Challenges in process optimization for new feedstocks and energy sources

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

Modern advancements in continuous-flow aided kinetic analysis

Although kinetic analysis has traditionally been conducted in a batch vessel, continuous-flow aided kinetic analysis continues to swell in popularity.

Data mining and knowledge discovery in databases for urban solid waste management: A scientific literature review

The processes related to solid waste management (SWM) are being revised as new technologies emerge and are applied in the area to achieve greater environmental, social and economic sustainability for society. To achieve our goal, two robust review protocols (Population, Intervention, Comparison, Outcome, and Context (PICOC) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)) were used to systematically analyze 62 documents extracted from the Web of Science database to identify the main techniques and tools for Knowledge Discovery in Databases (KDD) and Data Mining (DM) as applied to SWM and explore the technological potential to optimize the stages of collecting and transporting waste. Moreover, it was possible to analyze the main challenges and opportunities of KDD and DM for SWM. The results show that the most used tools for SWM are MATLAB (29.7%) and GIS (13.5%), whereas the most used techniques are Artificial Neural Networks (35.8%), Linear Regression (16.0%) and Support Vector Machine (12.3%). In addition, 15.3% of the studies were conducted with data from China, 11.1% from India and 9.7% of the studies analyzed and compared data from several other countries. Furthermore, the research showed that the main challenges in the field of study are related to the collection and treatment of data, whereas the opportunities appear to be linked mainly to the impact on the pillars of sustainable development. Thus, this study portrays important issues associated with the use of KDD and DM for optimal SWM and has the potential to assist and direct researchers and field professionals in future studies.

Development of a Dynamic Modeling Approach to Simulate a Segmented Distillation Column for Flexible Operation

The need for flexible process equipment has increased over the past decade in the chemical industry. However, process equipment such as distillation columns have limitations that significantly restrict flexible operation. We investigate a segmented tray column designed to allow flexible operation. The design consists of radial trays connected at the downcomer of each tray. Each segment can be operated separately, but depending on the capacity of the feed stream, additional segments can be activated or deactivated. The connection between the trays aims to transfer liquid from one stationary segment to the adjacent inactive segment, thereby reducing the time required for the start-up process. In a case study on the separation of methanol and water, we perform dynamic simulations to assess the reduction in the start-up time of inactive segments. The results confirm the advantages over standard tray designs. The segmented distillation column is a step towards improving the flexibility of separation operations.

Sustainable Biological Ammonia Production towards a Carbon-Free Society

A sustainable society was proposed more than 50 years ago. However, it is yet to be realised. For example, the production of ammonia, an important chemical widely used in the agriculture, steel, chemical, textile, and pharmaceutical industries, still depends on fossil fuels. Recently, biological approaches to achieve sustainable ammonia production have been gaining attention. Moreover, unlike chemical methods, biological approaches have a lesser environmental impact because ammonia can be produced under mild conditions of normal temperature and pressure. Therefore, in previous studies, nitrogen fixation by nitrogenase, including enzymatic ammonia production using food waste, has been attempted. Additionally, the production of crops using nitrogen-fixing bacteria has been implemented in the industry as one of the most promising approaches to achieving a sustainable ammonia economy. Thus, in this review, we described previous studies on biological ammonia production and showed the prospects for realising a sustainable society.

Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method

The dynamic optimization of promising forced periodic processes has always been limited by time-consuming and expensive numerical calculations. The Nonlinear Frequency Response (NFR) method removes these limitations by providing excellent estimates of any process performance criteria of interest. Recently, the NFR method evolved to the computer-aided NFR method (cNFR) through a user-friendly software application for the automatic derivation of the functions necessary to estimate process improvement. By combining the cNFR method with standard multi-objective optimization (MOO) techniques, we developed a unique cNFR–MOO methodology for the optimization of periodic operations in the frequency domain. Since the objective functions are defined with entirely algebraic expressions, the dynamic optimization of forced periodic operations is extraordinarily fast. All optimization parameters, i.e., the steady-state point and the forcing parameters (frequency, amplitudes, and phase difference), are determined rapidly in one step. This gives the ability to find an optimal periodic operation around a sub-optimal steady-state point. The cNFR–MOO methodology was applied to two examples and is shown as an efficient and powerful tool for finding the best forced periodic operation. In both examples, the cNFR–MOO methodology gave conditions that could greatly enhance a process that is normally operated in a steady state.

Developments, Trends, and Challenges in Optimization of Ship Energy Systems

A review of developments, trends, and challenges in synthesis, design, and operation optimization of ship energy systems is presented in this article. For better understanding of the context of this review, pertinent terms are defined, including the three levels of optimization: synthesis, design, and operation (SDO). The static and dynamic optimization problems are stated mathematically in single- and multiobjective form. The need for intertemporal optimization is highlighted. The developments in ship energy systems optimization throughout the years is clearly presented by means of journal articles, giving the main characteristics of each article. After the review of what has been done up to now, ideas for future work are given. Further research needs for optimization of ship energy systems are mentioned: further development of methodology for synthesis optimization and SDO optimization, including transients, uncertainty, reliability, and maintenance scheduling. Hints are given for expansion of the system border in order to include aspects belonging to other disciplines, such as electrical and control engineering as well as hull and propulsor optimization, thus, opening a way to the holistic ship optimization.