Envelope and Window Design for Enhanced Energy Efficiency



Available June 2024

Understanding the critical role of envelope design in determining heating and cooling loads, this lecture delves into various energy-efficient design metrics, and their sensitivity analysis to discern their impact effectively. Participants will gain insights into passive envelope design measures aimed at increasing energy efficiency through strategic leveraging of orientation, shading, thermal properties, and building shape considerations. Additionally, the lecture offers insights into the window glazing properties such as U-factor, Solar Heat Gain Coefficient (SHGC), Visible Transmittance (VT), and emittance. Special emphasis is placed on the advantages of Low-E Glass, particularly in colder climates, enhancing participants' understanding of how such features contribute to energy conservation. Geared towards architects and constructors, this session offers resources for deeper exploration and understanding of envelope design's pivotal role in energy efficiency.

Learning Objective 1: 
Participants will gain insights into passive design factors aimed at increasing energy efficiency through envelope design.
Learning Objective 2: 
Participants will learn the impact of design measures through sensitivity analysis and prioritize them according to building needs and design goals.
Learning Objective 3: 
Participants will be informed of the importance of minimizing thermal bridges on the building envelope and learn tactics to prevent/minimize them.
Learning Objective 4: 
Participants will be able to analyze different glazing specifications to make well-informed decisions aligned with the building's requirements.
Learning Units: 
1 LU
Course Status: 
AIA Course Number: 

Farnaz Nazari
Research Scientist I
In 2023, Farnaz became part of IDL as a research scientist, contributing her expertise to a variety of projects that bridge different fields. Her background centers on the application of artificial intelligence (AI) in architectural design. Additionally, she holds an interest in sustainable building design, energy efficiency, and utilizing machine learning and deep learning in these areas. Currently pursuing a PhD in Construction Science at Texas A&M University, Farnaz holds master’s degrees in Computer Science and Building Physics from Texas A&M University and the University of Tehran, respectively. Her academic path and role at IDL merge to drive innovative research in the realm of technology and sustainable construction.