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Effective modelling of the Rotating Packed Bed (RPB) process is crucial for accurately simulating CO2 absorption in aqueous amine solutions. Existing models often incorporate simplifying assumptions and rarely capture the simultaneous variations of critical phenomena inside the RPB apparatus, such as gas phase CO2 mass flow rate, liquid and gas temperatures, and pressure drop. This work addresses these challenges by developing a rate-based, steady-state model designed for CO2 capture, using monoethanolamine (MEA) as the solvent. Unlike previous works, this model effectively captures all these critical phenomena simultaneously. The model employs a first principles approach and solves material and energy balance equations using the shooting method. Two-film theory is used to represent mass transfer in conjunction with up-to-date correlations. The predicted results exhibit excellent agreement with the experimental data for a 30 wt. % MEA solution when comparing rich loading, with a maximum deviation of 1.1 %. The analysis of previously overlooked phenomena in RPB-based CO2 absorption provides valuable insights regarding the variations of key parameters along the radius, such as the influence of pressure drop and temperature. The observed decrease in gas pressure and sharp drop near the inner radius demonstrate the significant impact of frictional losses. In contrast, the temperature profiles of the gas and liquid phase reveal the interplay between exothermic reactions and counter-current flow.

The corrosion behavior of two stainless steels (316L and 304L) was evaluated using a CO2-loaded aqueous solution of 30 wt.% monoethanolamine (MEA) with a view to simulating corrosion related mechanisms in amine treatment procedures. Corrosion behavior was experimentally evaluated as a function of CO2 loading and solution temperature, using electrochemical techniques (polarization curves, cyclic polarization, and EIS measurement). The results reveal that the aqueous MEA solution containing CO2 creates a favorable environment for the corrosion of both stainless steels. The rate of corrosion is accelerated when the temperature of the loaded MEA solution rises, which was attributed to the thermal degradation of the loaded MEA, thus causing higher kinetics of the cathodic reactions at higher temperatures. More specifically, for the SS 304L the corrosion rate is almost doubled when the solution temperature is increased from 25 °C to 40 °C and is quadrupled when the solution temperature rises to 80 °C. For the SS 316L, the corrosion rate becomes almost threefold and sixfold upon increasing temperature of the load amine solution to 40 °C and 80 °C, respectively. The overall corrosion rate of SS 316L is lower with respect to the SS 304L for the same temperature and loading conditions. The essential dependency of corrosion rate on solution type (unloaded and loaded MEA solution) demonstrates that the corrosion process and reactions are controlled by a diffusion mechanism.

Intensified agricultural activities with an excessive fertiliser utilisation result in high penetration rates for several chemical compounds through soil to the ground water reservoirs. One of the main components in fertilisers are nitrate ions, which at high concentrations have harmful effects on human health. There is a number of available technologies for nitrate removal, but the majority of them use chemical additives and generate waste that has to be treated before their release to the environment. One promising alternative is the electrodialysis (ED) process. To make the process more sustainable and allow the deployment of such systems to remote areas where limits on electric power consumption may be present, the ED system can be powered by photovoltaic (PV) solar panels. The challenge is to operate the system efficiently under the intermittence of the solar radiation and the variations in the water concentration of nitrates. In this work, a mathematical model describing the removal of nitrate ions, under a variety of meteorological conditions, and for a variable daily demand of drinking water has been developed. Solar radiation and nitrate feed are real data from an area with drinking water contamination problem. This simulation model predicts the removal rate of nitrate ions, the sizing of the solar panels and the capacity of the battery with respect to the battery’s state of charge. Efficient energy management strategies are developed to ensure that the targeted pure water demand in terms of volume and concentration of nitrates is met and the use of non-renewable, externally provided electricity is minimised.

In this work a pilot plant with a rotating packed bed (RPB) reactor for nanoparticle production is demonstrated. The overall process is explained and the preliminary experimental outcomes are interpreted. The experiments are performed with slacked lime suspensions and CO2 gas. Three crucial process parameters, namely rotating speed, slurry flow and gas flow rate, were studied for their impact on the process key performance indicators (KPIs) of reaction time (trxn), particle size ( ?? ) and capture efficiency (?CO2). A factorial design with three factors and two levels was employed in order to attain a generalized view of the process behavioral trends. The reaction time was derived from pH measurements. Products were characterized by X-ray diffraction, scanning electron microscopy and particle size distribution measurement methods. Capture efficiency was estimated through gas flow rate measurements. The results indicated the successful production of nano-sized calcite particles with diameters down to 34 nm.

