The Dividing Wall Column (DWC) offers significant potential in saving both energy- and capital cost compared to conventional distillation sequences. However, there are some issues regarding flexibility and control that require attention in reducing the risks or uncertainties in achieving the potential benefits in practical operation. This calls for control and optimization methods that rely on the available measurement data and less on simulation models. The "Perturb and Observe" method is a simple algorithm that seems suitable for this on-line optimisation task. A series of experiments have been carried out at the Kaibel-column pilot at NTNU and some key results are presented. The method is combined with a conventional control structure at the regulatory layer.

This study investigates control strategies for the flexible operation of heat pump-assisted distillation processes, focusing on the heat integrated distillation column configuration. The methanol/water separation system was selected as a case study and modelled to achieve 99.9 wt% AA-grade methanol purity. A limiting piece of equipment for flexible operation of heat pump assisted distillation is the compressor. To assess its impact on flexible operation, dynamic simulations in Aspen Dynamics were conducted for two heat integrated distillation column control strategies: one using fixed compressor duty and one using variable compressor duty. The control performance for a 20% throughput disturbance, as well as for a 50% turndown ratio scenario was investigated. Results show that fixed-duty operation maintains robust stability and rapid disturbance recovery even at 50% turndown, while variable-duty operation delivers higher efficiency for moderate load changes but cannot sustain low-load s... [more]

To improve the energy efficiency of distillation processes, various process intensification concepts have been proposed, including direct heat integration and thermal coupling. Identifying the most suitable alternative for a given separation task requires a rigorous and consistent techno-economic optimization. Superstructure models typically rely on isobaric operation and fixed HETP values, in order to avoid treating column hydraulics when solving the already challenging mixed-integer nonlinear optimization problems. In order to overcome this limitation and evaluate the effect of the simplification, the current work extends a rigorous equilibrium-stage superstructure model to account for tray-specific pressure drop and HETP values. A polylithic solution approach is implemented to improve the convergence for the resulting optimization problems. The proposed approach is demonstrated for the optimization of heat-integrated distillation sequences operated at close to atmospheric and vacuum... [more]

Dynamic simulation of distillation columns and chemical reactors remains essential for plant design, controllability analysis, and economic optimization. High-purity separations of close-boiling mixtures present significant computational challenges due to nonlinear thermodynamic behavior and stiff differential-algebraic equation (DAE) systems. This work presents a unified Python/JAX framework integrating four computational modules: (1) Peng-Robinson thermodynamics with complex-step differentiation, (2) nonlinear solvers (Newton, Broyden, Newton-Krylov) with automatic Curtis-Reid scaling, (3) DAE solver with Radau IIA collocation and intelligent auto-selection, and (4) constrained optimization using the Augmented Lagrangian Method with JAX automatic differentiation. The framework leverages JAX's just-in-time compilation (JIT), vectorization (vmap), and automatic differentiation (AD) to achieve near-compiled-language performance. Validation includes: nonlinear solver benchmarks with Newt... [more]

Liquefied Natural Gas (LNG) plays a strategic role in the global energy transition, as it represents a less carbon-intensive alternative to coal. Separation of CO2 from raw natural gas is a critical step for meeting LNG specifications and enabling Enhanced Oil Recovery (EOR) in offshore fields. However, high CO2 concentrations and formation of a CO2 ethane azeotrope increase the process complexity, often requiring extractive distillation with heavier hydrocarbons. Severe limitations are faced in offshore environments due to their weight, volume and high energy consumption. Due to that, Process Intensification (PI) seeks to enhance heat and mass transfer efficiency, potentially reducing equipment volume and weight. Rotating Packed Beds (RPB) have demonstrated significant potential for intensifying LNG purification by using centrifugal forces to drive liquid through a porous medium in contact with a gas stream. Experimental measurements of total pressure drop, and local liquid holdup are... [more]

This work presents a data-driven surrogate modeling framework for predicting distillation behavior assuming an infinite number of stages and distillation limits informed by residue-curve topology and pinch-point feasibility analysis. The framework provides a direct mapping from feed composition and distillate-to-feed ratio (D/F) to distillate and bottom product compositions, making it suitable for flowsheet synthesis and optimization applications. The approach combines three components: a classifier that identifies feasible singular-point splits, a boundary regression model that predicts D/F limits separating pure- and mixed-product operating regimes, and a neural network that interpolates product compositions in the intermediate regime. The method is demonstrated for the ternary system ethanol, benzene, and water at 1 atm using data generated from rigorous vapor-liquid-liquid equilibrium analysis. Results show that the framework provides reliable predictions for pure splits while reta... [more]

