Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (Version 2.4 - English Plots & Kilometer Units)
+# app.py (Version 2.5 - Chinese UI & English Plots)
 # -*- coding: utf-8 -*-
 """
 Refraction & Reflection Seismology Demonstrator (Gradio Web App)
@@ -6,10 +6,11 @@ Refraction & Reflection Seismology Demonstrator (Gradio Web App)
 This application is generated based on the Specification-Driven Development (SDD)
 process, fulfilling all user stories and acceptance criteria defined in `spec.md` v2.2+.
 
-Version 2.4 changes:
-1.  (Units) Converted all inputs, calculations, and displays from meters to kilometers.
-2.  (I18N) Translated all plot titles, labels, and legends to English.
-3.  Removed the CJK font setup as it is no longer needed for the plots.
+Version 2.5 changes:
+1.  (I18N) Reverted all UI components (labels, buttons, titles) and dynamic
+    Markdown text to Traditional Chinese.
+2.  (I18N) Kept plot-internal text (axes, legends, titles) in English as requested.
+3.  (Units) The unit system remains in kilometers (km) and km/s for usability.
 """
 
 # =============================
@@ -28,45 +29,45 @@ import matplotlib.pyplot as plt
 from PIL import Image
 
 # =============================
-# 2. Core Physics & Data Models
+# 2. Core Physics & Data Models (Units: km, km/s)
 # =============================
 
 @dataclass
 class Model2LayerRefraction:
-    V1: float # UNITS: Now in km/s
-    V2: float # UNITS: Now in km/s
-    h1: float # UNITS: Now in km
+    V1: float
+    V2: float
+    h1: float
 
     def validate(self):
         if not (self.V1 > 0 and self.V2 > 0 and self.h1 > 0):
-            raise ValueError("Model parameters (V1, V2, h1) must be positive.")
+            raise ValueError("模型參數 (V1, V2, h1) 必須是正數。")
         if self.V2 <= self.V1:
-            raise ValueError("V2 must be greater than V1 for critical refraction.")
+            raise ValueError("V2 必須大於 V1 才能發生臨界折射。")
 
 @dataclass
 class ModelReflectionSimple:
-    V1: float # UNITS: Now in km/s
-    h1: float # UNITS: Now in km
+    V1: float
+    h1: float
 
     def validate(self):
         if not (self.V1 > 0 and self.h1 > 0):
-            raise ValueError("Model parameters (V1, h1) must be positive.")
+            raise ValueError("模型參數 (V1, h1) 必須是正數。")
 
 @dataclass
 class SurveyLine:
-    length: float # UNITS: Now in km
+    length: float
     n_geophones: int
 
     def validate(self):
         if self.length <= 0:
-            raise ValueError("Survey length must be positive.")
+            raise ValueError("測線長度需為正數。")
         if self.n_geophones < 2:
-            raise ValueError("Number of geophones must be at least 2.")
+            raise ValueError("檢波器數量需 ≥ 2。")
 
     def positions(self) -> np.ndarray:
         return np.linspace(0.0, self.length, self.n_geophones)
 
-# --- Physics functions now operate in km and km/s ---
+
 def critical_angle(V1: float, V2: float) -> float:
     s = np.clip(V1 / V2, -1 + 1e-12, 1 - 1e-12)
     return float(np.arcsin(s))
@@ -87,7 +88,7 @@ def refraction_travel_times(model: Model2LayerRefraction, x: np.ndarray) -> Tupl
 def robust_line_fit(x: np.ndarray, t: np.ndarray) -> Tuple[float, float]:
     mask = np.isfinite(x) & np.isfinite(t)
     if np.sum(mask) < 2:
-        raise ValueError("Not enough points for linear regression.")
+        raise ValueError("線性回歸的點數不足。")
     A = np.vstack([x[mask], np.ones(np.sum(mask))]).T
     a, b = np.linalg.lstsq(A, t[mask], rcond=None)[0]
     return float(a), float(b)
@@ -96,16 +97,16 @@ def invert_from_first_arrivals(x: np.ndarray, t_first: np.ndarray, which_first:
     x_dir, t_dir = x[which_first == 0], t_first[which_first == 0]
     x_ref, t_ref = x[which_first == 1], t_first[which_first == 1]
 
