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The T-junction configuration is a classical test case for thermal fatigue phenomena. Turbulent penetration and unsteady thermal stratification can occur when hot and cold fluids mix in T-junction pipes at NPPs, which may lead to time-varying thermal stress and even induce thermal fatigue failure. In this paper, mock-up experimental and analyses were conducted to develop a new method to calculate the wall temperature fluctuations of mixing T-junction pipes only by the temperature and velocity information of the fluid in branch and main pipe. The experimental results prove the effectiveness of this new method.

This paper proposes a practical data-driven method to model the nodal water pressure transfer of urban water distribution network (WDN) systems. The suitable upstream-downstream node pairs are found out by correlation analysis of the nodal water pressure measurements and corresponding wavelet coefficients at level 3. To quantify the pressure transfer relation of each pair, we construct a linear model respectively. This method could be used in large-scale WDNs for which there is incomplete pipe network information. Real pressure data of a big city in the east of China are used to validate the proposed method. The simulation results show that the MAPE is less than 4.1%, which supports the potential implementation of this method for real operation.

Grid voltage parameters, including the amplitude, frequency and phase angle, are crucial information for real-time control and protection in power systems. Currently, the phase-locked loop methods are widely used for voltage parameters estimation. However, they could hardly achieve accurate estimation in the presence of unbalanced grid voltage and harmonic disturbance. In this paper, a novel three-phase sinusoid-locked loop (SLL) approach is proposed to address the estimation issue of the unbalanced grid voltage parameters. Firstly, the unbalanced three-phase grid voltage is decomposed as the positive and negative sequences based on the instantaneous symmetrical components theory. Then, two SLLs based on the principles of the virtual synchronous machine (VSM) are developed for the positive and negative sequence grid voltages, respectively. Following the idea of SLL, the output voltage of the VSM is locked with the input grid voltage when the real power and reactive power are both driven to zero. Eventually, the unbalanced three-phase grid voltage is reconstructed with the estimated parameters of the positive and negative sequence voltages. Simulation results demonstrate that the proposed SLL approach achieves excellent estimation performance with respect to the unbalanced grid voltage.

T0620. The gap metric is applied to investigate the nonlinearity of the boiler-turbine system to determine the linearization points for nonlinear model such that a Takagi-Sugeno fuzzy model of appropriate accuracy and complexity is obtained. The FAMPC is then designed based on the fuzzy model that is online updated to well approximate the nonlinear dynamics. The fuzzy model is validated with the plant data of a 300 MW unit and the result shows good agreement. The simulation cases demonstrate the proposed controller has good tracking performance and strong robustness.

Grid voltage parameters, including the amplitude, frequency and phase angle of the grid voltage, are essential for real-time control and protection in power systems. Current approaches mainly focus on adopting a phase-locked loop or its derivatives for parameters estimation. However, they could hardly achieve fast response and are sensitive to voltage variations and disturbances. In this paper, the estimation of grid voltage parameters is recast as an observer design problem. An exosystem model of the sinusoidal voltage is established at first. Then, a framework for the observer-based methods is proposed for the robust estimation of single-phase grid voltage parameters. Moreover, a second-order sliding mode observer (SMO), which actually has the lowest order among all possible observers, is designed to estimate the parameters. Based on the Lyapunov theory, the asymptotic stability of the closed-loop SMO is proved. Compared with two other typical methods, simulations are carried out to illustrate the effectiveness and robustness of the proposed approach in the presence of voltage variations and external disturbances. In addition, the proposed estimation approach may also be valuable for online fault detection of voltage sag and low-frequency oscillation.

In this paper, a method to estimate the target value of terminal temperature difference of horizontal three-segment feed water heater under various working conditions is proposed. The temperature of the water at the outlet of the condensation segment is obtained through mass and energy balance on the basis of actual extracted steam flow rate. Then by means of energy balance equation and heat transfer efficiency equation, the temperature of the outlet water at maximum heat transfer efficiency is calculated, thus obtaining the terminal temperature difference target value. Results based on offline operation data of a real 1000 MW supercritical power plant are given and the difference between target value and actual operation value could be used to estimate the loss differential of the terminal temperature difference.

As more stringent requirements are proposed for the load and frequency regulation in modern power grid, the performance of load tracking and main steam pressure stability becomes more important for the safe and economical operation of thermal power plants. In this paper, a new nonlinear control-oriented model of drum boiler-turbine system is developed with a balance between fidelity and simplicity, and validated with history operating data from a real 300 MW subcritical coal-fired unit over wide range. Then, feedback linearization is applied to the nonlinear model, resulting in two independent linear subsystems. Moreover, a sliding mode tracking controller is constructed for coordinated control based on the linearized model. Simulation results are presented to demonstrate the good tracking performance and strong robustness of the proposed approach.

To control the surface temperature on a steel ingot is of practically important task during the heat-treating process. However, it is often difficult to carry out a direct measurement in heating furnace in a long run due to the high temperature. In this work, a study on the surface temperature distribution of a steel ingot is carried out based on a three-dimensional CFD simulation. And then a temperature predictive model is proposed with the aim to predict the surface temperature on the steel ingot more accurately.

Modeling and simulation technology of biological reaction is the important method of theoretical studies and production control. However the greatest technical difficulties of biological reaction modeling is how to identify and discuss the undetermined parameters existing in the complex system by analyzing limited experimental data— to look for an intelligent optimization algorithm that can optimize multivariable and mult-extremum high dimensional nonlinear functions effectively. This thesis took the fed-batch fermentation model in the penicillin industrial production for example, based on the industrial control rolling simulation software, discussed the application characteristics and their improvement of the real model of four widely used optimization algorithms: Simplex Algorithm, Genetic Algorithm, Simulated Algorithm and Particle Swarm Optimization. Lastly, the thesis proposed a new combined optimization algorithm— Genetic-simplex Algorithm by analyzing the complementarity of SIM and GA. Proved by the results of industrial rolling simulation this algorithm has combined the advantages of Simplex Algorithm and Genetic Algorithm, possessing excellent optimization ability.

The characteristics of the antibiotic fermentation process with parallel lines are analyzed. The assignment of tasks, units and events is described by two sets of binary variables. Based on continuous time representation, a mixed integer linear programming (MILP) model of the antibiotic fermentation process is built. The computational example of cephalosporin fermentation process demonstrates the feasibility and validity of the scheduling model

The work outlined in this paper is towards developing a portable, economy blood glucose meter for self-monitoring of blood glucose, which has high performance-price ratio with multifunction and is attractive to the average people. Its functions include blood glucose concentration measurement, LCD display, historical records restore, calendar/timer. It enables the patients with diabetes to detect blood glucose with a glucose oxidase electrode independently at home. This paper will outline hardware configuration in the implementation and software management. Especially, graphic trend curve on LCD allows individuals to easily see how actual blood glucose readings compare with historical records stored in the meter and show how individuals stay within their specific target range so that they can determine how well they are controlling their diabetes. Experimental results indicate that this device is easy-to-use and suitable for home blood glucose monitoring for patients.

Spike sorting is a prerequisite for studying the multi-channel extracellular recordings. A new method is developed for spike sorting in multi-channel extracellular recordings of retinas. Based on the assumption that noise follows Gaussian distribution, spike templates are constructed based on principal component analysis and subtractive clustering, then a template matching procedure is applied to choose the best-fit template or templates combination for overlapping spikes so that after subtracting the template or templates combination from the spike event, the sum of squared residue follows Chi-square distribution. Artificial spike trains are used to assess the performance of the proposed method.