New Optimization Method, the Algorithms of Changes, for Heat Exchanger Design

Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption. In this paper, a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger. This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts. In AOC, the hexagram operations in I Ching are generalized to binary string case and an iterative process, which imitates the I Ching inference, is defined. Before applying the AOC to the heat exchanger design problem, the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP). Based on the TSP results, the AOC is shown to be superior to the genetic algorithms (GA). The AOC is then used in the optimal design of heat exchanger. The shell inside diameter, tube outside diameter, and baffles spacing are treated as the design (or optimized) variables. The cost of the heat exchanger is arranged as the objective function. For the heat exchanger design problem, the results show that the AOC is comparable to the GA method. Both methods can find the optimal solution in a short period of time.

Reagent optimization for on-line simultaneous polarographic determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of anextremely large excess of Zn^(2+)

Reagents are optimized for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in zinc sulfate solution, which contains an extremely large excess of Zn^(2+). First, the reagents and their doses for the experiment are selected according to the characteristics of the zinc sulfate solution. Then, the reagent doses are optimized by analyzing the influence of reagent dose on the polarographic parameters(i.e. half-wave potential E_(1/2) and limiting diffusion current I_p). Finally, the optimization results are verified by simultaneously determining trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+). The determination results indicate that the optimized reagents exhibit wide linearity, low detection limits, high accuracy and good precision for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+).

Optimizing Low-Temperature Heat Recovery in a Refinery Fluid Catalytic Cracking Unit Based on Pinch Analysis

In this paper, the research was focused on optimizing low-temperature heat recovery to adopt multi-effect distil- lation （MED） in desalination by pinch technology. And further analysis indicated that phase changes occurred during the heat recovery process. In such case, the feed stream was divided into two streams： the liquid feed stream and the gaseous feed stream. Through calculation, the optimal ATmin was established at 26℃, and the total cost of heat exchange process was only $1.098× 106. By using the Problem Table Algorithm for pinch analysis, the temperature of the hot and the cold steams was 119℃ and 93 ℃, respectively. At a temperature higher than 119 ℃, all heat of the hot stream could not be cooled by the condenser, and the minimum heat load of utility （QH.min） was 440457.64 kW; and at a temperature below 93 ℃, all heat of the cold stream could not be provided by the heater, and the minimum cold load of utility （QC.min） was 1965993.85 kW. Finally, the synthesis of heat exchanger network was established through integrating two heat exchanger networks.

NEURAL NETWORK INTELLIGENT SYSTEM FOR THE ON-LINE OPTIMIZATION IN CHEMICAL PLANTS

A strategy of developing on-line optimization intelligent systems based on combiningflowsheeting simulation and optimization package with artificial neural networks(ANN)is presented inthis paper.A number of optimization cases for a certain chemical plant are obtained off-line byusing PROCESS-Ⅱ or other flowsheeting programming with optimization.Then,taking these cases astraining examples,we establish a neural network systems which can be used on-line as an optimizer toobtain setpoints from input data sampled from distributed control system through gross error detectionand data reconciliation procedures.Such an on-line optimizer possesses two advantages over nonlinearprogramming package:first of all,there is no convergence problem for the trained ANN to be usedonline;secondly,the frequency for setpoints updating is not limited because only algebraic calculationrather than optimization is required to be carried out on-line.Here two key problems ofimplementing ANN approaches to the on-line optimization

Research on Distribution of Electromagnetic Environment around Substations and Optimization Layout of On-line Monitoring

The characteristics and distribution law of electromagnetic environment around substations with different levels of voltage were studied,and the main influencing factors were discussed. Meanwhile,a scheme for locating monitoring points suitable for an on-line monitoring system of electromagnetic environment was proposed.

Multi‐objective particle swarm optimisation of complex product change plan considering service performance

Design change is an inevitable part of the product development process.This study proposes an improved binary multi‐objective PSO algorithm guided by problem char-acteristics(P‐BMOPSO)to solve the optimisation problem of complex product change plan considering service performance.Firstly,a complex product multi‐layer network with service performance is established for the first time to reveal the impact of change effect propagation on the product service performance.Secondly,the concept of service performance impact(SPI)is defined by decoupling the impact of strongly associated nodes on the service performance in the process of change affect propagation.Then,a triple‐objective selection model of change nodes is established,which includes the three indicators:SPI degree,change cost,and change time.Furthermore,an integer multi‐objective particle swarm optimisation algorithm guided by problem characteristics is developed to solve the model above.Experimental results on the design change problem of a certain type of Skyworth TV verify the effectiveness of the established optimisation model and the proposed P‐BMOPSO algorithm.