-    if x_dir.size < 2: raise ValueError("Not enough direct wave arrivals for inversion.")
-    if x_ref.size < 2: raise ValueError("Not enough refracted wave arrivals for inversion. Increase survey length or layer thickness.")
+    if x_dir.size < 2: raise ValueError("直接波初達點不足，無法反演。")
+    if x_ref.size < 2: raise ValueError("折射波初達點不足，請增加測線長度或層厚。")
 
     a1, _ = robust_line_fit(x_dir, t_dir)
     a2, b2 = robust_line_fit(x_ref, t_ref)
 
-    if a1 <= 0 or a2 <= 0: raise ValueError("Non-physical slope (<=0) derived from data.")
+    if a1 <= 0 or a2 <= 0: raise ValueError("從數據導出的斜率非物理值 (≤0)。")
     V1_est, V2_est, t0_est = 1.0 / a1, 1.0 / a2, b2
 
-    if V2_est <= V1_est: raise ValueError("Inversion resulted in V2 <= V1, geometry may be insufficient.")
+    if V2_est <= V1_est: raise ValueError("反演得到 V2 ≤ V1，幾何可能不足或假設不適用。")
 
     ic_est = math.asin(min(0.999999999999, V1_est / V2_est))
     h1_est = (t0_est * V1_est) / (2.0 * math.cos(ic_est))
@@ -165,7 +166,7 @@ def plot_reflection_png(x, t_direct, t_reflect, t0, title="Reflection T-X (Singl
     buf.seek(0)
     return Image.open(buf).convert("RGBA")
     
-def plot_inversion_exercise_png(true_data: Dict, guess_data: Dict, title: str = "T-X Plot: Your Guess vs. Problem"):
+def plot_inversion_exercise_png(true_data: Dict, guess_data: Dict):
     fig, ax = plt.subplots(figsize=(7, 5), dpi=160)
     
     ax.plot(true_data['x'], true_data['t'], 'k--', linewidth=2, label="Original T-X Curve (Problem)")
@@ -176,7 +177,7 @@ def plot_inversion_exercise_png(true_data: Dict, guess_data: Dict, title: str =
 
     ax.set_xlim(0, max(true_data['x']))
     ax.set_ylim(0, max(true_data['t']) * 1.1)
-    ax.set(xlabel="Epicentral Distance (km)", ylabel="P-wave Travel Time (s)", title=title)
+    ax.set(xlabel="Epicentral Distance (km)", ylabel="P-wave Travel Time (s)", title="T-X Plot: Your Guess vs. Problem")
     ax.grid(True, linestyle="--", alpha=0.4)
     ax.legend()
     fig.tight_layout()
@@ -187,7 +188,7 @@ def plot_inversion_exercise_png(true_data: Dict, guess_data: Dict, title: str =
     return Image.open(buf).convert("RGBA")
 
 # =============================
-# 4. Gradio UI Callback Functions
+# 4. Gradio UI Callback Functions (I18N: Chinese Text Output)
 # =============================
 def simulate_refraction(V1, V2, h1, length, n_geophones, plot_reflection_toggle):
     try:
@@ -210,15 +211,15 @@ def simulate_refraction(V1, V2, h1, length, n_geophones, plot_reflection_toggle)
 
         try:
             V1_est, V2_est, h1_est = invert_from_first_arrivals(x, t_first, which_first)
-            inv_md = (f"### Inversion Results (from First Arrivals)\n- V1_est ≈ **{V1_est:.2f} km/s**\n- V2_est ≈ **{V2_est:.2f} km/s**\n- h1_est ≈ **{h1_est:.2f} km**\n")
+            inv_md = (f"### 反演結果 (由初達)\n- V1_est ≈ **{V1_est:.2f} 公里/秒**\n- V2_est ≈ **{V2_est:.2f} 公里/秒**\n- h1_est ≈ **{h1_est:.2f} 公里**\n")
         except Exception as e:
-            inv_md = f"### Inversion Results\n- Inversion failed: {e}"
+            inv_md = f"### 反演結果\n- 無法反演：{e}"
 
