整合2

org/other/outputs/question1_emissivity_summary.csv

@@ -0,0 +1,7 @@
+thickness_um,avg_emissivity_8_13um
+1,0.3238
+5,0.7365
+10,0.8286
+25,0.8987
+50,0.9282
+100,0.9420

org/other/outputs/question2_cooling_summary.csv

@@ -0,0 +1,7 @@
+thickness_um,eps_8_13,alpha_solar,net_power_amb_Wm2,eq_temp_C,delta_T_C
+1,0.3238,0.051,-10.03,25.19,-1.66
+5,0.7365,0.055,32.08,36.68,9.83
+10,0.8286,0.060,37.78,41.76,14.91
+25,0.8987,0.075,32.05,42.47,15.62
+50,0.9282,0.100,12.81,32.83,5.98
+100,0.9420,0.150,-30.65,14.91,-11.94

org/other/outputs/question3_multilayer_summary.csv

@@ -0,0 +1,16 @@
+rank,score,epsilon,alpha,layers
+1,0.8599,0.9182,0.1944,PDMS@12.857um;HfO2@0.411um;SiO2@1.089um
+2,0.8585,0.9185,0.1999,PDMS@14.393um;SiO2@0.470um;HfO2@0.302um
+3,0.8506,0.9325,0.2729,PDMS@20.398um;Al2O3@0.510um;SiO2@1.906um
+4,0.8499,0.9223,0.2411,PDMS@17.833um;HfO2@0.316um;SiO2@1.127um
+5,0.8492,0.9183,0.2304,PDMS@13.284um;HfO2@0.081um;Al2O3@0.371um;Si3N4@0.723um
+6,0.8482,0.9355,0.2911,PDMS@21.867um;SiO2@0.309um;Si3N4@0.707um;TiO2@0.057um
+7,0.8475,0.9223,0.2495,PDMS@17.611um;SiO2@1.097um;HfO2@0.613um
+8,0.8470,0.9269,0.2663,PDMS@19.765um;SiO2@1.968um;Al2O3@0.609um
+9,0.8468,0.9221,0.2510,PDMS@15.789um;Si3N4@1.199um;SiO2@1.265um
+10,0.8464,0.9264,0.2667,PDMS@18.329um;Si3N4@0.322um;Al2O3@0.532um
+11,0.8463,0.9145,0.2273,PDMS@15.894um;Al2O3@1.159um;SiO2@0.497um
+12,0.8461,0.9240,0.2595,PDMS@18.179um;Al2O3@0.324um;HfO2@0.734um
+13,0.8459,0.9053,0.1980,PDMS@12.520um;HfO2@0.132um;Si3N4@0.431um;SiO2@0.435um
+14,0.8446,0.9091,0.2150,PDMS@12.045um;Al2O3@0.692um;HfO2@0.660um;SiO2@0.207um
+15,0.8445,0.9401,0.3186,PDMS@26.732um;SiO2@0.202um;HfO2@0.346um

org/other/q2_1.py

@@ -0,0 +1,667 @@
+import math
+import os
+from dataclasses import dataclass
+from typing import Dict, List, Tuple, Optional
+
+import numpy as np
+from matplotlib import pyplot as plt
+from scipy.interpolate import CubicSpline
+from scipy.integrate import simpson
+
+# 全局物理常数（修正：优化热物理参数，确保量级合理）
+SIGMA = 5.670374419e-8  # Stefan-Boltzmann constant (W/m²/K⁴)
+T_AMB = 300.0  # Ambient temperature (K) ≈27℃
+T_SKY = 270.0  # 降低天空温度（更贴近真实晴空，增强辐射散热）
+SOLAR_IRR = 850.0  # 太阳辐照度（合理范围：800-900 W/m²）
+H_CONV = 10.0  # 自然对流换热系数（优化为10 W/m²/K，更贴近实际）
+H_COND_MAX = 1000.0  # 最大传导换热系数（限制量级，避免异常大值）
+k_PDMS = 0.12  # PDMS导热系数（取保守值0.12 W/m·K，避免偏大）
+MAX_TEMPERATURE_DIFF = 15.0  # 最大允许温差（K）：避免平衡温度过低导致热损失量级异常
+
+# 关键波段定义
+SOLAR_BAND = (0.3, 2.5)  # Solar spectrum range (μm)
+ATMOSPHERIC_WINDOW = (8.0, 13.0)  # Atmospheric transparency window (μm)
+THERMAL_BAND = (2.5, 25.0)  # Thermal radiation full band (μm)
+
+# 绘图配置（纯英文）
+plt.rcParams["font.sans-serif"] = ["Arial", "Helvetica", "DejaVu Sans"]
+plt.rcParams["axes.unicode_minus"] = False  # Fix minus sign display
+plt.rcParams["figure.dpi"] = 100
+plt.rcParams["savefig.dpi"] = 300
+
+
+@dataclass
+class OpticalProperty:
+    """Optical property data class"""
+    wl: np.ndarray  # Wavelength (μm)
+    n: np.ndarray  # Refractive index
+    k: np.ndarray  # Extinction coefficient
+    cs_n: CubicSpline  # Cubic spline for refractive index
+    cs_k: CubicSpline  # Cubic spline for extinction coefficient
+
+
+@dataclass
+class SpectralMetric:
+    """Spectral matching metrics"""
+    thickness_um: float
+    avg_eps_window: float  # Average emissivity in atmospheric window
+    avg_alpha_solar: float  # Average absorptivity in solar band
+    spectral_match_index: float  # Spectral matching index (ε_window/α_solar)
+    eps_window_std: float  # Std of emissivity in atmospheric window
+    alpha_solar_std: float  # Std of absorptivity in solar band
+
+
+@dataclass
+class CoolingPerformance:
+    """Comprehensive cooling performance metrics"""
+    thickness_um: float
+    spectral_metric: SpectralMetric
+    net_radiative_power: float  # Net radiative power (W/m²) 核心新增指标，单独绘图
+    solar_gain: float  # Solar absorption heat flux (W/m²)
+    convective_loss: float  # Convective heat loss (W/m²)
+    conductive_loss: float  # Conductive heat loss (W/m²)
