Venturi cavitation exhibits unique scaling that deviates from power-law relationships of cavitation length of the flows around wedges or hydrofoils derived from potential-flow theory, due to its inherent longitudinal pressure gradients. This study investigates Venturi cavitation flows through controlled blowdown experiments with high-speed visualization. The nondimensional time-averaged cavitation length $L_{\mathrm{cav}}^{*}$ and pressure recovery coefficient $\kappa$ are discussed under varying cavitation number ($\sigma$) and Reynolds number ($\mathrm{Re}$) conditions. Four distinct cavitation patterns [supercavitation (SPR), cloud cavitation, sheet cavitation, and streak cavitation] are identified, with transitions from SPR to noncavitation as $\sigma$ or $\kappa$ increases, resulting in decreasing $L_{\mathrm{cav}}^{*}$. A piecewise mapping relationship between $\sigma$ and $\kappa$ is established, and a combined model using short cavity (for $L_{\mathrm{cav}}^{*}\ll 1$) and extended cavity (for $L_{\mathrm{cav}}^{*}>\frac{h}{(H-h)tan{\theta }_2(tan{\theta }_1+tan{\theta }_2)}$) models with logarithmic smoothing accurately predicts $L_{\mathrm{cav}}^{*}\left(\frac{\sigma +1}{\kappa }\right)$. This approach enables cavitation flow pattern identification and cavity length prediction based on $\sigma \text{−}\kappa$ mapping, providing a practical tool for engineering evaluation across various Venturi geometries.

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• Cavitation
• Flow control
• Multiphase flows