Research on Marine Fuel Boiler Drum Water Level Model and Dynamic Analysis

2014 ◽  
Vol 989-994 ◽  
pp. 1449-1452
Author(s):  
Miao Zhu
Keyword(s):  
Mathematical Model ◽  
Simple Model ◽  
Water Level ◽  
Model Simulation ◽  
Marine Fuel ◽  
Boiler Water ◽  
Modeling Process ◽  
Two Factors ◽  
Level Model ◽  
Boiler Drum

This article first mathematical model of boiler water level, and then in MATLAB/ SIMULINK environment, the model simulation, and thus the dynamic characteristics of the model for analysis. Many real boiler parameters and variables, complex, by simplifying the modeling process, ignores some factors and variables, a simple model can be obtained results almost true fit. Boiler water level of the model established in considering the effect of steam flow and water flow of two factors.

Traditional Versus New Technology Boiler Drum Water Level Instruments

2016 ◽  
Author(s):  
Zhelin Liu ◽  
John Michael Harris ◽  
Jichuan Liu ◽  
Dong Han ◽  
Lei Liu
Keyword(s):  
Water Level ◽  
New Technology ◽  
Large Error ◽  
Actual Situation ◽  
Boiler Water ◽  
Wide Margin ◽  
Design Change ◽  
Level Measurement ◽  
Boiler Drum ◽  
Constant Head

The art and science of boiler drum water level measurement has long been the source of questionable results. A low-tech examination of the boiler drum reveals where the drum level has been controlling — there is a water mark inside the drum. The problem is obvious; the mark in the drum and that in the control system do not agree. The level is off by a wide margin. This paper seeks to explain how poor assumptions are the source of the error. Then two design approaches are considered to eliminate the sources of error. Consider that boiler drum water is not saturated; feedwater entering from the economizer is below saturation. Also consider the constant head chamber. Typically, the reference leg is considered to be at ambient temperature, but it is really a gradient starting at near drum temperature. The effect of these two poor assumptions is a relatively large error such that the true level is different from indicated level. Once this situation is understood, it is possible to redesign instruments which take the actual situation into account. One such instrument is nearly the same as the original DP-type instrument, but the constant head chamber is located inside the drum. This design change deals with both errors. It eliminates the differences in temperature and density between the constant head leg and the water inside the drum. It also exposes the constant head leg to the exact same temperature as the boiler water, thus eliminating the need for complicated (and incorrect) formulae to compensate for the differences in density. A second design approach is to “steam jacket” an instrument located outside the drum, thus eliminating the differences in temperature and density. This is an appropriate way to deal with the Conductivity Probe and the Boiler Water gauge glass. By steam jacketing these instruments, we can make the water temperature between the indicator and the drum almost the same.

Recommended Configuration of Boiler Drum Water Level Control and Protection System

2016 ◽  
Author(s):  
Zhelin Liu ◽  
John Michael Harris ◽  
Jichuan Liu ◽  
Shengli Yu ◽  
Mingxin Zhou
Keyword(s):  
High Pressure ◽  
Control System ◽  
Water Level ◽  
Critical Level ◽  
Protection System ◽  
Level Control ◽  
Boiler Water ◽  
Protection Systems ◽  
Boiler Drum ◽  
Gauge Glass

For a high pressure boiler above 1,400 psi (9.7 MPa), the boiler drum level Control and Protection systems serve two distinct, but complementary functions. The Control system needs to control drum level. Protection is done for safety. If the drum level reaches a critical level, the Protection system shuts down the boiler to avoid damage. One must meet ASME Boiler Code requirements, get the job done correctly, and minimize the number of instruments required. By ASME Boiler Code, one must have at least one Boiler Water Gauge Glass. How many Control instruments are needed? If a single boiler drum water level instrument is used and this instrument suffers a failure, there is a problem. Even if two instruments are used and one fails, one does not know which to trust. Logic dictates that one requires a minimum of three Control instruments. Before discussing Protection, it is good to discuss the characteristics of the instruments available:

Design of Control of DC Motor

2014 ◽  
Vol 611 ◽  
pp. 325-331
Author(s):  
Ľubica Miková ◽  
Michal Kelemen ◽  
Vladislav Maxim ◽  
Jaromír Jezný
Keyword(s):  
Mathematical Model ◽  
Virtual Environment ◽  
Computer Technology ◽  
Current Practice ◽  
Scientific Literature ◽  
Model Simulation ◽  
Graphical Interface ◽  
Dc Motors ◽  
Matlab Program ◽  
Simulation Results

In current practice the use of mathematical models is substantially widespread, reason being the recent increase in development of programs for this purpose, with the option of model simulation in a virtual environment, proportional to the evolving computer technology. The article contains a mathematical model created using Matlab program. The simulation results are compared with scientific literature that addresses DC motors and evaluated. For simplicity, a graphical interface was created.

