Designing a digital twin will be crucial in developing automation-based future manufacturing systems. The design of digital twins involves data-driven modelling of individual manufacturing units and interactions between the various entities. The goals of future manufacturing units such as zero waste at the plant scale can be formulated as a model-based optimal control problem by identifying the necessary state, control inputs, and manipulated variables. The fundamental assumption of any model-based control scheme is the availability of a “reasonable model”, and hence, assessing the goodness of the model in terms of stability and sensitivity around the optimal parameter value becomes imperative. This work analyses the data-driven model of an acetaminophen production plant obtained from SINDy, a nonlinear system identification algorithm using sparse identification techniques. Initially, we linearize the system around optimal parameter values and use local stability analysis to assess the... [more]

Chemical looping Reforming (CLR) is seen as a promising technology for blue hydrogen production. With proper control, CLR in fixed bed reactors has demonstrated the capability to generate blue hydrogen and nitrogen from a single reactor. To enhance efficiency and H2 purity in the product stream, integration of a CLR reactor with a heat recovery system and a Shift reactor is essential. This study explores the design and control of an integrated CLR-Shift reactors system. The integrated system yields a product stream with 75% H2 mole fraction during the Reforming step of CLR, and a nitrogen with high purity (98%) during the Oxidation step. In the best-case scenario, the integrated system produces H2 and N2 at a molar ratio of 1.26 with H2 production efficiency of 80.1%.

This paper introduces a computational framework for selecting green solvents to separate multilayer plastic films, particularly those challenging to recycle through mechanical means. The framework prioritizes the selective dissolution of polymers while considering solvent toxicity. Initial screening relies on temperature-solubility dependence, utilizing octanol-water partition coefficients (LogP) to identify non-toxic solvents (LogP = 3). Additionally, guidelines from GlaxoSmithKline (GSK), Registration, Evaluation, Authorization, and Restriction of Chemical Regulation (REACH), and the US Environmental Protection Agency (EPA) are employed to screen for green solvents. Molecular-scale models predict temperature-dependent solubilities and LogP values for polymers and solvents. The framework is applied to identify green solvents for separating a multilayer plastic film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). The case study demons... [more]

Biorefineries can reduce carbon dioxide emissions while serving the global chemical demand market. Governments are also using carbon pricing policies, such as carbon taxes, cap-and-trade models, and carbon caps, as a strategy to reduce emissions. The use of biomass feedstocks in conjunction with carbon capture usage and storage technologies are mitigation strategies for global warming. Businesses can invest in these technologies to accommodate the adoption of these policies. Rapid action is necessary to halt global warming, which results in aggressive policies. In this work, a multi-period process design and planning problem is developed for the design and capacity expansion of biorefineries. The three carbon pricing policies are integrated into the model and parameters are selected according to the aggressive scenario denoted by the Paris Agreement. The results show that the cap-and-trade policy achieves a higher net present value evaluation over the carbon tax model across all pareto... [more]

This study investigates the feasibility of valorizing pulp and pulp sludge (PPS) into methane through anaerobic digestion (AD) with a focus on techno-economic analysis (TEA). Three scenarios are evaluated: (A) the base case, (B) sludge AD with alkaline pretreatment using green liquor dregs (GLD), and (C) co-digestion with nitrogen-rich feedstocks. The evaluation is applied to a common PPS, consisting of 70% primary sludge (PS) from the primary clarifier and 30% secondary sludge (SS) from biological treatments from a kraft mill. Theoretical methane potential (TMP) is determined using the Buswell equation. The study highlights the significance of co-digestion with nitrogen-rich feedstocks in enhancing the economic viability of the AD process for PPS, providing valuable insights for sustainable waste management and resource recovery in the pulp and paper industries.

Increases in population and improvements in living standards have significantly increased the demand for animal products worldwide. However, modern livestock agriculture exerts significant pressure on the environment due to high material and energy requirements. These systems also generate significant amounts of waste that can cause severe environmental damage when not handled properly. Thus, if we wish to enable farmers to meet this increased demand in a sustainable way, technology pathways must be developed to convert livestock agriculture into a more circular economy. With this end in mind, we propose a novel framework (which we call ReNuAl) for the recovery of nutrients from livestock waste. ReNuAl integrates existing technologies with a novel biotechnology approach that uses cyanobacteria (CB) as a multi-functional component for nutrient capture and balancing, purifying biogas, and capturing carbon. The CB can be applied to crops, reducing the need for synthetic fertilizers like d... [more]

