Topology optimisation of biphasic adsorbent beds for gas storage

Amigo, R. C. R.; Prado, D. S.; Paiva, J. L.; Hewson, Robert; Silva, E. C. N.

doi:10.1007/s00158-018-2117-x

Cited by 7 publications

(7 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We now give here a result about the regularity of the boundary stress tensor that justify the equivalence between (1,2) and its weak formulation (4). The latter can also be used when considering inhomogeneous traction boundary conditions such as ε 2Re −1 S( u) − p n = ϕ, on some part of the boundary.…”

Section: Picard-like Iteration For Solving the Non-linear Discrete Prmentioning

confidence: 90%

“…Let u, v, w ∈ X. From the continuous Sobolev' embedding H 1 (Ω) ⊂ L 4 (Ω) together with Hölder inequality, we get that…”

Section: Well-posedness Of the Darcy-brinkman-forchheimer Problemmentioning

confidence: 99%

“…where ( u, p) satisfies (4) and ( u h , p h ) = ( w h + I X h V , p h ) satisfies (13). We then get optimal error estimates for the finite element approximation using a discretization of the porosity of the solution to the Darcy-Forcheimer-Brinkman model with mixed boundary conditions.…”

Section: The Non-linear Problem Using a Discrete Porositymentioning

confidence: 99%

“…Lemma 19. Assume that ε ∈ L ∞ (Ω) ∩ W 1,4 (Ω) and that α(ε), β(ε) ∈ L ∞ (Ω). Let f ∈ L 2 (Ω) d and ( u, p) ∈ H 1 (Ω) d × L 2 (Ω) satisfying (1).…”

Section: Theorem 2])mentioning

confidence: 99%

“…Another advantage of having a finite element formulation with discrete parameters is when one deals with so-called topology optimization problems (see e.g. [4,42,5,38]) or parametric optimization problem [6,Chapter VI]. Indeed, using discretization of these parameters are nedded to define discrete optimization problem and to prove the convergence of discrete optimal solution toward the continuous optimal solutions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Error analysis for the finite element approximation of the Darcy–Brinkman–Forchheimer model for porous media with mixed boundary conditions

Cocquet

Rakotobe²,

Ramalingom³

et al. 2021

Journal of Computational and Applied Mathematics

View full text Add to dashboard Cite

This paper deals with the finite element approximation of the Darcy-Brinkman-Forchheimer equation, involving a porous media with spatially-varying porosity, with mixed boundary condition such as inhomogeneous Dirichlet and traction boundary conditions. We first prove that the considered problem has a unique solution if the source terms are small enough. The convergence of a Taylor-Hood finite element approximation using a finite element interpolation of the porosity is then proved under similar smallness assumptions. Some optimal error estimates are next obtained when assuming the solution to the Darcy-Brinkman-Forchheimer model are smooth enough. We end this paper by providing a fixedpoint method to solve iteratively the discrete non-linear problems and with some numerical experiments to make more precise the smallness assumptions on the source terms and to illustrate the theoretical convergence results.

show abstract

Section: Picard-like Iteration For Solving the Non-linear Discrete Prmentioning

confidence: 90%

“…Let u, v, w ∈ X. From the continuous Sobolev' embedding H 1 (Ω) ⊂ L 4 (Ω) together with Hölder inequality, we get that…”

Section: Well-posedness Of the Darcy-brinkman-forchheimer Problemmentioning

confidence: 99%

Section: The Non-linear Problem Using a Discrete Porositymentioning

confidence: 99%

“…Lemma 19. Assume that ε ∈ L ∞ (Ω) ∩ W 1,4 (Ω) and that α(ε), β(ε) ∈ L ∞ (Ω). Let f ∈ L 2 (Ω) d and ( u, p) ∈ H 1 (Ω) d × L 2 (Ω) satisfying (1).…”

Section: Theorem 2])mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Error analysis for the finite element approximation of the Darcy–Brinkman–Forchheimer model for porous media with mixed boundary conditions

Cocquet

Rakotobe²,

Ramalingom³

et al. 2021

Journal of Computational and Applied Mathematics

View full text Add to dashboard Cite

show abstract

Optimization loop based on adjoint sensitivity analysis for flows through porous media with adsorption

Chieregatti

Lima

Hayashi

et al. 2021

Numerical Meth Engineering

View full text Add to dashboard Cite

In the past few years, the development of inverse design and optimization methods has opened up new possibilities. The adjoint method is of great significance in that context, since it permits high fidelity to flow‐physics at comparatively low computational costs. The present work focuses on adsorbed gas storage systems. Its contribution is the development of an alternative approach to the adjoint contour problem, which ensures that the latter is as well‐posed as the physical problem, itself. This approach proves to be fully consistent with Cacuci's methodology for computing sensitivity derivatives, which enables us to extend their scope. It allows for the evaluation of sensitivities with respect to parameters other than those pertaining to geometry, that is, to those that control the system operation such as average mass flux, convective heat transfer, inlet and external temperature. The main goal of this work is to obtain and validate a basic structure of an optimization loop algorithm (OLA) based on adjoint method, applied to adsorption natural gas storage systems, with pressure and density of adsorption as objective functions.

show abstract

Functionally graded optimisation of adsorption systems with phase change materials

Prado

Amigo

Hewson

et al. 2021

Struct Multidisc Optim

Self Cite

View full text Add to dashboard Cite

Adsorption phenomena are encountered in several engineering applications. One of its uses is in the storage and transport of gas in the form of adsorption tanks. The exothermic nature of the adsorption process decreases adsorption capacity presenting an impetus to understand the thermal characteristics of the gas storage process. Studies using mixtures of phase change materials and adsorbents in adsorption tanks demonstrate potential improvements in the adsorption capacity of the tanks. They also show that the distribution of phase change materials and adsorbent are important. Thus, this work presents two approaches for optimising the adsorbent domain. The first is to use a semi-analytic model to determine the best homogeneous material concentration for the adsorbent and phase change material for the vessel composition. The other is to use a 2D axisymmetric model to perform FGM optimisation to distribute material in the tank. Results for both models are presented and discussed for different conditions. The study shows that, for the cylindrical geometry, FGM optimisation is always, at least, marginally better than the homogeneous distribution from the semi-analytic model. However, FGM optimisation demands more computing time increases the complexity of implementation and results assembling. The semi-analytic approach is a possible alternative for optimising adsorption systems with phase change material mixed with adsorbents.

show abstract

Topology optimisation of biphasic adsorbent beds for gas storage

Cited by 7 publications

References 35 publications

Error analysis for the finite element approximation of the Darcy–Brinkman–Forchheimer model for porous media with mixed boundary conditions

Error analysis for the finite element approximation of the Darcy–Brinkman–Forchheimer model for porous media with mixed boundary conditions

Optimization loop based on adjoint sensitivity analysis for flows through porous media with adsorption

Functionally graded optimisation of adsorption systems with phase change materials

Contact Info

Product

Resources

About