Continuous Prediction Model of Carbon Content in 120 t Converter Blowing Process

A continuous prediction model of carbon content of 120 t BOF is established in this paper. Based on the three-stage decarburization theory and combined with the production process of 120 t converter, the effects of oxygen lance height and top blowing oxygen flow rate are also considered in the model. The explicit finite difference method is used to realize continuous prediction of carbon content in the converter blowing process. The model parameters such as ultimate carbon content in molten pool are calculated according to the actual data of 120 t BOF, which improves the hit rate of the model. Process verification and end-point verification for the continuous prediction model have been carried out, and the results of process verification indicate that the continuous prediction model established in the paper basically accords with the actual behavior of decarburization. Moreover, the hit ratio of the continuous prediction model reached 85% for the prediction of end-point carbon content within a tolerance of ±0.02%.

Download Full-text

The Converter Steelmaking End Point Prediction Model Based on RBF Neural Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.577.98 ◽

2014 ◽

Vol 577 ◽

pp. 98-101

Author(s):

Xian Liang Dong ◽

Shi Dong

Keyword(s):

Neural Network ◽

Mathematical Model ◽

Prediction Model ◽

Carbon Content ◽

Rbf Neural Network ◽

Converter Steelmaking ◽

Prediction Problem ◽

Model Based ◽

End Point ◽

The Mathematical Model

The mathematical model of convert steelmaking end point prediction model based on RBF(Radical Basis Function) is presented in this paper. According to the end point prediction problem of the converter steelmaking production prediction problem, we establish the forecast model of converter steelmaking process which describes the relationship between variables such as hot metal quality, oxygen blowing, the quality of the cooling agent and additives etc. and the end point molten steel temperature and carbon content. The prediction system is multidimensional and nonlinear. The model between variables and the target is unknown. For this situation, this paper applies RBF neural network to forecast target, establishing the prediction model based on RBF neural network. So as to obtain the variables and the mathematical model between steel endpoint temperature and carbon content.

Download Full-text

Prediction Model of End-Point Carbon Content for BOF Based on LM BP Neural Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.189-193.4446 ◽

2011 ◽

Vol 189-193 ◽

pp. 4446-4450

Author(s):

Chang Rong Li ◽

Hao Wen Zhao ◽

Qing Yin

Keyword(s):

Neural Network ◽

Prediction Model ◽

Carbon Content ◽

Bp Neural Network ◽

Static Model ◽

Influential Factors ◽

Target Error ◽

End Point ◽

Endpoint Control ◽

Lm Algorithm

Reaction process of BOF steelmaking is a very complex physical chemistry process which is very difficult to describe linearity. The traditional static model has poor accuracy, and the target hit rate is low. Based on the analysis of the major influential factors, the influential factors of converter smelting on the endpoint control of carbon content are fixed in this paper. A prediction model of end-point carbon content for BOF is established based on Levenberg-Marquardt (LM) algorithm of BP neural network. The simulated results show that the hitting rates of end-point carbon content reached 80% when accuracy of target error is ±0.025%.

Download Full-text

Modelling and Numerical Valuation of Power Derivatives in Energy Markets

Advances in Applied Mathematics and Mechanics ◽

10.4208/aamm.10-m1133 ◽

2012 ◽

Vol 4 (03) ◽

pp. 259-293 ◽

Cited By ~ 1

Author(s):

Mai Huong Nguyen ◽

Matthias Ehrhardt

Keyword(s):

Finite Difference ◽

Gaussian Quadrature ◽

Jump Diffusion ◽

Model Parameters ◽

Initial Condition ◽

Swing Options ◽

Power Derivatives ◽

Explicit Finite Difference ◽

Theta Method ◽

Explicit Finite Difference Method

AbstractIn this work we investigate the pricing of swing options in a model where the underlying asset follows a jump diffusion process. We focus on the derivation of the partial integro-differential equation (PIDE) which will be applied to swing contracts and construct a novel pay-off function from a tree-based pay-off matrix that can be used as initial condition in the PIDE formulation. For valuing swing type derivatives we develop a theta implicit-explicit finite difference scheme to discretize the PIDE using a Gaussian quadrature method for the integral part. Based on known results for the classical theta-method the existence and uniqueness of solution to the new implicit-explicit finite difference method is proven. Various numerical examples illustrate the usability of the proposed method and allow us to analyse the sensitivity of swing options with respect to model parameters. In particular the effects of number of exercise rights, jump intensities and dividend yields will be investigated in depth.

