Equation-Oriented (EO) modeling techniques have been gaining popularity as an alternative for simulating and optimizing process systems due to their flexibility and ability to leverage state-of-the-art solvers inaccessible to many procedural modeling approaches. Despite these advantages, adopting EO modeling tools remains challenging due to the significant learning curve and effort required to build and solve models. Many techniques are available to help diagnose problems with EO process models and reduce the effort required to create and use them. However, these techniques still need to be integrated into EO modeling environments, and many modelers are unaware of sophisticated EO diagnostic tools. To survey the availability of model diagnostic tools and common workflows, the U.S. Department of Energy’s Institute for the Design of Advanced Energy Systems (IDAES) has conducted user experience interviews of users of the IDAES Integrated Platform (IDAES-IP) for process modeling. The inter... [more]

We present the implementation of combined junior course projects encompassing three core courses: reaction engineering, separations, and process simulation and design. The combined project aims to enhance the vertical integration of process design learning through all levels of the curriculum. We design the projects to utilize novel modular process technologies (e.g., membrane separation) and to emphasize new process design goals (e.g., sustainability, decarbonization). Two example projects, respectively on green methanol synthesis and ethylene oxide production, are showcased for project implementation. Feedback from junior and senior students is also presented to motivate the development of such joint project in CHE curriculum. We will also discuss the challenges we hope to address to maximize student learning from this unique project.

Equation-oriented (EO) modeling has the potential to enable the effective design and optimization of the operation of advanced energy systems. However, advanced modeling of energy systems results in a large number of variables and non-linear equations, and it can be difficult to search through these to identify the culprit(s) responsible for convergence issues. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms so they can be rescaled. A further singular value decomposition can be performed to identify degenerate sets of equations and remaining scaling issues. This work presents an EO model of a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. The IDAES diagnostics tools were successfully applied to this flowsheet to identify problems to im... [more]

Managing oil and gas produced water, characterized by hypersalinity and large volumes, presents significant challenges. This paper introduces an advanced optimization framework, PARETO, which offers a novel approach to strategic water management, emphasizing produced water (PW) treatment, quality tracking, quantification of emissions, and environmental justice. This work presents a case study showcasing different produced water management challenges. The PARETO framework demonstrated its effectiveness in optimizing water management strategies in line with environmental sustainability and regulatory compliance.

Triacetic acid lactone (TAL) is a bio-privileged molecule with potential as a chemical precursor, traditionally synthesized from petroleum. Current trends are shifting towards the use of renewable biomass or CO2-derived feedstocks to enhance sustainability. However, comprehensive studies on the techno-economic viability and carbon life cycle of such methods are limited. This study assesses TAL production from conventional glucose and a novel approach co-feeding Yarrowia lipolytica (YL) with glucose and formic acid (FA), aiming for a more cost-effective and eco-friendly process. We confront the inherent challenges in this process by exploring different technology scenarios using kinetic bioprocess modeling underpinned by techno-economic analysis (TEA) and life cycle assessment (LCA) to identify the most cost-effective and sustainable routes to TAL production. A noteworthy component of our investigation centers around the prospect of recycling and utilizing the CO2 emitted from the YL bi... [more]

This work explores the economic and environmental opportunities for sustainable aviation fuel (SAF) in the Brazilian sugarcane industry. Brazil was one of the first countries to use biomass fuels for transportation and is currently the 2nd largest producer of the world’s bioethanol. Bioethanol produced from sugarcane can be upgraded to SAF via the American Society for Testing and Materials (ASTM)-certified pathway alcohol-to-jet (ATJ); however, at least two challenges exist for commercial implementation. First, technologies to produce bio-jet fuels cost more than their conventional fossil-based counterparts. Second, there is considerable uncertainty regarding returns on investment as the sugar and ethanol markets have been historically volatile. As such, we propose a new optimization model to inform risk-conscious investment decisions on SAF production capacity in sugarcane mills. Specifically, we propose a linear program (LP) to model an integrated sugarcane mill that can produce suga... [more]

The study of sustainable design has gained prominence in response to the growing emphasis on environmental and social impacts of critical infrastructure. Addressing the different dimensions inherent in sustainability issues necessitates the application of many-objective optimization techniques. In this work, an illustrative four-objective design system is formulated, wherein uncertainties lie within two different socially-oriented objectives. A stochastic community detection approach is proposed to identify robust groupings of objectives. The findings reveal that the modularity of the optimal solution surpasses that of the average graph, thus demonstrating the efficacy of the proposed approach. Furthermore, a comprehensive exploration of the Pareto frontiers for both the robust and single-scenario best groupings is undertaken, demonstrating that using the robust grouping results in little to no information loss about tradeoffs.

