Functionally graded optimisation of adsorption systems with phase change materials

Abstract

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.

Finite Element Modeling of Atmospheric Water Extraction by Way of Highly Porous Adsorbents: A Roadmap for Solver Construction with Model Factor Sensitivity Screening

“…We neglected the left-hand side unsteady and convective terms which yield the Brinkman equation in equation line 2. Assuming negligible viscous effects (μ v ∇ 2 v v ), we resolve Darcy’s law in equation line 3. This simplified model for density displacement can now replace v v in eq to form a single continuity equation. − This dimensionless characterization of vapor velocity, v v , is known to produce good approximations for gas adsorption in moderate bed porosity and does not require meeting LBB conditions . Kinetic functions such as diffusivity and equilibrium loading characterize vapor displacement and only require approximations for pressure and temperature.…”

“…8−10 This dimensionless characterization of vapor velocity, v v , is known to produce good approximations for gas adsorption in moderate bed porosity 11 and does not require meeting LBB conditions. 12 Kinetic functions such as diffusivity and equilibrium loading characterize vapor displacement and only require approximations for pressure and temperature. Energy Balance.…”

“…The updated pressure and temperature resolve phase concentrations by way of the LDF and then proceeding to the next time step. 12,28 Time discretization follows the backward Euler method.…”

“…This allows for a numerical design in which the mass and energy equations complete numeric differentiation and update pressure and temperature state variables before proceeding to solve for the fluid structure interaction of the vapor phase, the adsorbed phase, and the adsorbent. The updated pressure and temperature resolve phase concentrations by way of the LDF and then proceeding to the next time step. , Time discretization follows the backward Euler method.…”

A numerical investigation of a fixed bed CO2 adsorption process using Phase Change Materials.

“…A typical curve is the bed capacity (calculated in the breakthrough point) in the y-axis versus the volume fraction of the phase change material in the column in the x-axis (BELLAN et al, 2015;HORSTMEIER;GOMEZ LOPEZ;AGAR, 2016;MOTA, 2008;PRADO et al, 2021;SAKANAKA et al, 2020;TOLEDO et al, 2013).…”