scholarly journals Computational Fluid Dynamics Simulation and Experimental Study of Key Design Parameters of Solar Thermal Collectors

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
James Allan ◽  
Zahir Dehouche ◽  
Sinisa Stankovice ◽  
Alan Harries
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Thermal Efficiency ◽  
Thermal Contact ◽  
High Surface ◽  
Heat Removal ◽  
Solar Thermal ◽  
Dynamics Simulation ◽  
Low Flow ◽  
Design Parameters

Numerical simulation enables the optimization of a solar collector without the expense of building prototypes. This study details an approach using computational fluid dynamics (CFD) to simulate the performance of a solar thermal collector. Inputs to the simulation include; heat loss coefficient, irradiance, and ambient temperature. A simulated thermal efficiency was validated using experimental results by comparing the calculated heat removal factor. The validated methodology was then applied to five different inlet configurations of a header–riser collector. The most efficient designs had uniform flow through the risers. The worst performing configurations had low flow rates in the risers that led to high surface temperatures and poor thermal efficiency. The calculated heat removal factor differed by between 4.2% for the serpentine model and 12.1% for the header–riser. The discrepancies were attributed to differences in thermal contact between plate and tubes in the simulated and actual design.

scholarly journals Computational Fluid Dynamics of Heat Transfer in Stirred Tank Reactors

2021 ◽  
Author(s):  
Chaitanya Moholkar ◽  
Punit Gharat ◽  
Vivek Vitankar ◽  
Channamallikarjun Mathpati ◽  
Jyeshtharaj Joshi
Keyword(s):  
Heat Transfer ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Reynolds Number ◽  
Heat Removal ◽  
Design Parameters ◽  
Operational Parameters ◽  
Power Requirement ◽  
Maximum Heat ◽  
Maximum Heat Transfer

In the present work, computational fluid dynamics study of stirred tanks of three sizes (20L, 400L and 5000L) provided with helical coils has been carried out. Various design parameters (impeller diameter, type and clearance) and operational parameters (Reynolds Number and Power per unit volume) have been varied and their effect on process side heat transfer coefficient has been studied. CFD model is validated with experimental work of Cummings and West[9] and in house experimentation. Design settings of D/T=0.5, C/T=0.33 for PBTD450 resulted in maximum heat transfer (5440 W/m2K for P/V=1000 W/m3). For constant RPM and constant D/T (Constant Reynolds Number), Increasing the power number of impeller increased process side HTC at the cost of increased power requirement (decreasing efficiency). In such cases, proper selection of impeller system needs to be made based on the requirements of heat removal and optimizing parameters such as product yield, product quality etc.

Computational Fluid Dynamics Simulation of a Tubular Aerosol Reactor for Solar Thermal ZnO Decomposition

2007 ◽  
Author(s):  
Christopher Perkins ◽  
Alan W. Weimer
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Surface ◽  
High Surface Area ◽  
Dynamics Simulation ◽  
Base Case ◽  
Reactor Wall ◽  
Conductive Heat ◽  
Sensitive Material ◽  
Aspect Ratios

Computational fluid dynamics simulations were performed to model solar ZnO dissociation in a tubular aerosol reactor at ultra-high temperatures (1900 K–2300 K). Reactor aspect ratios ranged between 0.15 and 0.45, with the smallest ratio base case corresponding to a reactor diameter of .02286 m. Gas flowrates were set such that the Ar:ZnO ratio was greater than 3:1 and the system residence time was below 2 s. The system was found to exhibit highly laminar flow in all cases (Re ∼ 10), but gas velocity profiles did not seriously affect temperature profiles. Particle heating was nearly instantaneous, a result of the high radiation heat flux from the wall. There was essentially no difference between gas and particle temperatures due to the high surface area for conductive heat exchange between the phases. Calculation of ZnO conversion showed that significant conversions (>90%) could be attained for residence times typical of rapid aerosol processing. Particle sizes larger than 1 μm negatively affected conversion, but sizes of 10 μm still gave acceptable conversion levels. Simulation of reaction of product oxygen with the reactor wall showed that a reactor constructed of an oxidation-sensitive material would not be a viable choice for a high temperature solar reactor.

Computational Fluid Dynamics Simulation of a Tubular Aerosol Reactor for Solar Thermal ZnO Decomposition

2007 ◽  
Vol 129 (4) ◽  
pp. 391-404 ◽  
Author(s):  
Christopher Perkins ◽  
Alan Weimer
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
High Surface ◽  
Dynamics Simulation ◽  
Base Case ◽  
Reactor Wall ◽  
Conductive Heat ◽  
Sensitive Material ◽  
Aspect Ratios

Computational fluid dynamics simulations were performed to model solar ZnO dissociation in a tubular aerosol reactor at ultrahigh temperatures (1900–2300K). Reactor aspect ratios ranged between 0.15 and 0.45, with the smallest ratio base case corresponding to a reactor diameter of 0.02286m. Gas flow rates were set such that the Ar:ZnO ratio was greater than 3:1 and the system residence time was below 2s. The system was found to exhibit highly laminar flow in all cases (Re∼10), but gas velocity profiles did not seriously affect temperature profiles. Particle heating was nearly instantaneous, a result of the high radiation heat flux from the wall. There was essentially no difference between gas and particle temperatures due to the high surface area for conductive heat exchange between the phases. Calculation of ZnO conversion showed that significant conversions (>90%) could be attained for residence times typical of rapid aerosol processing. Particle sizes of >1μm negatively affected conversion, but sizes of 10μm still gave acceptable conversion levels. Simulation of reaction of product oxygen with the reactor wall showed that a reactor constructed of an oxidation-sensitive material would not be a viable choice for a high temperature solar reactor.

scholarly journals Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
David R. Rutkowski ◽  
Alejandro Roldán-Alzate ◽  
Kevin M. Johnson
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Velocity Fields ◽  
Dynamics Simulation ◽  
Patient Specific ◽  
4D Flow Mri ◽  
4D Flow ◽  
Flow Phase ◽  
Flow Mri ◽  
Trained Network

AbstractBlood flow metrics obtained with four-dimensional (4D) flow phase contrast (PC) magnetic resonance imaging (MRI) can be of great value in clinical and experimental cerebrovascular analysis. However, limitations in both quantitative and qualitative analyses can result from errors inherent to PC MRI. One method that excels in creating low-error, physics-based, velocity fields is computational fluid dynamics (CFD). Augmentation of cerebral 4D flow MRI data with CFD-informed neural networks may provide a method to produce highly accurate physiological flow fields. In this preliminary study, the potential utility of such a method was demonstrated by using high resolution patient-specific CFD data to train a convolutional neural network, and then using the trained network to enhance MRI-derived velocity fields in cerebral blood vessel data sets. Through testing on simulated images, phantom data, and cerebrovascular 4D flow data from 20 patients, the trained network successfully de-noised flow images, decreased velocity error, and enhanced near-vessel-wall velocity quantification and visualization. Such image enhancement can improve experimental and clinical qualitative and quantitative cerebrovascular PC MRI analysis.

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