Liquid Reflection Inclination Sensor Container Design
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Solution Overview
Problem
The existing methods for designing liquid reflection inclination sensors are time-consuming and costly, as they require physical prototypes and repeated testing under various conditions to optimize the container shape for sensor specifications, especially with the demand for downsizing and varying liquid properties and temperature conditions.
Innovation Solution
A method that calculates the liquid surface shape using the Young-Laplace and hydrostatic pressure formulas, performs optical simulations with an imaginary mirror plane, and adjusts the container shape to ensure image accuracy meets sensor specifications, allowing for swift and cost-effective design of a cylindrical container with a minimum size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a physical prototype method is used to optimize container shape, then manufacturing precision can be achieved, but development time and cost increase significantly
Solution Approach 1:
The patent creates a virtual copy of the container and liquid surface in a simulation environment. The container shape is modeled digitally, and the liquid surface is simulated using the Young-Laplace equation to replicate actual physical behavior. This virtual model allows repeated testing and optimization without physical prototypes, maintaining manufacturing precision through accurate simulation while eliminating time-consuming physical iterations.
Solution Approach 2:
The patent replaces the mechanical system of physical prototyping and manual testing with a computational simulation system. The Young-Laplace equation-based liquid surface simulation and optical path tracing algorithms substitute for physical light sources, containers, and detectors. This substitution enables rapid virtual experimentation and optimization of container shapes without the time and resource constraints of physical manufacturing and testing cycles.
2Volume of moving object
If the container size is reduced to meet downsizing demands, then sensor compactness improves, but liquid surface shape stability deteriorates
Solution Approach 1:
The patent performs preliminary simulation analysis to determine the optimal container dimensions before actual manufacturing. By using the Young-Laplace equation to predict liquid surface behavior in small containers and performing optical simulations to assess image quality, the design process identifies container sizes that maintain sufficient liquid surface stability while achieving downsizing goals. This preliminary virtual testing prevents trial-and-error physical prototyping.
Solution Approach 2:
The patent systematically varies container dimension parameters (diameter, height, curvature radius) in the simulation to find the optimal balance between size reduction and liquid surface stability. By changing these geometric parameters in the virtual model and observing their effect on meniscus shape and optical performance, the invention identifies specific parameter ranges that achieve both compactness and stability requirements.
3Adaptability or versatility
If container shape is optimized for different temperature conditions and liquid properties, then sensor adaptability improves, but design complexity increases
Solution Approach 1:
The patent creates a universal simulation framework that can handle multiple liquid types and temperature conditions through a single integrated model. The Young-Laplace equation implementation allows input of different liquid density and surface tension values, while the optical simulation can accommodate various container geometries. This multi-functional simulation system eliminates the need for separate design processes for different conditions, reducing overall design complexity while improving adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the rapid and cost-effective determination of a container shape suitable for sensor specifications, reducing the time and expense associated with optimizing the container size and shape, while maintaining image accuracy across different conditions.
Implementation Method 1
calculates a shape of a liquid surface of a liquid in a horizontal direction 'x' and a vertical direction 'y' by utilizing the Young-Laplace formula and the hydrostatic pressure formula
Implementation Method 2
calculates a shape of a liquid surface of a liquid in a horizontal direction 'x' and a vertical direction 'y' by utilizing the Young-Laplace formula and the hydrostatic pressure formula
Implementation Method 3
obtains a light receiving pattern by reflecting a dark field pattern irradiated from an imaginary light source on an imaginary mirror plane having the shape of the liquid surface
Data Source
AI summary
A method of designing a container of a liquid reflection inclination sensor includes a liquid surface calculating step (S1) that calculates a shape of a liquid surface of a liquid in a horizontal direction “x” and a vertical direction “y” by utilizing the Young-Laplace formula and the hydrostatic pressure formula, the liquid surface formed on a plate extending vertically and infinitely with respect to a horizontal part of the liquid surface, an optical simulation step (S2) that obtains a light receiving pattern by reflecting a dark field pattern (4′) irradiated from an imaginary light source (2′) on an imaginary mirror plane (9a′) having the shape of the liquid surface, and a container adjusting step (S3-S4) that adjusts a shape of a cylindrical container (10) for enclosing the liquid by judging whether image accuracy of the light receiving pattern satisfies demanded sensor accuracy.