Maintenance is critical for industrial plants to ensure operational reliability and worker safety. In process industries, fouling, the accumulation of solid residues in equipment, poses a significant challenge, causing inefficiencies and productivity losses. Effective modeling of fouling evolution over time is essential for maintenance planning to prevent equipment from operating under suboptimal conditions. Traditional approaches to fouling prediction include equation-based models, which offer high precision but may struggle with continuously changing process bound-aries, and machine learning techniques, which are more adaptable but less effective at capturing rapidly evolving trends driven by complex underlying physics. This study introduces an innova-tive hybrid machine learning approach for predictive maintenance, combining the strengths of both methods. Pressure differential is modeled using an equation-based approach that links pressure data with fouling thickness, while the foul... [more]

Distillation processes account for a substantial share of the industrial energy demand. Yet, these energy requirements can be reduced by a variety of energy integration methods, including various forms of direct heat integration, multi-effect distillation, thermal coupling and vapor recompression. Consequently, these intensification methods should be evaluated quantitatively in comparison to each other for individual separation tasks, instead of benchmarking single options with conventional sequences or relying on simplified heuristics. In order to overcome the computational burden of a broad assessment of a large number of process alternatives, a computationally-efficient framework for the energetic and economic evaluation of such energy integrated distillation processes is presented, which builds on thermodynamically-sound shortcut models that do not rely on constant relative volatility and constant molar overflow assumptions.

A reinforcement learning framework is developed for the synthesis of distillation trains. The rigorous Naphtali-Sandholm algorithm for equilibrium separation modeling was implemented in JAX and coupled with the benchmarking Jumanji RL library. The vanilla actor-critic agent was successfully trained to build distillation trains for a seven-component hydrocarbon mixture. A transformer encoder structure was used to apply self-attention over the agent’s observation. The agent was trained on minimal data representation containing quantitative component flows and relative volatility parameters between present components. Training sessions involving 5·104 episodes (3·105 column designs) were typically run in under 60 minutes. While training was fast and reliable with appropriate tuning of the hyperparameters, further improvements are needed in the generalizability performance for similar separation problems.

Rapid and robust simulation of chemical production processes is critical to address core scientific questions related to process design, optimization, and sustainability. Efficiently solving a chemical process, however, remains a challenge due to their highly coupled and nonlinear nature. Graph abstractions of the underlying physical phenomena within unit operations may help identify potential avenues to systematically reformulate the network of equations and enable more robust convergence of flowsheets. To this end, we further refined a flowsheet graph-theoretic abstraction that consists of a mesh of interconnected variable nodes and equation nodes. The new network of equations is formulated at the phenomenological level agnostic to the thermodynamic property package by extending equation formulations widely used to solve multistage equilibrium columns. Decomposition of the graph by phenomena linearizes material and energy balances across the flowsheet by decoupling phenomenological n... [more]

Mechanical compression heat pumps are indispensable to facilitate the transition from thermally driven processes to renewable energy by electrification, upgrading low-temperature waste heat to recycle it at a higher temperature level. However, the implementation of such heat pumps up to date encounters limitations, due to equipment limitations and a lack of tools for the design of process concepts for the application of high-temperature heat pumps. The optimal design of heat pumps relies heavily on the selection of an appropriate refrigerant, as the thermodynamic properties significantly affect the heat pump cycle design and performance. While existing methods are capable of identifying thermodynamically beneficial refrigerants, they do not directly account for practical constraints such as limitations on the compressor discharge temperature, compression ratio, and vacuum operation. The current study proposes a fast-screening approach for arbitrary heat pump applications, considering a... [more]

The dividing wall column (DWC) has significant energy saving potential compared to conventional column sequences. However, to reach these savings in practice, it is essential that the control structures can track the optimal operation point despite inevitable changes in feed properties, performance characteristics and other uncertainties. Otherwise, the energy consumption may rise significantly or, more commonly, the DWC becomes unable to produce pure products even at its maximum reboiler duty. Extremum seeking control (ESC) is a model-free optimisation technique that may mitigate off-optimal operation in this environment. By active perturbation of selected manipulative variables, the algorithm infers gradient properties of the measured cost function and, by that, enables tracking of a moving optimum. Extremum seeking control can be used also in combination with other approaches, e.g. self-optimising control. Applied to the DWC, the presented perturb-and-observe algorithm, which can be... [more]

