A mathematical modeling approach was used as a tool for performance prediction and process design with implication to process upscaling.
The motivation behind the proposed approach is to combine the complementary predictive powers of multiple models in order to improve the performance of the prediction process.
The proper sizing of TES systems, which, in this application, is constituted by a steam accumulator vessel installed between the steam generator and the consumer, cannot be based on the sole initial and final state conditions of the steam storage, since a performance prediction of the process time-evolution is also required.
The specific objectives are: (1) Develop a detailed mathematical model of a zeolite membrane separation process for accurate performance prediction under industrial conditions, and (2) Perform conceptual process design and techno-economic evaluation of the overall process for an application specific flowsheet.
Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability.
Figure 6 can properly show the performance of BPNN in the prediction process.
Mathematical models are formulated for the working process and performance prediction.
In a literature review performed on injectivity issues in the WAG process, it was mentioned that use of base relative permeability data for CO2 oil systems without proper adjustments for IFT, oil swelling effect, etc., could lead to significant errors in performance prediction of CO2-based WAG process (Rogers and Grigg 2001).
The model developed herein will constitute fundamental for performance prediction and design of SWRO processes.
This paper describes the second phase involving process modeling for performance prediction, simulation, and design with upscaling implications.
