A Machine-Learning-Based Surrogate Model for Internal Flow Nusselt Number and Friction Factor in Various Channel Cross Sections

2021 ◽  
Author(s):  
Saeel S. Pai ◽  
Dhvaneel Visaria ◽  
Justin A. Weibel
Keyword(s):  
Machine Learning ◽  
Nusselt Number ◽  
Friction Factor ◽  
Cross Sections ◽  
Surrogate Model ◽  
Internal Flow

scholarly journals Internal Flow in an Enhanced Tube Having Square-cut Twisted Tape Insert

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 306 ◽  
Author(s):  
Agung Wijayanta ◽  
Pranowo ◽  
Mirmanto ◽  
Budi Kristiawan ◽  
Muhammad Aziz
Keyword(s):  
Nusselt Number ◽  
Friction Factor ◽  
Thermal Performance ◽  
Single Phase ◽  
Internal Flow ◽  
Working Fluid ◽  
Twisted Tape ◽  
Number Range ◽  
Enhanced Tube ◽  
Plain Tube

In this study, a numerical simulation has been conducted in order to evaluate the thermal hydraulic performance of a turbulent single-phase flow inside an enhanced tube equipped with a square-cut twisted tape (STT) insert. The classical twisted tape (CTT) insert was also investigated for comparison. The k-ε renormalized group turbulence model has been utilized as the turbulent model. Various twist ratios (y/W) of 2.7, 4.5, and 6.5 were investigated for the Reynolds number range of 8000–18,000, with water as the working fluid. The numerical results indicated that, in comparison with the plain tube (PT), the tube equipped with the STT with the twist ratios of 2.7, 4.5, and 6.5 led to an increase in the values of the Nusselt number and friction factor in the inner tube by 45.4–80.7% and 2.0–3.3 times, respectively; in addition, the highest thermal performance of 1.23 has been obtained. The results further indicated that the tube equipped with the CTT of the same twist ratios improved the Nusselt number and friction factor in the inner tube by 40.3–74.4% and 1.7–3.0 times, respectively, in comparison with the PT; further, the maximum thermal performance of 1.18 was achieved.

Efficiency assessment of using graphene nanoplatelets-silver/water nanofluids in microchannel heat sinks with different cross-sections for electronics cooling

2019 ◽  
Vol 30 (1) ◽  
pp. 347-372 ◽  
Author(s):  
Marjan Goodarzi ◽  
Iskander Tlili ◽  
Zhe Tian ◽  
Mohammad Reza Safaei
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Nusselt Number ◽  
Pressure Drop ◽  
Friction Factor ◽  
Cross Sections ◽  
Graphene Nanoplatelets ◽  
Heat Sinks ◽  
Pumping Power ◽  
Content Type

Purpose This study aims to model the nanofluid flow in microchannel heat sinks having the same length and hydraulic diameter but different cross-sections (circular, trapezoidal and square). Design/methodology/approach The nanofluid is graphene nanoplatelets-silver/water, and the heat transfer in laminar flow was investigated. The range of coolant Reynolds number in this investigation was 200 ≤ Re ≤ 1000, and the concentrations of nano-sheets were from 0 to 0.1 vol. %. Findings Results show that higher temperature leads to smaller Nusselt number, pressure drop and pumping power, and increasing solid nano-sheet volume fraction results in an expected increase in heat transfer. However, the influence of temperature on the friction factor is insignificant. In addition, by increasing the Reynolds number, the values of pressure drop, pumping power and Nusselt number augments, but friction factor diminishes. Research limitations/implications Data extracted from a recent experimental work were used to obtain thermo-physical properties of nanofluids. Originality/value The effects of temperature, microchannel cross-section shape, the volume concentration of nanoparticles and Reynolds number on thermal and hydraulics behavior of the nanofluid were investigated. Results are presented in terms of velocity, Nusselt number, pressure drop, friction loss and pumping power in various conditions. Validation of the model against previous papers showed satisfactory agreement.

