Magnetization Vector Data Compression via Normalized Integer Storage
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Solution Overview
Problem
Computer simulations for magnetic field analysis generate enormous data files due to the use of double-precision floating point numbers for magnetization vectors, leading to increased processing time and storage burdens, especially when visualizing the magnetization state of magnetic substances with a large number of elements.
Innovation Solution
A magnetization vector storing method that acquires saturation magnetization values from a database, divides each component of the magnetization vector by this value, and converts them into integer values for storage, reducing data size and processing time through data compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If double-precision floating point numbers are used for magnetization vectors, then precision is maintained, but data file size becomes enormous and processing time increases
Solution Approach 1:
The patent changes the data representation parameter from double-precision floating point to normalized integer values. By dividing magnetization vector components by saturation magnetization values and storing as integers, the data format is transformed to achieve compact storage while preserving essential information for visualization purposes.
Solution Approach 2:
The patent uses simplified integer representations instead of precise floating point numbers for storage. This disposable approximation approach accepts that full precision is not needed for visualization, allowing much more compact data storage that can be regenerated or reprocessed if higher precision is later required.
2Measurement precision
If double-precision floating point numbers are used for magnetization vectors, then precision is maintained, but processing time increases
Solution Approach 1:
The patent transforms the data parameter from floating point to integer representation, which enables faster processing operations. Integer arithmetic is inherently quicker than floating point arithmetic, and the normalized integer format allows for efficient storage and retrieval without the computational overhead of floating point operations.
3Quantity of substance
If normalization is applied to magnetization vectors, then data size is reduced, but potential precision loss may occur
Solution Approach 1:
The patent applies parameter transformation by normalizing magnetization vectors through division by saturation values and converting to integer format. This change in representation parameters achieves compact storage while maintaining sufficient precision for the intended visualization application, where absolute precision is less critical than efficient data handling.
Data Source
AI summary
A magnetization vector storing method includes: acquiring, by a computer, a saturation magnetization value of a material to be simulated from a database indicating the saturation magnetization value of each material; dividing each component of a magnetization vector indicating a magnetization state of the material to be simulated by the saturation magnetization value; and converting each component of the magnetization vector obtained after the dividing using the saturation magnetization into an integer value and storing the integer value in a storage unit.