Electrodialysis is an efficient process for the cleaning of industrial water effluent streams from toxic ionic substances with the simultaneous recovery of valuable ions for reuse. Energy consumption and waste recovery are the two key goals of the process. A dynamic optimisation program aims to determine the optimal operating conditions in terms of applied voltage and effluent flow rate in a batch operating scheme. A model is developed that accounts for the ion transfer through the ion selective membranes and the dynamics of the system. A combination of three objective functions targeting the minimisation of the overall batch process time, the minimisation of the electrical energy consumption required for the ion transfer, and the maximisation of the overall degree of separation is investigated. The manipulated variables applied voltage and feed stream flow rate are considered as piecewise constant during each time interval, spanning the duration of the entire batch. The dynamic optimisation problem is solved through standard non-linear programming techniques which calculate the optimal batch duration and condition profiles for the system. A multi-objective analysis is presented for various combinations of weight values for the joint objective function through the development of the Pareto optimal front. The current approach has been implemented in the removal and recovery of sulfuric anions from an aqueous solution and resulted in the achievement of a high degree of separation in a shorter period at a much lower energy consumption.

It is a well-established fact that activated sludge Wastewater Treatment Plants (WWTP) are placed among the most significant contributors of Greenhouse Gas (GHG) emissions. The task of intelligent emission control of such plants is a great challenge, mainly due to the highly nonlinear dynamics and associated uncertainty of its constituent bioprocesses. The need for more efficient and environmentally conscious control is ever increasing, due to the upsurge of industrial and urban water usage. In the current work, a nonlinear Model Predictive Control (MPC) scheme that considers an activated sludge model is developed for pulp and paper industry. The nonlinear MPC employs a flexible controller input structure through a process superstructure formulation that enables the adaptive utilisation of the most suitable set of manipulated variables based on the prevailing operating conditions. A generalised framework of this flexible controller type along with a nonlinear dynamic model for the plant accounting for the simultaneous satisfaction of stringent control objectives on the effluent quality and the GHG minimisation is developed. The proposed controller incorporates manipulated variables for all admissible aeration intensities, internal flow recirculation streams, external carbon sources, influent flow distribution in each bioprocessing unit, unit volume variations and recirculation flow percentage. Accurate simulations indicate the achievement of a superior emission reduction performance compared to state-of-the-art MPC implementations in WWTP. Every consideration of a manipulated variable set is associated with respect to its contribution to the total GHG reduction for each mode of operation.

District cooling (DC) systems are able to exploit locally available energy in order to supply cooling to local end-users through an integrated DC network. The present work aims at obtaining the critical decisions in the performance of a DC network at the operating level. End-users can be of different type (e.g., residential or commercial) with different demand profiles and an optimal strategy needs to be employed in order to satisfy the demand and minimise energy usage. In published literature the vast majority of the studies employ simplified mathematical models in order to describe the thermodynamic cycle used and only a handful of studies take into account the actual dynamics of the system transition from one state to the other as well as the time delay attributed to the cooling medium transfer through the network. The critical decisions involve the operating conditions and optimal allocation for the cooing of existing units in a suitable time interval, which form the basis for the satisfaction of requirements in cooling under demand variability. Although reduced order models of the process of ABR cycle are used, the time delay of the cooling medium transfer through the pipes is considered through the employment of validated first order plus time delay models. The proposed optimisation framework enables the identification of demand driven, highly performing solutions through the direct consideration of all interacting factors over a pre-defined time horizon. Optimal results include the definition of the optimal allocation of produced cooling effect in such way that cooling demand is always satisfied.

