P5.4: SapResult.intermediate exposes HLC, HLP, τ, annual averages

heat_transfer_coefficient_w_per_k (HLC), heat_loss_parameter_w_per_m2k
(HLP), time_constant_h, and the two annual averages
(internal_gains_annual_avg_w, mean_internal_temp_annual_avg_c) populated
on `intermediate`. The averages let sweep slices verify monthly-loop
outputs without re-summing 12 months.

134 SAP tests pass.

packages/domain/src/domain/sap/calculator.py

@@ -346,6 +346,11 @@ def calculate_sap_from_inputs(inputs: CalculatorInputs) -> SapResult:
         "thermal_bridging_w_per_k": ht.thermal_bridging_w_per_k,
         "infiltration_ach": inputs.infiltration_ach,
         "infiltration_w_per_k": hlc_v,
+        "heat_transfer_coefficient_w_per_k": hlc,
+        "heat_loss_parameter_w_per_m2k": hlp,
+        "time_constant_h": tau_h,
+        "internal_gains_annual_avg_w": sum(e.internal_gains_w for e in monthly) / 12.0,
+        "mean_internal_temp_annual_avg_c": sum(e.internal_temp_c for e in monthly) / 12.0,
     }
 
     return SapResult(

packages/domain/src/domain/sap/tests/test_calculator.py

@@ -177,6 +177,41 @@ def test_calculate_exposes_ventilation_intermediates() -> None:
     )
 
 
+def test_calculate_exposes_hlc_hlp_and_annual_averages() -> None:
+    # Arrange — P5 trace mode: HLC (W/K), HLP (W/m²K), time constant, and
+    # annual-average internal gains + mean internal temperature surface on
+    # `intermediate`. These are the worksheet-line aggregates §7 / §13
+    # depend on; the annual averages let sweep slices verify monthly-loop
+    # outputs without re-computing the 12-month sum themselves.
+    inputs = _baseline_inputs()
+
+    # Act
+    result = calculate_sap_from_inputs(inputs)
+
+    # Assert
+    expected_hlc = (
+        inputs.heat_transmission.total_w_per_k
+        + inputs.infiltration_ach * inputs.dimensions.volume_m3 * 0.33
+    )
+    expected_hlp = expected_hlc / inputs.dimensions.total_floor_area_m2
+    assert result.intermediate["heat_transfer_coefficient_w_per_k"] == pytest.approx(
+        expected_hlc, rel=1e-9
+    )
+    assert result.intermediate["heat_loss_parameter_w_per_m2k"] == pytest.approx(
+        expected_hlp, rel=1e-9
+    )
+    assert result.intermediate["time_constant_h"] > 0.0
+
+    avg_gains = sum(e.internal_gains_w for e in result.monthly) / 12.0
+    avg_mit = sum(e.internal_temp_c for e in result.monthly) / 12.0
+    assert result.intermediate["internal_gains_annual_avg_w"] == pytest.approx(
+        avg_gains, rel=1e-9
+    )
+    assert result.intermediate["mean_internal_temp_annual_avg_c"] == pytest.approx(
+        avg_mit, rel=1e-9
+    )
+
+
 def test_higher_main_heating_efficiency_reduces_fuel_use() -> None:
     # Arrange — Direction check: doubling the boiler efficiency must halve
     # the main-heating fuel kWh, holding everything else constant.