Download Full-text

Development and Application of Control Model for Semi-Steel Steelmaking

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.154-155.1137 ◽

2010 ◽

Vol 154-155 ◽

pp. 1137-1142 ◽

Cited By ~ 1

Author(s):

Xin Teng Liang ◽

Yong Chen ◽

Jian Hua Zeng ◽

An Lin Li ◽

Gui Jun Li ◽

...

Keyword(s):

Prediction Model ◽

Carbon Content ◽

Real Time ◽

Basic Structure ◽

Static Model ◽

Control Model ◽

Oxygen Blow ◽

Time Prediction ◽

End Point ◽

Auxiliary Material

According to the actual characteristics of semi-steel steelmaking of PZH steel, a static model for prediction of the oxygen blow amount and consumption of auxiliary material is established, and an end-point prediction model based on carbon content and temperature of sublance is given. This paper introduced the calculating principle and basic structure about above two models detailed. The results show that, the static model has certain accuracy and reliability of these models are illustrated by actual application.The static model might provide immediately the predicting optimum auxiliary material amount and the oxygen blow amount for operator, which direct the operation in time. The end-point prediction model might give real time prediction for the carbon content and temperature on BOF Endpoint, which has high hitting ratio.

Download Full-text

Life Prediction Model of Mineral Admixture Cement Based-Materials under Early Age CO2-Erosion

Coatings ◽

10.3390/coatings11040413 ◽

2021 ◽

Vol 11 (4) ◽

pp. 413

Author(s):

Saisai Wang ◽

Jian Chen ◽

Xiaodong Wen

Keyword(s):

Prediction Model ◽

Life Prediction ◽

Experimental Tests ◽

Mineral Admixture ◽

Model Parameters ◽

Influence Coefficient ◽

Test Pieces ◽

Cement Based Materials ◽

Particle Group ◽

Life Prediction Model

Most of the existing models of structural life prediction in early carbonized environment are based on accelerated erosion after standard 28 days of cement-based materials, while cement-based materials in actual engineering are often exposed to air too early. These result in large predictions of the life expectancy of mineral-admixture cement-based materials under early CO2-erosion and affecting the safe use of structures. To this end, different types of mineral doped cement-based material test pieces are formed, and early CO2-erosion experimental tests are carried out. On the basis of the analysis of the existing model, the influence coefficient of CO2-erosion of the mineral admixture Km is introduced, the relevant function is given, and the life prediction model of the mineral admixture cement-based material under the early CO2-erosion is established and the model parameters are determined by using the particle group algorithm (PSO). It has good engineering applicability and guiding significance.

Download Full-text

Multi-day flow forecasting using the Kalman filter

Canadian Journal of Civil Engineering ◽

10.1139/l91-037 ◽

1991 ◽

Vol 18 (2) ◽

pp. 320-327 ◽

Cited By ~ 1

Author(s):

Murray A. Fitch ◽

Edward A. McBean

Keyword(s):

Kalman Filter ◽

Prediction Model ◽

Linear Prediction ◽

Measured Data ◽

System Model ◽

Parameter Estimates ◽

Model Parameters ◽

Forecasting Performance ◽

Optimal Forecasting ◽

Linear Prediction Model

A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm.

Download Full-text

Thermal Analysis of Expressway Considering Wind Effect

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.419.895 ◽

2013 ◽

Vol 419 ◽

pp. 895-904

Author(s):

X. Cao ◽

H. Miyashita ◽

T. Kako ◽

Z. Zhang ◽

B. Song

Keyword(s):

Mathematical Model ◽

Thermal Analysis ◽

Thermal Conduction ◽

Computer Calculation ◽

Basic Mechanism ◽

Weather Data ◽

Wind Effect ◽

Fortran Language ◽

Explicit Finite Difference ◽

Explicit Finite Difference Method

This paper reports a method of thermal analysis of expressway and the results of analysis of four expressways currently used in Japan. The authors built a mathematical model based on the principle of thermal conduction. For the boundary conditions in this mathematical model the influence of solar radiation, wind and air temperature etc. are taken into consideration. Explicit finite difference method is used in the analysis. The authors made an analysis program in Fortran language. Four main expressways distributing from the northern to the southern in Japan are chosen as the objects of this study. The observed weather data of the hottest days experienced by these expressways during the past 30 years is input into the computer calculation. The basic mechanism of expressway temperature change and effect factors are illuminated. The results are reported and discussed.

Download Full-text