An enhanced composting process with bioaugmentation: Mathematical modelling and process optimization

2021 ◽  
pp. 0734242X2110337
Author(s):  
Tea Sokač ◽  
Anita Šalić ◽  
Dajana Kučić Grgić ◽  
Monika Šabić Runjavec ◽  
Marijana Vidaković ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Process Conditions ◽  
Air Flow Rate ◽  
Optimal Process ◽  
Composting Process ◽  
Different Types ◽  
Adiabatic Reactor ◽  
The Mathematical Model ◽  
Good Agreement

In this paper, two different types of biowaste composting processes were carried out – composting without and with bioaugmentation. All experiments were performed in an adiabatic reactor for 14 days. Composting enhanced with bioaugmentation was the better choice because the thermophilic phase was achieved earlier, making the composting time shorter. Additionally, a higher conversion of substrate (amount of substrate consumed) was also noticed in the process enhanced by bioaugmentation. A mathematical model was developed and process parameters were estimated in order to optimize the composting process. Based on good agreement between experimental data and the mathematical model simulation results, a three-level-four-factor Box-Behnken experimental design was employed to define the optimal process conditions for further studies. It was found that the air flow rate and the mass fraction of the substrate have the most significant effect on the composting process. An improvement of the composting process was achieved after altering the mentioned variables, resulting in shorter composting time and higher conversion of the substrate.

Real-Time Implementation for Tuning PID Controller Based on Advanced Optimization Techniques for Micro-Robotics System

2021 ◽  
Vol 10 (6) ◽  
pp. 161-173
Author(s):  
Ehab S. Ghith ◽  
◽  
Mohamed Sallam ◽  
Islam S. M. Khalil ◽  
Mohamed Serry ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
Model Simulation ◽  
Search Algorithm ◽  
Optimization Techniques ◽  
Control Technique ◽  
Flower Pollination Algorithm ◽  
Labview Software ◽  
Laboratory Setup ◽  
Sine Cosine Algorithm

The process of tuning the PID controller’s parameters is considered to be a difficult task. Several approaches were developed in the past known as conventional methods. One of these methods is the Ziegler and Nichols that relies on accurate mathematical model of the linear system, but if the system is complex the former method fails to compute the parameters of PID controller. To overcome this problem, recently there exist several techniques based on artificial intelligence such as optimization techniques. The optimization techniques does not require any mathematical model and they are considered to be easy to implement on any system even if it complex, can reach optimal solutions on the parameters. In this study, a new approach to control the position of the micro-robotics system proportional - integral - derivative (PID) controller is designed and a recently developed algorithm based on optimization is known as the sparrow search algorithm (SSA). By using the sparrow search algorithm (SSA), the optimal PID controller parameters were obtained by minimizing a new objective function, which consists of the integral square Time multiplied square Error (ISTES) performance index. The effectiveness of the proposed SSA-based controller was verified by comparisons made with the Sine Cosine algorithm (SCA), and Flower pollination algorithm (FPA) controllers in terms of time and frequency response. Each control technique will be applied to the identified model (simulation results) using MATLAB Simulink and the laboratory setup (experimental results) using LABVIEW software. Finally, the SSA showed the highest performance in time and frequency responses.

Section 5. Tables of Suggested Water Chemistry Targets

2022 ◽  
pp. 28-30
Author(s):  
Keyword(s):  
Water Chemistry ◽  
Steam Generator ◽  
Prime Factor ◽  
Operating Pressure ◽  
Boiler Water ◽  
Water Contaminant ◽  
Internal Water ◽  
Boiler Drum ◽  
The Difference

Consensus water chemistry controls for the six types of steam generator systems are presented in Tables 1 through 7. The tabulated information is categorized according to operating pressure ranges because this is the prime factor that dictates the type of internal water chemistry employed, the normal cycles of feedwater concentration, the silica volatility, and the carryover tendency. The difference between steam and water densities decreases with increasing pressure and temperature; therefore, separating the steam/water phases completely in the boiler drum becomes increasingly difficult to achieve. Since the tendency to carryover is greater at higher operating pressures, it is necessary to maintain lower boiler water contaminant concentrations to meet the same steam purity target.

Stability Analysis of a Mathematical Model for Glioma-Immune Interaction under Optimal Therapy

2019 ◽  
Vol 20 (3-4) ◽  
pp. 269-285 ◽  
Author(s):  
Subhas Khajanchi
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Stability Analysis ◽  
Model Simulation ◽  
Equilibrium Points ◽  
Glioma Cells ◽  
Adjoint System ◽  
Cellular Immunotherapy ◽  
Theory Of Optimal Control ◽  
Malignant Glioma Cells

AbstractWe investigate a mathematical model using a system of coupled ordinary differential equations, which describes the interplay of malignant glioma cells, macrophages, glioma specific CD8+T cells and the immunotherapeutic drug Adoptive Cellular Immunotherapy (ACI). To better understand under what circumstances the glioma cells can be eliminated, we employ the theory of optimal control. We investigate the dynamics of the system by observing biologically feasible equilibrium points and their stability analysis before administration of the external therapy ACI. We solve an optimal control problem with an objective functional which minimizes the glioma cell burden as well as the side effects of the treatment. We characterize our optimal control in terms of the solutions to the optimality system, in which the state system coupled with the adjoint system. Our model simulation demonstrates that the strength of treatment $u_{1}(t)$ plays an important role to eliminate the glioma cells. Finally, we derive an optimal treatment strategy and then solve it numerically.

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