The evaluation of control properties in industrial processes is essential to achieve sustainability, a very relevant topic today. This study emphasizes the importance of control studies to ensure that processes are efficient, operable and safe. While strategies such as process intensification can reduce the size, cost, and consumption of energy, it can present challenges in control and operability. This work focuses on the evaluation of the control properties of schemes with different degrees of intensification for the purification of levulinic acid, with the aim of identifying designs with the best control properties and the best economic and environmental indicators. The schemes were designed under a systematic synthesis strategy and optimized using the hybrid method of differential evolution with a tabu list, considering the total annual cost and Eco-indicator 99. An open-loop study analyzed the relationship between manipulable variables and output variables using total condition nu... [more]

Recently, the focus on increasing process efficiency to reduce energy consumption has driven the adoption of alternative systems, such as Petlyuk distillation columns. It has been proven that, when compared to conventional distillation columns, these systems offer significant energy and cost savings. From an economic standpoint, achieving high-purity products alone does not ensure the feasibility of a process. Instead, balancing the trade-off between product purity and cost necessitates multi-objective optimization. While conventional optimization methods are effective, novel strategies like Bayesian optimization offer distinct advantages for handling complex systems. Bayesian optimization requires no explicit mathematical model and can efficiently optimize even when starting from a single initial point. However, as a black-box method, it demands a detailed analysis of hyperparameters, such as the acquisition function and the number of initial points, to ensure optimal performance. Thi... [more]

Superstructure based approaches have long been employed for optimal process synthesis problems. Due to the difficulties of using rigorous process models and simultaneous solutions, shortcut calculations have been the preferred means of modeling unit operations within larger process network problems. However, even with the use of shortcut equations to model the behaviour of unit operations, the resulting mixed-integer programs can be challenging to solve. Furthermore, generating the problem superstructure has often been done manually, presenting issues for scaling to larger problems. We demonstrate the use of an algorithmic approach to generate network superstructures for synthesis problems coupled with equation reformulations to yield an MIQCP (Mixed-Integer Quadratically Constrained Program) for networks of thermally coupled distillation columns. The combination of rapid problem generation with the ability to leverage recent advances in the performance of QCP (Quadratically Constraine... [more]

Despite the potential of electrification in transportation, diesel will remain one of the main fuels for decades. The replacement of diesel with biodiesel is one of the solutions to decrease the net emissions of diesel engines. However, biodiesel has limited performance in cold weather and requires fuel additives. In this context, choosing additives from non-edible, inexpensive, renewable sources is important. Ethyl levulinate, an ester derived from levulinic acid that can be produced from sugarcane, is a promising option because it improves the cold-flow properties of fuels and reduces soot emissions. In this work, a reactive distillation column was designed to produce ethyl levulinate. Because of the volatility order of the components involved in this reaction, levulinic acid was chosen as the excess reactant. Production cost was calculated based on ethanol price, capital cost, and operating expenses for several scenarios. The results showed that the optimized reactive distillation c... [more]

A generally applicable framework for the evaluation of the sustainability of distillation processes is proposed by aligning indicators directly to selected sustainable development goals (SDGs) created by the United Nations. The indicators are related to the goals good health and well-being (SDG 3), clear water and sanitation (SDG 6), affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry, innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), climate action (SDG 13) and life below water (SDG 14). A total of 12 sustainability indicators, including human toxicity potential, wastewater generation, water consumption, renewable energy share, energy demand, material footprint, profit, waste generation, recycling ratio of waste, greenhouse gas emission, eutrophication potential and acidification potential are assigned to selected SDGs. The application of the indicators is illustrated by two case studies: a batch (BD) and a conti... [more]

This study investigates the design of a two-column distillation (TCD) process to separate a dilute ternary Ethyl Acetate (EtAc)-Methanol (MeOH)-water waste solvent into nearly pure components. The separation is complicated by the presence of a homogeneous EtAc-MeOH azeotrope and a heterogeneous EtAc-water azeotrope, creating a distillation boundary that divides the ternary composition space into two distinct regions. To address this, the proposed flowsheet incorporates liquid-liquid phase separation to cross the distillation boundary, enabling feasible separation. Additionally, the pressure sensitivity of the distillation boundary is exploited to reduce the recycle rate, enhancing energy efficiency. The basic TCD flowsheet consists of a decanter, a high-pressure simple column, and a low-pressure divided-wall column (DWC). Heat integration (HI) is achieved using external process-to-process heat exchangers and vapor recompression (VR)-driven reboilers. The resulting energy-efficient HIVR... [more]

