Constructal multi-scale design of compact micro-tube heat sinks and heat exchangers

2007 ◽  
Vol 46 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Y.S. Muzychka
2021 ◽  
Author(s):  
Davide Cazzaro ◽  
Alessio Trivella ◽  
Francesco Corman ◽  
David Pisinger

2001 ◽  
Author(s):  
V. S. Travkin

Abstract The primary difficulty in semiconductor heat sink (and many other types of heat exchangers) research and design is not a lack of interest or money, but rather confusion with what being looked for and adequacy of the tools used for the search. As recently shown, there are few meaningful parameters (apart from sizes and weight) or physical characteristics of interest in semiconductor cooler design are local values. Even the maximum temperature of the base Tmax or semiconductor temperature are not local. In this work outlined the description in detail of arguments on how, and for what reasons, the measured data are to be simulated or measured and represented in a way that allows design goals to be formulated primarily with bulk physical characteristics. We demonstrate why studies of only averaged local integrated variables are not enough. Four sample semiconductor heat sinks of two morphologies (three samples of round pin fin and one sample of longitudinal rib fin sinks) were studied by different techniques and models. There were changes in by-pass values, external heat flux and flow rate. The results are depicted with using new parameters that better represent the needs of a design process as well as the usual parameters used in the past. Characteristics reported are the heat transfer rate in solid phase, relative fin effectiveness, and influence of only morphology features among others. Some suggestions for heat sink design are discussed.


Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2965 ◽  
Author(s):  
Augusto Della Torre ◽  
Gianluca Montenegro ◽  
Angelo Onorati ◽  
Sumit Khadilkar ◽  
Roberto Icarelli

Plate heat exchangers including offset-strip fins or dimple-type turbulators have a wide application in the automotive field as oil coolers for internal combustion engines and transmissions. Their optimization is a complex task since it requires targeting different objectives: High compactness, low pressure drop and high heat-transfer efficiency. In this context, the availability of accurate Computational Fluid Dynamics (CFD) simulation models plays an important role during the design phase. In this work, the development of a computational framework for the CFD simulation of compact oil-to-liquid heat exchangers, including offset-strip fins and dimples, is presented. The paper addresses the modeling problem at different scales, ranging from the characteristic size of the turbulator geometry (typically µm–mm) to the full scale of the overall device (typically cm–dm). The simulation framework is based on multi-scale concept, which applies: (a) Detailed simulations for the characterization of the micro-scale properties of the turbulator, (b) an upscaling approach to derive suitable macro-scale models for the turbulators and (c) full-scale simulations of the entire cooler, including the porous models derived for the smaller scales. The model is validated comparing with experimental data under different operating conditions. Then, it is adopted to investigate the details of the fluid dynamics and heat-transfer process, providing guidelines for the optimization of the device.


Author(s):  
H. Issa ◽  
M.Z. Tzen ◽  
M. Lenczner ◽  
R. Habib ◽  
E. Ostrosi ◽  
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Keyword(s):  

2011 ◽  
Vol 173 (2) ◽  
pp. 541-551 ◽  
Author(s):  
J.-M. Commenge ◽  
M. Saber ◽  
L. Falk

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Pinar Acar

Abstract We present a new sampling method for the multi-scale design of polycrystalline materials, which improves the computational time efficiency compared to the existing computational approaches. The solution strategy aims to find microstructure designs that optimize component-scale mechanical properties. The microstructure is represented with a probabilistic texture descriptor that quantifies the volume fractions of different crystallographic orientations. However, the original microstructure design space is high-dimensional and thus optimization in this domain is not favorable. Instead, we generate property closures, which are the reduced spaces of volume-averaged material properties that are computed in terms of the microstructural texture descriptors. We observe that the traditional design approaches which are based on sampling in the original microstructure space and sampling on the property closure are inefficient as they lead to highly concentrated design samples in the solution space. Therefore, we introduce a new sampling method in the property closure, which creates simplexes using the triangulation of the property hull and then generating samples for each simplex. Example problems include the optimization of Galfenol and α-titanium microstructures to improve non-linear material properties. The new sampling approach is shown to obtain better solutions while decreasing the required computational time compared to the previous microstructure design methods.


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