A district cooling system (DCS) is superior to conventional air conditioning as it helps to reduce energy consumption and protect the environment by reducing carbon dioxide emissions. The investigation of the actual/existing vapour compression refrigeration (VCR) system used in the DCS has not been well documented. In this context, energy, exergy, environmental and economic (4E) analysis of the VCR chiller, operated with R134a, used in heavy duty existing DC plant has been systematically performed and compared with the ecofreindly refrigerant R717. The impact of the evaporation temperature on the total equivalent warming impact (TEWI), coefficient of performance, exergy efficiency and cost rate is assessed. It is observed that the COP and exergy efficiency of the VCR with R717 is around 3 % higher compared to a VCR with R134a. This is attributed to the significantly higher latent heat of evaporation, which ultimately requires a lower mass flow rate of R717. It is observed that the total global warming impact and Combined cost of R717 are lower by 1.6 % compared to the R134a. Lower TEWI is attributed to the zero global warming potential, lower compressor power and higher COP of the VCR system with R717 in comparison to R134a. However, further detailed parametric analysis considering the capital cost is required to claim the superiority of R717.

Rotating Packed Beds (RPB) are receiving increased attention in CO2 capture, due to their considerably lower volume compared to conventional packed-beds and their beneficial effects on process capital costs. As a result of these advantages, RPB have also been considered as a CO2 mineralisation option for the production of precipitated calcium carbonate (PCC). In the area of CO2 capture, the few model-based investigations employ either the two-film or Higbie’s penetration theory to model the gas-liquid mass transfer as the main driving force of the systems’ operation. In the area of PCC production, there is only one model type available that is based on the two-film theory. While the latter includes the limiting assumption of linear and steady-state mass transfer within the liquid film, Higbie’s theory is considerably closer to realistic operation due to the assumption of time-dependent and non-linear, gas-to-liquid mass transfer. Considering this significant advantage, this work proposes for the first time a model for RPB-based, PCC production using Higbie’s penetration theory. The model is first developed and validated considering solvent-based CO2 capture with monoethanolamine (MEA) solvent, taking advantage of the available experimental data in published literature. The model is then adapted to PCC production to perform a parametric investigation based on various performance indicators. Results indicate that the proposed model enables improved accuracy compared to the two film theory. Higher rotation speeds and liquid flowrates enable improved mass transfer, whereas PCC production can be achieved at lower energy consumption simultaneously with high CO2 capture efficiency.

CO2 capture is of profound significance to mitigate emissions from fossil fuel combustion. Absorption technologies represent a mature approach for post-combustion CO2 capture, and, in this direction, the development of new solvent systems, alternative to aqueous ethanolamine (MEA) solutions that are currently used, has attracted significant research interest. Among the solvents that have been suggested, polyamines, such as diethylenetriamine (DETA) and triethylenetetramine (TETA), represent interesting candidates for use in amine mixture solvents. This work presents new high pressure experimental data for the solubility of CO2 in aqueous DETA and TETA solutions. The former system is investigated using two experimental techniques in order to expand the investigated pressure range. In addition, the obtained new experimental data are used to parameterize the Cubic-Plus-Association Equation of State (CPA EoS), which, in turn, coupled with the pseudo-chemical reaction approach, is used to satisfactorily describe the VLE behavior of the studied systems.

This work presents a CAMD (computer-aided molecular design) approach for the design of working fluid mixtures used in ABR (absorption refrigeration) cycles. Compared to previous works, the proposed approach introduces two major improvements. It employs for the first time an ABR process model in the course of CAMD, hence enabling the evaluation of the generated mixtures considering process performance indicators. It enables for the first time the simultaneous generation and evaluation of molecular structures for both refrigerants and absorbents. The employed model and CAMD optimization problem formulation incorporates major ABR operational driving forces pertaining to efficient refrigeration, sufficient solubility of mixture components and ease of separation in the generator. The approach employs a multicriteria assessment methodology both during CAMD and for the evaluation of selected mixtures using a more rigorous ABR model at a second stage. The work identifies novel mixtures, with Acetaldehyde/2-Methoxyethyl acetate and Acetaldehyde/Methanediol exhibiting the highest performance. The latter exhibits 3% higher COP (coefficient of performance) and cooling output than the reference mixture NH3/H2O, whereas it operates at 87 and 89% lower high and low cycle pressures. The novel mixtures are also compared with novel mixtures previously identified through a heuristic approach by the authors. The latter mixtures indicate overall higher ABR performance but similar or worse performance in safety, health and environmental impact indices. Further performance improvements may be achieved by including into CAMD additional chemical groups to be able to simulate the complex absorbent structures available in published works.

