Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Method for Dynamic Prediction of Oxygen Demand in Steelmaking Process Based on BOF Technology
by
Chen, Sujun
, Zhang, Kaitian
, Liu, Yu
, Zhang, Liu
, Zheng, Zhong
in
Accuracy
/ Algorithms
/ Analysis
/ Basic converters
/ Big Data
/ Carbon
/ Chemical elements
/ Collaboration
/ Dephosphorizing
/ Energy
/ Furnaces
/ Heat
/ Iron compounds
/ Liquid metals
/ Methods
/ Optimization
/ Oxygen consumption
/ Oxygen demand
/ Oxygen steel making
/ Prediction models
/ Predictions
/ Scheduling
/ Scrap
/ Steel
/ Steel industry
/ Steel production
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Method for Dynamic Prediction of Oxygen Demand in Steelmaking Process Based on BOF Technology
by
Chen, Sujun
, Zhang, Kaitian
, Liu, Yu
, Zhang, Liu
, Zheng, Zhong
in
Accuracy
/ Algorithms
/ Analysis
/ Basic converters
/ Big Data
/ Carbon
/ Chemical elements
/ Collaboration
/ Dephosphorizing
/ Energy
/ Furnaces
/ Heat
/ Iron compounds
/ Liquid metals
/ Methods
/ Optimization
/ Oxygen consumption
/ Oxygen demand
/ Oxygen steel making
/ Prediction models
/ Predictions
/ Scheduling
/ Scrap
/ Steel
/ Steel industry
/ Steel production
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Method for Dynamic Prediction of Oxygen Demand in Steelmaking Process Based on BOF Technology
by
Chen, Sujun
, Zhang, Kaitian
, Liu, Yu
, Zhang, Liu
, Zheng, Zhong
in
Accuracy
/ Algorithms
/ Analysis
/ Basic converters
/ Big Data
/ Carbon
/ Chemical elements
/ Collaboration
/ Dephosphorizing
/ Energy
/ Furnaces
/ Heat
/ Iron compounds
/ Liquid metals
/ Methods
/ Optimization
/ Oxygen consumption
/ Oxygen demand
/ Oxygen steel making
/ Prediction models
/ Predictions
/ Scheduling
/ Scrap
/ Steel
/ Steel industry
/ Steel production
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Method for Dynamic Prediction of Oxygen Demand in Steelmaking Process Based on BOF Technology
Journal Article
Method for Dynamic Prediction of Oxygen Demand in Steelmaking Process Based on BOF Technology
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Oxygen is an important energy medium in the steelmaking process. The accurate dynamic prediction of oxygen demand is needed to guarantee molten steel quality, improve the production rhythm, and promote the collaborative optimization of production and energy. In this work, a analysis of the mechanism and of industrial big data was undertaken, and we found that the characteristic factors of Basic Oxygen Furnace (BOF) oxygen consumption were different in different modes, such as duplex dephosphorization, duplex decarbonization, and the traditional mode. Based on this, a dynamic-prediction modeling method for BOF oxygen demand considering mode classification is proposed. According to the characteristics of BOF production organization, a control module based on dynamic adaptions of the production plan was researched to realize the recalculation of the model predictions. A simulation test on industrial data revealed that the average relative error of the model in each BOF mode was less than 5% and the mean absolute error was about 450 m3. Moreover, an accurate 30-minute-in-advance prediction of dynamic oxygen demand was realized. This paper provides the method support and basis for the long-term demand planning of the static balance and the short-term real-time scheduling of the dynamic balance of oxygen.
This website uses cookies to ensure you get the best experience on our website.