Magnetic resonance imaging and numerical modelling of hydrodynamics in vibrated bubbling fluidized beds
Magnetic resonance imaging and numerical modelling of hydrodynamics in vibrated bubbling fluidized beds
批准号:
471615686
负责人:
Professor Dr.-Ing. Stefan Heinrich
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
流化床在化工、能源转化、制药等工业领域有着广泛的应用。振动鼓泡流化床通常用于食品工业中粉末的干燥,因为由此产生的颗粒运动增强。尽管它们被广泛使用,但我们对流化床内流体动力学的基本物理理解仍然有限,并且基于经验或半经验关系,这些关系仅在狭窄的参数范围内有效,这使得设备设计的放大不可靠且昂贵。典型的分析方法要么是侵入式的,从而干扰过程,要么是基于二维数据的。近年来,非侵入式层析成像技术越来越多地用于研究流化床。磁共振成像技术(MRI)是一项主要应用于医学领域的技术,特别适合于从流化床内部获取空间和时间分辨的动态信息。除了实验研究外,近年来由于计算能力的提高,流化床的数值模拟也变得越来越重要。该项目的主要目的是将流化床技术的专业知识和新颖的模拟方法与创新的实时磁共振成像相结合。作为主要仪器应用(INST 153/152-1 FUGG)的一部分,DFG授予的MRI系统目前正在TUHH安装。MRI系统将具有与临床系统相似直径的垂直孔定向,磁场强度为3特斯拉。该系统将采用强大的磁场梯度和射频硬件,从而实现高空间和时间分辨率。本文将对有振动和无振动的流化床以及不同颗粒类型的流化床进行研究,以详细深入地了解颗粒性质和流化参数对三维流体力学的影响。本项目获得的三维MRI数据与常用的相关性、侵入式探头测量结果和伪二维仪器获得的图像数据进行了比较。除了这些实验研究外,还将进行计算流体动力学模拟与离散元模型(CFD-DEM)的耦合。MRI数据再次用于验证这些数值模型,并对其流化流体动力学预测精度进行了基准测试。这里的重点将是验证常用的阻力和湍流模型以及粗粒度方法。振动将通过移动几何和网格建模。振动和非振动流化床的实时MRI数据将使我们能够验证现有相关性的准确性,或者在TUHH的新型MRI系统中以无与伦比的空间和时间分辨率开发新的更准确的相关性。
英文摘要
Fluidized beds are widely applied in several industrial fields, such as chemical engineering, energy conversion, and pharmaceuticals production. Vibrated bubbling fluidized beds are typically used in the food industry for drying of powders due to the resulting enhanced particle movement. Despite their widespread use, our fundamental physical understanding of the hydrodynamics occurring within fluidized beds is still limited and based on empirical or semi-empirical relations, that are valid only within narrow parameter ranges, making the scale-up of the apparatus design unreliable and expensive. Typical analysis methods are either intrusive and thus interfering with the process or based on 2D data. In recent years, non-intrusive tomographic techniques are increasingly used to study fluidized beds. Magnetic resonance imaging (MRI), a technique that has been mainly applied in the medical field, is particularly suited for obtaining spatially and temporally resolved dynamic information from the interior of fluidized beds. Besides experimental investigations, numerical modelling of fluidized beds has become more and more important during the last years due to increased computational power.The main aim of this project is to combine expertise in fluidized bed technology and novel simulation approaches with innovative real-time magnetic resonance imaging. An MRI system granted by DFG as part of a major instrumentation application (INST 153/152-1 FUGG) is currently being installed at TUHH. The MRI system will feature a vertical bore orientation of a diameter similar to those of clinical systems and a magnetic field strength of 3 Tesla. The system will employ powerful magnetic field gradients and radiofrequency hardware allowing high spatial and temporal resolution. Fluidized beds with and without vibration and different particle types will be investigated to get a detailed and thorough understanding of the effect of particle properties and fluidization parameters on the 3D hydrodynamics. The 3D MRI data obtained in this project are compared with frequently used correlations and with the results of intrusive probe measurements and image data obtained in pseudo-2D apparatuses. In addition to these experimental investigations, computational fluid dynamics simulations coupled with the discrete element model (CFD-DEM) will be performed. The MRI data are again used to test and validate these numerical models and benchmark their prediction accuracy of fluidization hydrodynamics. A specific focus here will be on the validation of frequently used models for drag forces and turbulence as well as coarse graining approaches. The vibration will be modelled by moving geometry and mesh. The real-time MRI data of vibrated and non-vibrated fluidized beds will allow us to validate the accuracy of existing correlations or develop new and more accurate correlations with the unparalleled detail in spatial and temporal resolution in the novel MRI system at TUHH.
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