The growing size and complexity of energy system optimization models, driven by high-resolution
spatial data, pose significant computational challenges. This study introduces methods to reduce model’s size and improve computational efficiency while preserving solution accuracy. First, a composite-curve-based approach is proposed to aggregate granular data into larger resolutions without averaging out specific properties. Second, a general clustering method groups geographically proximate fields, replacing multiple transportation arcs with a single arc to reduce transportation-related variables. Lastly, a two-step algorithm that decomposes the supply chain design problems into two smaller, more manageable subproblems is introduced. These methods are applied to a case study of switchgrass-to-biofuels network design in eight U.S. Midwest states, demonstrating their effectiveness with realistic and detailed spatial data.

Three different implementations of the flipped class paradigm were used to teach Chemical Engineering students at Imperial College London (ICL) in the 2023-24 academic year: (1) The 3rd year elective course Introduction to Numerical Methods (INM) taught in its entirety in flipped format (the "good"); (2) The 2nd year core course on Process Dynamics and Control (PDC), with the first half of the course on process dynamics taught in traditional lecture format, and the second half on process control taught in flipped format (the "bad"); and (3) a one-week workshop on heat integration, taught as part of a 3rd year core course on Process Design (PD), taught in flipped format (the "surprising"). This paper describes these three implementations in detail and presents and analyzes the responses from student surveys intended to ascertain students' perceptions about the level of their satisfaction with the flipped class approach and the degree to which they achieved mastery of the taught... [more]

Maintaining sufficient amounts of dissolved oxygen throughout a microbial cultivation is a classic control task in bioprocess engineering to avoid negative effects onto cell physiology and productivity. But traditional PID-based algorithms struggle when faced with pulsed substrate additions and the resulting sudden surge of oxygen uptake. In this work a nonlinear MPC is employed and compared to a PID setup for the cultivation of an E. coli strain exposed to intermittent feeding. Both controllers are tuned for a fast pulse response combined with efficient and robust control action. Their performance was tested in-silico with isolated feed pulses, as well as throughout a full cultivation run. Further, the effects of parameter uncertainty were investigated to assess the impact of a model-plant mismatch. The results showed that the predictive nature of the MPC is well suited for maintaining the dissolved oxygen levels above a threshold and outperforms the PID in almost all investigated sim... [more]

Optimization under uncertainty is inherent to many PSE applications ranging from process design to RTO. Reaching process true optima often involves learning from experimentation, but actual experiments involve a cost (economic, resources, time) and a budget limit usually exists. Finding the best trade-off on cumulative process performance and experimental cost over a finite budget is a Partially Observable Markov Decision Process (POMDP), known to be computationally intractable. This paper follows the nonmyopic Bayesian optimization (BO) approximation to POMDPs developed by the machine-learning community, that naturally enables the use of hybrid plant surrogate models formed by fundamental laws and Gaussian processes (GP). Although nonmyopic BO using GPs may look more tractable, evaluating multi-step decision trees to find the best first-stage candidate action to apply is still expensive with evolutionary or NLP optimizers. Hence, we propose modelling the value function of the first-st... [more]

Active learning is widely recognized as an effective teaching approach that can improve classroom outcomes. This is enabled by providing the time for students to apply new knowledge, make mistakes, correct them, and repeat the process until mastery is achieved. One way to implement active learning is through the flipped classroom paradigm. However, to be effective, active learning depends on providing students with a variety of open-ended problems, ranging in difficulty from introductory to advanced levels. This paper presents four food-themed problems for use in numerical methods and process control courses:
1. Formulating Willy Wonka’s new chocolate bar: An introductory linear programming problem focused on translating verbal descriptions into mathematical models.
2. Optimal production for the Matrix Pizza company: A more advanced mixed-integer linear programming problem involving multiple scheduling scenarios.
3. Optimal frying time for fried ice cream production: A transient hea... [more]

These are the slides presented at the ESCAPE 35 conference on Monday July 7, 2025, in the talk with the same name. They briefly introduce the concept of exergy with a basic overview, and provide seven easy examples that professors can use in their courses. The topics include heating systems, pinch analysis, energy efficiency, energy integration, steam generation, utilities, heat pumps, organic Rankine cycles, direct air capture of CO2, and CO2 compression and sequestration. See the linked conference paper for more information.