This paper presents optimal design for an energy-integrated biogas-fuel cell system for renewable electricity generation. The integrated process consists of two steps. The first step generates hydrogen from biogas via methane steam reforming (SMR), whereas the second step electrochemically converts this hydrogen into electricity using a solid oxide fuel cell (SOFC). These two steps are coupled via material and energy integration. Specifically, various design alternatives like anode and/or cathode gas recycling, biogas upgradation by CO2 removal, external versus direct internal reforming, and auxiliary power production through steam and/or micro gas turbine are explored to improve the overall efficiency and total annualized cost of the system. Specifically, a flowsheet superstructure is developed by incorporating all the available design alternatives. An optimal flowsheet with minimum total annualized cost is extracted from this superstructure using formal optimization techniques to mee... [more]

Reverse electrodialysis (RED) is a nascent renewable technology that generates clean, baseload electricity from salinity differences between two water streams, a renewable source known as salinity gradient energy (SGE). Full-scale RED progress calls for robust techno-economic and environmental assessments. Using generalized disjunctive programming (GDP) and life cycle assessment (LCA) principles, this work proposes cost-optimal and sustainable RED process designs involving different RED stack sizes and width-over-length ratios to guide the design and operation from the demonstration to full-scale phases. Results indicate that RED units will benefit from larger aspect ratios with a relative increase in net power of over 30% with 6 m2 membrane size. Commercial RED unit sizes (0.25–3 m2) require larger aspect ratios to reach an equal relative increase in net power but exhibit higher power densities. The GDP model devises profitable RED process designs for all the assessed aspect ratios in... [more]

Most studies in process systems engineering are applying incomplete methods when incorporating sustainability. Including sustainability is a laudable goal, and practitioners are encouraged to develop systems that promote economic, environmental, and social aspects. Ten methods that are often overlooked in performing sustainable process systems engineering are listed in this effort and discussed in detail. Practitioners are encouraged to create designs that are inherently safer, to be more complete in their identification of process chemicals used and released, to be complete in their definitions of supply chains, and to apply additional environmental impact categories. Other methods point to items that are factors in process systems engineering such as disruptive recycling, robust superstructures for optimizations, and employing complete sets of objectives. Finally, users should be aware that sustainability tools are available, which might have been outside of their awareness.

Sand produced along with well-production fluids accumulates in the surface facilities over time, taking valuable space, while the sand carried with the fluids damages downstream equipment. Thus, sand is separated from the fluid in the sand traps and separators and removed during periodic clean-ups. But at high sand productions, the probability of unscheduled facilities shutdowns increases. Such extreme production conditions can be handled by strategic planning and optimal design of the separator network to enable maximum sand separation at minimal equipment cost while ensuring the accumulation extent is within tolerable limits. This paper develops a mathematical model to optimize the separator network design to maximize sand separation while the sand accumulation extent and total equipment cost are minimal. The optimization model is formulated using multi-objective mixed-integer nonlinear programming (MINLP). The capabilities of the developed model to assist sand management in the sepa... [more]

Ethylene is a crucial precursor for a diverse spectrum of products and services. As global production exceeds 150 million tons annually and is projected to surpass 255 million tons by 2035, the imperative for sustainable and efficient ethylene production becomes increasingly clear. Despite Externally Heated Crackers (EHCs) dominating ethylene production for over a century, they face intrinsic limitations that necessitate transformative solutions, including intense radial thermal gradients, high metal demand, and substantial CO2 emissions. This study employs a robust combination of Computational Fluid Dynamics (CFD) coupled with detailed chemical kinetics to rigorously assess selected configurations of Internally Heated Crackers (IHCs) against the leading EHC designs. Our findings reveal that IHCs exhibit the potential to enhance ethylene output by a factor of 1.66 when compared to EHCs of the same length, diameter, and surface temperature. These results herald a promising era for devel... [more]