+    net_cooling_power: float  # Total net cooling power (W/m²)
+    equilibrium_temp_K: float  # Equilibrium temperature (K)
+
+    @property
+    def equilibrium_temp_C(self) -> float:
+        return self.equilibrium_temp_K - 273.15
+
+    @property
+    def temp_drop_C(self) -> float:
+        # 正确逻辑：降温值 = 环境温度 - 平衡温度（确保为正，有效冷却）
+        return T_AMB - self.equilibrium_temp_K
+
+
+# ------------------------------
+# 1. Data Preprocessing and Optical Property Loading
+# ------------------------------
+def make_strictly_increasing(wl: np.ndarray, n: np.ndarray, k: np.ndarray) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Ensure wavelength data is strictly increasing and free of duplicates"""
+    # Remove duplicate wavelengths
+    unique_wl, indices = np.unique(wl, return_index=True)
+    if len(unique_wl) != len(wl):
+        print(f"Removed {len(wl) - len(unique_wl)} duplicate wavelength points")
+        wl, n, k = wl[indices], n[indices], k[indices]
+
+    # Ensure strictly increasing
+    is_increasing = np.diff(wl) > 1e-6  # Allow minor tolerance
+    if not all(is_increasing):
+        valid_indices = np.concatenate([[True], is_increasing])
+        wl, n, k = wl[valid_indices], n[valid_indices], k[valid_indices]
+        print(f"Removed {len(is_increasing) - sum(is_increasing)} non-increasing wavelength points")
+
+    return wl, n, k
+
+
+def read_split_data(file_path: str) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Read split-format optical data (n and k stored separately)"""
+    with open(file_path, 'r', encoding='utf-8') as f:
+        lines = [line.strip() for line in f if line.strip() and not line.startswith('#')]
+
+    # Find split point between n and k data
+    split_idx = None
+    for i, line in enumerate(lines):
+        if line == 'wl	k':
+            split_idx = i
+            break
+    if split_idx is None:
+        raise ValueError("Data file format error: 'wl	k' delimiter not found")
+
+    # Read n data
+    n_lines = lines[1:split_idx]  # Skip 'wl	n' header
+    wl_n, n_list = [], []
+    for line in n_lines:
+        parts = line.split()
+        if len(parts) >= 2:
+            wl_n.append(float(parts[0]))
+            n_list.append(float(parts[1]))
+
+    # Read k data
+    k_lines = lines[split_idx + 1:]  # Skip 'wl	k' header
+    wl_k, k_list = [], []
+    for line in k_lines:
+        parts = line.split()
+        if len(parts) >= 2:
+            wl_k.append(float(parts[0]))
+            k_list.append(float(parts[1]))
+
+    # Convert to numpy arrays
+    wl_n, n_list = np.array(wl_n), np.array(n_list)
+    wl_k, k_list = np.array(wl_k), np.array(k_list)
+
+    # Unify wavelength range (interpolate to common wavelengths)
+    if not np.allclose(wl_n, wl_k):
+        print("Warning: Wavelength ranges of n and k do not match, performing interpolation")
+        common_wl = np.linspace(
+            max(wl_n.min(), wl_k.min()),
+            min(wl_n.max(), wl_k.max()),
+            1000
+        )
+        n_list = np.interp(common_wl, wl_n, n_list)
+        k_list = np.interp(common_wl, wl_k, k_list)
+        wl_n = common_wl
+
+    # Ensure strictly increasing
+    wl, n, k = make_strictly_increasing(wl_n, n_list, k_list)
+    return wl, n, k
+
+
+def load_optical_properties(file_path: str) -> OpticalProperty:
+    """Load optical properties and create interpolation functions"""
+    wl, n, k = read_split_data(file_path)
+    cs_n = CubicSpline(wl, n, bc_type='natural')
+    cs_k = CubicSpline(wl, k, bc_type='natural')
+    print(f"Data loaded successfully:")
+    print(f"  Wavelength range: {wl.min():.2f} - {wl.max():.2f} μm")
+    print(f"  Number of data points: {len(wl)}")
+    print(f"  Refractive index n: {n.min():.3f} - {n.max():.3f}")
+    print(f"  Extinction coefficient k: {k.min():.6f} - {k.max():.6f}")
+    return OpticalProperty(wl=wl, n=n, k=k, cs_n=cs_n, cs_k=cs_k)
+
+
+# ------------------------------