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]

In this paper, we present our recent advances and achievements in automatic control course in the engineering study of cybernetics at the Faculty of Chemical and Food Technology STU in Bratislava. We describe the course elements and procedures used to improve teaching, learning, and administration experience. We discuss on-line learning management system, various teaching aids like e-books with/without solutions to practice examples, computer generated questions, video lectures, choice of computation and simulation tools.
The course is provided in the presence form of study for about 20 students, but it relies on on-line tools and methods. Starting from this academic year, flipped design of the course was designed. We describe our experience in the preparation of such a change and some initial feedback from the students.
The course concentrates on input/output linear approximation of processes in chemical and food technology and discusses poles/zeros, process dynamics, frequency and... [more]

Deploying engineered carbon dioxide removal strategies like direct air capture (DAC) will be
imperative to meet net-zero targets, given the biophysical constraints associated with land-based
methods. Thoroughly devised deployment pathways for DAC could ease the financial burdens of
adopting the technology at climate-relevant scales. Key drivers for the optimal regional rollouts of
DAC include the available energy supply and geological capacities for CO2 storage. These factors
also impose temporal constraints considering the evolving nature of energy systems and the
development of CO2 transport and storage infrastructure over time. As DAC technologies exhibit
differences in their system demands, integrating various methods into deployment strategies may
address potential trade-offs arising from regional resource endowments. Commercial-ready options
use solid sorbents or liquid solvents, while emerging methods extend to electrochemical devices
like bipolar membranes. These tech... [more]

Process control should be one of the most exciting chemical engineering undergraduate courses! This presentation describes our experience transforming "Chemical Process Control" into "Data Analytics, Optimization, and Control" at the University of Notre Dame (required in the second semester of the junior year). In six hands-on experiments, students practice data-centric modeling and analysis using the Ardunio-based Temperature Control Lab (TCLab) hardware. The semester learning goals are:
- Develop mathematical models for dynamical systems from data and first principles using modern statistical methods;
- Predict dynamical system performance using numerical methods;
- Analyze, implement, tune, and debug feedback controllers using the hands-on laboratory;
- Formulate and solve optimization problems for decision-making;
- Demonstrate mastery of at least two of the above skills in an open-ended group project.

The goal of this presentation is to share our strategy to modernize... [more]

Overview presenation by Prof. Alexander Dowling at the Public Affairs & Information Committee (PAIC) Town Hall at AIChE Annual Meeting in 2024.

This visual presentation introduces the concept of exergy to a chemical process systems engineering audience, such as how to compute it for heat and for substances at various pressures and temperatures. The presentation also goes over seven examples of how exergy analysis can be used in process design education, such as in utility or capital cost estimation, heat integration, direct air capture, power production, carbon dioxide capture and compression, and pinch analysis.

As part of efforts to reduce carbon emissions in the iron and steel industry, which are especially pertinent in Canada due to rising carbon taxes, Canadian producers have been investigating the effects of replacing coal used in pulverized coal injection with biochar. Although there has been research into the economic value and effect on net life cycle emissions of using the biochar product itself, there are no comprehensive techno-economic analyses which investigate the value and potential uses of the by-products of biomass pyrolysis. These by-products include volatile organic compounds, known collectively as tar or bio-oil, and light gases, which are mainly hydrogen, carbon monoxide, carbon dioxide, and methane. Since only 20-30% of the mass of pyrolyzed biomass is actually converted to char, with the rest converted to the by-products, [1] usage of these by-products is likely the key to increasing the value of biochar to a degree that makes up for the market price of biochar currently... [more]

This work highlights the role of process system engineering (PSE) principles (especially simulation and optimization) in the development of a COVID-19 vaccine and other kinds of vaccines. As a result of a unique multi-national collaboration of PSE-minded chemical engineers, immunologists, and pathologists, we have created computer models of how the human body's immune system responds to vaccine injections of various kinds. The STochastic Omentum REsponse model (STORE) is stochastic, agent-based, and dynamic, and tracks how T-cells and antigen presenting cells interact, change, divide, and respond after an immune event such as a vaccine injection or an infection. Using model parameters related to dosage, injection schedule, genetic traits of the patient, and various vaccine or immune system properties, the STORE model can be used to predict how the human body responds in the days and weeks after a vaccine injection.