There is a need to drastically reduce greenhouse gas emissions. While significant progress has been made in electrifying transport, heavy duty transportation and aviation are not likely to be capable of electrification in the near term, spurring significant research into biofuels. When coupled with carbon capture and storage, biofuels can achieve net-negative greenhouse gas emissions via many different conversion technologies such as fermentation, pyrolysis, or gasification to produce ethanol, gasoline, diesel, or jet fuel. However, each pathway has a different efficiency, capital and operating costs, and potential for carbon capture, making the optimal pathway dependent on policy and spatial factors. We use the Integrated Markal-EFOM System model applied to the USA, adding a rich suite of biofuel and carbon capture technologies, region-specific CO2 transportation and injection costs, and government incentives from the Inflation Reduction Act. We find that under current government ince... [more]

Modern mechanical recycling infrastructure for plastic is capable of processing only a small subset of waste plastics, reinforcing the need for parallel disposal methods such as landfilling and incineration. Emerging pyrolysis-based chemical technologies can “upcycle” plastic waste into high-value polymer and chemical products and process a broader range of waste plastics. In this work, we study the economic and environmental benefits of deploying an upcycling infrastructure in the continental United States for producing low-density polyethylene (LDPE) and polypropylene (PP) from post-consumer mixed plastic waste. Our analysis aims to determine the market size that the infrastructure can create, the degree of circularity that it can achieve, the prices for waste and derived products it can propagate, and the environmental benefits of diverting plastic waste from landfill and incineration facilities it can produce. We apply a computational framework that integrates techno-economic analy... [more]

Utilizing sustainable energy sources is crucial for expanding the range of solutions available to meet the growing energy demand and reducing reliance on environmentally damaging and depleting conventional fuels. Biosolids, a type of biomass, are generated as secondary effluent during wastewater treatment process in municipal and industrial sites. These solids possess the potential to serve as a sustainable energy source due to their richness of carbon. For an extended period, biosolids have been landfilled, even though it can be considered a wasteful use of a precious resource and a possible mean for contamination to the food supply chain. This has served as an extra impetus to investigate the potential for harnessing the capabilities of these substances. While many research studies have looked at different ways to put biomass waste to use, very little has been written on biosolids, especially those derived from industrial sources. This research assesses the feasibility of transformin... [more]

Some of the most highly trusted and ubiquitous process simulators have solution methods that are incompatible with algorithms designed for equation-oriented optimization. The natively unconstrained Efficient Global Optimization (EGO) algorithm approximates a black-box simulation with kriging surrogate models to convert the simulation results into a reduced-order model more suitable for optimization. This work evaluates several established constraint-handling approaches for EGO to compare their accuracy, computational efficiency, and reliability using an example simulation of an amine post-combustion carbon capture process. While each approach returned a feasible operating point in the number of iterations provided, none of them effectively converged to a solution, exploring the search space without effectively exploiting promising regions. Using the product of expected improvement and probability of feasibility as next point selection criteria resulted in the best solution value and re... [more]

Critical minerals are essential to the future of clean energy, especially energy storage, electric vehicles, and advanced electronics. In this paper, we argue that process systems engineering (PSE) paradigms provide essential frameworks for enhancing the sustainability and efficiency of critical mineral processing pathways. As a concrete example, we review challenges and opportunities across material-to-infrastructure scales for process intensification (PI) with membranes. Within critical mineral processing, there is a need to reduce environmental impact, especially concerning chemical reagent usage. Feed concentrations and product demand variability require flexible, intensified processes. Further, unique feedstocks require unique processes (i.e., no one-size-fits-all recycling or refining system exists). Membrane materials span a vast design space that allows significant optimization. Therefore, there is a need to rapidly identify the best opportunities for membrane implementation, t... [more]

We study the design and optimization of a multicomponent seawater desalination process with zero liquid discharge (ZLD). The designed process is highly integrated with multiple sub processing units that include humidification-dehumidification, Lithium Bromide absorption chiller, multi-effect evaporators, mechanical vapor compression, and crystallization. Aspen Plus software with E-NRTL and SOLIDS thermodynamic packages are used for modeling and simulation of desalination and crystallization units, respectively. In addition to this, we use data-driven optimization to find the best operating condition (i.e., the temperature of the last effect evaporator) that minimizes the overall energy consumption of the designed plant with an output constraint imposed on the mass fraction of salts going to the ZLD system should be greater than 20 wt.% to achieve the ZLD goal. We use a local sample-based data-driven optimizer, Nonlinear Optimization with the Mesh Adaptive Direct Search (NOMAD) algorith... [more]