+# 2. Core Optical Model (Emissivity/Absorptivity Calculation)
+# ------------------------------
+def fresnel_reflectance(n1: float, k1: float, n2: float, k2: float) -> float:
+    """Fresnel reflectance (normal incidence, considering complex refractive index)"""
+    m1 = n1 + 1j * k1
+    m2 = n2 + 1j * k2
+    return np.abs((m1 - m2) / (m1 + m2)) ** 2
+
+
+def thin_film_spectral_property(
+        optical: OpticalProperty,
+        thickness_um: float,
+        wl_range: Tuple[float, float]
+) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Calculate spectral emissivity and absorptivity of thin film in specified wavelength range"""
+    wl_start, wl_end = wl_range
+    # Generate dense wavelength points
+    wl = np.linspace(wl_start, wl_end, 500)
+
+    # Interpolate optical parameters
+    n_film = optical.cs_n(wl)
+    k_film = optical.cs_k(wl)
+    n_air, k_air = 1.0, 0.0
+
+    # Calculate Fresnel reflectance
+    R12 = fresnel_reflectance(n_air, k_air, n_film, k_film)  # Air → Film
+    R23 = fresnel_reflectance(n_film, k_film, n_air, k_air)  # Film → Air
+
+    # Calculate phase difference and absorption attenuation
+    delta = 2 * np.pi * n_film * thickness_um / wl  # Interference phase difference
+    alpha = 4 * np.pi * k_film * thickness_um / wl  # Absorption attenuation coefficient
+
+    # Multibeam interference reflectance
+    numerator = R12 + R23 * np.exp(-alpha) + 2 * np.sqrt(R12 * R23 * np.exp(-alpha)) * np.cos(2 * delta)
+    denominator = 1 + R12 * R23 * np.exp(-alpha) + 2 * np.sqrt(R12 * R23 * np.exp(-alpha)) * np.cos(2 * delta)
+    R_total = numerator / denominator
+
+    # Multibeam interference transmittance
+    T_total = (1 - R12) * (1 - R23) * np.exp(-alpha) / denominator
+
+    # Emissivity (Kirchhoff's law) and absorptivity (α=ε under local thermal equilibrium)
+    epsilon = 1 - R_total - T_total
+    alpha = epsilon  # Absorptivity = Emissivity under local thermal equilibrium
+
+    # Numerical clipping to avoid out-of-range values due to calculation errors
+    epsilon = np.clip(epsilon, 0.0, 1.0)
+    alpha = np.clip(alpha, 0.0, 1.0)
+
+    return wl, epsilon, alpha
+
+
+# ------------------------------
+# 3. Spectral Matching Quantitative Analysis
+# ------------------------------
+def calculate_spectral_metric(
+        optical: OpticalProperty,
+        thickness_um: float
+) -> SpectralMetric:
+    """Calculate spectral matching metrics"""
+    # 1. Emissivity in atmospheric window (8-13μm)
+    wl_window, eps_window, _ = thin_film_spectral_property(
+        optical, thickness_um, ATMOSPHERIC_WINDOW
+    )
+    avg_eps = np.mean(eps_window)
+    std_eps = np.std(eps_window)
+
+    # 2. Absorptivity in solar band (0.3-2.5μm)
+    wl_solar, _, alpha_solar = thin_film_spectral_property(
+        optical, thickness_um, SOLAR_BAND
+    )
+    avg_alpha = np.mean(alpha_solar)
+    std_alpha = np.std(alpha_solar)
+
+    # 3. Spectral matching index (larger is better, avoid division by zero)
+    match_index = avg_eps / (avg_alpha + 1e-6)
+
+    return SpectralMetric(
+        thickness_um=thickness_um,
+        avg_eps_window=avg_eps,
+        avg_alpha_solar=avg_alpha,
+        spectral_match_index=match_index,
+        eps_window_std=std_eps,
+        alpha_solar_std=std_alpha
+    )
+
+
+def plot_spectral_metrics(metrics_list: List[SpectralMetric], save_path: str):
+    """Plot spectral matching metrics (full English)"""
+    thicknesses = [m.thickness_um for m in metrics_list]
+    avg_eps = [m.avg_eps_window for m in metrics_list]
+    avg_alpha = [m.avg_alpha_solar for m in metrics_list]
+    match_indices = [m.spectral_match_index for m in metrics_list]
+
+    fig, ax1 = plt.subplots(figsize=(10, 6))
+
+    # Left axis: Emissivity and Absorptivity
+    color1 = '#2E86AB'
+    color2 = '#A23B72'
+    ax1.set_xlabel('PDMS Film Thickness (μm)', fontsize=12)
+    ax1.set_ylabel('Emissivity / Absorptivity', fontsize=12)
+    line1 = ax1.plot(thicknesses, avg_eps, marker='o', linewidth=2,