The STORE model consists of a collection of small, agent-based mode... [more]

The performance of Solid Oxide Fuel Cells (SOFCs) degrades due to various reactions. Lack of a general model based on these reactions that predicts SOFCs long-time performance with few assumptions, limits commercialization of SOFCs. In this work, a detailed mathematical model is constructed to evaluate SOFCs long-term performance with regard to operating conditions. Most of the reactions that greatly deteriorates SOFCs components; such as Ni coarsening and oxidation, anode pore diameter changes, deterioration of anode conductivity and electrolyte conductivity, and sulfur poisoning are considered in this model to ensure that it yields reliable and precise results. A broad literature survey indicated that previously developed models only account for a part of these reactions and hence they do not provide accurate results. Rest of the models, on the other hand, are regression models that have been fitted to experimental data and thus are valid in a limited range of operating parameters.... [more]

Solid oxide fuel cells (SOFCs) are a promising next-generation technology for power production from fossil fuels. Because they convert chemical energy into electricity electrochemically, they are generally more efficient than combustion-based power plants due to the thermodynamic limitations of combustion cycles, and accordingly, have lower carbon intensities [1]. However, one of the main drawbacks of SOFCs (and SOFC stacks) is that they can degrade over time in a variety of ways, including accruing damage to the anode, cathode, interconnects, and other cell or stack components. SOFCs are most commonly used in “constant power” mode, in which the fuel flow rate and current density are increased over time to counteract the degradation effects and yield a constant power output. However, higher flow rates cause the degradation rates to grow even faster, resulting in a lifetime potentially as short as 1.5 years [2].

Recent research has found that by operating in “constant voltage” mode,... [more]

Ternary separation using the process of semicontinuous distillation was proposed to be carried out in a single distillation column and a process vessel, which is called the middle vessel [1]. During the process of separation, inlet and outlet material streams of the middle vessel are either operational or non-operational based on its state. With the help of these state-dependent discrete actions, periodic feed charges and the intermediate-boiling product discharges are carried out in the middle vessel, while the low and high volatile components are removed continuously from the column. This periodic process is thus modelled mathematically as a limit-cycle oscillating hybrid system [2] for design purposes. The semicontinuous distillation process design involves estimating equipment sizes, controller tuning parameters, and column design parameters which are all time-invariant parameters of the oscillating hybrid system. These system parameters are chosen to operate the process in a hydra... [more]

In this contribution, I will discuss ongoing efforts to retool the sophomore-level “Numerical and Statistical Analysis” course (required) to provide a scaffolding for all students to develop core competencies in computing, applied statistics, and mathematical modeling throughout their undergraduate experience and profession careers. Beginning in Spring 2019, we are transitioning from MATLAB to Python for several reasons including consistency with “Chemical Process Control” (junior, required) and college-wide electives in data science and statistical computing that already use Python. I will also share experiences using Jupyter notebooks and cloud-based computing platforms such as Colaboratory to incorporate active learning into lectures and tutorials and to remove technical barriers for students. Content and assignments have been reorganized to emphasize mastery of foundational skills in preference over content breadth. For example, students are now required to submit hand-written pseu... [more]

Recovering nutrients from wastewaters and wastes, such as sewage sludge and food waste, as sustainable bio-based products provides a key solution to major environmental problems. Classical technology development approaches for resource recovery largely ignore the real-world variability in raw waste materials, which currently hinders the successful implementation of recovery strategies. A major challenge is to create a consistent, sustainable and environmentally friendly supply of high-quality end-products that can compete with fossil-derived products currently on the market. There is urgent need for a paradigm shift from classical technology development approaches to sustainable integrated end-user focused strategies, supported by a reliable, competitive and repeatable quality assurance framework. An improved balance between efficiency and cost in bio-based production chains is needed, while continuously assuring product quality and safety. This
presentation suggests the use of a qual... [more]

