Multi-scale analyses of cycled industrial-scale packed-bed adsorbers

Separations processes account for 10%–15% of the total energy consumed in process\ua0industries worldwide. In such separation processes, it is common to use activated carbon in packed-bed adsorbers, to remove undesired substances from a process stream.\ua0This is particularly useful for the removal of harmful volatile organic compounds\ua0(VOCs) in a multitude of settings and in an ever-growing, billion-dollar industry.\ua0Much research effort has been expended in understanding and improving the use\ua0of activated carbon for VOC removal. In this context, numerical modeling has\ua0become an increasingly useful tool as computers become more powerful and faster.Most of the currently used numerical models describe laboratory-scale environments,\ua0where the circumstances regarding the state and operation of the adsorbers are well-controlled. However, very little work has been done on this topic for industrial scale,\ua0with real-world operational cycles and bed states. Since there are major differences\ua0between the industrial operation of packed-bed units and laboratory-scale controlled\ua0environments, the applicability and performance of numerical models for real-world\ua0industrial settings need to be investigated.In this work, a one-dimensional (1D) numerical model is formulated for an industrial-size adsorber and compared with real-world, industrial temperature data from a\ua0biomass gasification plant operated in Gothenburg, Sweden. The end-goal of the\ua0model is an improved understanding of the requirements for a successful numerical\ua0model of real-world, industrial conditions. This is done to facilitate the design and\ua0optimization of packed-bed setups for industrial conditions before construction of\ua0the actual facilities, as well as to characterize and improve units that are already operational. The model is also used to study how best to simulate industrial conditions\ua0and how to use steam as a regeneration medium for temperature-swing adsorption\ua0(TSA) operation.To improve packed-bed adsorbers, a detailed three-dimensional (3D) numerical study\ua0is also performed on the material packing structure. Here, the flow through a bed\ua0section is studied and packings with different particle shapes are compared using the\ua0Lattice Boltzmann Method (LBM).The results show that major trends in the industrial data are captured, while some\ua0aspects of the dynamics of the real process are not well-described. This is due to the\ua0complex composition of the product gas from biomass gasification, and limitations\ua0associated with the adopted modeling for steam and water. The results also show\ua0that in order to simulate industrial cases, the cycling procedure used in industry\ua0should be incorporated into the model, so as to account for the different adsorption\ua0mechanisms that emerge during cycling. Finally, it is shown that packing the bed\ua0with spherical (rather than cylindrical) particles reduces the pressure drop across\ua0the bed

Numerical simulations of industrial-scale packed-bed adsorbers

A common technique for removing harmful substances, for either persons or equipment, from a stream is to use the phenomenon of adsorption. This technique is used in, for example, water purification, personal protection, chemical and pharmaceutical production and biomass gasification. In a biomass gasification plant called GoBiGas in Gothenburg, Sweden, beds packed with activated carbon were used to remove light tars from the product gas, where the tars adsorbes to the carbon. This was a step in the gas cleaning train used for the production of bio-methane from forest residue streams in an efforttowards a more carbon neutral future. However, the operation of packed beds for continuous substance removal both requires energy, and puts certain technological demands on the plant. For the production of bio-methane, all losses in the plant influence not only the economical aspects, but also the carbon footprint of the end product. Since carbon neutrality is a compelling reason for using bio-methane, this puts further demands on the bed operation. Here, numerical simulations offer increasing opportunities, both with respect to energy optimization, but also to bed design and operation.In this work, we formulate a numerical model for an industrial sized adsorber, used in GoBiGas for benzene removal. The end goal includes an increased general understanding of the requirements for a successful numerical model of real-world, industrial conditions. This is done in order to be able to better design and optimize packed bed setups for industrial conditions before the actual facilities are built. However, the work also allows to better understand and optimize setups already online. The work presented here includes both analysis of industrial data from GoBiGas and an establishment of how a baseline numerical model performs.The numerical model is based on solving the governing equations for the system, with no industry-specific parameter tuning. This is important in order to be able to use the models as a predictive tool, useful in e.g. bed design. A finite volume method is used to numerically simulate the flow, mass- and heat-transport in both time and space. The temperature at different axial positions in the bed is used to compare the numerical simulations with the industrial data. We show that a baseline formulation captures the main characteristics of the temperature signals in a bed but there are dynamics of theindustrial data that are not captured. Three areas are identified that require additional development for a better predictability. Those are that a more complete description of the actual gas composition and a more realistic evaporation rate are required and a model for water drainage would benefit the model

