What question did this study set out to answer?

The research aims to understand how plate breathing affects friction factors in gasketed plate heat exchangers (GPHEs) and to develop predictive models.

March 7, 2026Open Access

Experimental and machine learning-based predictions of thermohydraulic performance in gasketed plate heat exchangers with three corrugated plate geometries

Key Points

The research aims to understand how plate breathing affects friction factors in gasketed plate heat exchangers (GPHEs) and to develop predictive models.
Conducted a systematic experimental investigation of three corrugation patterns: Chevron, Zigzag, and Four-Quadrant.
Tested the patterns at three tightening levels under controlled inlet-pressure differences.
Measured local friction factors, overall heat-transfer conductance, and Nusselt numbers for each channel.
Friction factors showed up to 100% variation between expanded and constricted channels based on geometry and tightening levels.
Heat-transfer performance was more stable, with Nusselt number variations limited to 3–16%.
Predictive models reduced uncertainty by up to 50% compared to classical correlations, with MAPE of 3–9% and MLP model achieving MAPE ≈ 3.5%.

Abstract

Gasketed plate heat exchangers (GPHEs) are widely used in thermal systems, yet substantial discrepancies persist among published friction-factor correlations, even for nominally similar corrugated geometries. A key unresolved cause is plate pack breathing—elastic deformation driven by inlet-pressure asymmetry and tightening—which creates expanded and constricted channels with distinct hydraulic behavior. This work reports a systematic experimental investigation of three corrugation patterns (Chevron, Zigzag, and Four-Quadrant) tested at three tightening levels (0.98 A, 1.00 A, and 1.02 A) under controlled inlet-pressure differences. Local friction factors ( f ), overall heat-transfer conductance ( UA ), and Nusselt numbers ( Nu ) were determined independently for each channel to quantify breathing effects. Results show that friction factors are highly sensitive to deformation: depending on geometry and tightening level, differences on f- values between expanded and constricted channels reach up to 100%, explaining much of the scatter in existing f–Re correlations. In contrast, heat-transfer performance is comparatively robust, with tightening level-induced data dispersion in Nu limited to 3–10% (Chevron), 4–12% (Zigzag), and 3–16% (Four-Quadrant). Predictive models were developed using symbolic regression and a multilayer perceptron (MLP) neural network. The symbolic models achieved mean absolute percentage errors (MAPE) of 3–9%, corresponding to a reduction in prediction uncertainty of up to 50% compared with classical correlations that neglect tightening and inlet-pressure asymmetry. The MLP model showed superior performance, retaining MAPE ≈ 3.5% and strong generalization under Reynolds-range exclusion tests. This study clarifies the causes regarding friction-factor inconsistencies in GPHEs and provides validated predictive tools for operation under asymmetric or non-uniform tightening conditions. • Local friction factors measured in expanded and constricted channels of GPHEs. • Plate breathing shown as key cause of scatter in f–Re correlations. • Nusselt only mildly affected by tightening across all geometries. • Chevron plate shows best overall thermo-hydraulic performance. • Symbolic regression and ANN accurately predict GPHE behavior.

Experimental and machine learning-based predictions of thermohydraulic performance in gasketed plate heat exchangers with three corrugated plate geometries

Key Points

Abstract

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