In response to the outcomes-based accreditation model, the Chemical Engineering and Chemical and Biological programs at the University of British Columbia identified 60 indicators to evaluate the 12 graduate attributes outlined by the Canadian Engineering Accreditation Board (CEAB). These indicators are evaluated in each of years 2, 3 and 4 of the program in order to track student progress. Indicator data collection began to be implemented in the 2014/2015 academic year. Indicator data has been collected each year and trends in this data have been analyzed.
These indicators are now undergoing a broad review by the programs to assess their effectiveness. As part of this process, semi-structured interviews were conducted with each faculty member involved in instructing both programs. These interviews focused on a number of topics including:

• appropriateness of current indicator assignments to courses
• confidence as to whether the data gathered in the course measures the indicator... [more]

Open educational resources (OER) can be defined as freely-accessible openly licensed works that can be used for teaching, learning and research. Studies have shown OER to be equally as effective or better than conventional resources (1). The University of British Columbia’s Chemical and Biological Engineering Department has developed a number of OER over the past few years in collaboration with a variety of partners within and outside of the university. This poster will present two of the OER developed for use in a variety of departmental core courses.

One OER developed was open online homework problems on the WeBWorK system. This online homework system, commonly used by many math departments, issues each student a unique set of numbers for a problem. The system provides students with instant feedback and can interpret a variety of mathematical operations, allowing solutions to be formatted in a number of ways. This allows students to collaborate in solving the problem without havin... [more]

This presentation concerns the promising new area of flexible polygeneration, a chemical process design concept in which a chemical plant is able to change its product outputs throughout its lifetime in response to changing market conditions, business objectives, or other external factors. In this talk we present a new flexible polygeneration process system that can switch between dimethyl ether (DME) or methanol production, depending on need. Classic flexible polygeneration systems typically utilize separate process trains for each product, in which whole process trains are turned on or off (or up or down) depending on the current product. However, our proposed process combines the two process trains into one, in which most of the process equipment is always used during either mode of production, but with different operating conditions. In this work, we show how this significantly reduces capital expenditure, reduces the plant footprint, and ultimately is more economical than a tradit... [more]

This poster was presented by me at the CACHE 50th Anniversary meeting on the Future of Cyber Assisted Chemical Engineering Education: http://cache50th.org/?page=youngfaculty

It summarizes my experiences with rennovating the New Jersey Institute of Technology's Chemical Engineering Curriculum through an Infusion of Computation and Multiphysics Modeling. It also proposes the use of COMSOL Multiphysics Apps as a teaching visual aide.

While topics in the chemical engineering curriculum generally involve the macroscale, e.g., focusing on process design and optimizations, many of the grand challenges facing chemical engineers today involve molecular level chemistry. Having an appreciation for molecular-level phenomena will better prepare chemical engineers to handle problems in energy, water, food, catalysis, advanced materials, and other fields. In this presentation, we discuss homework/project problems that we have developed for use in the Material and Energy Balances, Separations, Kinetics, and Thermodynamics courses that explore molecular level phenomena and molecular-level simulation approaches. Specifically, these problems focus on intermolecular interactions, connections between molecular configurations and macroscopic observables, how molecular level properties control material performance, and simulation strategies that enable exploration of the molecular level. An aim of the assignments is to demonstrate sim... [more]

This presentation deals with the issue of modularization of chemical plants, defined in the sense of designing smaller-capacity facilities (“modules”) that could be used to process geographically-distributed resources or serve distributed customers. Using established scaling relations, it is demonstrated that technologies that scale up well (i.e., for which capital cost increases sublinearly with capacity) scale down poorly, and vice versa. A further analysis of scale-down and modularization is carried out from the perspective of scaling of individual unit operations and their contribution to the plant cost stack. Following the same line of reasoning, it is shown that units that scale down well will scale up poorly and vice-versa. On this basis, it is argued that scaling relations can be used not only to guide the design of modular processes based on existing technology, but also to direct research towards new designs that alleviate the cost problems associated with units that have poo... [more]