To mitigate the effects of catastrophic failure while maintaining resource and production efficiencies, energy systems need to be designed for resilience and sustainability. Conventional approaches such as redundancies through backup processes or inventory stockpiles demand high capital investment and resource allocation. In addition, responding to unexpected “black swan” events requires that systems have the agility to transform and adapt rapidly. To develop targeted solutions that protect the system efficiently, the supply chain network needs to be considered as an integrated multi-scale system incorporating every component from individual process units all the way to the whole network. This approach can be readily integrated with analogous multiscale approaches for sustainability, safety, and intensification. In this work, we bring together classical supply chain resilience with process systems engineering to leverage the multi-scale nature of energy systems for developing resilienc... [more]

Plastics are widely used for their affordability and versatility across many consumer and industrial applications. However, the end-of-life (EoL) management stage can often lead to releasing hazardous chemical additives and degradation products into the environment. The increasing demand for plastics is expected to increase the frequency of material releases throughout the plastic EoL management activities, creating a challenge for policymakers, including ensuring proper material segregation and disposal management and increasing recycling efficiency and material reuse. This research designed a Python-based EoL plastic management tool to support decision-makers in analyzing the holistic impacts of potential plastic waste management policies. The constructed tool was developed to reduce the complexity of material flow analysis calculations, estimating material releases, and environmental impacts. The utility of the tool was tested through the hypothetical nationwide adoption of an exten... [more]

Aiming to mitigate the environmental impact derived from fossil fuels, we propose an integrated carbon capture-biomass gasification process is proposed to produce low-carbon hydrogen as an alternative energy carrier. The process begins with the pre-treatment of empty fruit bunches (EFB), involving grinding, drying, torrefaction, and pelletization. The resulting EFB pellet is then fed into a dual gasifier, followed by a catalytic cracking of tar and water gas shift reaction to produce syngas, aiming to increase its H2 to CO ratio. Subsequently, we explore two alternatives (DEPG and MEA) for syngas upgrading by removing CO2. Finally, a PSA system is modeled to obtain H2 at 99.9% purity. The pre-treatment stage densifies the biomass from an initial composition (%C 46.47, %H 6.22, %O 42.25) to (%C 54.10, %H 6.09, %O 28.67). The dual gasifier operates at 800°C, using steam as a gasifying agent. The resulting syngas has a volume concentration (%CO 20.0, %CO2 28.2, %H2 42.2, %CH4 5.9). Next s... [more]

One of the main challenges to support life in space is the development of sustainable, circular processes that reduce the high cost of resupply missions. Space biomanufacturing is an emerging paradigm that aims to reduce the need for resources, enabling on-demand manufacture of products. The cost of installing biomanufacturing systems in space depends on the cost of transporting the system components, which is directly proportional to their mass/weight. From this perspective, the system mass is a critical factor that dictates process design, and this has important implications in how we can approach such design. For instance, mass constraints require circular use of resources and tight process integration (to minimize resupply) and restricts the type of resources and equipment needed. In this work, we evaluate the lactic acid bioproduction design using Escherichia coli, Saccharomyces cerevisiae, and Pichia pastoris. We use the Equivalent System Mass (ESM) metric as a key design measure... [more]

In this paper, we study the design optimization of methanol production with the goal of minimizing methanol production cost. One challenge of methanol production via carbon dioxide (CO2) hydrogenation is the reduction of operating costs. The simulation of methanol production is implemented within the Aspen HYSYS simulator. The feeds are pure hydrogen and captured CO2. The process simulation involves a single reactor and incorporates recycling at a ratio of 0.995. The methanol production cost is determined using an economic analysis. The cost includes capital and operating costs, which are determined through the equations and data from the capital equipment-costing program. The decision variables are the pressure and temperature of the reactor contents. The optimization problem is solved using a derivative-free algorithm, pyBOUND, a Python-based black-box model optimization algorithm that uses random forests (RFs) and multivariate adaptive regression splines (MARS). The predicted minimu... [more]

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]

Sustainable and economically viable plastic recycling methodologies are vital for addressing the increasing environmental consequences of single-use plastics. In this study, we evaluate the plastic waste management value for the state of Georgia, US and investigate the potential of introducing novel depolymerization methods within the network. An equation-based formulation is developed to identify the optimum supply-chain design given the geographic location of existing facilities. Chemical recycling technologies that have received increasing attention are evaluated as candidate technologies to be integrated within the network. The optimum supply-chain design is selected based on environmental and economic objectives. The designed network of pathways uses a mix of different technologies (chemical and mechanical recycling) in a way that are both economically environmentally sound.