Computer-aided molecular and process design (CAMPD) tries to find the best molecules together with their optimal process. If the optimization problem considers two or more components as degrees of freedom, the resulting mixture design is challenging for optimization. The quality of the solution strongly depends on the accuracy of the thermodynamic model used to predict the thermophysical properties required to determine the objective function and process constraints. Today, most molecular design methods employ thermodynamic models based on group counts, resulting in a loss of structural information of the molecule during the optimization. Here, we unlock CAMPD based on property prediction methods beyond first-order group-contribution methods by using molecule superstructures, a graph-based molecular representation of chemical families that preserves the full adjacency graph. Disjunctive programming is applied to optimize molecules from different chemical families simultaneously. The de... [more]

In this work, we propose a Mixed Integer Nonlinear Programming (MINLP) model to determine the optimal sustainable design of a poly(hydroxyalkanoate)s (PHAs) production plant configuration and its heat exchanger network (HEN). The superstructure-based optimization model considers different carbon sources as raw material: glycerol (crude and purified), corn starch, cassava starch, sugarcane sucrose and sugarcane molasses. The PHA extraction section includes four alternatives: the use of enzymes, solvent, surfactant-NaOCl or surfactant-chelate. Model constraints include detailed capital cost for equipment, mass and energy balances, product specifications and operating bounds on process units. To assess the feasibility of the PHA plant, we considered the Sustainability Net Present Value (SNPV) as the objective function, a multi-criteria sustainability metric that considers economic, environmental and social pillars. The Net Present Value (NPV) was also calculated. SNPV metric provides usef... [more]

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high-fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High-fidelity simulations are effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuratio... [more]

Critical minerals and rare earth elements play an important role in our climate change initiatives, particularly in applications related with energy storage. Here, we use discrete optimization approaches to design a process for the recovery of Lithium and Cobalt from battery recycling, through membrane separation. Our contribution involves proposing a Generalized Disjunctive Programming (GDP) model for the optimal design of a multistage diafiltration cascade for Li-Co separation. By solving the resulting nonconvex mixed-integer nonlinear program model to global optimality, we investigated scalability and solution quality variations with changes in the number of stages and elements per stage. Results demonstrate the computational tractability of the nonlinear GDP formulation for design of membrane separation processes while opening the door for decomposition strategies for multicomponent separation cascades. Future work aims to extend the GDP formulation to account for stage installatio... [more]

In response to the global imperative to address climate change, this research focuses on enhancing the transparency and efficiency of the Carbon Capture Utilization and Storage (CCUS) supply chain under carbon tax. We propose a decision-making framework that integrates the CCUS supply chain's optimization model, emphasizing carbon tax policies, with a blockchain network. Smart contracts play a pivotal role in automating the exchange and utilization of carbon emissions, enhancing the digitalization of the CCUS supply chain from source to sink. This automation facilitates seamless matching of carbon sources with sinks, efficient transfer of emissions and funds besides record-keeping of transactions. Consequently, it improves the monitoring, reporting, and verification processes within the CCUS framework, thereby simplifying compliance with regulatory mandates for net emission reductions and carbon taxation policies. By eliminating reliance on third-party verifiers, our blockchain-based... [more]

Inspired by Nature, we propose that synergies between biorefinery and mineral refinery can be exploited so that at least a part of the carbon is captured before being released to the atmosphere. In doing so, carbon is captured not only from CO2 but also from biomass and developing more such processes may be the cornerstone for controlling CO2 emissions. A comparison of circular economy in traditional biorefineries and bio-mineral refineries is done by using general chemical formulas and it is shown that the bio-mineral refinery captures carbon. In this work, we have shown that Serpentine may be used to partially neutralise biomass pyrolysis oil. The extracted oil may be used as feedstock to produce downstream chemicals and further studies are required to produce the same.

