Multi-objective Optimization of a Spouted Bed

Performance of the gas-solid spouted bed benefits from solid's uniformity structure (UI) with lower pressure drop (PD). Spouted bed system needs to be optimized to achieve the maximum performance.Therefore; the focus of this work is to maximize the UI and to minimize the PD along the bed. Three selected decision variables are affecting these objectives that are; gas' velocity, particle's density and particle's diameter. Steady-state measurements were carried out to study the effect of the decision variables on UI and PD in the 60° conical shape spout-air bed with the diameter of 3 inches and height of 36 inches. Radial concentration of particles (glass and steel beads) at various elevations of the bed under different flow patterns were measured using sophisticated optical probes. High- accuracy pressure transducer monitored the pressure drop across the bed. Solid's density has found the effective variable on both UI and PD.  Multi-objective   genetic algorithm (GA) has found the best stochastic technique for highly nonlinear hybrid spouted system. The reliability of optimization search can be enhanced by adaptation of the GA's operators. Optimum results have 14 sets of new operating conditions would improve the efficiency of the bed. Maximum UI obtained with high-density steel beads, and minimum PD could obtain with low-density glass beads at low gas' velocity. It was observed that the gas' velocity was the sensitive variable for UI and PD changing. Keywords: Genetic algorithm; Optimization; Pressure drop; Spouted bed; Uniformity index

Improving the Performance of a Spouted Bed via Uniformity Index Using Stochastic Optimization

This work focuses on maximizing the solid's uniformity structure (UI) that could enhance the performance of the spouted bed. Furthermore, UI is affected by operating conditions, which are considered as decision variables of the optimization process. The selected decision variables are; gas velocity, solid's density and solid's diameter. Steady-state measurements were carried out in the 60° conical shape spout-air bed. Concentration of particles (glass and steel beads) at various elevations of the bed under different flow patterns were measured using sophisticated optical probes. Optimization technique is a powerful tool for selecting the best operating conditions could overcome the instability of the system and improves the uniformity of the particles across the bed. The stochastic global genetic algorithm has found the suitable search for the non-linear hybrid spouted bed. The optimal results indicate that maximum UI is 0.534 could be obtained with; gas velocity of 0.741 m/s, solid's diameter of 1.09 mm and solid's density of 6648.0 Kg/m3. Velocity of gas and diameter of solid particles were observed the sensitive variables with the uniformity index changing. Keywords: Genetic algorithm, Optimization, Spouted bed, Uniformity index

Simulation and Optimization of a Continuous Biochemical Reactor

The present work focused on the dynamic and optimization of a continuous biochemical reactor using the glucose as a substrate. Simulated model provides the development of the process and reducing the risk of experimental runs. The selected process variables are; dilution rate (D), feed substrate concentration (Si), pH and temperature (T).The  major effect of D was observed at Si below 20 g/L. pH and T are affecting within Si of 60 g/L.Si is the effective process variable on the dynamic characteristics of the reactor. Reasonable agreement has found when compared the simulated results with that obtained by the previous work .Optimization technique guides the decision maker to select the best operating conditions.Stochastic genetic algorithm has found suitable for the nonlinear reactor.Optimal results indicate that the maximum biomass concentration (X) is 80.57 g/L at Si of 197.56 g/L and low D of 0.1(1/hr).Si was the sensitive variable for changing of the objective X.   Keywords: Biochemical reactor; Dynamic model; Optimization; Simulation

Adaptive Genetic PH Control of a Wastewater Treatment Unit via LABView

This work focuses on study the dynamics and pH control of   a wastewater treatment unit contaminated with toxic metals; Cu, Cr and Fe. PH is the major key factor of the precipitation process. Sodium sulfide (Na2S) was selected, as a chemical additive to adjust the pH of water.LABview is the powerful tool to operate and control the experimental lab scale treatment unit. The predicted dynamic model of the pH process is first order lag system with dead time. The reliable tuning of control parameters could be obtained by the Internal Model Control (IMC) technique. PD scheme was undesirable control for the noisy mixed system. PI mode has found the best control strategy for the unsteady state pH process. Genetic algorithm (GA) is the suitable global stochastic technique for adaptation the controller's settings. PI genetic adaptive mode could improve the pH control of the wastewater. Keywords: Adaptive genetic; Control; Heavy metals; LABview; pH; Wastewater

Optimization of Pressure Drop in a Spouted Bed via Genetic Algorithm

Dropping of pressure drop (PD) across the spouted bed could reduce the dissipated pumping energy and improve stability and uniformity of solid particles. The selected decision variables are; gas velocity, solid's density and solid's diameter. Steady-state measurements were carried out in the 60° conical shape spout-air bed. Concentration of solid particles (glass and steel beads) at various elevations of the bed under different flow patterns were measured  by using sophisticated optical probes. Optimization technique helps the decision makers to select the best set of operating conditions. Stochastic genetic algorithm has found suitable for the non-linear hybrid spouted bed. Optimum results would provide the design and operation of the bed. It has been found that the low-density glass beads of high -particle diameter at low gas' velocity, could obtain minimum PD. Particle's density is the effective variable on PD. Velocity of gas and diameter of solid particle have found the sensitive decision variables with PD changing. The sensitivity of the variables could be increased at unlimited upper bounds. Keywords: Genetic algorithm; Optimization; Pressure drop; Spouted bed; Solid particle

On The Time Lag of A First-Order Process’s Sinusoidal Response

The time lag (TL) of a linear first-order process’s sinusoidal response has been analyzed in the article....Key words: Process dynamics; Frequency response; Time lag; Time constantDetailed information of the article can be found in the full text

On The Time Lag of A First-Order Process’s Sinusoidal Response

The time lag (TL) of a linear first-order process’s sinusoidal response has been analyzed for a process time constant....................

Optimization and Control of Acation Exchanger :1- Steady State Optimization

The effect of process variables on the recovery of hardness from water byacation exchanger was studied. At steady state the process could be represented bysecond order nonlinear emperical model. Although this model was less accurate thanthe dynamic model,the results show agreement when compared with the experimentaldata. The steady state optimization model was used to limit the operating conditions ofthe system. The static feed forward control could be used with the aid of on – linedigital computer