Adjoint Sensitivity Calibration for Complex Flow Systems
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Solution Overview
Problem
Current methods for calibrating complex flow systems, such as river networks, are inefficient and resource-intensive, relying on human expertise and random or direct sensitivity calculations, which can be time-consuming and require significant computational resources.
Innovation Solution
A method involving the computation of adjoint sensitivity for each node in the system, based on comparisons between model outputs and observed values, to adjust coefficients and iteratively refine the model's accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct sensitivity calculations or random methods are used for calibration, then human expertise and intervention are required, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent implements an automated feedback mechanism where model outputs are continuously compared with observed values, and adjoint sensitivity calculations automatically generate corrections to coefficients. This closed-loop feedback system eliminates the need for human intervention in the calibration process while maintaining high model accuracy through iterative refinement.
Solution Approach 2:
The calibration system performs self-correction by automatically computing adjoint sensitivities and adjusting coefficients without human expertise. The model calibrates itself through the automated computation of sensitivity derivatives and iterative coefficient adjustment, making the process independent of human operators.
2Measurement precision
If direct sensitivity calculations are used for calibration, then model accuracy can be improved, but computational resources are significantly increased
Solution Approach 1:
The patent introduces adjoint sensitivity as an intermediary computational approach that bridges the gap between direct sensitivity calculations and model calibration. Instead of performing computationally expensive direct sensitivity calculations for all parameters, the adjoint method provides an efficient intermediate solution that captures the essential sensitivity information with reduced computational burden.
3Measurement precision
If manual calibration methods are used, then model precision can be adjusted, but extensive human intervention is required
Solution Approach 1:
The calibration system performs self-correction by automatically computing adjoint sensitivities and adjusting coefficients without human expertise. The model calibrates itself through the automated computation of sensitivity derivatives and iterative coefficient adjustment, making the process independent of human operators.
Solution Approach 2:
The patent implements an automated feedback mechanism where model outputs are continuously compared with observed values, and adjoint sensitivity calculations automatically generate corrections to coefficients. This closed-loop feedback system eliminates the need for human intervention in the calibration process while maintaining high model accuracy through iterative refinement.
Data Source
AI summary
Aspects of the present invention provide a solution for calibrating a model of a complex flow system. In an embodiment, a comparison is made between the output from the model and a set of observed values for each of a plurality of nodes in the complex flow system. An adjoint sensitivity is computed for each of the nodes based on the comparison. These computed adjoint sensitivities are used to adjust a set of coefficients of the models. This calibration process can be performed multiple times, periodically and/or continuously to maximize the accuracy of the model.