Membrane gas separation is used for natural-gas sweetening, hydrogen recovery, air separation, biogas upgrading and post-combustion carbon dioxide capture, yet general-purpose process simulators, both free and commercial, still lack a ready multicomponent membrane unit operation. The model is instead rebuilt for each study: as a custom block inside a licensed simulator that is not released, as a spreadsheet specific to one flowsheet, or as a rigorous code that runs outside the simulator and needs its own toolchain. We present an open, standards-based gas-permeation membrane unit operation that avoids this re-implementation. It complies with the CAPE-OPEN standard, registers and runs in the free COCO/COFE suite and in DWSIM, and delegates all thermodynamics to the host propertypackage through the Material Object, so the membrane is solved under the same equation of state as the rest of the flowsheet. A simulator-independent physics core implements the solution–diffusion cross-flow, co-current and counter-current models, with a choice of ideal partial-pressure or real-gas fugacity driving force and an optional adiabatic Joule–Thomson energy balance. The unit is validated against analytic, numerical and experimental references, reproducing the Weller–Steiner and Shindo benchmarks to order 10-4, tracking a twelve-point air-separation experiment to within 0.010 mole fraction, and recovering a spiral-wound flue-gas capture case. A two-stage carbon dioxide / methane sweetening flowsheet with interstage recompression and recycle, solved in-simulator, demonstrates membrane sizing and the feed-pressure, permeate-pressure and selectivity trade-offs alongside the surrounding compressors and coolers. The source is released under the MIT licence.

Recognizing methanol's versatile role as a chemical precursor and energy carrier, this study addresses its traditional production from fossil fuels and the associated challenges in pivoting to green alternatives due to the cost of green hydrogen. The research focuses on techno-economic analysis and optimization, employing a validated chemical process simulation tool integrated with economic analyses, reflecting CAPEX and OPEX models, and considering heat recovery to promote self-sufficiency. The study compares grey (traditional syngas) and green (biogenic CO2 and green hydrogen) methanol production pathways while also optimizing process factors, such as feed pressure, purge rate, temperature and catalyst volume, to achieve cost-effectiveness. In green methanol production specifically, the paper finds that optimal conditions are slightly milder than for grey methanol, highlighting the importance of process variables like purge rate given the high cost of green hydrogen. Still with current price level of hydrogen from electrolysis the levelised cost of methanol is several times more expensive via direct hydrogenation compared to production from fossil syngas. Results from the simulation-driven optimization underline the delicate balance between various objectives, such as minimizing costs or maximizing output, and demonstrate instances of pareto optimality. This study thus contributes with an integrated assessment of methanol production techniques, utilizing process simulation, economic evaluation, and heat integration for both grey and green methanol, aiming to pave the way for more sustainable chemical processes in the industry.

The rapid depressurization of pressure vessels containing hazardous substances in chemical plants, known as blowdown, is a critical process for ensuring plant safety. Blowdown significantly reduces the inventory as well as duration and rate of potential leaks, thereby mitigating the risks of escalation, fire, and explosion. In the present paper we propose a rigorous model for simulating the blowdown process, taking both real gas behavior, heat transport from the surroundings and the vessel wall as well as non‐equilibrium between vapor and liquid phase into account. The model is compared against well‐known experiments performed at Imperial College and Spadeadam test facility, which has been used extensively for the validation and benchmark of numerous academic and commercial codes with similar capabilities as the present model. The experimental validation of the developed model show good predictive capability and that the model captures both measured pressure, phase temperatures as well as predicted wall temperatures with adequate accuracy, both for single phase and condensing conditions.

This paper presents a framework for optimisation and techno-economic analysis of various pressurisation pathways for CO2 pipeline transportation. The pressurisation pathways include a conventional compression only case from initial to final pressure, a sub-critical compression part followed by cooling, liquefaction and pumping and also a super-critical compression part followed by cooling and dense phase pumping. The presented framework is developed based on open-source components and information available in the public domain. The framework includes a high level of flexibility to study variations in intial and final pressures, inclusion of inter-stage pressure drop, inter-stage cooling temperature, liquefaction/pumping pressure, among others. The implemented methods i.e. the thermodynamic and economic models applied, are rigorously validated and bench-marked against literature data. Contrary to former studies that focus mainly on reduction of the work required for pressurisation, the presented method includes additional capabilities to assess CAPEX, OPEX and the levelised cost of CO$_2$ compression. The analysis shows that in some cases the minimum levelised cost does not coincide with the minimum work. It is also demonstrated that for some cases the super-critical compression/cooling/pumping case and the sub-critical compression/cooling/liquefaction/pumping pathways provide optimal levelised cost compared to a multi-stage compression only case.

