The Computational Methods in Chemical Engineering specialty section publishes major advances in all aspects of mathematical and computational modeling related to chemical engineering challenges.
Articles that focus on computational models/methods or report on the applications of new computational methods to solve important chemical engineering problems across scales are welcome. This can range from molecular and product systems, unit operations and manufacturing plants, to infrastructure and ecosystems. Only sufficiently innovative reported models, methods or applications will be considered.
Areas covered by the specialty section include but are not limited to:
· Process Modelling: Principles of mathematical modelling in chemical engineering such as problem formulation, solution, discrete systems, methods of solution, understanding system behavior, or process simulation software.
· Product and Process Design:
- Analysis of design alternatives.
- Structure of process design systems, degrees of freedom, information flow.
- Computer-aided process and plant design programs, physical properties, specifications, recycle convergence, superstructure optimization, process economics, integrated product, and process design.
- Design of energy processes, including biorefinery, CO2 capture and utilization, natural gas processing, energy-water-food-climate nexus, and ecosystems design.
· Process and Energy Integration: heat integration, mass integration, work integration, pinch analysis, heat exchanger network, water network, hydrogen network, steam systems, heat recovery, and process and energy efficiency.
· Process Control: dynamic modelling of processes, dynamic estimation, feedback control, applications of standard controller features, stability, controller tuning, plant-wide control, cascade control, model predictive control, robust control, stochastic control, and integrated control, design and operations.
· Process Operations: scheduling of batch and continuous processes, production planning, dynamic optimization, real-time optimization, supply chain and logistics optimization, global optimization, optimization under uncertainty, surrogate-based optimization, smart manufacturing, process safety, and hazard identification.
· Process Data Analytics and Information Management: process monitoring, process fault diagnosis, root cause analysis, prognostics and preventive maintenance, industrial internet of things, cybersecurity in chemical industry, machine learning and deep learning for chemical engineering, and data science for molecular systems.
· Computational fluid dynamics and multi-physics simulation for chemical engineering related applications.
· Computational modeling and simulation of atomic, molecular and material systems.
Indexed in: coming soon
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