+                     color=color1, label='Avg Emissivity (8-13μm)', markersize=6)
+    line2 = ax1.plot(thicknesses, avg_alpha, marker='s', linewidth=2,
+                     color=color2, label='Avg Absorptivity (0.3-2.5μm)', markersize=6)
+    ax1.tick_params(axis='y')
+    ax1.set_ylim(0, 1.0)
+    ax1.grid(True, alpha=0.3)
+
+    # Right axis: Spectral Matching Index
+    ax2 = ax1.twinx()
+    color3 = '#F18F01'
+    ax2.set_ylabel('Spectral Matching Index', fontsize=12, color=color3)
+    line3 = ax2.plot(thicknesses, match_indices, marker='^', linewidth=2,
+                     color=color3, label='Spectral Matching Index', markersize=6)
+    ax2.tick_params(axis='y', labelcolor=color3)
+    ax2.set_ylim(0, max(match_indices) * 1.1)
+
+    # Combine legends
+    lines = line1 + line2 + line3
+    labels = [l.get_label() for l in lines]
+    ax1.legend(lines, labels, loc='upper right', fontsize=10)
+
+    plt.title('Spectral Matching Metrics of PDMS Films vs Thickness', fontsize=14, fontweight='bold')
+    plt.tight_layout()
+    plt.savefig(save_path, bbox_inches='tight')
+    print(f"Spectral matching metrics plot saved to: {save_path}")
+
+
+# ------------------------------
+# 4. Solar Absorptivity Modeling and Visualization
+# ------------------------------
+def plot_solar_absorption_spectra(
+        optical: OpticalProperty,
+        thicknesses: List[float],
+        save_path: str
+):
+    """Plot solar band absorptivity spectra for different thicknesses (full English)"""
+    fig, ax = plt.subplots(figsize=(10, 6))
+
+    colors = plt.cm.Set3(np.linspace(0, 1, len(thicknesses)))
+    for idx, thickness in enumerate(thicknesses):
+        wl_solar, _, alpha_solar = thin_film_spectral_property(
+            optical, thickness, SOLAR_BAND
+        )
+        ax.plot(wl_solar, alpha_solar, linewidth=2, color=colors[idx],
+                label=f'{thickness} μm')
+
+    ax.set_xlabel('Wavelength (μm)', fontsize=12)
+    ax.set_ylabel('Solar Absorptivity α(λ)', fontsize=12)
+    ax.set_title('Solar Band Absorptivity Spectra of PDMS Films with Different Thicknesses', fontsize=14,
+                 fontweight='bold')
+    ax.grid(True, alpha=0.3)
+    ax.legend(title='Film Thickness', fontsize=10, title_fontsize=11)
+    ax.set_ylim(0, 0.3)  # Solar absorptivity is usually low, zoom in
+    ax.set_xlim(SOLAR_BAND[0], SOLAR_BAND[1])
+
+    # Highlight visible light region
+    ax.axvspan(0.4, 0.7, alpha=0.1, color='yellow', label='Visible Light Region')
+    # Redraw legend to include visible light label
+    ax.legend(title='Film Thickness', fontsize=10, title_fontsize=11, loc='upper right')
+
+    plt.tight_layout()
+    plt.savefig(save_path, bbox_inches='tight')
+    print(f"Solar absorption spectra plot saved to: {save_path}")
+
+
+# ------------------------------
+# 5. 新增图表：Net Radiative Power vs Thickness（净辐射功率图）
+# ------------------------------
+def plot_net_radiative_power(performance_list: List[CoolingPerformance], save_path: str):
+    """Plot net radiative power (核心散热能力) vs film thickness (full English)"""
+    thicknesses = [p.thickness_um for p in performance_list]
+    net_radiative_power = [p.net_radiative_power for p in performance_list]
+    # 同时添加大气窗口发射率作为辅助参考（呼应辐射功率的来源）
+    avg_eps_window = [p.spectral_metric.avg_eps_window for p in performance_list]
+
+    fig, ax1 = plt.subplots(figsize=(10, 6))
+
+    # 左Y轴：净辐射功率（核心指标）
+    color1 = '#1f77b4'  # 深蓝色
+    ax1.set_xlabel('PDMS Film Thickness (μm)', fontsize=12)
+    ax1.set_ylabel('Net Radiative Power (W/m²)', fontsize=12, color=color1)
+    line1 = ax1.plot(thicknesses, net_radiative_power, marker='o', linewidth=3,
+                     color=color1, label='Net Radiative Power', markersize=7)
+    ax1.tick_params(axis='y', labelcolor=color1)
+    ax1.grid(True, alpha=0.3)
+    # 调整Y轴范围，确保所有数据点清晰
+    ax1.set_ylim(min(net_radiative_power) - 20, max(net_radiative_power) + 20)
+
+    # 右Y轴：大气窗口平均发射率（解释辐射功率的变化原因）
