A collection of Aspen Plus files for various cases used in the study (see attached report). Simulation cases include a base case, an optimized base case, and variants including cellulose incineration and no decolorization step versions.

Aspen Plus models of an acetic acid production process from CO2 via electrolysis. See linked report for full details.

Aspen Plus files that accompany the report Utilisation of Cement Flue Gas for Green Methanol Production: Process Design, Simulation, and Techno-Economic Assessment. See link.

This work valorises two industrial waste streams from Hope Cement Works—flue gas CO2 and low-grade waste heat—converting them into green methanol via catalytic hydrogenation with renewable hydrogen, while returning by-product O2 to the kiln for oxygen-enriched combustion. The plant captures 42.9 t/hr CO2 (88.7% efficiency) via monoethanolamine (MEA) absorption with rate-based RadFrac columns and produces 213 000 t/yr methanol over Cu/ZnO/Al2O3 at 230 ◦C/70 bar. Aspen Plus V14 simulation achieves 62.9% per-pass CO2 conversion and 99.7% overall via a 2.76:1 recycle loop. Six heat exchangers recover 66.5MW. Multi-objective ε-constraint optimisation reveals that the levelised cost of methanol (LCOM) and CO2 utilisation are positively correlated: the cost-optimal design achieves 99.5% utilisation because hydrogen (65–78% of operating expenditure, OPEX) is co-lost with CO2 in the purge. LCOM ranges from £779/t (£30/MWh) to £1303/t (UK grid); progressive integration of cement waste heat (£62/... [more]

This research presents a novel framework for the surrogate-based dynamic optimization of control schemes within chemical separation and purification processes such as the biorefinery downstream processing. The current study investigated the downstream of an enzymatic bioreactor responsible for the synthesis of 5-hydroxymethylfurfural value-added derivatives, focusing on the critical balance between operational costs and productivity. Two high-fidelity long short-term memory neural network-based surrogate models were developed to predict energy consumption and economic gain, both achieving a coefficient of determination (R2) exceeding 0.97. These models were subsequently integrated into a multi-objective optimization architecture to address an operating efficiency testing scenario characterized by stepwise inflow parameter changes. By exploring the resulting Pareto front, an optimal set of operational (control) settings was identified and validated. The results demonstrate that while en... [more]

Industrial decarbonization is crucial to reducing global emissions. Efficient processes lower energy use and reduce the environmental impacts, such as material use and waste, decreasing the overall industrial footprint. In this context, the present study explores the impact of reducing steam consumption (thermal energy) during the ammonia regeneration process in the production of sodium carbonate. A key feature of the Solvay process is ammonia recycling, which significantly reduces raw material consumption and ensures both economic and environmental sustainability. However, this stage is highly energy-intensive. To enhance energy efficiency in soda ash production, a study was conducted to analyze variation in temperature, pressure, and steam flow introduced into the ammonia regeneration system. The objective is to understand its impact on both ammonia recovery and the process's energy consumption. Variations in steam pressure do not impact on energy consumption of the process. By reduc... [more]

This work aims at verifying the CO2 absorption capture model using monoethanolamine (MEA) solvent developed by the U.S. DOE's Carbon Capture Simulation Initiative (CCSI) and performing uncertainty propagation of mass transfer, liquid hold-up and reaction kinetics properties in the complete model, which includes absorber and stripper columns. The verification of the Aspen Plus CCSI model, based on pilot plant data from the National Carbon Capture Center (NCCC) for a CO2 flue gas concentration between 7 and 11% (mol) allowed uncertainty quantification (UQ) analysis for four different selected operational points using Monte Carlo Simulation (MCS), where low liquid mass transfer parameters exhibited an impact on calculation convergence. Gaussian Processes (GP) surrogate model was implemented, followed by a sensitivity analysis in order to correlate the most sensitive parameters with studied outputs.

The growing global energy demand and the need to reduce dependence on fossil fuels have intensified efforts toward developing renewable alternatives. Among these, biodiesel and ethanol emerged as viable and sustainable fuel sources. In this context, the use of palm oil and ethanol as raw materials represents a promising production route, due to their availability, high productivity per unit of cultivated area, and renewable characteristics. However, ethanolic transesterification still faces challenges, such as lower productivity compared to methanolic processes and higher energy consumption due to reaction characteristics that impact the whole process. Bearing this in mind, this work aims to develop process simulations in Aspen Plus to optimize biodiesel production from palm oil and ethanol, coupled with an energy integration analysis. The process was divided into three main stages: (i) feed preparation, (ii) transesterification reaction, and (iii) separation and purification of biodie... [more]

