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Long Edge Of Deltoidal Icositetrahedron Given Volume Calculator

Formula Used:

\[ Long\ Edge = \left( \frac{7 \times Volume}{2 \times \sqrt{292 + 206 \times \sqrt{2}}} \right)^{\frac{1}{3}} \]

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1. What is the Long Edge of Deltoidal Icositetrahedron?

The Long Edge of Deltoidal Icositetrahedron is the length of the longest edge of the identical deltoidal faces that make up this polyhedron. It is an important geometric measurement in understanding the structure and properties of this specific shape.

2. How Does the Calculator Work?

The calculator uses the mathematical formula:

\[ Long\ Edge = \left( \frac{7 \times Volume}{2 \times \sqrt{292 + 206 \times \sqrt{2}}} \right)^{\frac{1}{3}} \]

Where:

Explanation: This formula derives the long edge length from the volume of the deltoidal icositetrahedron using mathematical constants and operations.

3. Importance of Long Edge Calculation

Details: Calculating the long edge is essential for geometric analysis, structural design applications, and understanding the spatial properties of this specific polyhedral shape in mathematical and engineering contexts.

4. Using the Calculator

Tips: Enter the volume of the deltoidal icositetrahedron in cubic meters. The value must be positive and valid for accurate calculation.

5. Frequently Asked Questions (FAQ)

Q1: What is a Deltoidal Icositetrahedron?
A: A Deltoidal Icositetrahedron is a Catalan solid with 24 deltoidal (kite-shaped) faces, 26 vertices, and 48 edges.

Q2: How accurate is this calculation?
A: The calculation is mathematically precise based on the derived formula, with accuracy depending on the precision of the input volume value.

Q3: What units should I use for volume?
A: Volume should be entered in cubic meters, though the formula works with any consistent unit system.

Q4: Can this formula be used for other polyhedra?
A: No, this specific formula applies only to the deltoidal icositetrahedron due to its unique geometric properties.

Q5: What if I get an error in calculation?
A: Ensure the volume value is positive and within reasonable limits. Extremely large or small values may cause computational limitations.

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