A Systems Approach to High Performance Buildings: A Computational Systems Engineering R&D Program to Increase DoD Energy Efficiency

Abstract

Retrofitting the existing building stock represents the largest and fastest way to reduce energy consumption for the DoD. However the current retrofit delivery process is manually intensive and expensive, focused on equipment selection for initial cost and not energy performance, and the design tools are not amenable to systems solutions that have the potential for substantially reducing energy consumption in buildings. Systems methodology and tools are necessary to deliver deep retrofits, i.e. significantly higher energy performance in existing buildings than is achievable by the current retrofit process. The report describes newly developed screening methodology and tools for early assessment of deep retrofit potential across the entire DoD stock of 250,000 buildings, use of sensitivity and uncertainty analysis tools to isolate critical design parameters and establish performance bounds during design, and reduced-order modeling tools for highly energy efficient building system control design. Validated tools were developed, and retrofit system options that can reduce energy consumption by 30-50% have been identified with existing DoD building use cases.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2012
Accession Number
ADA559156

Entities

People

  • Amit Surana
  • Angela Lewis
  • Bryan Eisenhower
  • Eugene Cliff
  • Igor Mezić
  • Jeff Borggaard
  • Jeff Seewald
  • John A. Burns
  • Kevin J Otto
  • Niranjan Desai
  • Paul Ehrlich
  • Russell Taylor
  • Satish Narayanan
  • Shui Yuan
  • Slaven Peles
  • Sunil K. Ahuja
  • Vladimir A. Fonoberov
  • Zheng O'neill

Organizations

  • United Technologies Corporation

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Energy Conservation
  • Energy Consumption
  • Engineers
  • Failure Mode And Effect Analysis
  • Fluid Dynamics
  • Heat Transfer
  • Load Monitoring
  • Mathematical Filters
  • Mathematical Models
  • Statistical Analysis
  • Systems Engineering
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Energy Conservation and Renewable Energy Engineering.
  • Software Engineering