K_TO_CV

Overview

Convert loss coefficient (K) to imperial valve flow coefficient (Cv).

Excel Usage

=K_TO_CV(K, D)

• K (float, required): Loss coefficient [-]
• D (float, required): Inside diameter of the valve [m]

Returns (float): Imperial Cv valve flow coefficient [gallons/minute]

Examples

Example 1: Basic K to Cv conversion

Inputs:

K	D
16	0.015

Excel formula:

=K_TO_CV(16, 0.015)

Expected output:

Result
2.6012

Example 2: Small K value

Inputs:

K	D
1	0.025

Excel formula:

=K_TO_CV(1, 0.025)

Expected output:

Result
28.9025

Example 3: Large K value

Inputs:

K	D
100	0.05

Excel formula:

=K_TO_CV(100, 0.05)

Expected output:

Result
11.561

Example 4: Small valve diameter

Inputs:

K	D
10	0.01

Excel formula:

=K_TO_CV(10, 0.01)

Expected output:

Result
1.4624

Python Code

import micropip
await micropip.install(["fluids"])
from fluids.fittings import K_to_Cv as fluids_k_to_cv

def k_to_cv(K, D):
    """
    Convert loss coefficient (K) to imperial valve flow coefficient (Cv).

    See: https://fluids.readthedocs.io/fluids.fittings.html#fluids.fittings.K_to_Cv

    This example function is provided as-is without any representation of accuracy.

    Args:
        K (float): Loss coefficient [-]
        D (float): Inside diameter of the valve [m]

    Returns:
        float: Imperial Cv valve flow coefficient [gallons/minute]
    """
    try:
        K = float(K)
        D = float(D)
    except (ValueError, TypeError):
        return "Error: K and D must be numbers."

    if K <= 0:
        return "Error: K must be positive."
    if D <= 0:
        return "Error: D must be positive."

    try:
        result = fluids_k_to_cv(K=K, D=D)
        return float(result)
    except Exception as e:
        return f"Error: {str(e)}"

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