         ic_deg = math.degrees(critical_angle(model.V1, model.V2))
-        info_md = (f"### Model Summary\n- Input: V1={model.V1:.2f} km/s, V2={model.V2:.2f} km/s, h1={model.h1:.2f} km\n- Critical Angle ic ≈ **{ic_deg:.2f}°**\n- Intercept Time t0 ≈ **{t0:.4f} s**\n- Crossover Distance x_c ≈ **{x_c:.2f} km**\n")
+        info_md = (f"### 模型摘要\n- 輸入：V1={model.V1:.2f} 公里/秒，V2={model.V2:.2f} 公里/秒，h1={model.h1:.2f} 公里\n- 臨界角 ic ≈ **{ic_deg:.2f}°**\n- 截距時間 t0 ≈ **{t0:.4f} s**\n- 交會距離 x_c ≈ **{x_c:.2f} 公里**\n")
         
         if plot_reflection_toggle and t0_reflection is not None:
-            info_md += f"- **Also showing reflection**\n  - Assumed reflector depth={h1:.2f} km, velocity={V1:.2f} km/s\n  - Reflection t0 ≈ **{t0_reflection:.4f} s**\n"
+            info_md += f"- **同時顯示反射波**\n  - 假設反射界面深度={h1:.2f} 公里，上層速度={V1:.2f} 公里/秒\n  - 零位移反射時間 t0(ref) ≈ **{t0_reflection:.4f} s**\n"
 
         pil_img = plot_combined_png(x, t_direct, t_refrac, t_first, which_first, t_reflect=t_reflect_data)
         
@@ -233,7 +234,7 @@ def simulate_refraction(V1, V2, h1, length, n_geophones, plot_reflection_toggle)
             return pil_img, info_md + "\n" + inv_md, df, tmp_csv.name
 
     except Exception as e:
-        return None, f"❌ Error: {e}", None, None
+        return None, f"❌ 錯誤：{e}", None, None
 
 
 def simulate_reflection(V1, h1, length, n_geophones):
@@ -247,7 +248,7 @@ def simulate_reflection(V1, h1, length, n_geophones):
         t_direct = x / model.V1
         t_reflect, t0 = reflection_tx_hyperbola(model.V1, model.h1, x)
 
-        info_md = (f"### Model Summary\n- Input: V1={model.V1:.2f} km/s, Reflector Depth h1={model.h1:.2f} km\n- Zero-offset time t0 = **{t0:.4f} s**\n### Notes\n- Simplified NMO Hyperbola: t(x) = √(t0² + (x/V1)²)")
+        info_md = (f"### 模型摘要\n- 輸入：V1={model.V1:.2f} 公里/秒，反射界面深度 h1={model.h1:.2f} 公里\n- 零位移二次程時間 t0 = **{t0:.4f} s**\n### 說明\n- 單一水平反射界面、單層速度的簡化 NMO 超曲線： t(x) = √(t0² + (x/V1)²)")
         pil_img = plot_reflection_png(x, t_direct, t_reflect, t0)
         df = pd.DataFrame({"x_km": x, "t_direct_s": t_direct, "t_reflection_s": t_reflect})
         with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode='w', newline='') as tmp_csv:
@@ -255,14 +256,13 @@ def simulate_reflection(V1, h1, length, n_geophones):
             return pil_img, info_md, df, tmp_csv.name
 
     except Exception as e:
-        return None, f"❌ Error: {e}", None, None
+        return None, f"❌ 錯誤：{e}", None, None
 
