Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering
Andrew Ortiz - Seward County Community College
Co-Author(s): Fred Hasler and Dan Weisenberger, Kansas State University, Manhattan, KS
As an Architectural Engineer, you have to be able to accomplish different tasks in different areas, such as Mechanical, Electrical, and Plumbing (MEP). In those areas the most problematic of them is commonly the lighting area because, the hand calculations are not extremely accurate due to only finding the average illuminance levels. In this research study a program called AGI32, developed by Lighting Analysts Inc will be used. AGI32 is a computational program that performs numerical point-by-point calculations of incident direct or reflected light on any real surface or imaginary plane. The reason for using AGI32 is that it helps predict or quantify the distribution of artificial or natural light in any environment. It is also easier and faster because, the program does all the rigorous hand calculations in a lot less time than it would take to do the calculations by hand. AGI32 references its calculation data back to the Illuminating Engineering Society (IES), which is a society that is made up of volunteers representing varied viewpoints and interests to achieve consensus on lighting recommendations. IES created a standardized lighting reference book, which includes recommended illuminance levels for a specific task. The research focus is to use a software called AGI32 to model a lighting system for a particular room on the K-State campus. In modeling the lighting system there are many things to take into consideration. Calculation points is one of the most important aspects of AGI32 modeling. When creating calculation grids, illumination accuracy is a key component. The location of the calculation points is important because, they need to be on the area where you will be performing the tasks, so that you can calculate if there is enough illumination. To create a more accurate calculation grid the distance between points is small, because if the points are closer together there will be an accurate representation of the model. In conclusion, AGi32 properly was able to model the given space and compare its results to the recommendations of IES. The program also created a 3D rendering of the space to show an owner what it will look like when it is finished, before it is actually constructed.
Funder Acknowledgement(s): National Science Foundation; Kansas Louis Stokes Alliance for Minority Participation, 1305059
Faculty Advisor: Fred Hasler, Fhasler@k-state.edu