Window Treatment Fabric Selection for Daylight and Glare Performance
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Solution Overview
Problem
Current window treatments lack consideration for fabric selection based on energy efficiency and occupant comfort, with fabrics typically chosen for aesthetic reasons rather than their performance in controlling daylight and glare.
Innovation Solution
A fabric selector tool that assesses environmental characteristics and fabric performance metrics to recommend optimal fabrics for window treatments, considering factors like daylight glare probability, spatial daylight autonomy, and view clarity, to enhance energy savings and occupant comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fabric is selected based solely on visual aesthetics, then aesthetic appeal is improved, but energy efficiency and occupant comfort deteriorate
Solution Approach 1:
The patent applies preliminary action by calculating and storing fabric performance metrics (daylight glare probability, spatial daylight autonomy, view clarity) in advance for multiple fabrics across different building environments. This pre-computed data is then used by the fabric selector tool to provide immediate recommendations without requiring real-time simulations, thus resolving the contradiction between ease of selection and energy efficiency by making performance-based selection as convenient as aesthetic selection.
2Ease of manufacture
If fabric is selected based solely on visual aesthetics, then aesthetic appeal is improved, but occupant comfort deteriorates
Solution Approach 1:
The patent calculates daylight glare probability, spatial daylight autonomy, and view clarity metrics in advance for each fabric-building environment combination. These pre-computed comfort metrics are stored and readily available to the fabric selector tool, enabling users to select fabrics that optimize occupant comfort without requiring complex real-time analysis, thus resolving the contradiction between ease of selection and glare control.
Solution Approach 2:
The patent introduces fabric performance metrics (daylight glare probability, spatial daylight autonomy, view clarity) as intermediary parameters that mediate between fabric selection and occupant comfort. These metrics serve as quantitative indicators that translate fabric properties and building characteristics into predictable comfort outcomes, enabling informed selection that balances aesthetics with glare reduction and comfort optimization.
3Loss of energy
If fabric performance metrics are calculated for multiple fabrics across different environments, then energy efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating fabric performance metrics for multiple fabrics across different building environments and storing these results for future use. This approach shifts the computational burden to an offline phase, allowing the online fabric selection process to simply retrieve and compare pre-computed metrics rather than performing complex simulations in real-time, thus resolving the contradiction between energy efficiency and system complexity.
4Loss of energy
If automated window treatment control is implemented, then energy savings are improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-determining optimal fabric selections based on building characteristics and performance metrics before automated control is implemented. This upfront optimization reduces the complexity of automated control by eliminating the need for complex real-time decision-making algorithms, as the fabric itself is already optimized for energy performance in the specific building environment, thus resolving the contradiction between energy savings and system complexity.
Data Source
AI summary
A fabric selection tool provides an automated procedure for recommending and/or selecting a fabric for a window treatment to be installed in a building. The recommendation may be made to optimize the performance of the window treatment in which the fabric may be installed. The recommended fabric may be selected based on performance metrics associated with each fabric in an environment. The fabrics may be ranked based upon the performance metrics of one or more of the fabrics. One or more of the fabrics, and/or their corresponding ranks, may be displayed to a user for selection. The recommended fabrics may be determined based on combinations of fabrics that provide performance metrics for various façades of the building. Using the ranking system provided by the fabric selection tool, the user may obtain a fabric sample and/or order one or more of the recommended fabrics.