Process Systems Engineering Research Articles

Physics Constrained Learning in Neural Network based Modeling

Neural Network (NN) models based on training solely using data are limited in their use due to issues related to extrapolability and interpretability. On the other hand, while mechanistic models based on governing physical laws can overcome these limitations, the unavailability of accurate mechanistic models render them unsuitable for critical applications. In this paper, we propose an approach to develop an NN model that is trained to exploit available data while also being regularized by physics based information; in other words the loss function of NN is augmented by constraints associated with the system physics. This approach, also known as PINNs (Raissi et al. 2019) has been applied to representative problems in process systems engineering (PSE) to evaluate its efficacy to represent the knowledge about the physics of the system while also exploiting the information in the data. It has been shown that in the presence of noisy data and partially known physics model, this approach can give better predictions compared to the conventional training methodology. It has also been shown that the constraints given by the physics based model are also satisfied to a greater extent as compared to models trained only on data.

Machine Learning and the Digital Era from a Process Systems Engineering Perspective

Machine Learning and the Digital Era from a Process Systems Engineering Perspective

Online Graduate Certificate in Data Science for the Chemical Industry

The Graduate Certificate in Data Science for the Chemical Industries was designed to provide skills to working professionals, via a fully online and asynchronous format. The certificate may also be earned by undergraduate and graduate students at Georgia Tech. The certificate consists of four courses. The two core courses are Data Analytics for Chemical Engineers and Data Driven Process Systems Engineering, which focus on providing basic data analytics skills with examples that are relevant to chemists and chemical engineers. Students also select two electives from a wide range of online offerings at Georgia Tech, allowing them to explore more fundamental or applied aspects of data science.

Ionic Liquid Assessment as Suitable Solvent for Biogas Upgrading Technology Based on the Process System Engineering Perspective

AbstractBiogas requires specific processing in terms of upgradation to remove acid gas contents, making it a profitable fuel with higher energy content. This is conventionally attained through physical or chemical absorption due to the higher selectivity towards CO2 and H2S. The conventional processing technology impacts the process with higher energy content for solvent regeneration, solvent loss causing a threat to the environment with its toxicity, and damaging the equipment by corrosion. In this view, ionic liquids (ILs) emerged as potential candidates providing a favorable facet in terms of both processing and ecological aspects. Hence, herein the potential of IL and deep eutectic solvent (DES) in comparison to the conventional solvents and technologies used for biogas upgrading based on process system engineering perspective that showcases techno‐economic, energy‐economic, and environmental aspects and opportunities that may lead towards establishing sustainable and effective processing of biogas is shown and a comprehensive review on the opportunities, prospects, and challenges to make IL and DES as future solvent for biogas upgrading on the commercial scale is provided.

MeerKAT systems engineering: tailoring the process for value and efficiency

Systems engineering (SE) processes applied on projects are often compliance driven with a focus on completeness, rather than value and efficiency. Most projects can benefit by applying better SE process tailoring. We illustrate how the SE process was tailored for the MeerKAT project by following broadly two strategies: customizing the process for the unique properties of the project and optimizing the process by identifying the high value process elements upfront and focusing the SE effort on these high value activities.

Twenty-Four Years of PRES Conferences: Recent Past, Present and Future-Process Integration Towards Sustainability

This paper reviews the Process Integration (PI) development related to the recent Conferences on Process Integration for Energy Saving and Pollution Reduction (PRES conferences) and makes suggestions for the future growth of PI branching out in the future. The conference history is now close to a quarter of the century–from 1998 to 2021, and has been flourishing despite the difficult COVID-19 period. The paper overviews the progresses in Process Integration with Pinch Analysis, heat exchangers and Process Integration, extensions of Process Integration for wider process system engineering, integration of renewable energy sources, Circular Economy, extended environmental footprints, extended water-energy nexus contribution to environmental assessment, COVID-19 pandemics environmental consequences, and ecosystem remediation and waste stream clean-up. Considerable progress in Process Integration has also been achieved thanks to PRES conferences. This overview is an attempt to demonstrate the contribution delivered and make suggestions for the future growth of the PI branching out during the next years. It has become apparent that further improvements of the PI technologies are necessary and possible for achieving sufficient reductions of resource demands and pollution so that available renewables and end-of-pipe cleaning can serve them, minimising the environmental impacts. The key methodology developments enabling this are multi-constraint Pinch Analysis and the joint use of several PI methods for delivering comprehensive macro-analyses.

