کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4917544 1428383 2016 43 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Painting with light: An interactive evolutionary system for daylighting design
ترجمه فارسی عنوان
نقاشی با نور: یک سیستم تکاملی تعاملی برای طراحی روزمره
کلمات کلیدی
سیستم های تولیدی مبتنی بر عملکرد، طراحی هدفمند، طراحی نور روز اینترفیس های دیجیتال، بهینه سازی عملکرد ساختمان، معماری پایدار،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Building and Environment - Volume 109, 15 November 2016, Pages 154-174
نویسندگان
, ,