Coupled Models for Secondary Metallurgical Melt Temperature Control
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Solution Overview
Problem
Existing metallurgical models inadequately represent heat/temperature losses of the melt during secondary metallurgical treatments, leading to inaccurate predictions and control of melt temperature, especially during transport and waiting phases, due to simplified assumptions about vessel thermal states and geometric relationships.
Innovation Solution
A system and method that couples a secondary metallurgical model with a vessel model to accurately predict melt temperature by exchanging information and adapting calculations, incorporating the actual thermal state and geometric relationships of the vessel, enabling continuous monitoring and precise control of the metallurgical process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simplified assumptions are used for vessel thermal state and geometric relationships, then the model complexity is reduced, but the prediction accuracy of melt temperature deteriorates
Solution Approach 1:
The patent combines the secondary metallurgical model with the vessel model into an integrated coupled model. The secondary metallurgical model handles metallurgical reactions and composition changes, while the vessel model handles heat transfer and thermal state. By merging these models and exchanging data between them (melt temperature, composition, vessel thermal state), the system achieves comprehensive prediction accuracy without requiring overly complex individual models.
Solution Approach 2:
The coupled model acts as an intermediary between the simplified vessel assumptions and accurate temperature prediction. The vessel model uses simplified geometric relationships and thermal state assumptions as inputs, but the coupled model mediates this by incorporating real-time data from the secondary metallurgical model (actual melt composition, temperature, reaction progress) to correct and refine the temperature predictions, thereby achieving accuracy despite simplified underlying assumptions.
2Reliability
If the vessel model is used alone to describe heat losses, then the actual thermal state of the vessel is considered, but the influences of metallurgical reactions on melt temperature cannot be represented with sufficient accuracy
Solution Approach 1:
The patent merges the vessel model (which accurately represents thermal state and heat losses) with the secondary metallurgical model (which accurately represents metallurgical reactions). The vessel model provides reliable heat loss calculations based on actual vessel thermal state, while the metallurgical model provides accurate reaction progress and composition data. Together, they comprehensively predict melt temperature with both thermal and chemical accuracy.
Solution Approach 2:
The coupled model implements feedback between the vessel model and metallurgical model. The vessel model receives input from the metallurgical model (melt composition, temperature, batch history) to adjust heat loss calculations, while the metallurgical model receives feedback from the vessel model (corrected temperature predictions) to refine reaction progress calculations. This mutual feedback ensures both vessel thermal state and metallurgical reaction influences are accurately represented.
3Device complexity
If homogeneous melt temperature is assumed, then the model calculation is simplified, but the actual temperature variations during transport and waiting phases are not represented
Solution Approach 1:
The patent transitions from a static homogeneous temperature assumption to a dynamic temperature field approach. The vessel model calculates spatial and temporal temperature distributions (temperature fields) that vary during transport and waiting phases. This dynamic model adapts to changing conditions (vessel movement, insulation, ambient temperature) while maintaining manageable complexity through numerical methods and boundary condition definitions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves prediction accuracy of melt temperature, reduces material and energy costs, and simplifies mechanical design by minimizing temperature measurements, while ensuring precise control and efficient energy input adjustments.
Implementation Method 1
The consideration of heat/temperature losses of the melt via the vessel body is based on simplified assumptions
Implementation Method 2
determining the radiation conditions of the melt
Implementation Method 3
vessel models for calculating a temperature field for a multi-body system consisting of melt and vessel
Data Source
Figure 1
Figure 2
AI summary
Metallurgical plant (1), comprising a secondary section (20) which has a vessel (21, 22) and is designed to further process a melt (S) provided by a primary unit (10) into the vessel (21, 22) within the scope of a secondary metallurgical treatment, and a control device (100) for controlling and/or regulating and/or planning the secondary metallurgical treatment of the melt (S) in the vessel (21, 22) of the secondary section (20), wherein the control device (100) comprises a model-based calculation section (110), characterized in that the model-based calculation section (110) comprises at least one secondary metallurgical model (120) and at least one vessel model (130) which are coupled to one another, and is designed to control the temperature of the melt (S) in the vessel (21, 22) of the secondary section (20) based on the coupling of the secondary metallurgical model (120) and the vessel model (130).