Multi-scale approaches for gas-to-liquids process intensification: CFD modeling, process synthesis, and global optimization

Onel, Onur; Niziolek, Alexander M.; Butcher, Holly; Wilhite, Benjamin A.; Floudas, Christodoulos A.

doi:10.1016/j.compchemeng.2017.01.016

Cited by 27 publications

(11 citation statements)

References 89 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For 10 bbl/d (1 bbl = 0.158987 m 3 ) modular microrefinery GtL units to convert wasted natural gas to Fischer‐Tropsch fuels, the investment for 100 units approaches the cost of a single 1000 bbl/d unit, which is 1 million US dollars. [ 102 ] Onel et al [ 108 ] also proposed intensified CH 4 steam methane reforming. They adopted a microchannel reactor and applied a multi‐scale approach that included CFD modelling.…”

Section: Process Intensification and Catalysismentioning

confidence: 99%

Process intensification connects scales and disciplines towards sustainability

Boffito

Rivas

2020

Can J Chem Eng

View full text Add to dashboard Cite

Process intensification (PI) has been established as a cluster of technologies able to produce more with less. While scientists around the globe advocate for new semantics that are increasingly tied to the notion of sustainability, what does the literature data say about PI? A Vosviewer bibliometric map of PI displays it as closely linked to the subjects of design, optimization, gas-to-liquid technologies, mass transfer, catalysis, and kinetics. We analyze the relationship between PI and these subjects while identifying misconceptions about the intensifying potential of some of them, as is the case for process optimization. We provide examples and summarize the recent technological trends for all these cases. Finally, we provide an outlook on the future of PI in which we identify elements that will be key to accelerate the adoption of PI technologies at the commercial scale.

show abstract

Section: Process Intensification and Catalysismentioning

confidence: 99%

Process intensification connects scales and disciplines towards sustainability

Boffito

Rivas

2020

Can J Chem Eng

View full text Add to dashboard Cite

show abstract

“…Extended Kalman Filter (EKF) was used as a BB model. Onel et al [41] used a serial GB model for prediction of reactor output composition of steam methane reforming (SMR) microchannel reactor. The non-linear fitting model was used as a BB model.…”

Section: Oil and Gas Processingmentioning

confidence: 99%

“…Application Category Process GB Type Target BB Type [55][56][57] Power plant estimation and control "thermal storage tank", "feed water heater/ heat exchanger" serial "temperature profile and the usable energy stored", "anomaly identification", "irradiation angle" "simultaneous perturbation stochastic approximation", "ANN", "fast recursive algorithm" [40][41][42][43][44] Oil and gas processing "estimation and control", "estimation", "estimation and optimization"…”

Section: Paper Industrymentioning

confidence: 99%

Gray-box Soft Sensors in Process Industry: Current Practice, and Future Prospects in Era of Big Data

et al. 2020

View full text Add to dashboard Cite

Virtual sensors, or soft sensors, have greatly contributed to the evolution of the sensing systems in industry. The soft sensors are process models having three fundamental categories, namely white-box (WB), black-box (BB) and gray-box (GB) models. WB models are based on process knowledge while the BB models are developed using data collected from the process. The GB models integrate the WB and BB models for addressing the concerns, i.e., accuracy and intuitiveness, of industrial operators. In this work, various design aspects of the GB models are discussed followed by their application in the process industry. In addition, the changes in the data-driven part of the GB models in the context of enormous amount of process data collected in Industry 4.0 are elaborated.

show abstract

“…Other topics not considered in this perspective paper but could be of interest to the reader are, intensified equipment selection, CFD modeling integrated with process synthesis and optimization, technoeconomic analysis of a specific PI alternative, and optimal reaction concepts for plantwide PI …”

Section: Perspectivesmentioning

confidence: 99%