Remote tutorials were designed and performed to demonstrate color appearance phenomena to students. Results suggest that remote lab demonstrations can provide an alternative to in-person lab sessions with caveats and offer additional benefits.
Circadian metrics quantify the non-image forming effects of light. Circadian metrics are based on the spectral power distribution (SPD) and intensity of a light source and human visual and non-image forming response to optical radiation. However, circadian metrics can only estimate static SPDs. Multi-primary LED systems generate a vast number of SPD combinations. A single metric cannot characterize the metric variation enabled by tunable solid-state lighting devices. There are no known metrics to quantify the capabilities of tunable lighting systems in terms of circadian metrics. A three-dimensional metric is proposed to quantify the variability in circadian metrics. The dimensions of the proposed circadian metric variability (CMV) are (a) a circadian metric, (b) energy efficiency metric, and (c) a lighting quality metric. Sample CMV measures are provided by generating SPDs in a seven-channel tunable lighting system at 20% dimming steps. Resulting in 279,936 test SPD combinations are filtered for nominal “whiteness” according to ANSI C78.377-2017 specifications. Each dimension of CMV is discretized by rounding the metric to significant figures. Each discretized unit of the CMV space can be considered significant or detectable different. The total volume of CMV represents the number of unique SPDs that can be created within a multi-primary LED system. A graphical representation of CMV shows the interrelation between different measures. CMV quantifies variation at the product level rather than in-situ variability of biological stimuli.
The spectral power distribution of light sources can be optimized to achieve optimal target goals, such as energy efficiency, color quality, and circadian synchronization. Although several researchers investigated the optimization of light sources for circadian and color rendition metrics, the complex relationship and trade-offs between three distinct parameters (circadian, color rendition, and energy efficiency metrics) have not been widely investigated. Here, multilevel analyses of four clusters of metrics (radiometric, photometric, colorimetric, and circadian) have been conducted. Metric correlation analysis was conducted for 308 theoretical and commercially available light sources, and results suggest that melanopic irradiance correlates highly with irradiance but does not correlate well with correlated color temperature. There was a negative but weak correlation between circadian metrics and energy efficiency measures. Energy efficiency and color quality were inversely correlated. In the following analysis, the spectra of an 18-channel LED system were optimized using a multi-objective genetic algorithm in several combinations, and the effect of the number and the order of the optimization parameters on metric relationships were analyzed. The number of optimization parameters significantly affected the optimal results. The order of optimization parameters only changed the relationship between color fidelity index and luminous efficacy of radiation but did not have an impact on the color fidelity index and melanopic radiance relationship. There was an inverse relationship between melanopic irradiance and the luminous efficacy of radiation. Trade-off analysis highlights the importance of the order and number of target parameters in the optimization process.
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