In the present work numerical investigations of the two-phase flow field inside a Rotating Packed Bed (RPB) are performed with the use of Computational Fluid Dynamics (CFD). The RPB geometry will eventually be used for the production of nanoparticles of CaCO3 and 4MgCO3Mg(OH)24H2O. In the respect, the development of appropriate numerical models for the optimization of the overall process is significant and the use of CFD methods and the development of representative CFD models can be of prime interest. For this reason, a computational grid modelling of the rotating packed bed geometry was created in which two fluids, one in gas phase and one in liquid phase, are flowing in co-flow alignment. For the gas phase fluid, properties of air were applied, while for the liquid phase properties of water were used. The Realizable k-e turbulence model was used for the computations together with the volume of fluid (VOF) methodology in order to model the two-phase flow development and the gas-liquid interactions. The numerical analysis was performed using a steady flow assumption by applying a rotating frame of motion for the RPB geometry. The RPB geometry was modelled as an isotropic porous medium of predefined pressure loss formula taking into consideration the RPB core geometrical characteristics. The results from the computations provided a detailed view inside the RPB core revealing the various interactions between the gas and liquid phases in relation to the RPB operational conditions. The results of the computational study will provide appropriate information that will help in the development of simpler but accurate RPB computational models which will be able to provide rapid and reliable results regarding the two-phase flow field development and interaction inside the RPB core.

Electrodialysis is a promising electrochemical process for separation and recovery of useful ions from waste waters. The large number of parameters involved in electrodialysis models makes their estimation challenging. This work proposes a systematic sensitivity analysis approach to identify the impact model parameter variations exert on multiple electrodialysis performance indicators, within a wide operating range. This enables the robust mapping of electrodialysis performance toward the direction of maximum variability in the multi-dimensional parametric space and the identification of operating regimes, where the input parameters exhibit the highest sensitivity. Such regimes are used to determine upper and lower limits in the parameter estimation problem. Parameters and ranges exerting insignificant changes on the output electrodialysis indicators are omitted from evaluation, which reduces the associated complexity. The approach is validated against published experimental results obtained for a lead ions removal electrodialysis recirculation batch process. Only four out of nine parameters need to be estimated, while excellent match is observed between experimental and predicted data.

Phase-change solvents is a solution to the energy penalty problem of post-combustion CO2 capture. While the improved thermodynamic performance of processes using phase-change solvents is previously demonstrated, there is no research done on the environmental and health aspects of such processes. The purpose of this study is to bridge this gap with the help of combined life cycle and safety, health and environment hazard assessment. In terms of life cycle analysis, steam for the reboiler, CO2 compression for transport and electricity consumption by the flue gas blower are the main contributors to the impact, however, in comparison with the conventional solvents, phase-change solvents will require additional electricity and reclaimer steam input due to phase-separation and potential increase of degradation compounds, the overall energy requirement is, however, smaller. The assessment indicated that phase-change solvent systems may experience additional problems of accumulation of harmful solvent degradation products due to the design of the process. The study highlights that in comparison with the conventional systems, phase-change solvent process might require additional safety equipment, but the overall environmental and health impact of the system is expected to be lower.

A systematic sensitivity analysis approach is proposed to assess the robustness of thermodynamic model predictions employed in ABR processes. A sensitivity matrix is developed which incorporates the derivatives of multiple ABR performance indicators (e.g. coefficient of performance, generated cooling, mass flowrate of working fluid etc.) with respect to multiple thermodynamic property parameters propagated through different thermodynamic prediction models. The dominant eigenvector direction of the sensitivity matrix is identified and used to explore the ABR process behaviour as indicated by the change of ABR performance indicators under simultaneous, multiple and finite thermodynamic parameter variations. This enables the robust mapping of ABR performance toward the direction of maximum variability in the multiparametric space and hence the identification of a thermodynamic model which supports robust predictions regardless of variability. The approach is illustrated in a single effect ABR process system using the NH3/H2O mixture. Among various thermodynamic models we find that the Schwartzentruber-Renon with eNRTL are the most robust combination to parameter variability.

This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS) for energy management of hybrid energy systems uncertainty. The systems power grand composite curve is formulated with the chance constraint method to consider load stochasticity. In a predictive control horizon, the power grand composite curve is shaped based on the pinch analysis approach. The robust energy management strategy effected in a control horizon is inferred from the likelihood of a bounded predicted power grand composite curve, violating the pinch. Furthermore, the response of the system using the energy management strategies (EMS) of the proposed method is evaluated against the day-ahead (DA) and adaptive power pinch strategy.

