Investigation of dimensionless parameters and geometry effects on heat‐transfer characteristics of liquid sodium flowing over a flat plate

Kaladgi, Abdul Razak; Afzal, Asif; Ad, Mohammad Samee; Mk, Ramis

doi:10.1002/htj.21368

Cited by 13 publications

(7 citation statements)

References 23 publications

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“…The above non-dimensionalized parameters are selected based on previous research work that are close to conjugate study of parallel plate channel (Kaladgi et al 2019;Abdul Razak et al 2019;Mohamme Samee et al 2019;Samee et al 2018).…”

Section: Numerical Methodologymentioning

confidence: 99%

Parallel performance analysis of coupled heat and fluid flow in parallel plate channel using CUDA

2020

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The heat transfer analysis coupled with fluid flow is important in many real-world application areas varying from micro-channels to spacecraft's. Numerical prediction of thermal and fluid flow situation has become very common method using any computational fluid dynamics software or by developing in-house codes. One of the major issues pertinent to numerical analysis lies with immense computational time required for repeated analysis. In this article, technique applied for parallelization of in-house developed generic code using CUDA and OpenMP paradigm is discussed. The parallelized finite-volume method (FVM)-based code for analysis of various problems is analyzed for different boundary conditions. Two GPUs (graphical processing units) are used for parallel execution. Out of four functions in the code (U, V , P, and T), only P function is parallelized using CUDA as it consumes 91% of computational time and the rest functions are parallelized using OpenMP. Parallel performance analysis is carried out for 400, 625, and 900 threads launched from host for parallel execution. Improvement in speedup using CUDA compared with speedup using complete OpenMP parallelization on different computing machines is also provided. Parallel efficiency of the FVM code for different grid size, Reynolds number, internal flow, and external flow is also carried out. It is found that the GPU provides immense speedup and outperforms OpenMP largely. Parallel execution on GPU gives results in a quite acceptable amount of time. The parallel efficiency is found to be close to 90% in internal flow and 10% for external flow.

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Section: Numerical Methodologymentioning

confidence: 99%

Parallel performance analysis of coupled heat and fluid flow in parallel plate channel using CUDA

2020

Self Cite

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“…The contour plot shown in Figure 14 indicates that the lowest roughness is obtained when the flow rate is high and cutting speed is low [38][39][40]. This area appears at the back left corner of the plot.…”

Section: Predicted Results By Taguchi Methodmentioning

confidence: 99%

“…A nickel-based superalloy, Inconel 718 has features such as limited thermal conductivity, work hardening, and the ability to maintain strength in high-temperature environments, and it is tough to cut [37][38][39][40]. As a result, surface smoothness is critical when machining Inconel 718.…”

Section: Work Materials Usedmentioning

confidence: 99%

Inconel 718 Turning Process Parameters Optimization with MQL Nanofluid Based on CuO Nanoparticles

Mane¹,

Kallol²,

Doiphode³

et al. 2022

Journal of Nanomaterials

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This study examined the effects of a minimum quantity lubrication (MQL) and a Cupric oxide- (CuO-) based nanofluid on Inconel 718 machinability. Additionally, by using an MQL CuO-based nanofluid during the turning process, Inconel 718’s tribological characteristics are optimised. The experimentation was done using the minimum quantity lubrication (MQL) method. With the aid of magnetic stirring and an ultrasonic bath process, CuO nanoparticles were dispersed in distilled water, sunflower oil, and soyabean oil to create nanofluid. Soyabean oil contains uniformly distributed CuO nanoparticles. All the experimental trials are designed based on the L18 Taguchi-based orthogonal arrays and performed on CNC turning under MQL and nanofluid environment. There are four input parameters that were selected at mixed level, namely, cutting speed, feed rate, weight % of CuO in the nanofluid, and flow rate to analyze surface roughness and tool wear. In addition to that, the response surface method was used to identify the optimum condition for better surface roughness and tool wear. Surface roughness and tool wear were measured using the surface roughness tester and toolmaker’s microscope, respectively. Experimental results observed that cutting speed and weight % highly affect surface roughness whereas cutting speed and flow rate affect tool wear. The predicted optimal values for lower surface roughness are 160 ml/hr flow rate, 92.99 m/min cutting speed, 3 weight % of CuO, and 0.1 mm/min feed rate and for low tool wear 80 ml/hr flow rate, 92.99 m/min cutting speed, 3 weight % of CuO, and 0.1 mm/min feed rate.

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“…(8) are discretized using Alternating Direction Implicit (ADI) scheme and the resulting system of finite difference equations are solved using 'Thomas Algorithm'. The computer code validation and grid independence test are explained in detail in [29][30][31].…”

Section: Methodsmentioning

confidence: 99%

Temperature and Location of Hot Spots Variation with Spacing in a Vertical Parallel Plate Channel: Conjugate View

Mohammad¹,

Afzal²,

Razak³

et al. 2019

IJHT

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The objective of present investigation is twofold, one to determine the effect of operational parameter on maximum temperature (Hot spots temperature) in heat generating (uniform and non-uniform) vertical parallel plates and two is to find out the position of maximum temperature (hot spots location) when plates are placed apart at optimum spacing (Bopt). A conjugate two dimensional laminar forced convection analysis is carried out in which the equations regulating the heat and fluid flow are solved by using finite difference numerical technique and the obtained algebraic equations are solved by using Thomas algorithm. The parameters viz Reynolds Number (ReH), Conduction-Convection parameter (Ncc), Heat generation parameter (Qt), and Prandtl Number (Pr), Spacing between the plates (B) were considered for present study, while the aspect ratio (Ar) of the plate is kept constant. The major outcome of present study says that the location of hot spot is mainly affected by ReH and mode of heat generation (uniform and non-uniform). It is also found that the spacing between the plates (B), ReH, Pr and Ncc play a major role in reducing the hotspots temperature.

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Investigation of dimensionless parameters and geometry effects on heat‐transfer characteristics of liquid sodium flowing over a flat plate

Cited by 13 publications

References 23 publications

Parallel performance analysis of coupled heat and fluid flow in parallel plate channel using CUDA

Parallel performance analysis of coupled heat and fluid flow in parallel plate channel using CUDA

Inconel 718 Turning Process Parameters Optimization with MQL Nanofluid Based on CuO Nanoparticles

Temperature and Location of Hot Spots Variation with Spacing in a Vertical Parallel Plate Channel: Conjugate View

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