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Processes
Volume 13
Issue 10
10.3390/pr13103289
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Comprehensive Approach to Identifying the Parameters of a Counterflow Heat Exchanger Model Based on Sensitivity Analysis and Regularization Methods

by
Salimzhan Tassanbayev
,
Gulzhan Uskenbayeva
*,
Aliya Shukirova
*,
Korlan Kulniyazova
and
Igor Slastenov
Department of System analysis and Control, L. N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan
*
Authors to whom correspondence should be addressed.
Processes 2025, 13(10), 3289; https://doi.org/10.3390/pr13103289
Submission received: 27 August 2025 / Revised: 1 October 2025 / Accepted: 13 October 2025 / Published: 14 October 2025
(This article belongs to the Special Issue Artificial Intelligence-Based Analytics for Data-Driven Decision-Making in Industrial Process Engineering)
Versions Notes

Abstract

The study presents a robust methodology for simultaneous state and parameter estimation in nonlinear thermal systems, demonstrated on a counter-current heat exchanger model operating with nitrogen under industrial conditions. To address challenges of ill-conditioning and parameter correlation, local sensitivity analysis is combined with regularization through optimal parameter subset selection using orthogonalization and D-optimal experimental design. The Unscented Kalman Filter (UKF) is employed to jointly estimate the augmented state vector in real time, leveraging high-fidelity dynamic simulations generated in Unisim Design with the Peng–Robinson equation of state. The proposed framework achieves high estimation accuracy and numerical stability, even under limited sensor availability and measurement noise. Monte Carlo simulations confirm robustness to ±2.5% uncertainty in initial conditions, while residual autocorrelation analysis validates estimator optimality. The approach provides a practical solution for real-time monitoring and model-based control in industrial heat exchangers and offers a generalizable strategy for building identifiable, noise-resilient models of complex nonlinear systems.
Keywords: Kalman filter; simultaneous estimation; identifiability; sensitivity; regularization Kalman filter; simultaneous estimation; identifiability; sensitivity; regularization

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MDPI and ACS Style

Tassanbayev, S.; Uskenbayeva, G.; Shukirova, A.; Kulniyazova, K.; Slastenov, I. A Comprehensive Approach to Identifying the Parameters of a Counterflow Heat Exchanger Model Based on Sensitivity Analysis and Regularization Methods. Processes 2025, 13, 3289. https://doi.org/10.3390/pr13103289

AMA Style

Tassanbayev S, Uskenbayeva G, Shukirova A, Kulniyazova K, Slastenov I. A Comprehensive Approach to Identifying the Parameters of a Counterflow Heat Exchanger Model Based on Sensitivity Analysis and Regularization Methods. Processes. 2025; 13(10):3289. https://doi.org/10.3390/pr13103289

Chicago/Turabian Style

Tassanbayev, Salimzhan, Gulzhan Uskenbayeva, Aliya Shukirova, Korlan Kulniyazova, and Igor Slastenov. 2025. "A Comprehensive Approach to Identifying the Parameters of a Counterflow Heat Exchanger Model Based on Sensitivity Analysis and Regularization Methods" Processes 13, no. 10: 3289. https://doi.org/10.3390/pr13103289

APA Style

Tassanbayev, S., Uskenbayeva, G., Shukirova, A., Kulniyazova, K., & Slastenov, I. (2025). A Comprehensive Approach to Identifying the Parameters of a Counterflow Heat Exchanger Model Based on Sensitivity Analysis and Regularization Methods. Processes, 13(10), 3289. https://doi.org/10.3390/pr13103289

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