent developments in the modelling and control of climate and ventilation in agricultural buildings

机译:农业建筑气候和通风建模与控制的最新发展

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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 microclimate of horticultural glasshouses. This can be compared with the incomplete mixing and control volume concepts that have been investigated previously at Leuven. 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 heat transfer and micro-climate dynamics in the chamber; and second, to develop models that can form the basis for the design of optimal Proportional-Integral-Plus (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制(DBM)方法来建模农业建筑中的微观气候。这里,通过连续时间传递函数关系,在客观地,以纯粹的数据为基础,以纯粹的数据传输函数关系在客观地建模的不完美混合过程。然而,在其等同的微分方式形式中,这些模型可以在主动混合体积(AMV)概念方面解释,先前在兰开斯特与河流和土壤中的污染运输以及模拟园艺玻璃间微气密的污染运输中开发。这可以与先前在Leuven进行研究的不完全混合和控制体积概念进行比较。如本文中所述,研究项目的初始阶段中使用的数据已从Luven的大型仪表室中进行的一系列计划的通风实验中获得。该协同研究的整体目标是两倍:首先,为了更好地了解腔室中的传热和微气候动态;其次,开发可以为以前用于控制园艺玻璃中的微观气候的牲畜建筑物的牲畜建筑物设计的最佳比例积分加(PIP-LQ)气候控制系统的设计基础的模型。

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