-# UNITS: All presets updated to km and km/s
 REFRACTION_PRESETS: Dict[str, Dict] = {
-    "Engineering Geology / Bedrock Rippability": dict(V1=0.5, V2=2.5, h1=0.006, length=0.3, n_geophones=61),
-    "Hydrogeology / Water Table": dict(V1=0.4, V2=1.6, h1=0.004, length=0.2, n_geophones=41),
-    "Permafrost Engineering": dict(V1=0.7, V2=3.0, h1=0.0015, length=0.15, n_geophones=51),
-    "Crustal Scale / Moho Model": dict(V1=6.0, V2=8.0, h1=15.0, length=200.0, n_geophones=81),
+    "工程地質 / 岩盤面": dict(V1=0.5, V2=2.5, h1=0.006, length=0.3, n_geophones=61),
+    "水文地質 / 地下水面": dict(V1=0.4, V2=1.6, h1=0.004, length=0.2, n_geophones=41),
+    "寒區工程 / 永凍土": dict(V1=0.7, V2=3.0, h1=0.0015, length=0.15, n_geophones=51),
+    "地殼尺度 / 莫霍面模型": dict(V1=6.0, V2=8.0, h1=15.0, length=200.0, n_geophones=81),
 }
 def fill_refraction_preset(key: str):
     p = REFRACTION_PRESETS[key]
@@ -284,115 +284,176 @@ def interactive_exercise_callback(v1_guess, v2_guess, h1_guess):
         guess_data = {'x': x_km, 't_direct': t_direct, 't_refrac': t_refrac, 't_first': t_first}
         
         feedback_md = (
-            f"### Results for Your Guess\n"
-            f"- Crossover Distance x_c ≈ **{x_c:.2f} km**\n"
-            f"- Intercept Time t0 ≈ **{t0:.2f} s**\n"
+            f"### 你的猜測結果\n"
+            f"- 交會距離 x_c ≈ **{x_c:.2f} 公里**\n"
+            f"- 截距時間 t0 ≈ **{t0:.2f} s**\n"
             f"--- \n"
-            f"**Hint:** Adjusting $V_1$ changes the first slope; $V_2$ changes the second slope; $h_1$ changes the intercept time and crossover distance."
+            f"**提示：** 調整 $V_1$ 會改變第一段的斜率；調整 $V_2$ 會改變第二段的斜率；調整 $h_1$ 主要會改變截距時間 $t_0$ 和交會距離。"
         )
         pil_img = plot_inversion_exercise_png(TRUE_TX_DATA, guess_data)
         return pil_img, feedback_md
     except Exception as e:
-        return None, f"❌ Error: {e}"
+        return None, f"❌ 錯誤：{e}"
 
