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Example 11: Simulation Results Deep Dive

Extract structured results from a completed simulation — energy breakdown, envelope performance, HVAC sizing, and hourly data — without reading raw HTML.

Scenario

An engineer ran an annual simulation and wants to analyze results: end-use energy breakdown, envelope U-values, HVAC sizing adequacy, and January electricity profile.

Prompt

Show me the end-use energy breakdown, envelope summary, HVAC sizing, and hourly electricity for January from my last simulation run.

Tool Call Sequence

1. extract_end_use_breakdown(run_id=<id>, units="IP")
2. extract_envelope_summary(run_id=<id>)
3. extract_hvac_sizing(run_id=<id>)
4. extract_zone_summary(run_id=<id>)
5. extract_component_sizing(run_id=<id>, component_type="Coil")
6. query_timeseries(run_id=<id>, variable_name="Electricity:Facility",
     frequency="Daily", start_month=1, end_month=1)

Key Tools Used

Tool Purpose
extract_end_use_breakdown Energy by fuel type (heating, cooling, lighting, etc.)
extract_envelope_summary Wall/window U-values and areas
extract_hvac_sizing Zone/system autosized capacities
extract_zone_summary Per-zone areas and conditions
extract_component_sizing Individual equipment autosized values
query_timeseries Time-series data with date range filter

Tips

  • Use units="SI" for GJ, "IP" (default) for kBtu
  • component_type filter: "Coil", "Fan", "Pump", "Chiller", "Boiler"
  • query_timeseries requires output variables added before simulation
  • Default 10K point cap; raise via max_points for full-year hourly

Integration Test

See tests/test_results_extraction.py::TestExampleWorkflow