架构调整和敏感性分析代码附加

brayton_cycle/sensitivity.py

@@ -0,0 +1,50 @@
+# -*- coding: utf-8 -*-
+"""Evaluation helpers for cycle sensitivity analysis."""
+
+from .cycles import BraytonCycle
+
+
+RC_FIXED_KEYS = ("T_low", "T_high", "p_low", "p_high", "ploss")
+RC_PARAM_KEYS = (
+    "x",
+    "compressor_eff",
+    "recompressor_eff",
+    "turbine_eff",
+    "recuperator_eff",
+    "highT_recuperator_eff",
+)
+
+
+def _require_keys(data, required_keys, data_name):
+    missing = [key for key in required_keys if key not in data]
+    if missing:
+        missing_text = ", ".join(missing)
+        raise ValueError(f"{data_name} missing required keys: {missing_text}")
+
+
+def evaluate_rc_efficiency(fixed_params, params, refprop_path=None):
+    """Return the recompression Brayton cycle thermal efficiency.
+
+    The returned efficiency is a decimal value, for example 0.45 means 45%.
+    A new cycle instance is created for each evaluation so repeated sensitivity
+    runs do not reuse component state from previous cases.
+    """
+    fixed = dict(fixed_params)
+    cycle_params = dict(params)
+
+    _require_keys(fixed, RC_FIXED_KEYS, "fixed_params")
+    _require_keys(cycle_params, RC_PARAM_KEYS, "params")
+
+    cycle_kwargs = {"name": "rc efficiency evaluation"}
+    if refprop_path is not None:
+        cycle_kwargs["refprop_path"] = refprop_path
+
+    cycle = BraytonCycle(**cycle_kwargs)
+    return cycle.RC(
+        T_low=fixed["T_low"],
+        T_high=fixed["T_high"],
+        p_low=fixed["p_low"],
+        p_high=fixed["p_high"],
+        ploss=fixed["ploss"],
+        param=cycle_params,
+    )