 
 # =============================
-# 5. Gradio UI Layout
+# 5. Gradio UI Layout (I18N: Chinese UI)
 # =============================
-OVERVIEW_PRINCIPLES_MD = "..." # Content omitted for brevity
-REFERENCE_LINKS_MD = "..." # Content omitted for brevity
-SOLUTION_MD = "..." # Content omitted for brevity
+OVERVIEW_PRINCIPLES_MD = """
+### 地震震測法概述 (Seismic Methods Overview)
+地震震測法利用人造震源產生的震波在地下傳播、反射與折射，再被地表的檢波器接收。透過分析震波的走時 (Travel Time) 與接收位置 (Offset)，可以反演出地下地層的構造與速度參數。本演示器著重於兩種最基本的震測法：**折射震測** 和 **反射震測**。
+#### **1. 折射震測原理 (Seismic Refraction Principles)**
+折射震測主要用於探測近地表地層的速度分佈和界面深度，特別是在存在明顯速度差異（通常是下層速度大於上層速度）的界面。
+* **波路徑 (Wave Paths):**
+    * **直接波 (Direct Wave):** 震波沿著地表淺層（第一層介質）直接傳播到檢波器。其走時 $t_{\\text{direct}} = x / V_1$，呈直線關係。
+    * **折射波 (Head Wave / Critical Refraction):** 震波從震源發出，在傳播到第一層與第二層的界面時，若入射角達到「臨界角」(Critical Angle) $i_c$，震波會在界面處產生折射，並沿著界面以第二層速度 $V_2$ 傳播，同時向上層發射出「頭波」（Head Wave）被檢波器接收。
+    * **臨界角 $i_c$:** 遵循 Snell's Law，當 $V_2 > V_1$ 時，$i_c = \\arcsin(V_1 / V_2)$。
+    * **折射波走時 $t_{\\text{refracted}}$:** 通常表示為 $t_{\\text{refracted}} = x / V_2 + t_0$，其中 $t_0$ 為「截距時間」(Intercept Time)：$t_0 = \\frac{2h_1 \\cos(i_c)}{V_1}$。
+* **T-X 圖 (Travel Time - Offset Plot):**
+    * 在 T-X 圖上，直接波表現為過原點的直線，斜率為 $1/V_1$。
+    * 折射波表現為一條斜率較小（因為 $V_2 > V_1$）的直線，其截距為 $t_0$。
+    * 在近距離，直接波先到達；超過某個「交會距離」(Crossover Distance) 後，折射波會先到達。透過分析這些初達波 (First Arrivals)，可以反演出 $V_1, V_2, h_1$。
+#### **2. 反射震測原理 (Seismic Reflection Principles)**
+反射震測主要用於獲得地下精細的地層構造圖，類似於超音波成像。震波在遇到不同地質介質（阻抗差異）的界面時會產生反射。
+* **波路徑:** 震波從震源發出，在界面處反射，然後被檢波器接收。
+* **走時關係:** 對於單一水平反射界面，震源和檢波器之間的距離為 $x$，界面深度為 $h_1$，上覆地層速度為 $V_1$：
+    * **零位移反射時間 $t_0$:** 當 $x=0$ 時（震源和檢波器在同一點），$t_0 = 2h_1 / V_1$。
+    * **反射波走時 $t(x)$ (NMO 超曲線):** $t(x) = \\sqrt{t_0^2 + (x/V_1)^2}$。這是一個雙曲線 (Hyperbola) 形狀，稱為「正常時差」(Normal Moveout, NMO) 超曲線。
+* **T-X 圖:** 反射波在 T-X 圖上呈現為一個以 $t_0$ 為頂點的超曲線。分析其形狀可以反演出地層速度和深度。
+---
+"""
+REFERENCE_LINKS_MD = """
+### 參考資料 / 延伸閱讀
+- US EPA — Seismic Refraction：<https://www.epa.gov/environmental-geophysics/seismic-refraction>
+- USGS TWRI 2-D2 — *Application of Seismic-Refraction Techniques to Hydrologic Studies*：<https://pubs.usgs.gov/twri/twri2d2/pdf/twri_2-d2.pdf>
+- CLU-IN — *Seismic Reflection and Refraction – Geophysical Methods*：<https://www.cluin.org/characterization/technologies/default2.focus/sec/Geophysical_Methods/cat/Seismic_Reflection_and_Refraction/>
+- SEG Wiki — *Seismic refraction*（入門與教學圖）：<https://wiki.seg.org/wiki/Seismic_refraction>
+- UBC Open Textbook — *Geophysics for Practicing Geoscientists*（Seismic Refraction 章節）：<https://opentextbc.ca/geophysics/chapter/seismic-refraction/>
+- SEG Wiki — *Normal moveout*：<https://wiki.seg.org/wiki/Normal_moveout>
+- SEG Wiki — *Seismic reflection*：<https://wiki.seg.org/wiki/Seismic_reflection>
+---
+"""
+SOLUTION_MD = """
+### 參考解答與說明
+1.  **地殼速度 ($V_1$)**:
+    * 從圖中第一段直線（直接波）讀取，它通過 (0 km, 0 s) 和交會點 (30 km, 5 s)。
+    * $V_1 = \\Delta x / \\Delta t = (30 - 0) \\, \\text{km} / (5 - 0) \\, \\text{s} = \\mathbf{6.0 \\, \\text{km/s}}$。
+2.  **地函速度 ($V_2$)**:
+    * 從圖中第二段直線（折射波）讀取斜率，它通過 (30 km, 5 s) 和 (100 km, 13 s)。
+    * 斜率 $m_2 = \\Delta t / \\Delta x = (13 - 5) \\, \\text{s} / (100 - 30) \\, \\text{km} = 8 \\, \\text{s} / 70 \\, \\text{km}$。
+    * $V_2 = 1 / m_2 = 70 / 8 = \\mathbf{8.75 \\, \\text{km/s}}$。
+3.  **地殼厚度 ($h_1$)**:
+    * 首先計算截距時間 $t_0$。將第二段直線反向延伸至 $x=0$。
+    * 使用點斜式：$t - t_1 = m_2 (x - x_1) \\Rightarrow t - 5 = (8/70)(x - 30)$。
+    * 當 $x=0$ 時，$t_0 = 5 - (8/70) \\times 30 = 5 - 24/7 \\approx 1.57 \\, \\text{s}$。
+    * 使用公式 $h_1 = \\frac{t_0 V_1 V_2}{2\\sqrt{V_2^2 - V_1^2}}$。
+    * $h_1 = \\frac{1.57 \\times 6.0 \\times 8.75}{2\\sqrt{8.75^2 - 6.0^2}} \\approx \\frac{82.425}{2\\sqrt{76.56 - 36}} \\approx \\frac{82.425}{2 \\times 6.37} \\approx \\mathbf{16.5 \\, \\text{km}}$。
+4.  **推論**:
+    * 地殼 P 波速度約 6.0 km/s，地函 P 波速度約 8.75 km/s，這與大陸或海洋地殼的典型速度相符。
+    * 然而，地殼厚度約 16.5 km，這比典型的海洋地殼（約 5-10 km）厚，但比典型的大陸地殼（約 30-50 km）薄很多。
+    * 因此，這可能代表**過渡型地殼**，例如大陸棚、大陸裂谷，或是一個較厚的海洋地殼區域（如冰島）。
+"""
 
