Multi-Zone Storage Tank Modeling for Feedstock Property Prediction
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Solution Overview
Problem
In batch process control systems without mixers, it is challenging to accurately predict the properties of feedstock being pumped out of storage tanks into reactors due to stratification and incomplete blending, which affects the quality of the final product.
Innovation Solution
A multi-zone modeling technique is employed to model the properties of the storage tank pump-out feedstock, assuming layered input feedstock with some mixing due to convection and turbulence, allowing for updates and calculations of average properties and mixing factors based on new feedstock deliveries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-zone modeling is used to determine feedstock properties, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The storage tank is divided into multiple zones (e.g., top zone, middle zone, bottom zone) to represent different feedstock layers. Each zone tracks properties independently, allowing accurate determination of pump-out feedstock properties by identifying which zone corresponds to the pump outlet location. This segmentation resolves the contradiction by improving measurement precision through spatial differentiation while keeping the computational model relatively simple.
2Ease of operation
If flow rate measurements are not used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The invention introduces an intermediary computational model that uses readily available data (feedstock delivery properties, tank level, zone definitions) to calculate feedstock properties without requiring direct flow rate measurements. The multi-zone model acts as a mediator between input feedstock properties and pump-out properties, resolving the contradiction by maintaining measurement precision through computational estimation while improving ease of operation by eliminating complex flow measurements.
3Device complexity
If perfect blending is assumed, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
Instead of assuming perfect blending throughout the tank, the model segments the tank into multiple zones that represent different feedstock layers with potentially different properties. The pump-out properties are determined by identifying the active zone(s) at the pump outlet location, which may involve only one zone or a combination of zones. This approach improves manufacturing precision by accounting for stratification effects while keeping the model manageable through clear zone definitions and systematic property calculation methods.
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
This approach enables more accurate control of batch process product quality by accurately determining the properties of the pump-out feedstock, even without measuring flow rates or assuming perfect blending, thereby improving process control and product consistency.
Implementation Method 1
The model may include a projection of the properties describing a storage tank layer (or zone) of input material into the model. For each new load of storage tank input feedstock, model zones may be shifted and the zone from which the feedstock is drawn into a reactor (i.e., the zone including the pump out feedstock) may be updated with the properties from the new load.
Implementation Method 2
The feedstock in the pump out zone may be partially mixed with other feedstock in the storage tank
Data Source
AI summary
In a batch process control system employing storage tanks without mixers, properties of the storage tank pump out feedstock may be modeled to more accurately control the quality of a process. This model may not require the measurement of input or pump out flow or assume perfect blending. Rather, the developed model may assume that feedstock input into a storage tank may remain layered with some mixing due to continuous convection, turbulence during loading, or other factors. The model may include a projection of the properties describing a storage tank layer of input material into the model. For each new load of storage tank input feedstock, model zones may be shifted and the zone from which the feedstock is drawn may be updated with the properties from the new load.