The overarching goal of limiting the increase in global temperature to = 2.0° C likely requires both decarbonization and defossilization efforts. Direct air capture (DAC) and CO2 electrolysis stand out as promising technologies for capturing and utilizing atmospheric CO2. In this effort, we explore the details of designing and operating an integrated DAC-electrolysis process by examining some key parameters for economic feasibility. We evaluate the gross profit and net income to find the most appropriate capacity factor, average electricity price, syngas sale price, and CO2 taxes. Additionally, we study an optimistic scenario of CO2 electrolysis and perform a sensitivity analysis of the CO2 capture price to elucidate the impact of design decisions on the economic feasibility. Our findings underscore the necessity of design improvements of the CO2 electrolysis and DAC processes to achieve reasonable capacity factor and average electricity price limits. Notably, CO2 taxes and tax credits... [more]

Recent advances in process design for solvent-based, post-combustion capture (PCC) processes, such as the Piperazine/Advanced Flash Stripper (PZ/AFS) process, have led to a reduction in the energy required for capture. Even though PCC processes are progressively improving in Technology Readiness Levels (TRL), with a few commercial installations, incorporating carbon capture adds cost to any operation. Hence, cost reduction will be instrumental for proliferation. The aim of this work is to improve process economics through optimization and to identify the parameters in our economic model that have the greatest impact on total cost to build and operate these systems. To that end, we investigated changes to the optimal solution and the corresponding cost of capture considering changes in the price of utilities and solvent. We found that changes in solvent price had the most effect on the cost of capture. However, re-optimizing the designs in the event of price changes did not lead to sign... [more]

Circular systems design is an emerging approach for promoting sustainable development. Despite its perceived advantages, the characterization of circular systems remains loosely defined and ambiguous. This work proposes a network optimization framework that evaluates three objective functions related to economic and environmental domains and employs a Pareto analysis to illuminate the trade-offs between objectives. The US polyethylene terephthalate (PET) value chain is selected as a case study and represented via a superstructure containing various recycling pathways. The superstructure optimization problems are modeled as a mixed integer linear program (MILP) and linear programs (LPs), implemented in Pyomo, and solved with CPLEX for a one-year assessment horizon. Solutions to the circular economy models are then compared to the corresponding solutions of linear economy models. Preliminary results show that the optimal circular network is advantageous over the optimal linear network fo... [more]

Initial design stages are inherently complex and often lack comprehensive information, posing challenges in evaluating sustainability metrics. Machine Learning (ML) emerges as a valuable solution to address these challenges. ML algorithms, particularly effective in predicting environmental impacts of new chemicals with limited data, enable more informed decisions in sustainable design. This study focuses on employing ML for predicting the environmental impacts related to human health, ecosystem quality, climate change, and resource utilization to aid in early-stage environmental impact assessment of chemical processes. The effectiveness of the ML algorithm, eXtreme Gradient Boosting (XGBoost) tested using a dataset of 350 points, divided into training, testing, and validation sets. The study also includes a practical application of the model in a cradle-to-cradle LCA of N-Methylpyrrolidone (NMP), demonstrating its utility in sustainable chemical process design. This approach signifies... [more]

This study delves into the development and examination of various mathematical models for conventional steam-methane reforming (SMR) reactors, establishing a foundational basis for an electrified SMR reactor design. Distinct mathematical models with different scales and dimensions are derived. A basic 1D-fluid, 0D-catalyst (1D-0D) pseudo-homogeneous model is validated with plant data, and progressively advanced to a 2D-0D model considering radial transfer, then further extended to a rigorous 2D-1D model considering transfer phenomena between catalyst particle and fluid. Simulation cases are conducted under uniform design parameters, heat source and operation conditions. Comparative analyses focus on several key performance aspects, including temperature, reaction rate distribution, and outlet characteristics such as temperature, pressure, flow rate, composition and CH4 conversion. The models effectively describe the industrial SMR reactor behavior. Influences of scale and dimension of... [more]

The synthesis of energy systems necessitates simultaneous optimization of both design and operation across all components within the energy system. In real-world applications, this synthesis poses a mixed-integer nonlinear programming (MINLP) problem, considering nonlinear behaviours such as investment cost curves and part-load performance. The complexity increases further when seasonal energy storage is involved, as it requires temporal coupling of the full time series. Although numerous solution approaches exist to solve the synthesis problems simplified by linearization, methods for solving a full-scale problem are currently missing. In this work, we introduce a rigorous method, RiNSES4, to manage the nonlinear aspects of energy system synthesis, particularly focusing on long-term time-coupling constraints. RiNSES4 calculates the upper and lower bounds of the initial synthesis problem in two separate branches. The proposed method yields feasible solutions through upper bounds, while... [more]