2016
DOI: 10.1016/j.ijthermalsci.2016.02.001
|View full text |Cite
|
Sign up to set email alerts
|

Heat transfer enhancement of a periodic array of isothermal pipes

Abstract: We address the problem of two-dimensional heat conduction in a solid slab whose upper and lower surfaces are subjected to uniform convection. In the midsection of the slab there is a periodic array of isothermal pipes of general cross section. The main objective of this work is to find the optimum shapes of the pipes that maximize the Shape Factor (heat transport rate). The Shape Factor is obtained by transforming the periodic array of pipes into a periodic array of strips, using the generalized SchwarzChristo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

0
3
0

Year Published

2017
2017
2019
2019

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(3 citation statements)
references
References 39 publications
(83 reference statements)
0
3
0
Order By: Relevance
“…For example, the objective function can be the difference between the computed temperature and the measured/prescribed temperature and the unknowns can be the boundary conditions, physical properties or the geometry of the configuration [10,11,12,13,14,15]. Another example is to have the heat flux as the objective function and obtain the shapes that optimize it [16,17,18,19,20,21,9].…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…For example, the objective function can be the difference between the computed temperature and the measured/prescribed temperature and the unknowns can be the boundary conditions, physical properties or the geometry of the configuration [10,11,12,13,14,15]. Another example is to have the heat flux as the objective function and obtain the shapes that optimize it [16,17,18,19,20,21,9].…”
Section: Introductionmentioning
confidence: 99%
“…Hence the solver gets trapped in local minima or diverges. Regarding inverse shape optimization problems, remedies to address the ill-possing include mapping the physical domain onto a fixed computational domain [16,17,18,19,20,21] and redistribution of ill-ordered nodal points [12,13,14,15], Tikhonov regularization [22], homogenization [23], or transforming the problem into a parameter estimation by expanding the shape in terms of a small number of parameters, e.g. adaptive mesh [24], eigenfunction expansion [10], and mesh-morphing [25].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation