System and Method for Calculation of Thermodynamic Properties from Anomalous Reference Data
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Solution Overview
Problem
Existing thermodynamic property models for multicomponent refrigerant mixtures suffer from anomalous and noisy reference data, leading to inaccuracies and computational inefficiencies, which affect the performance of vapor compression systems.
Innovation Solution
A method to clean anomalous reference data by identifying and replacing anomalous points with estimated values, using domain-informed knowledge, and constructing interpolation functions with optimal coefficients for accurate and efficient thermofluid property calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If thermodynamic property models use reference data from iterative methods, then they can handle multicomponent refrigerant mixtures, but the reference data contains anomalies and noise that reduce accuracy
Solution Approach 1:
The patent applies preliminary action by detecting and correcting anomalies in reference data before constructing the thermodynamic property model. The system identifies anomalous data points using statistical methods and replaces them with corrected values, ensuring that the reference data is clean and accurate before being used to build the interpolation model. This preliminary correction step prevents anomalies from propagating into the final model, thereby improving accuracy while maintaining the ability to handle multicomponent mixtures
Solution Approach 2:
The patent introduces an intermediary data correction layer between the iterative method output and the thermodynamic model construction. This intermediary step uses statistical anomaly detection and correction algorithms to filter out noise and anomalies from the reference data, acting as a mediator that transforms raw iterative method output into clean, reliable reference data suitable for accurate model building
2Productivity
If thermodynamic property models are built from reference data with anomalies, then they can be constructed quickly, but the computational efficiency and accuracy of simulations are reduced
Solution Approach 1:
The system performs preliminary anomaly detection and correction on reference data before model construction, ensuring that the data used for building interpolation models is clean and consistent. This preliminary step maintains computational efficiency by using automated statistical methods to identify and correct anomalies quickly, while simultaneously improving the reliability and consistency of simulation results by eliminating data quality issues that would otherwise cause inconsistent system behavior
3Quantity of substance
If iterative methods are used to generate reference property data, then comprehensive thermodynamic data can be obtained, but the data contains errors that affect control and optimization accuracy
Solution Approach 1:
The patent applies the extraction principle by identifying and removing anomalous data points from the comprehensive reference data set generated by iterative methods. The system uses statistical anomaly detection to extract only the reliable, accurate data points while discarding erroneous ones, then uses this cleaned subset to construct the thermodynamic property model. This selective extraction maintains the comprehensiveness of the data coverage while eliminating accuracy-reducing errors
Solution Approach 2:
The system introduces an intermediary data filtering layer that processes the comprehensive reference data from iterative methods. This intermediary step uses statistical methods to identify and correct anomalies while preserving the overall data coverage and structure, thereby maintaining the completeness of thermodynamic data while improving the accuracy of individual property values
Data Source
AI summary
A system controls a vapor compression system containing multicomponent refrigerant mixture by modifying the actuator commands via an output interface, that realizes thermofluid property functions and their derivatives as interpolation functions constructed from anomalous reference thermodynamic property data. The system includes an interface configured to receive measurement data from sensors, a memory configured to store thermofluid property data and computer-executable programs including interpolation functions, and a processor for performing the computer-implemented method. The processor is configured to take as input two thermofluid property variables, and compute using interpolation functions a third thermofluid property variable and its derivatives with respect to input thermofluid property variables. Interpolation functions are constructed from anomalous reference thermodynamic property data by eliminating and replacing anomalous data points with estimated values matching expected physical properties of the fluid using domain-informed knowledge and using cleaned anomaly-free property data for calculating optimal coefficients of the interpolation functions.