On the roles of interstitial liquid and particle shape in modulating microstructural effects in packed-bed adsorbers

Several industrial applications use packed-bed reactors for heterogeneous processes with intermittent presence of interstitial liquid. One such example is steam-regenerated adsorption systems. Here, we computationally generate two randomly packed beds of the same voidage – one with spheres and one with cylinders – to study the role of particle shape in such a process. We analyze the geometrical characteristics and determine the flow, transport and reaction properties at the same driving pressure difference. We also establish the effect of liquid on these characteristics. The bed of spheres exhibits 69% higher permeability due to differences in microstructure, and its shorter retention time and lower specific surface yields lower conversion in a first-order heterogeneous reaction. However, at the same flow rate, the spheres could be expected to outperform the cylinders. The bed of cylinders exhibits more pronounced local concentration variations due to a dominance of smaller pores, which are not as readily accessible to the flow. The presence of interstitial liquid reduces the permeability and significantly changes the streamwise velocity distributions inside both beds, effectively homogenizing the geometries by filling up the smaller pores. The implications of the present findings for reduced-order modelling of packed-bed adsorbers are discussed

Investigation of steam regeneration strategies for industrial-scale temperature-swing adsorption of benzene on activated carbon

Large-scale separation of substances present at low concentrations is readily performed by adsorption in packed beds that requires recurring energy-intensive regeneration of the adsorbent. The present work uses numerical simulations previously developed for industrial-scale packed-bed benzene sorption on activated carbon with temperature-swing regeneration by steam to investigate the influence of steam properties and regeneration strategy on total energy performance and breakthrough behaviour. It is shown that using saturated steam lowers both the steam mass and energy consumption during regeneration of a fixed amount of benzene, whereas using superheated steam returns the bed to a more fresh-like state after each regeneration stage. The most promising variation tried implies a 19% reduction in the energy consumption. Furthermore, the importance of accounting for the real industrial cycling conditions in the optimization of packed-bed adsorbers is highlighted. It is shown that the participation of different sections of the bed during adsorption varies with the regeneration strategy, but is never as localized as predicted from a model for a fresh bed without cycling. Finally, the present results also show that the effluent purity attained during regeneration increases when high-temperature saturated steam is used, e.g. a 60-degree increase in steam temperature raises the purity by 11%

Finite-volume method for industrial-scale temperature-swing adsorption simulations

We formulate a mathematical model for temperature-swing adsorption systems. A finite-volume method is derived for the numerical solution of the model equations. We specifically investigate the influence of the choice of spatial discretization scheme for the convective terms on the accuracy, convergence rate and general computational performance of the proposed method. The analysis is performed with the nonlinear Dubinin-Radushkevich isotherm representing benzene adsorption onto activated carbon, relevant for gas cleaning in biomass gasification.The large differences in accuracy and convergence between lower- and higher-order schemes for pure scalar advection are significantly reduced when using a non-linear isotherm. However, some of these differences re-emerge when simulating adsorption/desorption cycling. We show that the proposed model can be applied to industrial-scale systems at moderate spatial resolution and at an acceptable computational cost, provided that higher-order discretization is employed for the convective terms

Effects of bed aging on temperature signals from fixed-bed adsorbers during industrial operation

The capacity of adsorber beds used in industrial-scale temperature-swing adsorption diminishes over time due to bed aging. Here, we present industrial data on the temperature signals from fixed-bed adsorbers using activated carbon designed to remove benzene and other impurities from the gas produced in biomass gasification. The aging of the adsorber beds proceeds due to irreversible adsorption of trace species and manifests itself via two simultaneous effects: a decrease in the availability of active adsorption sites over time and an increase in the overall thermal mass of the bed. Both effects tend to dampen the temperature response of the beds during operation, implying that they are easily confounded. Model descriptions of bed aging should account for both effects

