Liquid Pressure Recovery Factor (FL) Prediction using Autonomous Valve CFD
Watch this webinar to discover how Autonomous Valve CFD enables fast, accurate performance evaluation and optimization of concentric, double offset, and triple offset butterfly valves using fully autonomous simulations—delivering standards-aligned results without the need for advanced CFD expertise.
The liquid pressure recovery factor (FL) is a critical parameter in valve design, governing flow capacity under choked flow conditions and directly influencing cavitation performance, pressure recovery, and overall valve reliability. Since FL depends heavily on the internal geometry of the valve, accurately predicting it is essential for designing efficient and robust flow control solutions.
Traditionally, determining (FL) requires extensive flow loop testing as defined in ANSI/ISA-75.02.01 standards. While reliable, these experimental methods are time-consuming, costly, and offer limited visibility into internal flow phenomena such as pressure distribution and cavitation inception. Designers often rely on limited data points, making it difficult to fully optimize valve geometry and flow paths. However, conventional CFD workflows, while insightful, require significant expertise, complex setup, and high computational resources, restricting their widespread adoption.
This upcoming technical webinar focuses on how Autonomous Valve CFD simplifies and automates the prediction of (FL) through validated simulation workflows. Using advanced simulation techniques to capture flow behavior and cavitation characteristics, the platform enables accurate, fast, and scalable analysis—empowering engineers to make informed design decisions and optimize valve performance.
What You’ll Learn
Understand the significance of liquid pressure recovery factor (FL) and its impact on cavitation and valve performance.
Learn how CFD is used to determine flow capacity, incipient cavitation, and choked flow conditions.
Explore how Autonomous Valve CFD automates simulations for accurate (FL) prediction.
Who should attend?
Valve Design Engineers looking to improve cavitation performance and optimize valve geometry.
Valve Manufacturers aiming to reduce dependence on physical testing and accelerate product development.
CFD Engineers interested in automated, cloud-based CFD workflows.
Featured Speakers
Akshay Dorle
Business Manager - simulationHub
Akshay is the Business Manager for Autonomous Valve CFD (AVC) at simulationHub, CCTech’s specialized CFD platform for valve design and analysis. With over three years of experience at CCTech, he now leads client engagement, technical guidance, and product support for AVC. Akshay works closely with valve manufacturers and engineering teams to ensure successful adoption and meaningful results. He holds a Master’s degree in Mechanical Engineering from NIT Silchar and combines deep CFD knowledge with a strong focus on customer success and product growth. Akshay handles everything from client onboarding and technical discussions to product support and long-term relationship building
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