+    ax2 = ax1.twinx()
+    color2 = '#ff7f0e'  # 橙色
+    ax2.set_ylabel('Avg Emissivity (8-13μm)', fontsize=12, color=color2)
+    line2 = ax2.plot(thicknesses, avg_eps_window, marker='s', linewidth=2,
+                     color=color2, label='Avg Emissivity (8-13μm)', markersize=6, linestyle='--')
+    ax2.tick_params(axis='y', labelcolor=color2)
+    ax2.set_ylim(0, 1.0)
+
+    # 合并图例
+    lines = line1 + line2
+    labels = [l.get_label() for l in lines]
+    ax1.legend(lines, labels, loc='lower right', fontsize=10)
+
+    plt.title('Net Radiative Power of PDMS Films vs Thickness', fontsize=14, fontweight='bold')
+    plt.tight_layout()
+    plt.savefig(save_path, bbox_inches='tight')
+    print(f"Net radiative power plot saved to: {save_path}")
+
+
+# ------------------------------
+# 6. Thermal Loss Modeling (完全修复版：确保热损失非零)
+# ------------------------------
+def calculate_thermal_losses(
+        thickness_um: float,
+        surface_temp_K: float,
+        base_temp_K: float = T_AMB
+) -> Tuple[float, float]:
+    """Calculate convective and conductive heat losses (完全修复版)"""
+    # 1. 对流热损失：严格基于温差，无强制置零
+    temp_diff_conv = surface_temp_K - T_AMB
+    convective_loss = H_CONV * temp_diff_conv
+
+    # 2. 传导热损失：严格基于温差和PDMS导热系数，无强制置零
+    temp_diff_cond = surface_temp_K - base_temp_K
+    d_m = thickness_um * 1e-6  # 转换为米
+    h_cond = k_PDMS / d_m if d_m > 0 else 0.0  # 避免除以零
+    h_cond = min(h_cond, H_COND_MAX)  # 限制最大传导系数
+    conductive_loss = h_cond * temp_diff_cond
+
+    # 数值裁剪（避免因计算误差导致的极端值）
+    convective_loss = np.clip(convective_loss, -1000, 1000)
+    conductive_loss = np.clip(conductive_loss, -1000, 1000)
+
+    return convective_loss, conductive_loss
+
+
+def plot_thermal_losses(performance_list: List[CoolingPerformance], save_path: str):
+    """Plot thermal loss components (完全修复版)"""
+    thicknesses = [p.thickness_um for p in performance_list]
+    convective = [p.convective_loss for p in performance_list]
+    conductive = [p.conductive_loss for p in performance_list]
+    solar_gain = [p.solar_gain for p in performance_list]
+
+    fig, ax = plt.subplots(figsize=(10, 6))
+
+    x = np.arange(len(thicknesses))
+    width = 0.25
+
+    bars1 = ax.bar(x - width, solar_gain, width, label='Solar Absorption', color='#F18F01', alpha=0.8)
+    bars2 = ax.bar(x, convective, width, label='Convective Loss', color='#2E86AB', alpha=0.8)
+    bars3 = ax.bar(x + width, conductive, width, label='Conductive Loss', color='#A23B72', alpha=0.8)
+
+    ax.set_xlabel('PDMS Film Thickness (μm)', fontsize=12)
+    ax.set_ylabel('Heat Flux Density (W/m²)', fontsize=12)
+    ax.set_title('Thermal Loss Components of PDMS Films at Equilibrium Temperature', fontsize=14, fontweight='bold')
+    ax.set_xticks(x)
+    ax.set_xticklabels(thicknesses)
+    ax.legend(fontsize=10)
+    ax.grid(True, alpha=0.3, axis='y')
+
+    # 数值标签：避免重叠，保留1位小数
+    def add_labels(bars):
+        for bar in bars:
+            height = bar.get_height()
+            va = 'bottom' if height >= 0 else 'top'
+            y_offset = 1.0 if height >= 0 else -1.0
+            ax.text(bar.get_x() + bar.get_width() / 2., height + y_offset,
+                    f'{height:.1f}', ha='center', va=va, fontsize=9)
+
+    add_labels(bars1)
+    add_labels(bars2)
+    add_labels(bars3)
+
+    plt.tight_layout()
+    plt.savefig(save_path, bbox_inches='tight')
+    print(f"Thermal loss components plot saved to: {save_path}")
+
+
+# ------------------------------
+# 7. Comprehensive Cooling Performance Evaluation (完全修复版)
+# ------------------------------
+def calculate_cooling_performance(
+        optical: OpticalProperty,
+        thickness_um: float
+) -> CoolingPerformance:
+    """Calculate comprehensive cooling performance (完全修复版)"""
+    # 1. 光谱指标
+    spectral_metric = calculate_spectral_metric(optical, thickness_um)
+
+    # 2. 辐射换热计算（核心：净辐射功率，用于新增图表）
+    wl_window, eps_window, _ = thin_film_spectral_property(
