A CFD technique for predicting the performance of axisymmetric packed bed filters has been developed. The effect on the pressure drop of a non-uniform voidage distribution within the filter bed has been modelled. A radial voidage distribution was derived from a predictive model based on a modified Mueller equation. The pressure loss through the bed was calculated from the Ergun equation, using ...

A-Type heat exchangers are used to meet required heat load with minimum duct dimensions in air-conditioning applications. This greatly reduces the air-conditioning system footprint in residential and commercial applications. The angle and tube spacing of the A-type heat exchangers should be optimized for minimum duct size and maximum heat load. However, existing air side heat transfer and press...

Conditional Functional Dependencies (CFDs) are an extension of Functional Dependencies (FDs) by supporting patterns of semantically related constants, and can be used as rules for cleaning relational data. However, finding CFDs is an expensive process that involves intensive manual effort. To effectively identify data cleaning rules, we take 4 techniques for cleaning the data from sample relati...

Now a day centrifugal pumps are vital components of industries. Certainly, one of the most important specifications of centrifugal pumps are the performance curves. In the present work, performance curves of a centrifugal pumps are obtained by Computational fluid dynamics (CFD) and as an outcome, CFD results compare by practical curves. At the first step impeller and volute are designed with tw...

INTRODUCTION Computational fluid dynamics (CFD) has recently seen increased use in the design of pharmaceutical inhalers. The use of CFD in the design of inhalers is made difficult by the complex nature of aerosol generation. At present, CFD has provided valuable insight into certain aspects of inhaler performance, though limitations in computational power have prevented the full implementation...

The computational cost and memory demand required by fluid dynamics (CFD) codes simulations can become very high. Therefore, the application of convolutional neural networks (CNN) in this field has been studied owing to its capacity learn patterns from sets input data, which considerably approximate results CFD with relative low errors. DeepCFD code taken as a basis some slight variations param...