OPTIMIZATION OF THE METHOD OF SELECTING THE TOOTH NUMBER SERIES IN A SET OF CHANGE GEARS Part Ⅱ The Rules for Permuting the DBL’s of the First Order and Their Intercalated Sets

The problem in practice of determining the proper combination of Zi in a set of changegears may be abstracted to the problem of finding the proper combination and permutation ofthe elements ai,i+1 of the set A1 to give maximum M-d. Some results to find optimal combina-tions of the elements of the set A1 have been reported in part I. In this part, some rules forpermuting these elements are introduced. By means of these rules, three kinds of intercalated setsof A1 have been found, namely: （1） Sets with an even left wing, （2） Sets with coincidence of bothwings, and （3） Sets with circulated elements.

Matrix Riccati Equations in Optimal Control

In this paper, the matrix Riccati equation is considered. There is no general way for solving the matrix Riccati equation despite the many fields to which it applies. While scalar Riccati equation has been studied thoroughly, matrix Riccati equation of which scalar Riccati equations is a particular case, is much less investigated. This article proposes a change of variable that allows to find explicit solution of the Matrix Riccati equation. We then apply this solution to Optimal Control.

Improving Optimal Fingerprinting Methods Requires a Viewpoint beyond Statistical Science

While being successful in the detection and attribution of climate change,the optimal fingerprinting method(OFM)may have some limitations from a physics-and-dynamics-based viewpoint.Here,an analysis is made on the linearity,noninteraction,and stationary-variability assumptions adopted by OFM.It is suggested that furthering OFM needs a viewpoint beyond statistical science,and the method should be combined with theoretical tools in the dynamics and physics of the Earth system,so as to be applied for the detection and attribution of nonlinear climate change including tipping elements within the Earth system.

On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter

On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study,a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model,a state space model is developed.An improved algorithm,swarm energy conservation particle swarm optimization(SECPSO) ,is presented for the parameter identification in the mechanistic model,and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.

Land use optimization at small watershed scale on the Loess Plateau

At present, land use optimization at small watershed scale is the key measure to control soil erosion, restore the eco-environment and improve the farmers＇ living standard on the Loess Plateau, China. Based on the land use survey maps of 1966, 1988, 1997, 2003 and the digital topographic map of 1984 in Yangou watershed, and assisted by spatial techniques of GIS, the basic characteristics and driving forces of land use change in Yangou watershed are analyzed. According to the summarization of land-use optimization characteristics since 1997, and with the help of continuous monitoring data for years and farmer investigation data, this paper appraises eco-environmental benefits, economic benefits and sustainability of Yangou watershed. We have used sediment reduction benefits, coverage ratio of permanent vegetation, per capita food production and per capita income of farmers as indices. The results show that Yangou watershed project has successfully controlled the soil and water loss and the farmers＇ living standard has been improved markedly by reasonable adjustment to land use structure. The benefit of sediment reduction is higher than 80% and the coverage ratio of permanent vegetation reaches 61.03%. In 2006, the per capita income increased by 1493 yuan compared with the year 1998.The successful measures and experiences of Yan- gou watershed are worth promoting on the Loess Plateau.

Response of a Grassland Ecosystem to Climate Change in a Theoretical Model

The response of a grassland ecosystem to climate change is discussed within the context of a theoretical model.An optimization approach,a conditional nonlinear optimal perturbation related to parameter（CNOP-P） approach,was employed in this study.The CNOP-P,a perturbation of moisture index in the theoretical model,represents a nonlinear climate perturbation.Two kinds of linear climate perturbations were also used to study the response of the grassland ecosystem to different types of climate changes.The results show that the extent of grassland ecosystem variation caused by the CNOP-P-type climate change is greater than that caused by the two linear types of climate change.In addition,the grassland ecosystem affected by the CNOP-P-type climate change evolved into a desert ecosystem,and the two linear types of climate changes failed within a specific amplitude range when the moisture index recovered to its reference state.Therefore,the grassland ecosystem response to climate change was nonlinear.This study yielded similar results for a desert ecosystem seeded with both living and wilted biomass litter.The quantitative analysis performed in this study also accounted for the role of soil moisture in the root zone and the shading effect of wilted biomass on the grassland ecosystem through nonlinear interactions between soil and vegetation.The results of this study imply that the CNOP-P approach is a potentially effective tool for assessing the impact of nonlinear climate change on grassland ecosystems.