The rapid depressurisation of pressure vessels containing hazardous substances in chemical plants, known as blowdown, is a critical process for ensuring plant safety. Blowdown significantly reduces the inventory as well as duration and rate of potential leaks, thereby mitigating the risks of escalation, fire and explosion. In the present paper we propose a rigorous model for simulating the blowdown process, taking both real gas behaviour, heat transport from the surroundings and the vessel wall as well as non-equilibrium between vapour and liquid phase into account. The model is compared against well-known experiments performed at Imperial College and Spadeadam test facility, which has been used extensively for the validation and benchmark of numerous academic and commercial codes with similar capabilities as the present model. The experimental validation of the developed model show good predictive capability and that the model captures both measured pressure, phase temperatures as well as predicted wall temperatures with adequate accuracy, both for single phase and condensing conditions.

Simulation-based analysis estimating both the energy requirement of the entire carbon capture process and the purity of the recovered CO 2 is scarce. The purity of the captured CO 2 is crucial as it must meet a specification before transportation, preventing phase change and damage to the transportation system. This study conducted 31,104 simulations of a monoethanolamine carbon capture plant treating measured flue gas from an existing cement production plant. After capture, the CO 2 is treated through a deoxygenation unit followed by a compression train to fulfill specific quality specifications. Based on the sensitivity analysis, the energy consumption of the post-treatment process decreased with increased purity downstream. Despite this, the total energy consumption was not affected. Moreover, after the two-step purification the CO 2 stream was able to successfully fulfill the specification for NO x, O 2, NH 3, Ar, CO, SO 2. However, failing to meet the H 2O concentration requirements of both considered specifications and the N 2 concentration specified for ship transport. Thus, increasing the post-treatment energy cost or standard adjustments is required for future applications.

To achieve long-term greenhouse gas neutrality in aviation, replacing fossil aviation fuels with Sustainable Aviation Fuels (SAF) from renewable sources is essential. A SAF production process from renewable hydrogen and carbon dioxide, was designed using Aveva Process Simulation, followed by comprehensive economical assessments. The designed process leads to an annual production of 37kt of SAF, with 97% of the molecules featuring a carbon chain length between 8 and 16. This output indicates a robust and targeted production capability. With an in-depth optimization of the methanol reactor, it was found that the profitability of the plant aligns with other SAF studies, demonstrating a Minimum Selling Price of Product of $2.46/kg after Heat Integration. In terms of economic profitability, the production of SAF using the methanol pathway appears to be an alternative to other SAF production pathways such as Fischer-Tropsch process but resides dependent on the evolution of H2 production technologies, novel SAF production processes and environmental regulations. Despite this, the price remains higher than the current cost of fossil jet fuels, posing a competitive challenge.

Although Indonesia has set a target for increasing the use of renewable energy for electricity generation, the use of coal as a source of energy will still dominate at least until 2040. Sulfur dioxide (SO2) along with other gases and particulates released from the use of coal in coal-fired power plants (CFPPs) may cause air pollution. The use of seawater, an abundant source of absorbent in a maritime country such as Indonesia, in flue gas desulfurization (SWFGD) absorbers, is an economical option for treating SO2 in an absorption tower compared to other alkaline chemicals, e.g. limestone (CaCO3) or magnesium hydroxide (Mg(OH)2). A model, which correlates the equilibrium of the reaction with the salinity of the absorbent, was developed to predict the sulfur dioxide scrubbing process inside an SWFGD absorber. The simulation also took into account the mass and energy balance during the scrubbing process. The calibration using field SWFGD data showed a good correspondence between field data and modelling results.

The interactions between aqueous solutions, gases, and minerals dictate the extent of issues such as scaling, degassing, and corrosion, which have a major impact on the performance of a vast number of industrial applications (e.g., geothermal plants, oil and gas production facilities, natural gas storage in saline aquifers, flue gas scrubbing, carbon sequestration, etc.). Among the different software programs available for aqueous chemistry calculations, Phreeqc and Reaktoro were tested and validated against a wide dataset of gas solubility measurements. For the datasets considered, the two programs essentially led to the same outcome with only a few discrepancies observed. Yet, the agreement between the models and experimental data was greatly affected by the selected database. The models implemented in Phreeqc and Reaktoro were also compared with the experimental bubble point pressure of fluids sampled at several geothermal wells. The satisfactory performance of both Phreeqc and Reaktoro for describing different chemical systems at a wide range of pressures and temperatures showcases their versatility and practicality for assisting in the design and optimization of various processes relevant to the energy transition (e.g., geothermal exploitation, CO2 /H2 transport and storage).