Pyrolysis is an emerging green pathway to produce bulk chemicals and sustainable fuels. However, pyrolysis oil requires stabilisation via hydrotreatment, and this process generates an aqueous waste containing alcohols (mainly methanol and ethanol), carboxylic acids, and some ketones. To increase the economic sustainability of biofuels production, there is increasing interest in recovering these valuable chemicals from water. Reliable thermodynamics are necessary to address the separation and design of equipment to fractionate such complex mixtures, with multiple azeotropes and non-idealities. The Non-Random Two-Liquids (NRTL) models in both Aspen Plus V12.0 and COFE V3.7, a license-free software released by AmsterChem, do not accurately reproduce the equilibrium measurements of most of the binary and ternary mixtures involving water, a C1-C4 alcohol, and a light carboxylic acid. This work aims to retune the activity-based model to improve the NRTL model predictivity, using experimental... [more]

As economies advance towards decarbonization, industry follows suit. The ammonia (NH3) sector heavily relies on the energy- and carbon-intensive Haber-Bosch (HB) process, which accounts for nearly 2% of global CO2 emissions due to its reliance on fossil fuels. Emerging technologies are paving the way for fully renewable NH3 production, although the most mature green process still relies on the HB process, entirely replacing fossil fuels with electrolytic green hydrogen (H2). This work introduces the first developments towards the gradual incorporation of green H2 and air-separated nitrogen (N2) into a conventional NH3 production plant. Using Aspen Plus® V14 for modelling and simulation of Steam Methane Reforming (SMR), different scenarios incorporating 0 to 40 % of these alternative feedstocks were analyzed. An economic objective function is used in each scenario's optimization. To improve green H2 incorporation and ensure operational constraints were met, the simulations used an adapt... [more]

Direct air capture is gaining significant interest due to its potential to achieve carbon-negative emissions. With the aim to reduce the energy consumption and in line with the electrification of chemical processes, the absorption direct air capture system is integrated into a bipolar membrane electrodialysis cell stack for solvent regeneration and carbon dioxide release. The scheme solution is characterized by carbon dioxide bubbles inside the cell reducing efficiency so that other regeneration schemes have been proposed in the literature. A direct comparison of those is missing in the existing state of the art: the present work wants to fill this gap. In addition to the above process, the reaction of the rich solution with a weak organic acid and the use of both nanofiltration and reverse osmosis membranes are considered in other process schemes. The three case studies are modelled in Aspen Plus software with the aim to compare the energy consumption and total cost while the environm... [more]

The present work aims to demonstrate the synergy achieved through the integration of biomass gasification with a direct air capture (DAC) system to maximize overall CO2 removal capacity, while simultaneously converting waste into value-added products (hydrogen) and supplying the energy required for DAC operation (BG-H2P-DAC). The proposed configuration is modeled using Aspen Plus to investigate the synergistic interactions and key performance indicators of the BG-H2P-DAC system. Parametric analyses are conducted by varying gasification temperature, air inlet flow rate, and amine concentration and flow rate. The results indicate that increasing the monoethanolamine (MEA) concentration from 10% to 40% leads to a gradual decline in CO2 capture efficiency, accompanied by a reduction in CO2 slip. The system achieves a net specific electricity consumption of 0.0293 MWh/t CO2, confirming that the electricity generated from the integrated steam power cycle is sufficient to fully offset the ele... [more]

The manufacturing industry is the second largest emitter of CO2, with the cement industry being one of the main contributors (7-8 % of the global emissions). Carbon capture and utilization (CCU) technologies are promising decarbonization solutions for the cement industry, addressing both fossil fuel-related (40 %) and process-derived emissions (60 %). Within a cement plant, producing synthetic natural gas (SNG) from captured CO2 is particularly suitable, as it is sufficient to fully replace solid fuels in the rotary kiln. On the other hand, the use of zero-carbon fuels, such as green ammonia, is also recognized as a promising approach for decarbonization. In this work, a superstructure was developed to explore alternative routes for producing SNG and green ammonia from CO2 and N2 in cement plant flue gas, respectively. The routes were modelled in Aspen Plus® V14, and their economic viability was assessed. Currently, the most promising route, at a cost of 109 €/tonne of flue gas, involv... [more]

