scholarly journals Improving the Efficiency of the Three-Stage Technique of Mathematical Model Identification of Complex Thermal Power Equipment

2020 ◽  
Vol 209 ◽  
pp. 03002
Author(s):  
Vitalii Alekseiuk
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Thermal Power ◽  
Great Part ◽  
Model Identification ◽  
Identification Accuracy ◽  
Model Parameters ◽  
Power Equipment ◽  
Operation Conditions ◽  
The Mathematical Model

The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes an effective three-stage technique of mathematical model identification of complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. The article presents a new formulation of the optimization problem for more efficient identification of mathematical models of heat power equipment. An effective three-stage technique of mathematical model identification of complex thermal power equipment was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit.

scholarly journals An improved technique for identification of mathematical model parameters of thermal power equipment and assessment of its performance

2019 ◽  
Vol 114 ◽  
pp. 06009
Author(s):  
Aleksandr Kler ◽  
Vitalii Alekseiuk ◽  
Aleksei Maksimov
Keyword(s):  
Mathematical Model ◽  
Thermal Power ◽  
Identification Accuracy ◽  
Model Construction ◽  
Model Parameters ◽  
Power Equipment ◽  
Control Parameters ◽  
Accuracy Of Measurements ◽  
Improved Technique ◽  
The Mathematical Model

The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes a technique improved by the author for identification (adjustment, verification) of mathematical model parameters for complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. An improved technique for identification of mathematical model parameters was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit and an example of the optimization calculation of the real operation condition in order to reduce specific fuel consumption for electricity generation. In addition, the paper discusses an issue of assessing the identification accuracy of mathematical model parameters of thermal power equipment that depends on the accuracy of measurements of control parameters used to adjust the model, as well as on the correctness of the mathematical model construction and the calculation technique applied.

scholarly journals DEVELOPING EXPANDED POWELL’S ALGORITHM TO IDENTIFY THE MATHEMATICAL MODEL PARAMETERS FOR TRANSESTERIFICATION OF FISH FAT INTO BIODIESEL FUEL

2011 ◽  
Vol 14 (3) ◽  
pp. 34-48
Author(s):  
Hai Xuan Le ◽  
Anh Huynh Tuyet Le
Keyword(s):  
Mathematical Model ◽  
Random Search ◽  
Equation System ◽  
Optimal Operation ◽  
Descent Method ◽  
Steepest Descent Method ◽  
Biodiesel Fuel ◽  
Model Parameters ◽  
Operation Conditions ◽  
The Mathematical Model

By employing the system approach methodology, this research showed the expansion of Powell’s algorithm to solve the identification of kinetic parameters in the differential equation system which describes the transesterification of fish fat into biodiesel fuel. The expanded Powell’s method is developed on the basis of the algorithm that combines Taxi-Cab method with random search method and gradient method (steepest descent method). The obtained results allow us to simulate and optimize the biodiesel fuel production in order to assess the influence of technological factors on the effect of process and to determine the optimal operation conditions. The expanded Powell’s algorithm can also be advantageously applied to simulation or optimizzation in the cases when the mathematical model of the research object contains several parameters which must be identified.

scholarly journals Identification of heat exchangers according to the criterion of energy efficiency

2019 ◽  
Vol 276 ◽  
pp. 06022 ◽  
Author(s):  
Vladimir Velichkin ◽  
Vladimir Zavyalov
Keyword(s):  
Mathematical Model ◽  
Energy Efficiency ◽  
Mathematical Models ◽  
Control Systems ◽  
Heat Exchangers ◽  
Control Object ◽  
Control Action ◽  
Model Parameters ◽  
Quality Of Control ◽  
The Mathematical Model

The article presents the results of the analysis of the characteristics of heat exchangers methods for determining their mathematical models. The necessity of the availability of the mathematical model during the synthesis of automatic control systems with desired properties. The method of identification of the thermal control object by the testing control action is proposed. Since technological control objects always be an energy of interaction the energy efficiency criterion applied for automatic formation of the control action. Also the analytical self-adjusting system with a reference model in the form of an integrating link was applied. From the analytical researches it follows that the movement of the system along the optimal trajectory occurs at a constant speed and does not depend on the properties of the control object, and the optimal control depends on the properties of the control object, time, and technological requirements. It is shown that mathematical models of heat exchangers of the first and second orders are determined quite simply. The accuracy of the mathematical model parameters is limited only by the accuracy of the experimental data. The quality of control systems with desired properties, synthesized by experimental, and accurate models are virtually indistinguishable.

scholarly journals Spectral and integral methods of determining parameters in selected electric arc models with a forced sinusoid current circuit