 theme = gr.themes.Soft(primary_hue=gr.themes.colors.blue, secondary_hue=gr.themes.colors.sky).set(
     body_background_fill="#f8f9fa", block_background_fill="white", block_radius="16px", block_shadow="0 4px 12px rgba(0,0,0,.08)")
 
 with gr.Blocks(theme=theme, css=".markdown h2, .markdown h3 { margin-top: .6rem; } .footer-note { font-size: 12px; color: #6b7280; }") as demo:
-    gr.Markdown("# Refraction & Reflection Seismology Demonstrator")
+    gr.Markdown("# 折射 & 反射 震測原理演示器")
+
     with gr.Tabs():
-        with gr.Tab("Overview"):
-            # UI content...
-            pass
-        with gr.Tab("Refraction Simulator"):
+        with gr.Tab("概述 Overview"):
+            gr.Markdown(
+                """
+**目標**：以簡化二層水平模型（折射）與單層水平反射界面（反射），說明近地表地震方法的走時幾何與參數反演。  
+**注意**：此為教學簡化模型。真實場域常見側向變化、多層、低速夾層、速度反轉與噪音；需採用更進階處理（多層射線追蹤、折射層析、RMS/NMO/疊加），或與 **GPR / MASW / 電阻率** 等多方法聯合解譯。
+                """,
+                elem_classes=["footer-note"]
+            )
+            gr.Markdown(OVERVIEW_PRINCIPLES_MD)
+            gr.Markdown(REFERENCE_LINKS_MD)
+
+        with gr.Tab("折射 Refraction 模擬器"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    # UNITS: All labels and values changed to km, km/s
-                    V1_r = gr.Number(label="V1 (km/s)", value=1.5, precision=2)
-                    V2_r = gr.Number(label="V2 (km/s)", value=3.0, precision=2)
-                    h1_r = gr.Number(label="h1 (km)", value=0.02, precision=3)
-                    length_r = gr.Number(label="Survey Length (km)", value=1.0, precision=2)
-                    n_r = gr.Slider(label="Number of Geophones", value=51, minimum=2, maximum=401, step=1)
-                    plot_reflection_toggle_r = gr.Checkbox(label="Overlay Reflection Plot", value=False)
-                    run_r = gr.Button("🚀 Run Refraction Simulation", variant="primary")
+                    V1_r = gr.Number(label="V1 (公里/秒)", value=1.5, precision=2)
+                    V2_r = gr.Number(label="V2 (公里/秒)", value=3.0, precision=2)
+                    h1_r = gr.Number(label="h1 (公里)", value=0.02, precision=3)
+                    length_r = gr.Number(label="測線長度 (公里)", value=1.0, precision=2)
+                    n_r = gr.Slider(label="檢波器數量", value=51, minimum=2, maximum=401, step=1)
+                    plot_reflection_toggle_r = gr.Checkbox(label="同時顯示反射波", value=False)
+                    run_r = gr.Button("🚀 執行折射模擬", variant="primary")
                 with gr.Column(scale=2):
-                    out_img_r = gr.Image(label="T-X Plot (Refraction / Combined)", type="pil")
+                    out_img_r = gr.Image(label="T-X 圖 (英文)", type="pil")
                     out_info_r = gr.Markdown()
-                    out_df_r = gr.Dataframe(label="Synthetic Data (Downloadable CSV)")
-                    out_csv_r = gr.File(label="Download CSV")
+                    out_df_r = gr.Dataframe(label="合成資料 (可下載 CSV)")
+                    out_csv_r = gr.File(label="下載 CSV")
             run_r.click(simulate_refraction, inputs=[V1_r, V2_r, h1_r, length_r, n_r, plot_reflection_toggle_r], outputs=[out_img_r, out_info_r, out_df_r, out_csv_r])
 
