首页> 外文OA文献 >Investigation of turbulent multiphase flows in a flat panel photobioreactor and consequent effects on microalgae cultivation; using Computational Fluid Dynamics (CFD) simulation and Particle Image Velocimetry (PIV)
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Investigation of turbulent multiphase flows in a flat panel photobioreactor and consequent effects on microalgae cultivation; using Computational Fluid Dynamics (CFD) simulation and Particle Image Velocimetry (PIV)

机译:研究平板光生物反应器中湍流的多相流动及其对微藻培养的影响;使用计算流体动力学(CFD)模拟和粒子图像测速(PIV)

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摘要

Algae presents itself as a versatile feedstock for the production of fuels and chemicals ranging from omega-3 fatty acids to Jet-A or JP-8 jet fuels. Mixing of algae culture systems is vital to creating this feedstock. A review of mixing details the many algae culture systems employed to produce algae biomass. It also explores the many mixing methods utilized within the culture system and the importance for the design of these mixing methods. This importance of design has led many researchers to develop mathematical approaches to determining mixing characteristics of algae culture systems. Computational Fluid Dynamics (CFD) uses mathematical techniques to characterize fluid dynamics with the ability to designate thousands of equations to be solved by a computer processor. CFD is known for its strength in design and simulation. This technique allows a user to model a system of fluids to predict movement and therefore effectiveness of design while bypassing physical construction. Studies into this technique are presented and express the strength of CFD as a single phase solver and the current challenges of using CFD as a multiphase solver. To complete an understanding of turbulent mixing effects on algae growth performance, multiphase flows were investigated using a measurement technique of Particle Image Velocimetry (PIV). PIV was used to measure the liquid phase fluid characteristics of a Flat Panel Bioreactor (FPB) that was undergoing mixing by steady state aeration. Parameters such as flow rate (Q), mean velocity (v), and mean Turbulent Kinetic Energy (TKE) were characterized for each experiment that was tested across different aeration schemes. These parameters were weighted against each other to come up with a quality of mixing term, San (M) , which was able to predict the ranking of algae growth performance amongst each experiment. As multiphase flows and their consequent effects on microalgae growth performance are further understood, techniques of CFD may be able to simulate and predict effectiveness solely using computing tools.
机译:藻类本身是一种通用的原料,可用于生产燃料和化学品,从omega-3脂肪酸到Jet-A或JP-8喷气燃料。藻类培养系统的混合对于创建这种原料至关重要。有关混合的评论详细介绍了用于生产藻类生物质的许多藻类培养系统。它还探讨了培养系统中使用的许多混合方法以及这些混合方法设计的重要性。设计的重要性已导致许多研究人员开发出数学方法来确定藻类培养系统的混合特性。计算流体动力学(CFD)使用数学技术来表征流体动力学,并能够指定要由计算机处理器解决的数千个方程。 CFD因其在设计和仿真方面的实力而闻名。该技术允许用户对流体系统建模,以预测运动,从而预测设计的有效性,同时绕过物理构造。提出了对该技术的研究,并表达了CFD作为单相求解器的优势以及使用CFD作为多相求解器的当前挑战。为了完全理解湍流混合对藻类生长性能的影响,使用粒子图像测速技术(PIV)的测量技术研究了多相流。 PIV用于测量通过稳态曝气进行混合的平板生物反应器(FPB)的液相流体特性。对于通过不同曝气方案进行测试的每个实验,对流量(Q),平均速度(v)和平均湍动能(TKE)等参数进行了表征。将这些参数相互加权以得出混合项质量San(M),它可以预测每个实验中藻类生长性能的排名。随着对多相流及其对微藻生长性能的影响的进一步理解,CFD技术可能能够仅使用计算工具来模拟和预测有效性。

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    del Ninno, Matteo Power;

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  • 年度 2012
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