scholarly journals A Study on Performance of Different Open Loop PID Tunning Technique for a Liquid Flow Process

2016 ◽  
Vol 6 (2) ◽  
pp. 13-22
Author(s):  
Pijush Dutta ◽  
Asok Kumar
Keyword(s):  
Liquid Flow ◽  
Open Loop ◽  
Flow Process

Simulation of Nanoimprint Based on PSQ-L Polymer

2014 ◽  
Vol 609-610 ◽  
pp. 1498-1502
Author(s):  
Xin Guo ◽  
Ming Zhu Sun ◽  
Ming Shan Zhao ◽  
Xin Zhao
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Layer Thickness ◽  
Liquid Flow ◽  
Static Model ◽  
Simulation System ◽  
Flow Process ◽  
Static State ◽  
Simulation Process ◽  
Waveguide Fabrication

A method of simulating nanoimprint process dynamically is proposed and a software program has been made to complete the simulation process automatically. Finite element method (FEM) is used to reveal mechanism of how the liquid flow in the imprint process by every static state. By means of static model iteration,we make a software to simulate the flow process dynamically and it can be used to forecast the result of the nanoimprint. The simulation system is used to predict residual layer thickness in the waveguide fabrication process.

scholarly journals Continuous gas/liquid–liquid/liquid flow synthesis of 4-fluoropyrazole derivatives by selective direct fluorination

2011 ◽  
Vol 7 ◽  
pp. 1048-1054 ◽  
Author(s):  
Jessica R Breen ◽  
Graham Sandford ◽  
Dmitrii S Yufit ◽  
Judith A K Howard ◽  
Jonathan Fray ◽  
...  
Keyword(s):  
Liquid Flow ◽  
Flow Process ◽  
Flow Synthesis ◽  
Direct Fluorination

4-Fluoropyrazole systems may be prepared by a single, sequential telescoped two-step continuous gas/liquid–liquid/liquid flow process from diketone, fluorine gas and hydrazine starting materials.

scholarly journals Design of Flow Control System with A Kickback Flow as A Manipulated Variable

Eksergi ◽  
2017 ◽  
Vol 14 (2) ◽  
pp. 23
Author(s):  
Yulius Deddy Hermawan
Keyword(s):  
Steady State ◽  
Flow Control ◽  
Liquid Flow ◽  
Stability Criterion ◽  
Closed Loop ◽  
Open Loop ◽  
Loop Model ◽  
Point Change ◽  
Controller Gain ◽  
Control Configuration

The open loop experiment of water flow dynamic in pipe has been done in laboratory. Pump was used to flow water in pipe. Part of liquid from discard of pump was recycled back to the suction of pump (kickback) and adjusted to control the liquid flow to the next process. The open loop laboratory experiment produced the steady state parameters; they were discard flowrate =16.6 [L/min], kickback flowrate =5.8 [L/min], and liquid flowrate to the next process =10.8 [L/min]. These steady state parameters were then used as the initial value for closed loop simulation with computer programming. This study has proposed the liquid flow control configuration by manipulating the kickback flow. Proportional Integral (PI) was proposed to control the flow and Routh-Hurwitz (RH) stability criterion was chosen to predict the range of the controller gain (Kc) that gives stable response. The closed loop model was solved analytically with Laplace method for both servo and regulatory problems. The set point change of flow and disturbance were made based on step function. The scilab software was used to do closed loop simulation. Based on RH stability criterion, the controller gain should be negative in order to give stable response. The closed loop simulation showed that by using controller gain Kc=–0.5 and integral time constant tI=0.3 [min], stable and fast response with Integral Absolute Error (IAE) near to zero (0,0022) could be achieved.

scholarly journals Modelling of Liquid Flow control system Using Optimized Genetic Algorithm

2020 ◽  
Vol 8 (2) ◽  
pp. 565-582
Author(s):  
Pijush Dutta ◽  
Asok Kumar
Keyword(s):  
Genetic Algorithm ◽  
Liquid Flow ◽  
Linear Models ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Liquid Density ◽  
Flow Process ◽  
Computational Optimization ◽  
Non Linear ◽  
Selection Of

Estimation of a highly accurate model for  liquid flow process industry and control of the liquid flow rate from experimental data is an important task for engineers due to its non linear characteristics. Efficient optimization techniques are essential to accomplish this task.In most of the process control industry flowrate  depends upon a multiple number of parameters like sensor output,pipe diameter, liquid conductivity ,liquid viscosity & liquid density etc.In traditional optimization technique its very time consuming for manually control the parameters to obtain the optimial flowrate from the process.Hence the alternative approach , computational optimization process is utilized by using the different computational intelligence technique.In this paper three different selection of Genetic Algorithm is proposed & tested against the present liquid flow process.The proposed algorithm is developed based on the mimic  genetic evolution of species that allow the consecutive generations in  population to adopt their environment.Equations for Response Surface Methodology (RSM) and Analysis of Variance (ANOVA) are being used as non-linear models and these models are optimized using the proposed different selection of Genetic optimization techniques. It can be observed that the among these three different selection of Genetic Algorithm ,Rank selected GA  is better than the other two selection (Tournament & Roulette wheel) in terms of the accuracy of final solutions, success rate, convergence speed, and stability.

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