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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Virtual Light Sensing Technology for Fast Calculation of Daylight Autonomy Metrics.

Sergey Ershov1, Vadim Sokolov1,2, Vladimir Galaktionov1

  • 1Keldysh Institute of Applied Math RAS, 125047 Moscow, Russia.

Sensors (Basel, Switzerland)
|February 28, 2023
PubMed
Summary

This study presents a fast virtual sensing method for calculating Daylight Autonomy metrics, essential for architectural design. The efficient approach accurately simulates annual sunlight exposure and spatial Daylight Autonomy, optimizing building energy performance.

Keywords:
Annual Sunlight ExposureDaylight Autonomyblinds controllighting simulationspatial Daylight Autonomyvirtual light sensing technology

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Area of Science:

  • Building Science and Architecture
  • Computational Simulation and Modeling
  • Sustainable Design and Energy Efficiency

Background:

  • Virtual sensing technology offers a computational alternative to physical measurements in architectural design.
  • Accurate daylight analysis is crucial for energy-efficient building design, necessitating efficient simulation methods.
  • Key metrics like Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) require extensive annual simulations.

Purpose of the Study:

  • To develop and present a computationally efficient method for calculating Daylight Autonomy metrics.
  • To ensure the accuracy and practicality of the proposed method for complex architectural models.
  • To incorporate an automated sensing area definition and an optimization procedure for blinds control within the simulation.

Main Methods:

  • Implementation of a novel algorithm for the fast calculation of Daylight Autonomy metrics.
  • Global illumination simulations performed hourly for an entire year.
  • Development of an original algorithm for automatic sensing area setting and an optimization procedure for blinds control based on overexposure.

Main Results:

  • The proposed method demonstrates good agreement with straightforward calculations and existing solutions, validating its accuracy.
  • The method achieves significantly higher computational efficiency, enabling calculations within a reasonable timescale.
  • The integrated blinds control optimization enhances the practical application of sDA calculations.

Conclusions:

  • The developed method provides an accurate and efficient solution for annual daylight performance simulations in architectural projects.
  • This approach facilitates multiple daylight metric calculations during project development, supporting energy-saving design decisions.
  • The automated features and blinds control optimization represent advancements in virtual sensing for sustainable architecture.