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Capturing CO2 is necessary to abate the climate crisis. Amine CO2 capture is the most mature technology but suffers from high thermal energy consumption for solvent regeneration. Heat pumps are a proven technology with which to electrify industrial processes. This study investigates an integrated heat pump system used to electrify an amine CO2 capture unit for a biogas upgrading process using aqueous monoethanolamine. The study evaluates the potential of such integrated systems through the overall energy consumption at varied stripper pressures between 0.313 to 1.813 bara and includes a techno-economic analysis to determine the levelized cost. The most optimal heat pump scenario utilizes a vacuum operated stripper at 0.513 bara and reduces the overall energy consumption by 68 % compared to a classical amine scrubbing unit. The techno-economic analysis shows that the levelized costs for biogas upgrading per MWh of produced biomethane may be reduced by up to 33 % from 47 €/MWh to 31 €/MWh by implementing heat pump electrification systems and a vacuum operated stripper compared to a scenario using natural gas.

A novel kinetic model for the aqueousphase hydrogensulfide scavengingreactions using MEA-triazine (HET) is proposed. The assumptions ofthe model are based on experimental observations obtained by NMR spectroscopy,supporting the existence of 3,5-bis-(2-hydroxyethyl)-hexahydro-1,3,5-thiadiazine(TDZ) as a quantitative reaction intermediate and showing the protonationbehavior of HET and the lack of protonation of 5-(2-hydroxyethyl)-hexahydro-1,3,5-dithiazine(DTZ). Experimental kinetic data were obtained with a new in situRaman spectroscopy setup, which enabled monitoring the time-variationof bisulfide concentrations in a batch stirred reacting system attemperatures of up to 75 degrees C for HET/HS- initialconcentration ratios from 0.5 to 5. The optimal model parameters wereregressed from the experimental data using a brute force optimizationmethod. The rate constants of the first and second scavenging reactionswere estimated to be 0.435 and 0.004 L mol(-1) s(-1) at 25 degrees C, and the activation energies were 68and 57 kJ mol(-1), respectively.

The interactions between aqueous solutions, gases, and minerals dictate the extent of issues such as scaling, degassing, and corrosion, which have a major impact on the performance of a vast number of industrial applications (e.g., geothermal plants, oil and gas production facilities, natural gas storage in saline aquifers, flue gas scrubbing, carbon sequestration, etc.). Among the different software programs available for aqueous chemistry calculations, PHREEQC and Reaktoro were tested and validated against a wide dataset of gas solubility measurements. For the datasets considered, the two programs essentially led to the same outcome with only a few discrepancies observed. Yet, the agreement between the models and experimental data was greatly affected by the selected database. The models implemented in PHREEQC and Reaktoro were also compared with the experimental bubble point pressure of fluids sampled at several geothermal wells. The satisfactory performance of both PHREEQC and Reaktoro for describing different chemical systems at a wide range of pressures and temperatures showcases their versatility and practicality for assisting in the design and optimization of various processes relevant to the energy transition (e.g., geothermal exploitation, CO2 /H2 transport and storage).

Performance curves of turbomachinery are the essential materials required for getting a deep insight into the operation of these facilities under different operating conditions. For driving these performance curves, a sort of expensive and rigorous experiments are required on the turbomachinery. This study investigates the possibility of predicting the performance curves of multi-stage centrifugal natural gas compressors with offshore applications using data mining techniques (e.g., Linear Regression), thereby eliminating the need for the required experiments for this objective. The main focus of this article has been specifically on predicting the polytropic efficiency and polytropic head performance curves of such compressors. The database of the project includes an extensive information bank related to different centrifugal compressors in various operating conditions. A large portion of the database is used for training the predictive models, and the remaining is used for tests and validations. Besides, cross-validation has also been done to ensure the reliability of the results. The study results prove that it is possible to predict the performance curve of centrifugal compressors with limited samples, although marginal errors are inevitable. The results showed that the trained model has a better performance in high flow rates. Accordingly, the maximum RMSE of the head in high flow rates was 3 kJ/kg and in low flow rates 11 kJ/kg. In addition, the maximum RMSE of efficiency in high flow rate was 0.02 and in low flow rate was 0.24.