Influence of lane change on stability analysis for two-lane traffic flow

This paper deals mainly with the influence of lane changing behaviours on the stability of two-lane traffic flow under a periodic boundary condition. Following the description of an optimal velocity model for two vehicle groups and the derivation of their stability conditions, the feedback signals, which involve information about vehicles from both lanes acting on the two-lane traffic system, are introduced into the optimal velocity model. The control signals play a role in alleviating the traffic jam only if the traffic state is in congestion, and their role will vanish if the traffic state is in the steady state. The numerical simulations show that lane changing behaviours can break the steady state of two-lane traffic flow and aggravate the traffic disturbance, but the control method would successfully suppress the traffic jam eventually, which implies that the conclusions obtained here have certain theoretical and practical significance.

Statistical Procedures for Estimating and Detecting Climate Changes

This paper provides a concise description of the philosophy, mathematics, and algorithms for estimating, detecting, and attributing climate changes. The estimation follows the spectral method by using empirical orthogonal functions, also called the method of reduced space optimal averaging. The detection follows the linear regression method, which can be found in most textbooks about multivariate statistical techniques. The detection algorithms are described by using the space-time approach to avoid the non-stationarity problem. The paper includes （1） the optimal averaging method for minimizing the uncertainties of the global change estimate, （2） the weighted least square detection of both single and multiple signals, （3） numerical examples, and （4） the limitations of the linear optimal averaging and detection methods.

On-line Chatter Detection Using an Improved Support Vector Machine

On-line chatter detection can avoid unstable cutting through monitoring the machining process.In order to identify chatter in a timely manner,an improved Support Vector Machine(SVM)is developed in this paper,based on extracted features.In the SVM model,the penalty factor(e)and the core parameter(g)have important influence on the classification,more than from Kernel Functions(KFs).Hence,first the classification results are conducted using different KFs.Then two methods are presented for exploring the best parameters.The chatter identification results show that the Genetic Algorithm(GA)approach is more suitable for deciding the parameters than the Grid Explore(GE)approach.

The Optimal Control for the Output Feedback Stochastic System at the Risk-Sensitive Cost

The optimal control of the partially observable stochastic system at the risk-sensitive cost is considered in this paper. The system dynamics has a general correlation between system and measurement noise. And the risk-sensitive cost contains a general quadratic term (with cross terms and extra linear terms). The explicit solution of such a problem is presented here using the output feedback control method. This clean and direct derivation enables one to convert such partial observable problems into the equivalent complete observable control problems and use the routine ways to solve them.

On-Line Recognition of Handwritten Chinese Characters

For the design of a system for on-line recognition of handwritten Chinesecharacters stroke segment ordering is such a difficult problem no good solution is availableto it yet so far.An optimal stroke segment matching algorithm based on stroke structureinformation is proposed in this paper.Results of experiments are presented so thatcomparison can be made between the proposed algorithm and the stroke segmentmatching method based on the strokes’absoulute coordinates.

Research on Optimize Prediction Model and Algorithm about Chaotic Time Series

We put forward a chaotic estimating model, by using the parameter of the chaotic system, sensitivity of the parameter to inching and control the disturbance of the system, and estimated the parameter of the model by using the best update option. In the end, we forecast the intending series value in its mutually space. The example shows that it can increase the precision in the estimated process by selecting the best model steps. It not only conquer the abuse of using detention inlay technology alone, but also decrease blindness of using forecast error to decide the input model directly, and the result of it is better than the method of statistics and other series means. Key words chaotic time series - parameter identification - optimal prediction model - improved change ruler method CLC number TP 273 Foundation item: Supported by the National Natural Science Foundation of China (60373062)Biography: JIANG Wei-jin (1964-), male, Professor, research direction: intelligent compute and the theory methods of distributed data processing in complex system, and the theory of software.

An Improved Rate Control Method Based on Modification at Scene Change for H.264

This paper presents an improved rate control method for H.264. First, the scene changes are detected by the average absolute difference of the brightness histograms between the adjacent frames. Then, the bit allocation and quantization parameters are adjusted, using a certain threshold. In addition, the calculation of the mean absolute difference （MAD） is modified in an alternative way, which makes the rate distortion optimization （RDO） more accurate. Extensive simulation results show that the proposed method, compared with G012, can improve the average peak signal-to-noise ratio （PSNR） and moderate the image quality.

Design and Application of Optimization Software for Substation Operation Mode Based on EMS

This paper proposes a kind of optimization software for substation operation mode, which can not only read data on-line from EMS, but also calculate total loss of substations in parallel operation, split operation or individual operation mode. It can also select the most optimized way and feed the conclusion back to EMS to make substations operate in the most optimized way. The software is suitable for optimization of substation in rural power grid.