A forest-fire model for technology risk transfer

Based on the transmission characteristics of networks and the systematization of technical risks in national major science and technology projects, the risk transmission mechanism of national major science and technology projects is deeply discussed herein. Firstly, the system of systems (SoS) engineering process model of national major science and technology projects is constructed, including two levels and three stages. Secondly, the hierarchical structure of national major science and technology projects is analyzed, and the risks are divided into different levels, such as SoS, system, subsystem, equipment, module, and components. Finally, we describe the risk transfer mechanism using the forest-fire model and outline a risk control strategy. The results show that the findings are helpful for recognizing the essence and transmission mechanism of technical risks of national major science and technology projects and for reducing the risk from the source. The research results can be applied to project management in the transportation field.

SyPSE: A Symbolic Computation Toolbox for Process Systems Engineering Part I─Architecture and Algorithm Development

The main technical approaches to solving nonlinear systems are based on numerical computation in the field of process systems engineering (PSE). However, the convergence and reliability of numerica...

SyPSE: A Symbolic Computation Toolbox for Process Systems Engineering Part II─Design for PSE Applications

Process simulation, optimization, and flexibility analysis have received considerable attention in the field of Process Systems Engineering (PSE). In this work, a unified solution strategy is propo...

Development methodologies for ontology‐based knowledge management systems: A review

AbstractKnowledge management systems (KMS) are computer‐based systems highly valued in business organizations because they support knowledge management (KM) processes. Most KMS have been developed using non‐intelligent computer technology—that is, DMS, CMS, DBMS, and CIS—, and thus, they cannot provide advanced capabilities. Consequently, enhanced KMS using intelligent technologies of ontologies with inference engines—called ontology‐based knowledge management systems (OKMS)—have been proposed in the last three decades. Nowadays, however, the implementation of OKMS in real‐world settings is still scarce. Lack of comprehensive and systematic development methodologies including Project Management and Technical Systems Engineering processes—as the Systems and Software Systems Engineering standards propose—have been suggested as a factor that inhibits OKMS implementations. In this study, we review the OKMS literature (1990–2021 period)—from six seminal studies located using a research search engine—to assess OKMS development methodologies that can be considered comprehensive and systematic. Five methodologies were identified and assessed using an evaluation subset from the ISO/IEC/IEEE 15288:2015 Systems and Software Engineering standard. Two of them—CommonKADS and NeON—were found with a high comprehensive and systematic level and both are suggested for organizations interested in OKMS implementations, but none of them qualified as agile, which is a current development approach for systems and software systems. Hence, further empirical research toward the realization of comprehensive and systematic OKMSs development methodologies, including agile versions, is suggested for fostering the implementation of OKMS in real‐world settings.

A systemic framework for addressing cybersecurity in construction

Today, the built environment is designed, built, and managed using digital technology, making it increasingly exposed to cyber security risks. Cybersecurity is a general topic, and the construction sector has been borrowing general solutions and frameworks. However, the construction industry is specific and needs a specialized framework that would assist in understanding and managing cybersecurity. We have studied general cybersecurity frameworks, cybersecurity standards, research literature, and first principles of systems theory and process engineering. Drawing from that, we developed an original framework that identifies three kinds of wrongful activities: stealing, lying, and harming. It identifies four elements that can be affected by wrongful activities: information asset, material asset, person, and system. It defines cybersecurity as the absence of the three wrongs across the four kinds of elements. The framework is construction-specific, and as such, a useful tool for senior management to understand security problems and organize security processes. It can lead to better standardization and also helps the researchers to structure future work on the topic. The latter should be concentrated in areas where construction was found to be different: the dynamic and overlapping process and organizational boundaries in the design stage, the exposed shared design information, and the vulnerability of control information of the built environment, particularly in critical infrastructures.

