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Approximate process models for batch reactors can be developed via a gray ☐ modeling technique known astendency modeling.
This work investigates how batch reactors can be optimized to increase the yield of a desired product coupling two appealing techniques for process control and optimization: the nonlinear model predictive control (NMPC) and the dynamic real-time optimization (D-RTO).
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Temperature control of processes that involve the heating and cooling of a closed batch reactor can be a real problem for conventional Proportional-Integral-Derivative based loop controllers.
Temperature control of processes that involve the heating and cooling of a closed batch reactor can be a real problem for conventional proportional-integral-derivative (PID) based loop controllers.
The Haldane kinetics for 2-CP utilization in the batch reactor can be described as (Pirbazari et al. 1996) frac{{{text{d}}S}}{{{text{d}}t}} = - frac{mu X}{Y}, (18 where X is the biomass concentration (Ms L−3).
Cumulative molecular masses from a semi-batch reactor can be higher than those from a batch reactor when a relatively reactive initiator is used.
The reactor can be operated in batch or continuous mode.
For a comparison of batch- and continuous proteolysis, the residence time in the continuous reactor can be directly compared with the same batch processing time.
Fed-batch reactors can also be used as differential reactors.
With regard to the use of bioreactors for nitrogen removal, sequencing batch reactors (SBRs) can be used to achieve nitrification under aerobic conditions and denitrification under anoxic conditions.
The diazo coupling reactions of Part I have sufficiently well-defined properties that the models of Part II and [2] for CSTR and batch reactor respectively can be evaluated.
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