2016 ◽  
Vol 65 (1) ◽  
pp. 87-103 ◽  
Author(s):  
Antoni Sawicki ◽  
Maciej Haltof
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Power Supply ◽  
Electric Arc ◽  
Dynamic Processes ◽  
Model Parameters ◽  
Static Characteristics ◽  
Integral Methods ◽  
The Mathematical Model ◽  
Linear Shape

Abstract The paper discusses problems arising in attempts to accurately represent dynamic processes of an electric arc by means of simple mathematical models. It describes the properties of the universal Pentegov model, employing any shape of static voltagecurrent characteristics of an arc. Next, it presents spectral and integral measuring methods for determining arc parameters in the Mayr, Cassie and Pentegov models of the electric arc with a forced sinusoid current circuit, with the raising static characteristics of hyperbolic-flat and hyperbolic-linear shape. The influence is discussed of the random power supply disturbances on errors of determining the mathematical model parameters.

MATHEMATICAL MODEL AND EXPERIMENTAL ESTIMATION OF THERMAL PROCESSES IN HEATING MODULE AS A PART OF STEAM ABLATION DEVICE FOR VARICOSE VEINS TREATMENT

2021 ◽  
pp. 117-125
Author(s):  
Дина Владимировна Кривоносова ◽  
Евгений Сергеевич Ермолаев
Keyword(s):  
Mathematical Model ◽  
Varicose Veins ◽  
Thermal Power ◽  
Thermal Characteristics ◽  
Steam Injection ◽  
Heating Element ◽  
Vein Wall ◽  
Tissue Heating ◽  
Comparison Of The Results ◽  
The Mathematical Model

На сегодняшний день в России для лечения варикозного расширения вен часто проводятся малоинвазивные операции методами радиочастотной или лазерной облитерации, при этом метод паровой облитерации при лечении варикозной болезни не применяется совсем. Однако метод паровой облитерации обладает существенными преимуществами: малый объём и биоинертность рабочей среды - водяного пара, его невысокая температура - 120 °С, исключающая вероятность образования нагара и перфорации венозной стенки. Целью данной работы является разработка математической модели для расчёта тепловых характеристик блока нагревания, входящего в устройство для лечения варикозной болезни методом паровой облитерации. Модель описывает теплообменные процессы в гидравлической трубке блока нагревания и может быть полезна при расчёте размеров нагревательного элемента, обеспечивающих нагрев и парообразование определённой порции воды. С целью верификации математической модели результаты моделирования были сопоставлены с экспериментальными данными. Была проведена серия экспериментов, в ходе которых были получены значения энергии, содержащейся в одной инжекции пара, и объём воды в одной инжекции, а также оценена фактическая тепловая мощность нагревателя. Сравнение результатов имитационного моделирования и значения фактической тепловой мощности пара, полученной экспериментальным путем, показала работоспособность математической модели. Разработанная математическая модель позволяет подбирать геометрические параметры нагревательного элемента в зависимости от требуемой тепловой мощности, которая должна быть обеспечена блоком нагревания, а также варьировать параметры нагревательного элемента для разной степени нагрева тканей Today in Russia minimally invasive varicose veins treatment is often performed using radiofrequency or laser ablation, while the method of steam ablation is not used at all. However, the steam ablation method has significant advantages: a small volume and biological inertness of the working substance - sterile water vapor, its low temperature - 120 °C, excluding the carbon deposits and perforation of the vein wall. The purpose of this work is to develop a mathematical model for calculating the thermal characteristics of the heating module as a part of the device for varicose veins treatment using steam ablation. The model describes heat exchange processes in the hydraulic circuit of the heating module and can be applied to calculate the dimensions of the heating module which provides heating and vaporization of a certain portion of water. In order to verify the mathematical model, the simulation results were compared with experimental data. A series of experiments were carried out in which the energy contained in one steam injection and the volume of water in one injection were estimated, as well as the actual thermal power of the heating module. Comparison of the results of simulation and the value of the actual thermal power of steam obtained experimentally showed the efficiency of the mathematical model. The proposed mathematical model allows to select the geometric parameters of the heating element depending on the required thermal power, which must be provided by the heating module, and also to vary the parameters of the heating element for different degrees of tissue heating

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

scholarly journals NECESSITY TO IMPROVE THE MATHEMATICAL MODEL OF FREIGHT CARS TO STUDY CASES OF ITS DERAILMENTS

2020 ◽  
pp. 442-451
Author(s):  
А.V. Batig ◽  
A. Ya. Kuzyshyn
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Computer Experiment ◽  
Rolling Stock ◽  
Software Systems ◽  
Freight Car ◽  
The Stability ◽  
The Many ◽  
The Impact ◽  
The Mathematical Model