Proactive Human Error Reduction Using the Systems Engineering Process

Abstract Many existing simple systems are incapable of meeting current demand and are quickly becoming obsolete, indicating that more challenging systems and designs will exist in the future. If new technologies are not implemented correctly, human error in operation can quickly manifest. The pattern of human performance degradation when novel technologies are introduced has been found in a wide range of endeavors. For example, the Three Mile Island nuclear accident was a consequence of unanticipated interaction of multiple failures in a system of immense complexity in addition to inadequate training and human factors, such as human–computer interaction design oversight relating to ambiguous control room indicators. To combat the negative effects, advancing technologies may have on plant operations; this study discusses several concepts: operator involvement in the systems engineering process; human performance integration with system operational requirements and system testing, evaluation, and validation; and procedures and training development in the systems engineering process. The isolation and bolstering of human performance improvement within the systems engineering process pose a novel approach to moderating human error associated with incorporating advanced technology in nuclear facilities.

Challenges in Optimization and Control of Biobased Process Systems: An Industrial-Academic Perspective

Biobased slurry processes and large-scale continuous chemical production share many similarities. These concern not only process technologies and equipment but also staffing (positions/educations) and plant operations, including methods and technologies for planning, scheduling, and control. Process Systems Engineering (PSE) approaches have been applied successfully in large-scale chemical production to optimize processes of high complexity. By replacing rules-of-thumb and oversimplified calculations with rigorous quantification and automation, PSE increases the profitability of a wide range of processes. Such improvement potential also exists in the bioindustry, which traditionally comprises many small-scale and batch plants deployed in food or pharmaceutical production. The article elucidates the most important operational challenges of such processes. It brings together academic research and industrial perspectives by contrasting a careful revision of literature with a survey of personnel working in industrial biobased production settings in Denmark. This analysis allows showing the existence of a gap between academic research focus and industrial need, for instance, concerning production processes with humans-in-the-loop. Furthermore, differences between chemical and biobased processes are pointed out, highlighting some limitations of applying PSE to biobased processes. A deeper understanding of these limitations is fundamental to assessing risks when identifying process improvement potential. Finally, the article suggests a possible roadmap for the development of frameworks for the optimization of industrial biobased processes based on existing works in chemical processing.

9th Asian Symposium on Process Systems Engineering

9th Asian Symposium on Process Systems Engineering

Knowledge expression, numerical modeling and optimization application of ethylene thermal cracking: From the perspective of intelligent manufacturing

Applications of process systems engineering (PSE) in plants and enterprises are boosting industrial reform from automation to digitization and intelligence. For ethylene thermal cracking, knowledge expression, numerical modeling and intelligent optimization are key steps for intelligent manufacturing. This paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking; introduces the frameworks, methods and algorithms that have been proposed over the past 10 years and discusses the advantages, limitations and applications in industrial practice. An entire set of molecular-level modeling approaches from feedstocks to products, including feedstock molecular reconstruction, reaction-network auto-generation and cracking unit simulation are described. Multi-level control and optimization methods are exhibited, including at the operational, cycle, plant and enterprise level. Relevant software packages are introduced. Finally, an outlook in terms of future directions is presented.

High performance protonic ceramic fuel cell systems for distributed power generation

The technology landscape around distributed generation continues to evolve in response to increasing demand for high-efficiency, low-emission, low-cost power generation. While emerging distributed power technologies, such as solid oxide fuel cells (SOFCs), continue to advance, they still face challenges due to their high capital costs, and shorter lifetimes that typically arise from electrochemical stack performance degradation at high operating temperatures (>750 °C). Recent advancements in protonic ceramic fuel cells (PCFCs) offer the potential to mitigate drawbacks of their higher temperature SOFC counterparts by enabling lower operating temperatures (550 °C–600 °C) with acceptable power densities. The present work leverages the recent progress in protonic ceramic cell and stack technology development to generate viable system configurations and evaluate the energetic performance potential of PCFC-based systems for stationary power generation. Process system engineering of two water-neutral system concepts, which provide 25 kW of electric power and process hot water, are presented and evaluated through sensitivity studies. Stack design parameters are altered and used to gauge the effect on system performance characteristics, including fuel cell stack and balance-of-plant sizing requirements, and electric and cogeneration efficiencies. The study finds that the potentially high per-pass fuel utilization capability of PCFC stacks could enable unprecedented electric efficiencies approaching 70% without hybridization with other prime movers.

