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Painting with light: An interactive evolutionary system for daylighting design

机译:用光绘画:用于日光设计的交互式进化系统

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Painting with Light is a user-guided interactive evolutionary system for daylighting design. It allows architects to use color to specify desired light levels in spaces, and searches for solutions that bring building geometry and materials close to performance targets. The proposed interface addresses a main limitation of generative design systems based on building performance metrics, by allowing the user to specify daylight spatial patterns with a high degree of granularity. This development poses new challenges for both objective function and penalty function definitions. Painting with Light automatically computes and displays statistical indexes that inform the user on the deviation error between the performance of the solution found by the system and the desired targets. The system was implemented in Python on top of a popular Computer-Aided Design software, Rhinoceros, as an add-on to its Visual Programming Language, Grasshopper. This choice of implementation allows access to Grasshopper's built-in functions and methods for 3D parametric modeling, to tools that provide direct access to Radiance, a lighting simulation software, and to different types of genetic algorithms. Five experiments were conducted on a freeform parametric model for progressive system calibration, which encompassed four steps: 1) adjustment of painted targets to fit the problem feasible solution space; 2) devise appropriate weights and penalty factors for the fitness function; 3) test two different evolutionary solvers; 4) test the system's capability to find a predefined solution where the optimal values were known. After calibration, the system was able to produce solutions that closely approximate the painted goals. (C) 2016 Elsevier Ltd. All rights reserved.
机译:“用光绘画”是用于日光设计的用户指导的交互式进化系统。它允许建筑师使用颜色来指定空间中所需的光照水平,并寻找使建筑物的几何形状和材料接近性能目标的解决方案。所提出的界面通过允许用户以高度的粒度指定日光空间模式,从而解决了基于建筑性能指标的生成设计系统的主要局限性。这一发展对目标函数和惩罚函数定义都提出了新的挑战。用光绘画会自动计算并显示统计指标,这些指标会告知用户系统发现的解决方案性能与所需目标之间的偏差误差。该系统是在Python上流行的计算机辅助设计软件Rhinoceros之上实现的,该软件是其可视化编程语言Grasshopper的附加组件。这种选择的实现方式允许访问Grasshopper的内置功能和方法用于3D参数化建模,可以使用提供直接访问Radiance,照明模拟软件以及不同类型的遗传算法的工具。在用于渐进式系统校准的自由参数模型上进行了五个实验,包括四个步骤:1)调整绘制目标以适合问题可行的解决方案空间; 2)为适应度功能设计适当的权重和惩罚因子; 3)测试两个不同的进化求解器; 4)测试系统的能力,以找到已知最佳值的预定义解决方案。校准后,系统能够产生接近绘制目标的解决方案。 (C)2016 Elsevier Ltd.保留所有权利。

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