Optimizing Sustainability and Space: Emory University's Campus Life Center Transformation

Emory University Campus Life Center

Emory University Campus Life Center

Architect: Duda Paine Architects

MEP Engineers: IMEG Corp

Contractor: Holder Construction

Consultants: Pattern

Correlated Analysis to Design Phase

Climate Analysis

Pre-Design and Concept Design

Energy Analysis

Concept Design and Schematic Design

Daylight and Glare Analysis

Schematic Design & Design Development

Facade Studies

Design Development & Construction Drawings

Water Use Analysis

Concept Design and Schematic Design

Cost v. Energy Optimization

Design Development & Construction Drawings

Project Overview

At 117,00 sq. ft., the Campus Life Center on the Emory University campus caters to the growing space demands, allows flexibility and efficient dining services, technology and infrastructure upgrades, and more room for student organizations and gathering space. With the University’s commitment to sustainability, the Campus Life Center has high performance targets.

Climate Analysis

Climate Data – A basic understanding of the existing climate conditions is vital for making performance design decisions. The following climate studies are created `automatically using cove.tool.​​

climate analysis in cove.tool

Energy Analysis

A basic understanding of target values is key to comparing performance design decisions.

EUI – Expressed as energy per square foot per year, knowing the EUI values of design decisions and  other iterations, one can get the best value for performance. Below the design team used cove.tool to find their buildings benchmarks in order to inform and guide the team towards setting their own energy targets. The USA national median for EUI was 51 kBtu/sqft/yr

energy analysis in cove.tool

Daylight and Glare Analysis

Daylight quantity and quality is a critical part of any building. It becomes especially critical when studying a campus center with students. Many studies have linked daylight to productivity and wellness. cove.tool allowed the team to use the Revit model export for the following daylight and glare studies.

daylight and glare analysis in cove.tool

Facade Studies

The ability to rapidly test out varying facade design and compare glazing percentage, overhangs vs fins, window sizes and location was critical for the facade design. The below study created using cove.tool’s rapid facade prototyping features allows users to do that in minutes.

facade studies in cove.tool

Water Use Analysis

Being a part of the campus meant studying not just indoor water use for low flow fixtures, but also outdoor water use. This meant grey water re-use strategies, storm water capture, rain water  harvesting, irrigation and more. The cove.tool water feature had not been launched at the time of this project. This feature allows users to study indoor and outdoor water use for their project as shown  below.

water use analysis in cove.tool

Cost v. Energy Optimization

Being a integrated team with the contractors on board at early stages of design, cost was a critical component of decision making throughout the design. This cost was able to be optimized using cove.tool. cove.tool uses advanced algorithms to optimize for first cost and assists in making rigorous metric based decisions on cost and energy.

optimization analysis in cove.tool

As seen in the diagram above, many decisions including, window type, wall insulation, roof insulation, HVAC, Photovoltaic panels, shading strategy and sensors had multiple options that needed to be tested. This leads to over 20,000 possible combinations, each with a different energy use and a different cost. cove.tool allowed studying these to discover the most cost optimal way to get to the best performance.

optimization analysis in cove.tool

​​​In the graph above, each vertical line represents one decision. The blue line represents every possible combination and these can be filtered based on potential LEED points, EUI, Energy Savings, Payback and First Cost Premiums. For a project with a target payback less than 10 years and EUI target of 45 or below.

Optimization analysis in cove.tool

The design team used cove.tool to find the absolute lowest cost option.

Resources

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