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X-WR-CALDESC:Events for National Institute of Building Sciences
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DTSTART;TZID=UTC:20250409T130000
DTEND;TZID=UTC:20250409T140000
DTSTAMP:20260430T222452
CREATED:20250428T135104Z
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SUMMARY:Using Urban Building Stock Digital Twins to Streamline Building Retrofit Planning for Urban Energy Efficiency and Resilience
DESCRIPTION:Rapid retrofitting of America’s existing building stock is of urgent national interest to improve energy efficiency and resilience. But how can cities plan for this significant transition with limited funding\, data\, resources\, and time? \nThis session introduces a practical and scalable Urban Building stock digital twin for energy modeling developed by the Environmental Systems Lab at Cornell University. Designed to operate on widely available data\, the model delivers robust\, city-scale building physics models for predicting building energy use and thermal response in power outages. The digital twin platform analyzes existing energy consumption patterns. It predicts future energy consumption trends\, allowing users to evaluate the impact of electrification\, building retrofits\, and extreme weather events on energy demand and emissions. It also enables cost and incentive modeling\, helping cities and utilities assess financial feasibility and prioritize retrofit strategies. The session features a real-world case study from Ithaca\, NY\, the first U.S. city to commit to 100% building decarbonization and community-wide carbon neutrality. Within the session\, we will provide pointers on how to scale this work to other communities. \n\nLearning Objectives\n\n\n\n\nIdentify key public data required to build city-scale energy simulation models and recognize how these models can be improved using city-specific or private datasets.\nUnderstand how Urban Building Energy Modeling (UBEM) serves as an effective tool to analyze existing energy consumption patterns and predict future energy trends.\nExplore how UBEMs could inform energy policy\, guide decarbonization planning\, and prioritize retrofit interventions by providing detailed and accurate information about building retrofit potential\, upgrade costs\, and incentives eligibility.\nLearn from real-world UBEM applications based on a case study from Ithaca\, NY\, the first U.S. city to commit to full building decarbonization.
URL:https://nibs.org/event/using-urban-building-stock-digital-twins-to-streamline-building-retrofit-planning-for-urban-energy-efficiency-and-resilience/
CATEGORIES:Building Innovation Webinar Series
LOCATION:
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DTSTART;TZID=UTC:20250424T120000
DTEND;TZID=UTC:20250424T130000
DTSTAMP:20260430T222452
CREATED:20250428T134803Z
LAST-MODIFIED:20250428T134803Z
UID:10000072-1745496000-1745499600@nibs.org
SUMMARY:Cognitive Digital Twins: A Roadmap for Evolving Operations and Maintenance in the Age of AI
DESCRIPTION:In this session\, TwinKnowledge will discuss a new type of digital twin that has emerged with AI\, cognitive digital twins (CDTs)\, and their implications for the AECO industry. \nCognitive digital twins enable O&M workflows that are supported end-to-end by AI. They are built on top of existing digital twins; they use AI to make sense of digital twin data\, generate insights such as anomaly detection and predictive maintenance for better decision-making/planning\, and combine information from scattered O&M documents to generate response plans for maintenance activities. \nTwinKnowledge will discuss what CDTs are\, why they are so valuable for O&M\, how they build on top of current digital twin systems\, and a general roadmap for where to start in evolving existing digital twin systems into cognitive digital twins. \n\nLearning Objectives\n\n\n\n\nWhat Is a cognitive digital twin (CDT)?\nWhy CDTs are so valuable for O&M\nHow CDTs work within current digital twin systems\nWhere any company can start with integrating CDT capabilities
URL:https://nibs.org/event/cognitive-digital-twins-a-roadmap-for-evolving-operations-and-maintenance-in-the-age-of-ai-2/
CATEGORIES:Building Innovation Webinar Series
LOCATION:
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