Heat Transfer and Pressure Drop of Periodically Fully Developed Swirling Laminar Flows in Twisted Tubes With Elliptical Cross Sections

2009 ◽  
Author(s):  
Fady Bishara ◽  
Milind A. Jog ◽  
Raj M. Manglik
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Nusselt Number ◽  
Friction Factor ◽  
Cross Section ◽  
Cross Sections ◽  
Laminar Flows ◽  
Elliptical Cross ◽  
Twist Ratio ◽  
Twisted Tubes

Periodically fully-developed swirling laminar flows in twisted tubes with elliptical cross sections are computationally simulated. The tubes are helically twisted and their geometry is described by the 180° twist ratios y of 3.0, 4.5 and 6.0, and ellipse cross-section aspect ratio of 0.7. Constant-property flow of water (nominal Pr = 3.0) with a Reynolds number range of 10 to 1200 is considered. The analysis quantifies the improvement in the Nusselt number as well as the increase in friction factor in order to map the effective heat transfer enhancement due to the twisted-tube-geometry-induced swirl flows. To this effect, the numerical results are compared with the baseline cases having a twist ratio of y = infinity, or straight elliptical cross-section tubes for which well established correlations are available. Numerical results show that the friction factor and the Nusselt number are a strong function of the twist ratio and the Reynolds number. The increase in fRe and Nu is higher as the twist becomes tighter (lower values of y). For Reynolds numbers below about 100, the heat transfer results do not deviate significantly from the straight-tube values, but at higher values of Re, significant enhancement in heat transfer is evident for all twist ratios considered here. The friction factor and Nusselt number results provided in this paper will help practicing engineers in integrating twisted elliptical tubes in various heat transfer applications.

Correlation development for Nusselt number and friction factor of a multiple type V-pattern dimpled obstacles solar air passage

2017 ◽  
Vol 109 ◽  
pp. 461-479 ◽  
Author(s):  
Anil Kumar ◽  
Raj Kumar ◽  
Rajesh Maithani ◽  
Ranchan Chauhan ◽  
Muneesh Sethi ◽  
...  
Keyword(s):  
Nusselt Number ◽  
Friction Factor ◽  
Air Passage ◽  
Type V ◽  
Multiple Type

Machine learning-based discrete event dynamic surrogate model of communication systems for simulating the command, control, and communication system of systems

SIMULATION ◽  
2018 ◽  
Vol 95 (8) ◽  
pp. 673-691 ◽  
Author(s):  
Bong Gu Kang ◽  
Kyung-Min Seo ◽  
Tag Gon Kim
Keyword(s):  
Machine Learning ◽  
Communication System ◽  
Surrogate Model ◽  
Discrete Event ◽  
System Of Systems ◽  
System Model ◽  
Characteristic Functions ◽  
Combat Effectiveness ◽  
Communication Effect ◽  
Event Dynamic

Command and control (C2) and communication are at the heart of successful military operations in network-centric warfare. Interoperable simulation of a C2 system model and a communication (C) system model may be employed to interactively analyze their detailed behaviors. However, such simulation would be inefficient in simulation time for analysis of combat effectiveness of the C2 model against possible input combinations while considering the communication effect in combat operations. This study proposes a discrete event dynamic surrogate model (DEDSM) for the C model, which would be integrated with the C2 model and simulated. The proposed integrated simulation reduces execution time markedly in analysis of combat effectiveness without sacrificing the accuracy reflecting the communication effect. We hypothesize the DEDSM as a probabilistic priority queuing model whose semantics is expressed in a discrete event systems specification model with some characteristic functions unknown. The unknown functions are identified by machine learning with a data set generated by interoperable simulation of the C2 and C models. The case study with the command, control, and communication system of systems first validates the proposed approach through an equivalence test between the interoperable simulation and the proposed one. It then compares the simulation execution times and the number of events exchanged between the two simulations.

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