This work investigated synergies for improved energy efficiency between integrated first- (1G) and second-generation (2G) sugarcane ethanol distillation, an energy-intensive unit operation, especially for stand-alone 2G ethanol. For this investigation, integrated and separated 1G2G distillation simulations were conducted using Aspen Plus v.10 assuming a dilute 2G fermentation beer with titer varying from 5 to 40 g/L. The results were then assessed in heating energy demand savings for distillation, and it was measured the potential of saved bagasse (boiler fuel) for valorization in either electricity or 2G ethanol. A life cycle assessment was also performed for a consequential approach to carbon emission reductions from energy savings. As our main result, distillation integration can maintain the heat demand of a stand-alone 1G mill, regardless of the 2G ethanol beer titer. This means energy savings between 9 and 15% in total ethanol heat demand, and between 46 and 92% in 2G ethanol hea... [more]

Acrylonitrile is a critical commodity chemical used to produce a variety of industrial polymers, such as carbon fibers, plastics, etc. Currently 90% of the global acrylonitrile production is based on propylene ammoxidation. However, there is no literature reporting the whole process holistically in detail, and which also looks into the energy utilization of the whole process including the reaction heat as well as the energy demands of the downstream separation. This original study provides a rigorous process design of the full process from a holistic viewpoint, covering 7 sections of acrylonitrile production (reaction, acid quenching, absorption-desorption, hydrogen cyanide recovery, acrolein recovery, acrylonitrile-acetonitrile-water separation, acetonitrile recovery sections). In order to further improve the energy efficiency, three energy integration strategies are proposed (1) Energy integrated downstream processing; (2) Systematic heat integration utilizing the heat of reaction; (... [more]

An intensified approach to ?-valerolactone (GVL) production is achieved using a reactive distillation column. Conventional methods require multiple units, leading to high energy consumption, costs, and limited scalability. The proposed technology integrates reaction and separation into a single unit, enhancing process efficiency for biomass-derived chemicals. A multiobjective optimization framework balances economic, environmental, and operational goals, reducing total annual cost (TAC) by 43% and environmental impact (EI99) by 45% compared to conventional processes. Additionally, energy consumption drops by 63%, while GVL production increases by 25%, highlighting the potential of reactive distillation for improved efficiency and sustainability.

Pressure-swing distillation (PSD) is a frequently applied method to separate pressure-sensitive azeotropic mixtures; however, its energy demand is very high. In continuous mode, PSD is performed in a system consisting of a high- and a low-pressure column. If the composition of the feed is between the azeotropic compositions at the two pressures, it can be introduced into any of the columns, leading to two possible column sequences. Depending on the feed composition, one of the sequences is optimal whether in terms of energy demand or total annual cost (TAC). In the present work, surrogate model-based optimization is applied to determine the optimal TAC value as a function of the feed composition between the azeotropic ones. As a first step, the column sequence with feeding into the high-pressure column is studied here. The mixture to be separated consists of water and ethylenediamine, which form a maximum-boiling azeotrope. The columns are modeled separately and a large number of simul... [more]

Supplementary Material for the contribution "Synthesis of Distillation Flowsheets with Reinforcement Learning using Transformer Blocks" by Niklas Slager and Meik Franke (UTwente) for ESCAPE 35

Herein, the Aspen models to the paper "Chemical recycling of plastic waste via production of ethylene from gasification syngas" are published. The model starts at syngas, as gasification was not modeled in Aspen Plus. Syngas is treated and fed into a methanation reactor. Ethylene is then produced via oxidative coupling of methane. The fractionation involves cryogenic distillation as well as CO2 capture. Latter one was modeled in a separate file.

2,3 butanediol (BDO) has garnered recent interest due to the high titer concentrations that can be obtained through biochemical routes and its potential for efficient conversion into long-chain hydrocarbons. BDO separation, however, is challenging given its low volatility and high affinity towards water. In this study, two BDO separation pathways were compared, single distillation and combined simulated moving bed (SMB) adsorption with distillation. The separations were incorporated into a 2018 biorefinery design developed by the National Renewable Energy Laboratory (NREL) to produce renewable fuels from corn stover, with BDO as an intermediate and adipic acid as the co-product. The comparison was performed on the basis of sustainability, using lifecycle greenhouse gas (GHG) emissions as the metric. It was found that using a single distillation column gives GHG emissions of 48 gCO2e/MJ for the renewable fuel. This is lower than 93 gCO2e/MJ for petroleum fuel but is higher compared to t... [more]