Permanent record · RIR–3013
Scalable Urban Energy Modeling for Climate Resilience in Densely Populated Coastal Metropolitan Regions
Urban energy demand is highly sensitive to climate-driven shifts in heating and cooling requirements. This study extends high-performance computing workflows to evaluate energy resilience in diverse urban building stocks.
How can scalable energy modeling workflows be optimized to inform urban climate resilience planning in diverse metropolitan environments?
Knowledge gap
What remains worth asking
The source suggests that while the workflow is effective for Nassau County, it remains useful to test its transferability to different urban typologies and climate zones.
Potential contribution
Why it may matter
Improved modeling accuracy supports targeted grid decarbonization and energy efficiency policies in urban areas.
Academic placement
OECD fields and topic tags
Scope: Metropolitan urban building stocks and regional energy grids. · Method signals: Computational simulation, Data modeling, Comparative spatial analysis
Possible study pathways
One question, different levels
Urban energy systems and climate modeling
Computational urban planning and energy policy
Qualification signal
88/100
- Requires access to high-performance computing resources.
- Open-access scholarly source and DOI metadata verified
Provenance
Research Idea Registry curation
- DOI and bibliographic metadata independently resolved
- Open-access status verified
- The research direction is transparently marked as AI-inferred
APA 7 source
Jalilian, R., & Kamel, E. (2025). Urban-scale building energy modeling under future climate scenarios: a scalable workflow and insights from Nassau County, New York. Frontiers in Energy Research, 13, Article 1683787. https://doi.org/10.3389/fenrg.2025.1683787
Paper abstract and discussion context; AI-inferred direction
Open source ↗