Tower optimization pressure

Extraction of potable water from saline waters by means of immiscible solvents has been shown to be theoretically possible, experimentally feasible, and economically attractive. Data presented show the process to be especially adaptable to the conversion of feed water in the range of 5000 to 10,000 p.p.m. It is adaptable to use of low-quality heat such as hot water from cooling towers or low pressure waste steam. By use of mixed solvent systems, the process can be optimized to take advantage of seasonal changes in temperature and sources of cold feed water and low-level heat sources. The process, in general, is somewhat more economical when a cold source of feed water is available. 

The absorber is essentially the same as that described for the single-pressure process. Tower size and specific design details can be optimized to the particular process conditions and may vary... 

Typically, the air-stripper manufacturer will supply liquid flow ranges acceptable for a particular tower. Selecting an air stripper for which the design flow is at the lower end of the tower s rated capacity will produce high contaminant removal rates, but may not optimize power requirements. For large-scale systems where significant operational costs may be incurred by overdesigning the system, the use of pressure-drop curves and calculations such as Eqs. (1)-(13) are required. 

Similar kinds of constraints involve the reflux ratio in distillation, which must exceed the minimum value for the required separation. If the distillation tower pressure is adjusted, the minimum reflux ratio will change and the actual ratio must be maintained above the minimum value. Even when optimization is not performed, the decision variable values must be selected to avoid violating the inequality constraints. In some cases, the violations can be detected when examining the simulation results. In other cases, the imit subroutines are unable to solve the equations as, for example, when the reflux ratio is adjusted to a value below the minimum value for a specified split of the key components. 

After these moves, pressure decreased and the heater temperature was increased another 5°F. Finally, the vacuum tower bottoms stripping steam rate, heater outlet temperature, and heater pass flow were optimized to obtain maximum gas oil production. These last items usually take some trial and error. 

For a typical flowsheet, such as the DME (dimethyl ether) PFD in Figure B.1.1 i Appendix B), there are many decision variables. The temperature and pressure of each unit can be varied. The size of each piece of equipment involves decision variables (usually several per unit). The reflux in tower T-201 and the purity of the distillate fromT-202 are decision variables. There are many more. Clearly, the simultaneous optimization of all of these decision variables is a difficult problem However, some subproblems are relatively easy. If Stream 4 (the exit from the methanol preheater) must be at 154°C, for example, the choice of which heat source to use (Ips, mps, or hps) is easy. There is only a sin e decision variable, there are only three discrete choices, and the choice has no direct impact on the rest of the process. The problem becomes more difficult if the temperature of Stream 4 is not constrained. 

Solvent oil is a by-product of the platinum reforming plant of petrochemical factories. The target of optimization is to increase the recovery of solvent oil. There are six affecting factors for the recoveiy of solvent oil reflux rate (X]), flow rate of the first side line (X2), pressure at tower top (X3), temperature of reflux (X4), temperature at solvent oil tower bottom (X5), temperature of the 35th-tower plate of solvent oil tower (Xe). Some data from the industrial records are listed in Table 14.2. 

---