One of the most important problems that pose a serious threat to the functioning of railways is the problem of freight cars derailment. However, according to statistics, the number of cases of the derailments of freight cars in trains annually grows. Тo prevent such cases, the necessary preventive measures are developed, and to study the causes of their occurrence, a significant number of mathematical models, programs and software systems created by leading domestic and foreign scientists. Studies of such mathematical models by the authors of this work have led to the conclusion that they are not sufficiently detailed to the extent that it is necessary for analyze the reasons of its derailment. At the same time, an analysis of the causes of the rolling stock derailments on the railways of Ukraine over the past five years showed that in about 20 % of cases they are obvious, and in 7 % of cases they are not obvious and implicitly expressed. The study of such cases of rolling stock derailment during an official investigation by the railway and during forensic railway transport expertises requires the use of an improved mathematical model of a freight car, which would allow a quantitative assessment of the impact of its parameters and rail track on the conditions of railway accidents. Therefore, taking into account the main reasons that caused the occurrence of such railroad accidents over the last five years on the railways of Ukraine, the article selected the main directions for improving the mathematical model of a freight car, allowing to cover all the many factors (explicit and hidden) and identify the most significant ones regarding the circumstances of the derailment rolling stock off the track, established on the basis of a computer experiment. It is proposed in the mathematical model of a freight car to take into account the guiding force, the value of which is one of the main indicators of the stability of the rolling stock. The authors of the article noted that not taking into account the influence of the guiding forces on the dynamics of the freight car can lead to an erroneous determination of the reasons for the rolling stock derailment or even to the impossibility of establishing them.

scholarly journals The analysis of flutter characteristics based on generalized parameters of eigen modes of vibrations

2021 ◽  
pp. 95-102
Author(s):  
K. I Barinova ◽  
A. V Dolgopolov ◽  
O. A Orlova ◽  
M. A Pronin
Keyword(s):  
Mathematical Model ◽  
High Speed ◽  
Dynamic Pressure ◽  
Mode Shapes ◽  
Scaled Model ◽  
Design Specifications ◽  
Operation Conditions ◽  
Flutter Analysis ◽  
Generalized Parameters ◽  
The Mathematical Model

Flutter numerical analysis of a dynamically scaled model (DSM) of a high aspect ratio wing was performed using experimentally obtained generalized parameters of eigen modes of vibrations. The DSM is made of polymer composite materials and is designed for aeroelastic studies in a high-speed wind tunnel. As a result of the analysis, safe operation conditions (flutter limits) of the DSM were determined. The input data to develop the flutter mathematical model are DSM modal test results, i.e. eigen frequencies, mode shapes, modal damping coefficients, and generalized masses obtained from the experiment. The known methods to determine generalized masses have experimental errors. In this work some of the most practical methods to get generalized masses are used: mechanical loading, quadrature component addition and the complex power method. Errors of the above methods were analyzed, and the most reliable methods were selected for flutter analysis. Comparison was made between the flutter analysis using generalized parameters and a pure theoretical one based on developing the mathematical model from the DSM design specifications. According to the design specifications, the mathematical model utilizes the beam-like schematization of the wing. The analysis was performed for Mach numbers from 0.2 to 0.8 and relative air densities of 0.5, 1, 1.5. Comparison of the two methods showed the difference in critical flutter dynamic pressure no more than 6%, which indicates good prospects of the flutter analysis based on generalized parameters of eigen modes.

scholarly journals Analysis on Present Mathematical Model for Predicting the Crop Production

2020 ◽  
Vol 9 (12) ◽  
pp. 168-170
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Real World ◽  
Crop Production ◽  
Ghg Emissions ◽  
Data Set ◽  
Factors Affecting ◽  
The Government ◽  
The Mathematical Model ◽  
Government Website

India is a worldwide agriculture business powerhouse. Future of agriculture-based products depends on the crop production. A mathematical model might be characterized as a lot of equations that speak to the conduct of a framework. By using mathematical model in agriculture field, we can predict the production of crop in particular area. There are various factors affecting crops such as Rainfall, GHG Emissions, Temperature, Urbanization, climate, humidity etc. A mathematical model is a simplified representation of a real-world system. It forms the system using mathematical principles in the form of a condition or a set of conditions. Suppose we need to increase the crop production, at that time the mathematical model plays a major role and our work can be easier, more significant by using the mathematical model. Through the mathematical model we predict the crop production in upcoming years. .AI, ML, IOT play a major role to predict the future of agriculture, but without mathematical models it is not possible to predict crop production accurately. To solve the real-world agriculture problem, mathematical models play a major role for accurate results. Correlation Analysis, Multiple Regression analysis and fuzzy logic simulation standards have been utilized for building a grain production benefit depending model from crop production. Prediction of crop is beneficiary to the farmer to analyze the crop management. By using the present agriculture data set which is available on the government website, we can build a mathematical model.

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