This paper describes a simplified calculation method for pipeline decompression wave speed based on a rigorous equation of state for pure CO 2 as well as mixtures with significant impurities.Calculations are performed assuming homogeneous equilibrium for the estimation of the speed of sound in the two-phase region and calculations are performed along an isentropic decompression path.These calculations are important for the design of pipelines and can be used to estimate the required wall thickness and/or material toughness when combined with e.g. the Battelle two curve method, thereby ensuring that a potential running ductile fracture is arrested.The calculations are validated against available literature data and is offered as an open source tool.For pure CO 2 at supercritical conditions the model results match experimental results very well, whereas for the dense liquid phase the pressure plateau in the decompression wave speed curve is over-predicted.For CO 2 with impurities the model calculations generally match experimental data, except for the experiment with a significant fraction of hydrogen and for the experiment with the highest amount of impurities of approx.6%.In these two cases the pressure plateau is under-predicted.

In this paper, a detailed evaluation of the open source process simulator DWSIM is presented. Using a previously published simulation model of an oil and gas separation plant, the results obtained with DWSIM are compared to a commercial process simulator widely used in the industry. The modelled flow scheme comprises a vast number of unit operations including separators (flash vessels), valves, splitters, mixers, compressors, heat exchangers, pumps and recycles (tear streams). The results obtained with DWSIM both for characterization of the inlet fluid as well as for a single operating state for the entire process, compare very well with the data obtained using a commercial tool. A rigorous comparison is made and generally, compared results are within 1% in deviation with a few exceptions. Further, an elaborate comparison is made for over 90 simulations with different settings where 10 independent variables are randomly varied over a wide range. Again, good agreement is found between the two tools. The results are very encouraging and provide fidelity in the use of the investigated open source process simulation tools in a professional environment.

The optimization of an oil and gas separation plant operating revenue has been performed for different characteristic reservoir fluid types (gas condensate, volatile oil, and black oil) using an evolutionary algorithm. A process simulation model mimicking a typical plant has been used as a black-box model and optimized with respect to nine design variables using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The plant studied has three separation stages, including gas recompression for each stage as well as a final gas boosting step before export. Each compression stage includes gas cooling and partial condensation upstream compressors. All condensate streams from the recompression system are recycled back into the separation system for increased liquid recovery. The results indicate the following common optimal settings among others: the first-stage temperature is optimal at the high bound, the third-stage temperature is optimal at the low bound, the temperature of the gas from the scrubber receiving gas from the middle stage separator is optimal at the lower bound. Some of the settings are different between the three fluids investigated, but with a clear trend among the fluids. One example is the optimal middle-stage separator pressure, which increases with decreasing gas-oil ratio of the fluid. Benchmarking the optimization potential indicates that an increased operating revenue of close to 1% may be realized for the gas condensate and the volatile oil, whereas the optimization potential is less for a black oil fluid type. It is also noted that this optimization may come at a significant penalty in terms of the energy required, especially for the volatile oil case.

HydDown (Andreasen, 2021) is a Python package for calculation of pressure vessel behaviour during filling (pressurisation) or discharge (depressurisation/blow-down). More specifically, the software allows calculation of vessel pressure, fluid inventory temperature as well as vessel wall temperature as a function of time during either filling or discharge operations. The applications are manifold and some examples are:

The optimisation of Post Carbon Capture (PCC) from a Waste-to-Energy plant has been studied using Kriging surrogate models trained from a set of rigorous process simulations. The surrogate models allow fast and efficient calculation of model responses required for the optimisation of operating parameters. Optimisation is performed using Differential Evolution (DE) requiring a vast amount of function calculations (>1000) which would be extremely time consuming if done with a rigorous process simulation model. It is found that for meeting a CO 2 removal efficiency of 85% for a flue gas containing 12.6 mole % CO 2 and a reboiler temperature limited to max. 120 °C, a L/G ratio of approx. 2.2 (kg/kg) is optimal. This is accompanied by a stripper/regenerator pressure of 1.85 bara, a temperature of the flue gas at the lower bound, a temperature approach of the lean amine entering the absorber of 6.5 °C (to the flue gas temperature), and a temperature approach in the L/R heat exchanger of 5 °C. The optimal lean and rich amine loading is approx. 0.21 and 0.52 (mole CO 2 /mole MEA).