Local Property Model Taylor Series Update Mechanism
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Solution Overview
Problem
Existing methods for simulating complex industrial systems, such as power generation and chemical processing, face inefficiencies in computing thermodynamic property and phase equilibrium characteristics due to the need for frequent updates of local models, which can lead to unnecessary computations or insufficient updates, especially when dealing with non-linear properties and complex thermodynamic equilibrium equations.
Innovation Solution
A method using comprehensive local property models that apply a Taylor series expansion to thermodynamic equations, allowing for automatic updates based on second-order terms and phase transition detection, reducing unnecessary computations by only updating when significant changes occur, and utilizing bi-level programming techniques to simplify complex mathematical expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If local models are updated frequently based on confidence delta threshold, then simulation accuracy is improved, but computational burden increases
Solution Approach 1:
The patent applies partial action by selectively updating local models only when necessary. Instead of continuously updating all models, the system evaluates the confidence delta threshold and updates only those models where the threshold is exceeded, performing a subset of the maximum possible updates to achieve sufficient accuracy while reducing computational burden
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring the confidence delta threshold and using this information to dynamically control model updates. The system measures the deviation from reference conditions and adjusts update frequency based on this feedback, ensuring accuracy is maintained only when and where needed
2Productivity
If Taylor series expansion is used to approximate thermodynamic functions, then computational burden is reduced, but accuracy deteriorates
Solution Approach 1:
The patent uses partial action by applying Taylor series expansion only within the valid local model region where the approximation remains accurate. The system calculates the expansion around a reference point and uses it only when the current state remains within the confidence delta threshold, avoiding excessive approximation that would compromise accuracy
Solution Approach 2:
The patent dynamically changes parameters by switching between Taylor series approximation and full thermodynamic calculations based on the confidence delta threshold. When the threshold is not exceeded, the simplified Taylor series parameters are used; when exceeded, the system transitions to more accurate but computationally intensive full calculations
3Device complexity
If independent updating of temperature, pressure, and composition models is performed, then model simplicity is maintained, but unnecessary updates occur for linear properties
Solution Approach 1:
The patent merges the updating logic for temperature, pressure, and composition models by introducing a unified confidence delta threshold mechanism. Instead of independently tracking each parameter's update conditions, the system combines their evaluation into a single threshold-based decision process that determines whether any model update is necessary, reducing redundant updates for linear properties
Data Source
AI summary
A method of estimating a thermophysical property of a fluid using a local model is disclosed herein. The method includes generating, for use within the local model, a series expansion of thermodynamic equations relating to the thermophysical property and one or more derivatives involving the thermophysical property. The method further includes evaluating, based upon a set of specified values of parameters of the fluid, a first order term of the series expansion and a second order term of the series expansion. The values of the first order term and the second order term are then compared. A value of the thermophysical property is then automatically updated when the values of the first order term and the second order term are found to differ by more than a predefined amount.