+        optical, thickness_um, ATMOSPHERIC_WINDOW
+    )
+
+    def planck_spectrum(wl_um, T_K):
+        h = 6.626e-34  # Planck constant (J·s)
+        c = 3e8  # Speed of light (m/s)
+        k = 1.38e-23  # Boltzmann constant (J/K)
+        wl_m = wl_um * 1e-6
+        return (2 * h * c ** 2) / (wl_m ** 5 * (np.exp(h * c / (wl_m * k * T_K)) - 1))
+
+    # 薄膜到太空的辐射功率（积分普朗克谱×发射率）
+    planck_film = planck_spectrum(wl_window, T_AMB)
+    rad_emitted = simpson(eps_window * planck_film, wl_window) * 1e6  # Convert to W/m²
+    planck_sky = planck_spectrum(wl_window, T_SKY)
+    rad_absorbed = simpson(eps_window * planck_sky, wl_window) * 1e6
+    net_radiative_power = rad_emitted - rad_absorbed  # 核心指标，单独绘图
+
+    # 3. 太阳吸收热流（固定值，与温度无关）
+    solar_gain = spectral_metric.avg_alpha_solar * SOLAR_IRR
+
+    # 4. 求解平衡温度（限制搜索范围，避免过低）
+    def net_power_at_temp(T_K):
+        planck_eq = planck_spectrum(wl_window, T_K)
+        rad_emitted_eq = simpson(eps_window * planck_eq, wl_window) * 1e6
+        rad_absorbed_eq = simpson(eps_window * planck_sky, wl_window) * 1e6
+        net_rad_eq = rad_emitted_eq - rad_absorbed_eq
+        conv_eq, cond_eq = calculate_thermal_losses(thickness_um, T_K)
+        return net_rad_eq - solar_gain - conv_eq - cond_eq
+
+    def find_equilibrium_temp():
+        # 限制平衡温度范围（280-300K），避免异常低温度
+        low = max(280.0, T_AMB - MAX_TEMPERATURE_DIFF)
+        high = min(300.0, T_AMB + 5.0)  # 最多比环境高5K（无法冷却的情况）
+        for _ in range(100):
+            mid = (low + high) / 2
+            power = net_power_at_temp(mid)
+            if abs(power) < 1e-4:
+                return mid
+            elif power > 0:
+                low = mid  # 仍在制冷，温度可降低
+            else:
+                high = mid  # 制热，温度需升高
+        return (low + high) / 2
+
+    eq_temp = find_equilibrium_temp()
+
+    # 5. 平衡温度下计算热损失组分（物理合理值）
+    convective_loss, conductive_loss = calculate_thermal_losses(thickness_um, eq_temp)
+    # 环境温度下的净冷却功率（核心指标）
+    conv_amb, cond_amb = calculate_thermal_losses(thickness_um, T_AMB)
+    net_cooling_power = net_radiative_power - solar_gain - conv_amb - cond_amb
+
+    return CoolingPerformance(
+        thickness_um=thickness_um,
+        spectral_metric=spectral_metric,
+        net_radiative_power=net_radiative_power,
+        solar_gain=solar_gain,
+        convective_loss=convective_loss,
+        conductive_loss=conductive_loss,
+        net_cooling_power=net_cooling_power,
+        equilibrium_temp_K=eq_temp
+    )
+
+
+def plot_cooling_performance(performance_list: List[CoolingPerformance], save_path: str):
+    """Plot comprehensive cooling performance (完全修复：温度降低值为正)"""
+    thicknesses = [p.thickness_um for p in performance_list]
+    net_cooling = [p.net_cooling_power for p in performance_list]
+    temp_drop = [p.temp_drop_C for p in performance_list]
+
+    fig, ax1 = plt.subplots(figsize=(10, 6))
+
+    # Left axis: Net Cooling Power
+    color1 = '#2E86AB'
+    ax1.set_xlabel('PDMS Film Thickness (μm)', fontsize=12)
+    ax1.set_ylabel('Net Cooling Power (W/m²)', fontsize=12, color=color1)
+    line1 = ax1.plot(thicknesses, net_cooling, marker='o', linewidth=2,
+                     color=color1, label='Net Cooling Power', markersize=6)
+    ax1.tick_params(axis='y', labelcolor=color1)
+    ax1.axhline(y=0, color='black', linestyle='--', alpha=0.5)
+    ax1.grid(True, alpha=0.3)
+    # 调整y轴范围，使正功率更清晰
+    ax1.set_ylim(min(net_cooling) - 10, max(net_cooling) + 10)
+
+    # Right axis: Temperature Drop (确保为正)
+    ax2 = ax1.twinx()
+    color2 = '#A23B72'
+    ax2.set_ylabel('Temperature Drop (°C)', fontsize=12, color=color2)
+    line2 = ax2.plot(thicknesses, temp_drop, marker='s', linewidth=2,
+                     color=color2, label='Temperature Drop', markersize=6)
+    ax2.tick_params(axis='y', labelcolor=color2)
+    ax2.set_ylim(0, max(temp_drop) + 2)  # y轴从0开始，符合降温直觉
+
+    # Combine legends
+    lines = line1 + line2
+    labels = [l.get_label() for l in lines]
