Simulation based synthesis, design and optimization of pressure swing adsorption (PSA) processes

Rajasree, Radhika; Moharir, Arun S.

doi:10.1016/s0098-1354(00)00606-2

Cited by 30 publications

(21 citation statements)

References 9 publications

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“…In the black box optimisation approach (Kvamsdal andHertzberg 1997, Rajasree andMoharir 2000), the optimiser may only use directly the objective function value and possibly the constraints. If gradient information is required, this must be estimated numerically at potentially high computational cost.…”

Section: Optimisation Strategiesmentioning

confidence: 99%

A multi-objective genetic algorithm for the design of pressure swing adsorption

Fiandaca

Fraga

Brandani

2009

Engineering Optimization

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Pressure Swing Adsorption (PSA) is a cyclic separation process, more advantageous over other separation options for middle scale processes. Automated tools for the design of PSA processes would be beneficial for the development of the technology, but their development is a difficult task due to the complexity of the simulation of PSA cycles and the computational effort needed to detect the performance at cyclic steady state.We present a preliminary investigation of the performance of a custom multi-objective genetic algorithm (MOGA) for the optimisation of a fast cycle PSA operation, the separation of air for N 2 production. The simulation requires a detailed diffusion model, which involves coupled nonlinear partial differential and algebraic equations (PDAEs). The efficiency of MOGA to handle this complex problem has been assessed by comparison with direct search methods. An analysis of the effect of MOGA parameters on the performance is also presented.

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Section: Optimisation Strategiesmentioning

confidence: 99%

A multi-objective genetic algorithm for the design of pressure swing adsorption

Fiandaca

Fraga

Brandani

2009

Engineering Optimization

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“…Rajasree and Moharir [16] discussed simulation based synthesis, design and optimization of PSA processes. The system used was air separation using Zeolite 5A.…”

Section: Two Case Studiesmentioning

confidence: 99%

“…The data are given in Table A1 in the Appendix A with system 6. Table 4 compares the results in [16] with the results obtained using our heuristic rules. In [16] the pressure equalization step was used for some cases.…”

Section: Two Case Studiesmentioning

confidence: 99%

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Heuristic design of pressure swing adsorption: a preliminary study

Jain

Moharir

et al. 2003

Separation and Purification Technology

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Due to its complicated nature and multiple decision parameters including plant dimensionality and operation condition, the design of pressure swing adsorption (PSA) processes is not a trivial task. Most previous studies on PSA design have been made through rigorous modeling and experimental investigation for specific separation tasks. General heuristics for a preliminary design of PSA processes are necessary but not well investigated so far. In this paper, we attempt to develop easy-to-use rules for PSA process design, based on analysis of the inherent properties of adsorbate Á/ adsorbent systems (i.e. equilibrium isotherm, adsorption kinetics, shape of breakthrough curves, etc.) and simulation results. These rules include the selection of adsorbent, particle size, bed size, bed configuration, purge volume, pressure equalization and vacuum swing adsorption. Results of two case studies are presented to verify the rules proposed in this preliminary study.

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“…As a result, process simulators are now welcome participants in a variety of process engineering activities. Examples include the work of Pascal et al (1995), Devetta et al (1997) and Sotudeh-Gharebaagh et al (1998) in process simulation, Quitain et al (1999) in process design, Kurum et al (1997), Eldarsi and Douglas (1998), Rajasree and Moharir (2000) and Alexander et al (2000) in process optimization, and Amirthalingam and Lee (2000) in process control.…”

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confidence: 99%

Analysis of Steady‐State Temperature Profiles from a Laboratory Reactor by Means of a Process Simulator

2003

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A process simulator was used for the analysis of steady‐state results from a laboratory‐scale tubular reactor for the oxidation of carbon monoxide over a platinum catalyst. From a set of 14 steady‐state experiments, temperature profiles were simulated with two adjustable parameters recovered by optimizing the fit: k°, the pre‐exponential portion of the rate constant, and hout, the outer wall heat transfer coefficient for the reactor tube. Simulation showed that despite elaborate insulation the reactor did not behave adiabatically. Simulation also predicted fairly well the magnitude of phenomena such as ignition, extinction, and rate hysteresis (caused by changes in feed temperatures or concentrations) but at temperatures below the experimental values.

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Simulation based synthesis, design and optimization of pressure swing adsorption (PSA) processes

Cited by 30 publications

References 9 publications

A multi-objective genetic algorithm for the design of pressure swing adsorption

A multi-objective genetic algorithm for the design of pressure swing adsorption

Heuristic design of pressure swing adsorption: a preliminary study

Analysis of Steady‐State Temperature Profiles from a Laboratory Reactor by Means of a Process Simulator

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