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org/q2.py

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+import numpy as np
+from scipy.constants import h, c, k
+from scipy.integrate import simps
+import matplotlib.pyplot as plt
+
+from org.q1 import emissivity
+
+
+# ------------------------------------------------
+# 1. 引用第一题的 emissivity() 函数
+# ------------------------------------------------
+# (假设已运行第一题代码)
+# emissivity(lambda_um, thickness_um)
+
+
+# ------------------------------------------------
+# 2. 黑体辐射谱
+# ------------------------------------------------
+def planck_lambda(lambda_um, T):
+    lambda_m = lambda_um * 1e-6
+    return (2*h*c**2)/(lambda_m**5) / (np.exp(h*c/(lambda_m*k*T)) - 1)
+
+# ------------------------------------------------
+# 3. 大气透过率（示例，可替换 MODTRAN 数据）
+# ------------------------------------------------
+def atmosphere_tau(lambda_um):
+    tau = np.ones_like(lambda_um)
+    window = (lambda_um >= 8) & (lambda_um <= 13)
+    tau[window] = 0.8
+    tau[~window] = 0.1
+    return tau
+
+# ------------------------------------------------
+# 4. 太阳辐照谱（简化 AM1.5）
+# ------------------------------------------------
+def solar_spectrum(lambda_um):
+    I0 = 1.5e3  # simplified scaling
+    return I0 * np.exp(-(lambda_um - 0.5)**2 / 0.4)
+
+# ------------------------------------------------
+# 5. 能量项计算
+# ------------------------------------------------
+def P_rad(Ts, lambda_um, eps):
+    return simps(eps * planck_lambda(lambda_um, Ts), lambda_um)
+
+def P_atm(Ta, lambda_um, eps):
+    return simps(eps * planck_lambda(lambda_um, Ta) * (1 - atmosphere_tau(lambda_um)), lambda_um)
+
+def P_solar(lambda_um, eps):
+    A = eps  # approximate absorption
+    return simps(A * solar_spectrum(lambda_um), lambda_um)
+
+def P_conv(Ts, Ta, h=5):
+    return h * (Ts - Ta)
+
+# ------------------------------------------------
+# 6. 净冷却功率
+# ------------------------------------------------
+def P_net(Ts, Ta, lambda_um, eps, h=5):
+    return P_rad(Ts, lambda_um, eps) - P_atm(Ta, lambda_um, eps) - P_solar(lambda_um, eps) - P_conv(Ts, Ta, h)
+
+# ------------------------------------------------
+# 7. 求稳态温度（解 Pnet=0）
+# ------------------------------------------------
+def solve_temperature(Ta, lambda_um, eps):
+    Ts = Ta
+    for _ in range(1000):
+        f = P_net(Ts, Ta, lambda_um, eps)
+        Ts -= 0.1 * f  # simple iteration
+    return Ts
+
+# ------------------------------------------------
+# 8. 运行示例
+# ------------------------------------------------
+lambda_range = np.linspace(0.35, 20, 2000)
+d_pdms = 10
+eps = emissivity(lambda_range, d_pdms)
+
+Ta = 300  # 环境温度
+Ts = solve_temperature(Ta, lambda_range, eps)
+
+print("Steady-state temperature:", Ts)
+
+# 曲线可视化
+T_list = np.linspace(250, 330, 200)
+P_list = [P_net(T, Ta, lambda_range, eps) for T in T_list]
+
+plt.figure(figsize=(10,5))
+plt.plot(T_list, P_list)
+plt.axhline(0, color='r')
+plt.xlabel("Temperature (K)")
+plt.ylabel("Net Cooling Power")
+plt.title("Cooling Power vs Temperature")
+plt.grid(True)
+plt.show()