Walter Wukovits

Modeling and simulation of high pressure water scrubbing technology applied for biogas upgrading

Depending on the end of use, the quality of biogas must be upgraded in order to utilize the maximum amount of energy necessary for proper applications. Upgrading biogas refers to the increase of methane concentration in product gas by removal of CO2, which increases its heating power. Several treatment technologies are available for biogas upgrading: high pressure water scrubbing (HPWS), pressure swing adsorption, membrane separation, chemical absorption, and gas permeation. Water absorption based on the physical effect of dissolving gases in liquids (HPWS) is a well-known technology and the most effective upgrading process, since provides a simultaneous removal of CO2 and H2S. This could ensure an increasing methane concentration and energy content per unit volume of biogas. In spite of this, few studies are published on biogas upgrading using pressurized water technology. In order to elucidate the performance of HPWS technology at industrial scale with the possibility of water regeneration and recirculation, effects of different operating parameters on the removal of undesired components from biogas were examined, based on modeling and simulation tools. For simulation, the commercial software tool Aspen Plus was applied. Equilibrium model was applied for simulating the absorption process. The simulation results were validated with experimental data from the literature. The results are summarized in terms of system efficiency, expressed as CH4 enrichment, methane loss, and CO2 removal. Finally, new data which can be further applied for scale-up calculations and techno-economic analysis of the HPWS process are provided.

Integration study on a two-stage fermentation process for the production of biohydrogen

In order to make the hydrogen economy fully sustainable, renewable resources have to be employed for its production. Simulation models, developed with Aspen Plus to calculate mass and energy balances, will be used to integrate the process steps necessary to produce pure hydrogen from biomass in a 2-stage fermentation process. The main challenge is the reduction of water and heat demand connected to the low substrate concentration in the fermentation steps; the easiest solution is to partly recirculate outgoing process streams. Electrolyte equilibrium was considered during simulation of different recirculation options to evaluate important effects on the pH and on the system osmolality. The results show that certain recirculation options can reduce the heat and water demand significantly. (Less)

Heat integration of a fermentation-based hydrogen plant connected with sugar factory

The paper is concerned with heat integration of a conceptual hydrogen plant connected with a sugar factory. The sugar factory serves as a source of sucrose-containing thick juice for the hydrogen plant, where this feedstock is processed to hydrogen. Moreover, this connection gives an opportunity to utilize waste heat from the sugar factory. Hydrogen is produced by two-stage fermentation, that is, thermophilic fermentation followed by photofermentation. The gas mixture obtained in the two process stages is supplied to the gas separation system, composed of absorbing and stripping columns for circulating amine solution, to separate hydrogen from carbon dioxide. Using Pinch Technology and considering sugar factory with its CHP plant as an energy source, the hydrogen plant is heat-integrated to minimise the energy consumption. (Less)

Exergy analysis of biological hydrogen production

Abstract Exergy is defined as the maximum work obtainable while the system contacts with environment reversibly. Exergy analysis is a powerful approach for analysing both the quantity and the quality of energy. This concept identifies the system components with the highest thermodynamic inefficiency and the processes that cause them. Exergy analysis was applied to a novel process for biological production of hydrogen from biomass in a combined bioprocess employing thermophilic and phototrophic bacteria. The exergy content of the process streams is calculated using MS-Excel program. Calculation of exergy incorporates chemical exergy, physical exergy and exergy of mixing. Special attention is given to the calculation of chemical exergy of biomass- and sugar components involved in the process.

A knowledge based system to support the process selection during waste water treatment

For the treatment of industrial wastewater a multitude of processes is available. It is the task of the chemical engineer to choose processes and to build up a treatment sequence suitable for the actual problem. Because of the large number of processes and process combinations, a knowledge-based system may be helpful during process selection and sequencing. The introduced knowledge based system delivers a treatment sequence based on heuristics and cost estimation. Depending on the supplied information a more or less detailed treatment sequence is suggested by the program. The article describes the aim and development of the knowledge based system, gives an overview on the program functions and presents the result of an example program consultation.

Assessment of biorefinery process intensification by ultrasound technology.

In the present work, on the basis of literature data, correlations for ultrasound-assisted dissolution of lignin and hemicelluloses from lignocellulosic raw material were defined in Aspen Plus® as function of applied power and duration of the ultrasound treatment. The dissolution yield of these biomass components was represented against the applied acoustic energy, taking into account the volume of solvent–solid treated in each case, making possible the calculation of ultrasonic power consumption in a simulated biorefinery pretreatment process. The proposed ultrasound-assisted process was techno-economically evaluated in terms of process yield and utility requirements. Furthermore, energy and exergy analyses were performed in order to assess the profitability of the simulated ultrasound-assisted biomass fractionation processes.

Modelling and Optimization of CO2 Absorption in Pneumatic Contactors Using Artificial Neural Networks Developed with Clonal Selection-Based Algorithm

Abstract Our research focuses on the application of airlift contactors (ALRs) for the decontamination of CO2-containing gas streams, such as biogas. To assess the performance of ALRs during CO2 absorption, a complex experimental programme was applied in a laboratory-scale rectangular pneumatic contactor, able to operate either as a bubble column or as an airlift reactor. Using the experimental data, a model based on artificial neural network (ANN) was developed. The algorithm for determining the optimal neural network model and for reactor optimization is clonal selection (CS), belonging to artificial immune system class, which is a new computational intelligence paradigm based on the principles of the vertebrate immune system. To improve its capabilities and the probability for highly suitable models and input combinations, addressing maximum efficiency, a Back-Propagation (BK) algorithm – a supervised learning method based on the delta rule – is used as a local search procedure. It is applied in a greedy manner for the best antibody found in each generation. Since the highest affinity antibodies are cloned in the next generation, the effect of BK on the suitability of the individuals propagates into a large proportion of the population. In parallel with the BK hybridization of the basic CS–ANN combination, a series of normalization procedures are included for improving the overall results provided by the new algorithm called nCS-MBK (normalized Clonal Selection-Multilayer Perceptron Neural Network and Back-Propagation algorithm). The optimization allowed for achieving the optimal reactor configuration, which leads to a maximum amount of CO2 dissolved in water.

Integration of the bio-ethanol process in a network of facilities for heat and power production from renewable sources using process simulation

Abstract The economic competitiveness of ethanol as a liquid fuel strongly depends on the amount of energy used during the production. To a sustainable production of fuel ethanol contributes also the use of energy from renewable sources. Process simulation is used to integrate a bio-ethanol plant in a network of facilities for heat and power production from residues of ethanol and feedstock production. Results show that depending on plant capacity and form of biogas utilization it is possible to cover heat demand using biogas produced from stillage of bioethanol fermentation. Partial combustion of straw from feedstock production even enables to cover the heat demand of small ethanol facilities.

Simulation and optimization of the reactive absorption of HF/HNO3 during pickling acid regeneration

The optimal operation of pickling acid regeneration is very important for its applicability and economical feasibility. This paper describes the simulation and optimization of the process conditions with the commercial process simulation programm ASPENplus 9.3. Beside the calculation and regression of physical properties, an important step was the implementation of reactions occuring during NO x -absorption in ASPENplus. The simulation model was improved by fitting with data from a pilot scale plant. Subsequently a sensitivity analysis was done to find process parameters to be optimized.