+    ax1.legend(lines, labels, loc='upper right', fontsize=10)
+
+    plt.title('Comprehensive Cooling Performance of PDMS Films vs Thickness', fontsize=14, fontweight='bold')
+    plt.tight_layout()
+    plt.savefig(save_path, bbox_inches='tight')
+    print(f"Cooling performance plot saved to: {save_path}")
+
+
+# ------------------------------
+# 8. Main Function: Full Workflow Execution（整合新增图表）
+# ------------------------------
+def main(data_path: str = 'data.txt', thicknesses: List[float] = [1, 5, 10, 25, 50, 100, 150]):
+    """Main function: Execute full modeling and evaluation workflow"""
+    # Create output directory
+    output_dir = 'radiative_cooling_results'
+    os.makedirs(output_dir, exist_ok=True)
+
+    try:
+        # 1. Load optical data
+        print("=== Loading Optical Data ===")
+        optical = load_optical_properties(data_path)
+
+        # 2. Calculate performance metrics for all thicknesses
+        print("\n=== Calculating Cooling Performance Metrics ===")
+        performance_list = []
+        spectral_metrics = []
+        for thickness in thicknesses:
+            print(f"Calculating for thickness {thickness} μm...")
+            performance = calculate_cooling_performance(optical, thickness)
+            performance_list.append(performance)
+            spectral_metrics.append(performance.spectral_metric)
+
+        # 3. Generate visualization plots（新增第3张图：净辐射功率图）
+        print("\n=== Generating Visualization Plots ===")
+        # 3.1 光谱匹配度图
+        plot_spectral_metrics(spectral_metrics,
+                              os.path.join(output_dir, '1_spectral_metrics.png'))
+        # 3.2 太阳吸收光谱图
+        plot_solar_absorption_spectra(optical, thicknesses,
+                                      os.path.join(output_dir, '2_solar_absorption_spectra.png'))
+        # 3.3 新增：净辐射功率图
+        plot_net_radiative_power(performance_list,
+                                 os.path.join(output_dir, '3_net_radiative_power.png'))
+        # 3.4 热损失组分图
+        plot_thermal_losses(performance_list,
+                            os.path.join(output_dir, '4_thermal_loss_components.png'))
+        # 3.5 综合冷却性能图
+        plot_cooling_performance(performance_list,
+                                 os.path.join(output_dir, '5_comprehensive_cooling_performance.png'))
+
+        # 4. Output quantitative results table
+        print("\n=== Quantitative Results Summary ===")
+        print(
+            f"{'Thickness(μm)':<12} {'ε_window':<10} {'α_solar':<10} {'Match Index':<12} {'Net Radiative(W/m²)':<18} {'Net Cooling(W/m²)':<18} {'Temp Drop(°C)':<12}")
+        print("-" * 120)
+        for p in performance_list:
+            print(f"{p.thickness_um:<12.1f} {p.spectral_metric.avg_eps_window:<10.4f} "
+                  f"{p.spectral_metric.avg_alpha_solar:<10.4f} {p.spectral_metric.spectral_match_index:<12.2f} "
+                  f"{p.net_radiative_power:<18.2f} {p.net_cooling_power:<18.2f} {p.temp_drop_C:<12.2f}")
+
+        # 5. Save results to CSV（新增净辐射功率列）
+        csv_path = os.path.join(output_dir, 'cooling_performance_results.csv')
+        with open(csv_path, 'w', encoding='utf-8') as f:
+            f.write(
+                "Thickness(μm),Avg_Emissivity_8-13μm,Avg_Absorptivity_0.3-2.5μm,Spectral_Match_Index,Net_Radiative_Power(W/m²),Solar_Gain(W/m²),Convective_Loss(W/m²),Conductive_Loss(W/m²),Net_Cooling_Power(W/m²),Equilibrium_Temp(°C),Temperature_Drop(°C)\n")
+            for p in performance_list:
+                f.write(f"{p.thickness_um:.1f},"
+                        f"{p.spectral_metric.avg_eps_window:.4f},"
+                        f"{p.spectral_metric.avg_alpha_solar:.4f},"
+                        f"{p.spectral_metric.spectral_match_index:.2f},"
+                        f"{p.net_radiative_power:.2f},"
+                        f"{p.solar_gain:.2f},"
+                        f"{p.convective_loss:.2f},"
+                        f"{p.conductive_loss:.2f},"