The oil and gas energy sector uses billions of gallons of water for hydraulic fracturing each year to extract oil and gas. The water injected into the ground for fracturing along with naturally occurring formation water from the oil wells surfaces back in the form of produced water. Produced water can contain high concentrations of total dissolved solids and is unfit for reuse outside the oil and gas industry without desalination. In semi-arid shale plays, produced water desalination for beneficial reuse could play a crucial role in alleviating water shortages and addressing extreme drought conditions. In this paper we co-optimize the design and operation of desalination technologies along with operational decisions across produced water networks. A multi-period produced water network model with simplified split-fraction-based desalination nodes is developed. Rigorous steady-state desalination mathematical models based on mechanical vapor recompression are developed and embedded at the... [more]

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider th... [more]

Multilayer plastic films are widely used in packaging applications because of their unique properties. These materials combine several layers of different polymers to protect food and pharmaceuticals from external factors such as oxygen, water, temperature, and light. Unfortunately, this design complexity also hinders the use of traditional recycling methods, such as mechanical recycling. Solvent-based separation processes are a promising alternative to recover high-quality pure polymers from multilayer film waste. One such process is the Solvent-Targeted Recovery and Precipitation (STRAPTM) process, which uses sequential solvent washes to selectively dissolve and separate the constituent components of multilayer films. The STRAPTM process design (separation sequence, solvents, operating conditions) changes significantly depending on the design of the multilayer film (the number of layers and types of polymers). Quantifying the economic and environmental benefits of alternative process... [more]

This paper considers the optimal incorporation of renewable ammonia production facilities into existing supply chain networks which import ammonia from conventional producers while accounting for uncertainty in this conventional ammonia price. We model the supply chain transition problem as a two-stage stochastic optimization problem which is formulated as a Mixed Integer Linear Programming problem. We apply the proposed approach to a case study on Minnesota's ammonia supply chain. We find that accounting for conventional price uncertainty leads to earlier incorporation of in-state renewable production sites in the supply chain network and a reduction in the quantity and cost of conventional ammonia imported over the supply chain transition horizon. These results show that local renewable ammonia production can act as a hedge against the volatility of the conventional ammonia market.

The food-energy-water nexus (FEWN) has been receiving increasing interest in the open literature as a framework to address the widening gap between natural resource availability and demand, towards more sustainable and cost-competitive solutions. The FEWN aims at holistically integrating the three interconnected subsystems of food, energy and water, into a single representative network. However, such an integration poses formidable challenges due to the complexity and multi-scale nature of the three subsystems and their respective interconnections. Additionally, the significant input data uncertainty and variability, such as energy prices and demands, or the evaluation of emerging technologies, contribute to the system’s inherent complexity. In this work, we revisit the FEWN problem in an attempt to elucidate and address in a systematic way issues related to its multi-scale complexity, uncertainty and variability. In particular, we provide a classification of the sources of data and te... [more]

In a world grappling with mounting plastic waste, the pursuit of sustainable plastic waste management has become pivotal in aligning with Circular Economy (CE) goals, with a strong emphasis on resource conservation, product durability, and carbon footprint reduction. The strategic implementation of recycling methods serves as a stepping stone for transitioning from linear to circular models. This work delves into plastic waste recycling technologies, specifically focusing on open and closed-loop approaches, providing a comprehensive evaluation anchored on economic, environmental, and circularity criteria. Different recycling techniques are thoroughly examined, with particular attention given to chemical recycling methods such as pyrolysis and gasification. This work introduces a comprehensive screening model driven by a new proposed circularity metric validated through a case study to assess these recycling pathways. The results reveal the substantial potential of chemical recycling te... [more]

Achieving worldwide sustainable development is a practical challenge that demands an efficient management of resources across their entire value chains. This practical task requires the optimal selection of pathways for extracting, processing, and transporting resources to meet the demands in different geographic regions at minimal economic cost and environmental impact. This work addresses the challenge by proposing a systematic framework for designing resource-processing networks that can be applied to resource management problems. The framework considers the integration and resource exchange within and across multiple processing clusters. It allows for the life cycle assessment of the environmental and economic impacts of the defined value chains, and design accordingly the different processing and transport systems from extraction to final use. The proposed representation and optimization model are demonstrated in a case study to assess the impact of energy transition under decarbo... [more]