Formulation of stresses in dry granular flows

We employ in this paper a Discrete Element Modelling (DEM) method to characterize rheology of dry, dense granular flows. We particularly look at the formulation of macroscopic system stresses based on the forces acting on individual particles. In addition, we study the possible coexistence in a domain of interest of different regimes of granular flow. The modelling framework is implemented in an open-source computational framework (OpenFOAM) in order to simulate dry granular flow in a Couette shear cell. The system is dense with particle volume fractions close to the maximum packing of particles. To accurately describe the contact forces on the particles, a soft-sphere model is used. Our simulations identify the following trends in the behaviour of granular material: increasing the values of the solid volume fraction, shear rate or friction, respectively, unambiguously leads to both higher stresses and their different distribution in the system. Finally, tendencies on the ratio between shear and normal stresses are investigated as a function of the volume fraction

Detailed simulations of heterogeneous reactions in porous media using the Lattice Boltzmann Method

Flows though porous media are commonly found in many systems, both naturaland manmade. A few examples from nature include petroleum reservoirs, soil andsolid biomass where industrial applications include fuel cells, foams and packed beds.Most of these areas are still subject to both scientific and engineering challengesranging from basic understanding to detailed optimization. A non-trivial part ofthe remaining challenges includes the interaction between macro-scale performanceand micro-scale characteristics. For some systems, it is possible to control and tunemicro-scale properties to optimize the overall performance of the application. Thisscenario typically manifests in the design of packed beds, especially when reactionsoccur within the bed. In such situations, particle shape and size distribution willaffect not only the pressure drop (and hence the preferential flow paths), but alsolocal reaction rates and thereby efficiency and selectivity.This work aims to understand and identify key design parameters that influencesreactions within a packed bed, and ultimately, the overall performance of the pack-ing. Representative microstructures of packed beds are generated with a DiscreteElement Method. Flow, temperature and concentration fields (cf. Figure 1) are thenfully resolved using the Lattice Boltzmann Method with a first order reaction schemeat the boundaries. Residence time, flow structures and permeability of the systemsare correlated to conversion and selectivity of the chemical reactions in the system.Comparisons between packings of different particle shapes and spacing serve to eluci-date phenomena involved in the process and implies design directions for macro-scaleoptimization

Finely resolved numerical simulations of reactive flow in porous media

A wide variety of scientific and engineering challenges involve flows through porous media. Applications range from flow through natural porous systems, such as petroleum reservoirs, soil and biomass char particles, to flows through artificially created porous systems such as packed beds, fuel cells, foams and membranes. In both natural and artificial systems, the microscale characteristics of the media can often, to different degrees, be controlled to optimize the macroscale performance of the application. The problem is then to find the optimal configuration of the porous system. This works aims to increase the understanding of which design parameters of a packed bed that influence the performance of homo-and heterogeneous reactions inside the bed.The flow, temperature and concentration fields in representative microstructures of various packed bed configurations are fully resolved in numerical simulations employing the Lattice Boltzmann Method (LBM), where homo-and heterogeneous chemistry is simultaneously accounted for. Detailed information about the flow structures, permeability and flow paths through the system is retrieved and correlated to the conversion and selectivity of the chemical reactions in the system. The dependence of a reactive porous system on different packing parameters, such as particle shape, spacing, and packing inhomogeneities is elucidated, and the implications for achieving optimal performance in a variety of different porous media are discussed

Packed-Bed Reactor Characterization of Steam-Regenerated Solvent Adsorbers for Raw-Gas Cleaning

Packed beds with activated carbon is a commonly used technology for removing unwantedsubstances from a process stream. To better understand how such beds operate and in orderto optimize their design and operation, one-dimensional models are typically employed.The multiphase aspects of these systems are typically neglected due to their complexity,even though regeneration with steam creates a liquid phase that may trickle through thebed, thereby effectively transporting heat and mass. This paper investigates andcharacterizes the differences in transport of gas and liquid in a representative packed bedthrough comprehensive three-dimensional numerical simulations. In addition, the effect ofheterogeneities in the packing of the bed on the transport of both phases is also investigated.It is confirmed that the dispersion of air may be well described by a conventional one-dimensional model, but that the dispersion of water requires an additional effort. It is alsofound that the system orientation significantly influences the water flow and that non-idealpacking has strong effects on the residence time distribution for both phases