Heavy-duty road transport remains a challenging sector to decarbonize, as full electrification of long-distance trucking is currently constrained by limitations in energy density and charging infrastructure. Alternative fuels such as hydrogen, biodiesel, and e-fuels are thus gaining increasing attention. In parallel, the cement industry is a major source of unavoidable, process-related CO2 emissions, offering an opportunity to use captured industrial CO2 as a feedstock for e-fuel production. This study evaluates the production of e-methanol and Fischer-Tropsch (FT) diesel from captured CO2 at an Austrian cement plant as a base case. Several system configurations are analyzed, including different electricity supply options across Europe and the use of biogenic versus fossil CO2. An integrated framework combining process simulation, techno-economic analysis, and life-cycle assessment is applied to compare both fuel pathways. Results show that the climate impact of e-fuels is highly depen... [more]

The transition from a linear, fossil-based polymer economy to a circular bio-economy is critical for mitigating resource depletion and greenhouse gas emissions. This study provides a rigorous comparison of two biomass-to-plastic pathways: a biochemical route (PLA via enzymatic hydrolysis) and a thermochemical route (bio-PE via gasification and MTO). Based on Aspen Plus simulations and a "lifetime-adjusted" lifecycle assessment framework, we evaluate the environmental performance of these routes in the transition from linear to circular systems. Unlike standard "cut-off" methods, the lifetime-adjusted model accounts for virgin make-up and molecular retention across multiple recycling cycles. Results indicate that at current 15% recycling rates, PLA exhibits the lowest global warming potential due to significant biogenic carbon sequestration. However, as recycling rates reach 75%, process efficiency becomes the dominant factor; the precise biochemical recycling of PLA continues to outper... [more]

Model simulation flowsheet of biomass gasification combined cycle system for simultaneous power and hydrogen production coupled with direct air capture in Aspen Plus.

Aspen Plus is used to simulate the process and compute the mass and energy flows for the complete process of polystyrene waste conversion into value-added chemicals. This demonstrates a pathway for the recycling of PS waste, which could contribute to a more sustainable industry environment

We designed a novel methylcyclohexane–toluene–hydrogen (MTH) based chemical heat pump (CHP) and determined its key performance indicators using Aspen Plus process simulations.

This document compiles the digital supplementary material associated with the article entitled “Optimizing Steam Flux for Energy Efficiency in Ammonia Recovery during Sodium Carbonate Production”, published in the peer-reviewed proceedings of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). It presents the effects of variations in steam pressure and temperature on the system’s temperature and mass flow rate.

This supplementary material provides additional process descriptions, process flowsheets and life-cycle inventories in order to reproduce the work presented in the manuscript. Further, more detailed derivations of the impact calculation model are given.

CCS is a well investigated and fairly promising technology for reducing the emission of carbon dioxide (CO2) to the atmosphere. However, it is rarely implemented in the industry due to its high cost. Therefore, this work proposes a cost optimized CCS chain which can be operated flexibly and safely. For the capture process a post combustion chemical absorption technology is chosen due to its retrofitting possibility to already existing power plants and its low capture cost. In order to find a cost efficient absorption process for different scenarios, the five most promising process configurations from previous work are combined into a superstructure in a rigorous rate based reactive Aspen Plus model. This in turn is optimized by a two-stage stochastic programming approach in Matlab. The optimal supply chain network is identified by a tailor made transshipment model implemented in GAMS, which accounts for the most promising transportation units, storage sites as well as direct utilizatio... [more]

Contains the Aspen Plus flowsheet files and Python source code for the modelling, simulation, and optimization of a process which converts captured CO2 and electricity into ethylene, considering intermittent electricity.

Aspen Plus simulations for the conversion of CO2 into Formaldehyde and related processes.

While process simulations often are either very rigid and accurate or very flexible and unprecise, informed decision making can only be maintained by establishing a detailed process model as early as possible within the project lifecycle while keeping relevant aspects of the process flexible enough. In this work, we present the development of a framework based on a dynamic interface between AspenPlus® process simulations and Python, enabling enhanced flexibility and automation for process modeling and optimization. This integration leverages the powerful simulation capabilities of AspenPlus® with the versatility of Py-thon for data analysis and optimization, delivering significant improvements in workflow efficiency and process control. By utilizing the dynamic simulation data exchange with Python, extensive parameter studies can be conducted.
In this provided dataset, the necessary input data, as well as the output files for each parameter run are provided. Furthermore, a .runtime an... [more]

This study presents a simple tool to provide decision-makers data that will facilitate informed decisions in selecting utilization for small- to medium-scale utilization of stranded natural gas resources that would otherwise be flared set to be flared. The methodology involves the simulation of different natural gas utilization technologies on Aspen Plus simulation software and utilizing the results to develop a tool on Python that enables the user to assess recoverable valuable products from different natural gas profiles. Ten utilization technologies were implemented, and six different natural gas profile (rich and lean) were used as case studies to ascertain the capabilities of the tool. The supplimentary material provides the interface of the proposed tool.