整合

org/other/question2_pdms_cooling.py

@@ -0,0 +1,157 @@
+import importlib.util
+import math
+import os
+from dataclasses import dataclass
+from typing import Dict, List, Tuple
+
+import numpy as np
+from matplotlib import pyplot as plt
+
+plt.rcParams["font.sans-serif"] = ["DejaVu Sans", "Arial", "Helvetica"]
+plt.rcParams["axes.unicode_minus"] = False
+
+SIGMA = 5.670374419e-8
+
+THICKNESSES = [1, 5, 10, 25, 50, 100]  # µm
+T_AMB = 300.0  # K (≈27 ℃)
+T_SKY = 280.0  # Clear dry sky equivalent radiation temperature
+SOLAR_IRR = 900.0  # W/m^2, clear sky noon
+H_CONV = 8.0  # W/m^2/K, natural convection + light wind
+
+
+def load_emissivity_module():
+    here = os.path.dirname(os.path.abspath(__file__))
+    target = os.path.join(here, "question1_pdms_emissivity.py")
+    spec = importlib.util.spec_from_file_location("q1", target)
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)  # type: ignore[arg-type]
+    return module
+
+
+def solar_absorptance(thickness_um: float) -> float:
+    """
+    Empirical assumption: In PDMS silver-coated system, visible light absorption
+    is determined by thin film scattering and internal losses.
+    At 1 µm, α≈0.05, absorption increases by 0.01 for every 10 µm increase in thickness, capped at 0.15.
+    """
+    return min(0.05 + 0.001 * thickness_um, 0.15)
+
+
+@dataclass
+class CoolingResult:
+    thickness_um: float
+    eps_window: float
+    alpha_solar: float
+    net_power_at_amb: float
+    eq_temp_K: float
+
+    @property
+    def eq_temp_C(self) -> float:
+        return self.eq_temp_K - 273.15
+
+    @property
+    def delta_T(self) -> float:
+        return self.eq_temp_K - T_AMB
+
+
+def net_cooling_power(temp_K: float, emissivity: float, alpha_s: float) -> float:
+    radiative = emissivity * SIGMA * (temp_K**4 - T_SKY**4)
+    solar_gain = alpha_s * SOLAR_IRR
+    convective = H_CONV * (temp_K - T_AMB)
+    return -solar_gain - convective + radiative
+
+
+def solve_equilibrium(emissivity: float, alpha_s: float) -> float:
+    low, high = 250.0, 330.0
+    f_low = net_cooling_power(low, emissivity, alpha_s)
+    f_high = net_cooling_power(high, emissivity, alpha_s)
+
+    if f_low * f_high > 0:
+        # No sign change, return endpoint with smaller energy consumption
+        return low if abs(f_low) < abs(f_high) else high
+
+    for _ in range(80):
+        mid = 0.5 * (low + high)
+        f_mid = net_cooling_power(mid, emissivity, alpha_s)
+        if abs(f_mid) < 1e-4:
+            return mid
+        if f_low * f_mid <= 0:
+            high, f_high = mid, f_mid
+        else:
+            low, f_low = mid, f_mid
+    return 0.5 * (low + high)
+
+
+def evaluate() -> Tuple[List[CoolingResult], str]:
+    q1 = load_emissivity_module()
+    emissivity_data = q1.compute_emissivity(THICKNESSES)
+
+    results: List[CoolingResult] = []
+    for d in THICKNESSES:
+        eps_window = emissivity_data.window_avg[d]
+        alpha_s = solar_absorptance(d)
+        net_amb = net_cooling_power(T_AMB, eps_window, alpha_s)
+        eq_temp = solve_equilibrium(eps_window, alpha_s)
+        results.append(
+            CoolingResult(
+                thickness_um=d,
+                eps_window=eps_window,
+                alpha_solar=alpha_s,
+                net_power_at_amb=net_amb,
+                eq_temp_K=eq_temp,
+            )
+        )
+
+    outdir = os.path.join(os.path.dirname(__file__), "outputs")
+    os.makedirs(outdir, exist_ok=True)
+    csv_path = os.path.join(outdir, "question2_cooling_summary.csv")
+    with open(csv_path, "w", encoding="utf-8") as f:
+        f.write("thickness_um,eps_8_13,alpha_solar,net_power_amb_Wm2,eq_temp_C,delta_T_C\n")
+        for res in results:
+            f.write(
+                f"{res.thickness_um},{res.eps_window:.4f},{res.alpha_solar:.3f},"
+                f"{res.net_power_at_amb:.2f},{res.eq_temp_C:.2f},{res.delta_T:.2f}\n"
+            )
+
+    fig_path = os.path.join(outdir, "question2_cooling_results.png")
+    plot_results(results, fig_path)
+
+    return results, csv_path
+
+
+def plot_results(results: List[CoolingResult], fig_path: str) -> None:
+    thickness = [r.thickness_um for r in results]
+    net_power = [r.net_power_at_amb for r in results]
+    delta_T = [r.delta_T for r in results]
+
+    fig, ax1 = plt.subplots(figsize=(9, 5))
+    ax1.bar(thickness, net_power, width=4, alpha=0.6, label="Net Cooling Power @T_amb")
+    ax1.set_xlabel("PDMS Film Thickness (µm)")
+    ax1.set_ylabel("Net Cooling Power (W/m²)")
+    ax1.axhline(0, color="black", linewidth=0.8)
+
+    ax2 = ax1.twinx()
+    ax2.plot(thickness, delta_T, color="tab:red", marker="o", label="Equilibrium Temperature Difference")
+    ax2.set_ylabel("Equilibrium Temperature Difference (K)")
+
+    lines, labels = ax1.get_legend_handles_labels()
+    lines2, labels2 = ax2.get_legend_handles_labels()
+    ax1.legend(lines + lines2, labels + labels2, loc="upper right")
+    fig.tight_layout()
+    plt.savefig(fig_path, dpi=300)
+    plt.close(fig)
+
+
+def main():
+    results, csv_path = evaluate()
+    print(f"Results written to: {csv_path}")
+    for r in results:
+        print(
+            f"d={r.thickness_um:>3} um, eps_8_13={r.eps_window:.2f}, alpha_sol={r.alpha_solar:.2f}, "
+            f"q_net(T_amb)={r.net_power_at_amb:.1f} W/m2, T_eq={r.eq_temp_C:.1f} °C "
+            f"(DeltaT={r.delta_T:.1f} K)"
+        )
+
+
+if __name__ == "__main__":
+    main()