A Commercial-Grade, Scalable Support and Training Services Platform

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0012054
Agency Tracking Number: 212802
Amount: $149,554.00
Phase: Phase I
Program: SBIR
Awards Year: 2014
Solicitation Year: 2014
Solicitation Topic Code: 03c
Solicitation Number: DE-FOA-0001046
Small Business Information
2549 Irving Street, Denver, CO, 80211-4540
DUNS: 070203477
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Peter Ellis
 () -
Business Contact
 Peter Ellis
Title: Mr.
Phone: (303) 895-5246
Email: peter.ellis@bigladdersoftware.com
Research Institution
The Department of Energy has funded the development of two industry-leading simulation enginesEnergyPlus and Radiancewhich are regarded in the US as the state of the art in modeling capabilities and accuracy. Despite being the most powerful engines in their respective areas, both are lagging behind in adoption compared to less capable tools. One significant factor limiting widespread adoption is a lack of high-quality, readily-available support and training services for both engines. The objective in Phase I is to research, develop, and pilot a prototype platform for providing commercial-grade, scalable support and training services for EnergyPlus and Radiance. The overall approach is to develop a platform composed of standardized systems and processes that leverage automation and web-based resources in order to deliver services at a low cost. Several support tasks will be researched and developed including a subscription-based support service, web-based documentation resources, and a question- and-answer web site. Several training tasks will be researched and developed including a new training workshop for EnergyPlus, a train-the-trainer program, and a web-based training resource. Commercial Applications and Other Benefits: The primary commercial application is to market for-pay services under a subscription model or pay-per-event model. Organizations will benefit from a decrease in the cost of modeling. The nation will benefit from increased uptake and adoption of accurate, powerful modeling engines that lead to identifying more opportunities for saving energy.

* Information listed above is at the time of submission. *

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