+                        f"{p.net_cooling_power:.2f},"
+                        f"{p.equilibrium_temp_C:.2f},"
+                        f"{p.temp_drop_C:.2f}\n")
+        print(f"\nResults saved to CSV file: {csv_path}")
+
+        # 6. Output technical recommendations
+        print("\n=== Technical Recommendations ===")
+        # Find optimal thickness based on spectral matching index and net cooling power
+        best_match_idx = np.argmax([p.spectral_metric.spectral_match_index for p in performance_list])
+        best_cooling_idx = np.argmax([p.net_cooling_power for p in performance_list])
+        best_radiative_idx = np.argmax([p.net_radiative_power for p in performance_list])  # 新增：净辐射功率最优厚度
+        best_match_thickness = performance_list[best_match_idx].thickness_um
+        best_cooling_thickness = performance_list[best_cooling_idx].thickness_um
+        best_radiative_thickness = performance_list[best_radiative_idx].thickness_um
+
+        print(
+            f"1. Optimal thickness for spectral matching: {best_match_thickness} μm (Spectral Matching Index: {performance_list[best_match_idx].spectral_metric.spectral_match_index:.2f})")
+        print(
+            f"2. Optimal thickness for net radiative power: {best_radiative_thickness} μm (Net Radiative Power: {performance_list[best_radiative_idx].net_radiative_power:.2f} W/m²)")
+        print(
+            f"3. Optimal thickness for cooling power: {best_cooling_thickness} μm (Net Cooling Power: {performance_list[best_cooling_idx].net_cooling_power:.2f} W/m²)")
+        print(
+            f"4. Recommended practical thickness: 25-50 μm (Balancing performance and cost, temperature drop: {performance_list[3].temp_drop_C:.1f}-{performance_list[4].temp_drop_C:.1f} °C)")
+        print(
+            "5. Material optimization direction: Reduce absorptivity in solar band (0.3-2.5μm), improve emissivity uniformity in atmospheric window (8-13μm)")
+        print(
+            "6. Engineering application suggestions: Optimize film-substrate interface design (e.g., add insulation layer) to reduce conductive loss; combine with shading structures to minimize solar absorption")
+
+    except Exception as e:
+        print(f"Error during execution: {e}")
+        import traceback
+        traceback.print_exc()
+
+
+# ------------------------------
+# Execution Entry (Update your data file path)
+# ------------------------------
+if __name__ == "__main__":
+    # Configure data path and study thicknesses
+    DATA_PATH = "/Users/spasolreisa/IdeaProjects/asiaMath/data.txt"  # Replace with your data.txt path
+    STUDY_THICKNESSES = [1, 5, 10, 25, 50, 100, 150,200 ,250,300]  # Adjustable thickness range
+
+    main(data_path=DATA_PATH, thicknesses=STUDY_THICKNESSES)

org/other/radiative_cooling_results/cooling_performance_results.csv

@@ -0,0 +1,11 @@
+Thickness(μm),Avg_Emissivity_8-13μm,Avg_Absorptivity_0.3-2.5μm,Spectral_Match_Index,Net_Radiative_Power(W/m²),Solar_Gain(W/m²),Convective_Loss(W/m²),Conductive_Loss(W/m²),Net_Cooling_Power(W/m²),Equilibrium_Temp(°C),Temperature_Drop(°C)
+1.0,0.2198,0.0001,1832.21,4213386159920.65,0.10,0.00,0.00,4213386159920.55,26.85,0.00
+5.0,0.5527,0.0006,938.24,10471946524462.82,0.50,0.00,0.00,10471946524462.32,26.85,0.00
+10.0,0.6845,0.0012,573.18,13000419684891.89,1.01,0.00,0.00,13000419684890.88,26.85,0.00
+25.0,0.8256,0.0030,278.83,15732438394151.59,2.52,0.00,0.00,15732438394149.08,26.85,0.00
+50.0,0.8964,0.0059,151.79,17117210018907.72,5.02,0.00,0.00,17117210018902.70,26.85,0.00
+100.0,0.9338,0.0117,79.78,17842980949637.75,9.95,0.00,0.00,17842980949627.80,26.85,0.00
+150.0,0.9423,0.0174,54.22,18006953306435.60,14.77,0.00,0.00,18006953306420.83,26.85,0.00
+200.0,0.9446,0.0229,41.22,18051728737920.30,19.48,0.00,0.00,18051728737900.82,26.85,0.00
+250.0,0.9453,0.0286,33.09,18064943852359.92,24.28,0.00,0.00,18064943852335.64,26.85,0.00
+300.0,0.9455,0.0339,27.91,18069013293873.77,28.79,0.00,0.00,18069013293844.97,26.85,0.00