Screening biorefinery pathways to biodiesel, green-diesel and propylene-glycol: A hierarchical sustainability assessment of process

Plant design implies the best choice among a set of feedstock-to-product process pathways. Multiple sustainability performance indicators can blur the decision, and existing sustainability assessment methods usually focus only on environmental life-cycle performance and corporate metrics or solely on the gate-to-gate process. It is relevant to incorporate integrated system analysis to address sustainability comprehensively. To this end, the Sustainable Process Systems Engineering (S-PSE) method was previously introduced to select the most sustainable feedstock-process-product configuration via four-dimensional indicators (environment, efficiency, health-&-safety, and economic), and then pinpoint the sustainability hotspots of the best design to unveil possible improvements. This work expands S-PSE by adding new features: (i) cradle-to-gate environmental assessment; (ii) composition of flowsheets; (iii) new indicators; (iv) statistical screening of indicators; and (v) 2030 Agenda compliance. A biorefinery case-study demonstrates S-PSE: to select the best pathway from soybean-oil, palm-oil, and microalgae-oil to biodiesel, green-diesel, and propylene-glycol. Firstly, statistical screening reduces the indicator set by 62%. Results evince all routes from microalgae-oil as economically unfeasible due to oil cost, despite superior environmental performance. S-PSE evinces palm-oil-to-biodiesel as the most sustainable due to lower cradle-to-gate emissions and manufacturing cost, with sustainability hotspots associated to hazardous methanol input and energy-intensive distillations. 2030 Agenda analysis also outlines palm-oil-to-biodiesel as best for 5 out of 10 Sustainable Development Goals linked to the reduced indicator set.

Selected papers from the 1st Brazilian Congress on Process Systems Engineering

Selected papers from the 1st Brazilian Congress on Process Systems Engineering

Importing participatory practices of the socio-environmental systems community to the process system engineering community: An application to supply chain

The Process System Engineering community has an extensive knowledge and skills on supply chain design: from the time dimension (production and flow planning) to the space dimension (geographic position of facilities). Nevertheless, supply chains are also social networks where multiple stakeholders have to collaborate while they have different, and sometimes, diverging objectives. For this reason, having a more realistic model representing collaboration between the various stakeholders involved is necessary and new methods that facilitate the development of a shared representation of the system must be introduced. We propose to import a participatory method, PARDI (Problematic, Actors, Resources, Dynamics and Interactions), from the Socio-Environmental System community to the practices of the Process System Engineering community. Based on this method, we develop a participatory process in order to collect the necessary knowledge on the supply chain and its context. Following this participatory process, we then develop an Agent-Based Model as a simulation and decision making tool to support collective scenario analyses and collectively draw solutions with stakeholders. Our participatory modeling approach necessarily imposes a multi stakeholders vision (within the modeling but also in the result analyses) and therefore the search for a modeling consensus. Thus, it brings a better inclusion of social aspects in problem solving which are usually poorly considered leading to implementation failure sometimes. By comparing our approach with the classic one of the Process Systems Engineering community, we highlight the strengths and weaknesses of both and how complementary they can be. A case study on the already existing supply chain of the chestnut wood in Cévennes area (France) illustrates the capabilities of our participatory methodology. It focuses on the socio-economic model design of the first two steps (forestry activities to harvest) in the supply chain as the latter is locked because of economic and social organisation issues. The objective is to find the best action levers to unlock the resistance that forest plot owners have to remove declining wood from their land.

Optimal control in chemical engineering: Past, present and future

Roger W.H. Sargent (1926–2018) was an unprecedented pioneer who foresaw the role that mathematical and computational tools would have in chemical engineering. His visionary work created the multidisciplinary field of Process Systems Engineering (PSE), a field that acts as a central hub influencing all subfields of chemical engineering. His particular interest in optimal control applied to industrial processes led him to develop numerical techniques to solve large-scale optimal control problems. In this work, a brief overview of the theory of optimal control is offered, spanning from its roots in calculus of variations to Pontryagin’s maximum principle and some of its extensions. Furthermore, important contributions made by Sargent and his students are presented. Selected applications currently found in literature are presented as well–ranging from classical chemical engineering systems to bioprocesses. Some future perspectives of the field are also presented in the concluding section.