Solvent-based CO2 capture technologies hold promise for future implementation but conventional solvents incur significant energy penalties and capture costs. Phase-change solvents enable a significant reduction in the regeneration energy but their performance has only been investigated under steady-state operation. In the current work, we employed a systematic approach for the evaluation of conventional solvents and mixtures, as well as phase-change solvents under the influence of disturbances. Sensitivity analysis was used to identify the impact that operating parameter variations and different solvents exert on multiple CO2 capture performance indicators within a wide operating range. The resulting capture process performance was then assessed for each solvent within a multi-criteria approach, which simultaneously accounted for off-design conditions and nominal operation. The considered performance criteria included the regeneration energy, solvent mass flow rate, cost and cyclic capacity, net energy penalty from integration with an upstream power plant, and lost revenue from parasitic losses. The 10 investigated solvents included the phase-change solvents methyl-cyclohexylamine (MCA) and 2-(diethylamino)ethanol/3-(methylamino)propylamine (DEEA/MAPA). We found that the conventional mixture diethanolamine/methyldiethanolamine (DEA/MDEA) and the phase-change solvent DEEA/MAPA exhibited both resilience to disturbances and desirable nominal operation for multiple performance indicators simultaneously.

In fossil-based refinery and biorefinery applications hydrogen is recovered by pressure swing adsorption and subsequently re-pressurized using mechanical compressors. Electrochemical hydrogen compression is an efficient way of separating and compressing H2 from a gaseous mixture within a compact device. In this work, a preliminary investigation of the integration of a bio-oil hydroprocessing unit with a complete novel gas polishing and separation unit was conducted. Apart from the electrochemical compressor, this includes a CO methanation reactor and a ZnO bed to remove the contained CO and H2S impurities of the hydroprocessing reactor outlet and safeguard the trouble-free operation of the electrochemical device. This first assessment revealed that several operating parameters such as the hydrotreating pressure, the gas polishing and separation temperature and the hydrogen recycling ratio limit the possible operating modes of the subsequent units.

The electrochemical hydrogen compressor (EHC) is a new system that can produce compressed purified H2 out of a complex mixture of gases, which includes no moving parts and mechanical losses, and operates isothermally. The simulation of this system is the focus of this work in order to produce a zero-dimensional, steady-state EHC model for process design in commercial tools such as AspenPlus™. The model calculates the overall voltage by considering the Nernst voltage, the Ohmic losses, and the activation overpotentials. The required power and cooling load are thereafter evaluated, while taking into account the water management. The inclusion of the aforementioned phenomena results in an EHC system that considers several operating parameters and could be readily used for process integration.

This work is focused on the optimization of the geometrical characteristics of a recuperator developed for aero engine applications, taking into consideration the aero engine geometrical constraints and limitations, in order to achieve feasible and implementable recuperator designs. For this reason, dedicated numerical surrogate tools were developed through which the effect of major geometrical features such as recuperator diameter, length, tubes arrangement and alignment could be directly included in order to assess their effect to recuperator operational performance characteristics such as recuperator effectiveness and inner/outer pressure losses. A large part of these activities was focused on the development of a nonlinear surrogate model incorporating the major geometrical features of the recuperator. In this tool, high-fidelity correlations regarding pressure losses and heat transfer, derived through experimental measurements and detailed CFD computations, were incorporated. Based on this model the recuperator performance was optimized using the simulated annealing algorithm resulting in the identification of recuperator design which can combine operational superiority with feasibility and implementation potential.

Efficient power generation from low to medium grade heat is an important challenge to be addressed to ensure a sustainable energy future. Organic Rankine Cycles (ORCs) constitute an important enabling technology and their research and development has emerged as a very active research field over the past decade. Particular focus areas include working fluid selection and cycle design to achieve efficient heat to power conversions for diverse hot fluid streams associated with geothermal, solar or waste heat sources. Recently, a number of approaches have been developed that address the systematic selection of efficient working fluids as well as the design, integration and control of ORCs. This paper presents a review of emerging approaches with a particular emphasis on computer-aided design methods.