Building Performance Simulation
Computational modeling that predicts how a building will perform across energy, daylight, thermal comfort, and airflow metrics before construction.
Definition
Building Performance Simulation uses physics-based computational models to predict a building's energy consumption, daylighting levels, thermal comfort, natural ventilation, and acoustic behavior before a single element is constructed. Traditionally run by specialist consultants using tools like EnergyPlus or IES VE, AI is making performance simulation more accessible by automating model setup from BIM geometry, running thousands of parametric variations in parallel, and translating results into actionable design recommendations that architects and engineers can use without deep simulation expertise. As energy codes tighten and net-zero targets become standard project requirements, performance simulation is moving from an occasional value-engineering exercise to a continuous design feedback loop integrated into every stage from concept through construction documentation.
In Depth
Performance simulation has existed in AEC for decades, but it has traditionally been the domain of specialists — energy consultants running EnergyPlus models, daylighting consultants setting up Radiance simulations, CFD experts modeling wind and ventilation patterns. The simulations required deep expertise, took hours or days to run, and usually happened only once or twice during design, often too late to influence major decisions.
AI is democratizing performance simulation by automating the setup, execution, and interpretation of simulations. Instead of a specialist manually translating a BIM model into a simulation-ready energy model — a process that can take days — AI automates the geometry extraction, material mapping, system assignment, and climate data integration. Instead of running a single simulation, AI runs thousands of parametric variations in parallel and presents the Pareto-optimal solutions: the designs that best balance energy performance, daylight quality, thermal comfort, and cost.
This shift from occasional specialist analysis to continuous design feedback changes how performance simulation fits into the design process. An architect exploring massing options can see the energy and daylight implications of each option in near real-time, making performance an active design parameter rather than a late-stage constraint. As energy codes tighten and net-zero mandates spread, this integration becomes essential: performance simulation is no longer a nice-to-have sustainability exercise but a core code compliance tool that every project needs.
Examples
AI that generates 2,000 facade design variants and simulates each for energy use, daylight autonomy, and glare, then presents the Pareto-optimal options to the design team.
Automated energy code compliance check that extracts the building envelope from a Revit model and runs a prescriptive-path analysis against ASHRAE 90.1.
Post-occupancy comparison that overlays actual metered energy data against the design-stage simulation predictions to calibrate future project models.
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Compatible Platforms
Nomic integrates with these platforms so you can use building performance simulation across your existing project data:
Frequently Asked Questions
Building Performance Simulation uses physics-based computational models to predict a building's energy consumption, daylighting levels, thermal comfort, natural ventilation, and acoustic behavior before a single element is constructed. Traditionally run by specialist consultants using tools like EnergyPlus or IES VE, AI is making performance simulation more accessible by automating model setup from BIM geometry, running thousands of parametric variations in parallel, and translating results into actionable design recommendations that architects and engineers can use without deep simulation expertise. As energy codes tighten and net-zero targets become standard project requirements, performance simulation is moving from an occasional value-engineering exercise to a continuous design feedback loop integrated into every stage from concept through construction documentation.
AI that generates 2,000 facade design variants and simulates each for energy use, daylight autonomy, and glare, then presents the Pareto-optimal options to the design team.. Automated energy code compliance check that extracts the building envelope from a Revit model and runs a prescriptive-path analysis against ASHRAE 90.1.. Post-occupancy comparison that overlays actual metered energy data against the design-stage simulation predictions to calibrate future project models.
Project Research: Instantly access all project-critical information from a single search interface. Automated Code Compliance: Check drawings against 380+ building codes and standards with cited answers.