-        with gr.Tab("Reflection Simulator"):
+        with gr.Tab("反射 Reflection 模擬器"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    # UNITS: All labels and values changed to km, km/s
-                    V1_s = gr.Number(label="V1 (km/s)", value=1.6, precision=2)
-                    h1_s = gr.Number(label="Reflector Depth h1 (km)", value=0.02, precision=3)
-                    length_s = gr.Number(label="Survey Length (km)", value=0.6, precision=2)
-                    n_s = gr.Slider(label="Number of Geophones", value=61, minimum=2, maximum=401, step=1)
-                    run_s = gr.Button("🚀 Run Reflection Simulation", variant="primary")
+                    V1_s = gr.Number(label="V1 (公里/秒)", value=1.6, precision=2)
+                    h1_s = gr.Number(label="反射界面深度 h1 (公里)", value=0.02, precision=3)
+                    length_s = gr.Number(label="測線長度 (公里)", value=0.6, precision=2)
+                    n_s = gr.Slider(label="檢波器數量", value=61, minimum=2, maximum=401, step=1)
+                    run_s = gr.Button("🚀 執行反射模擬", variant="primary")
                 with gr.Column(scale=2):
-                    out_img_s = gr.Image(label="T-X Plot (Reflection)", type="pil")
+                    out_img_s = gr.Image(label="T-X 圖 (英文)", type="pil")
                     out_info_s = gr.Markdown()
-                    out_df_s = gr.Dataframe(label="Synthetic Data (Downloadable CSV)")
-                    out_csv_s = gr.File(label="Download CSV")
+                    out_df_s = gr.Dataframe(label="合成資料 (可下載 CSV)")
+                    out_csv_s = gr.File(label="下載 CSV")
             run_s.click(simulate_reflection, inputs=[V1_s, h1_s, length_s, n_s], outputs=[out_img_s, out_info_s, out_df_s, out_csv_s])
 
-        with gr.Tab("Application Presets (Refraction)"):
+        with gr.Tab("應用示範 (折射)"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    preset_choice = gr.Radio(list(REFRACTION_PRESETS.keys()), label="Scenario", value="Engineering Geology / Bedrock Rippability")
-                    load_btn = gr.Button("Load Parameters")
-                    run_preset_btn = gr.Button("Run with Preset")
+                    preset_choice = gr.Radio(list(REFRACTION_PRESETS.keys()), label="情境", value="工程地質 / 岩盤面")
+                    load_btn = gr.Button("載入參數")
+                    run_preset_btn = gr.Button("一鍵執行")
                 with gr.Column(scale=2):
-                    # UNITS: All labels and values changed to km, km/s
-                    V1_p = gr.Number(label="V1 (km/s)", interactive=True)
-                    V2_p = gr.Number(label="V2 (km/s)", interactive=True)
-                    h1_p = gr.Number(label="h1 (km)", interactive=True)
-                    length_p = gr.Number(label="Survey Length (km)", interactive=True)
-                    n_p = gr.Slider(label="Number of Geophones", minimum=2, maximum=401, step=1, value=61, interactive=True)
-                    plot_reflection_toggle_p = gr.Checkbox(label="Overlay Reflection Plot", value=False)
+                    V1_p = gr.Number(label="V1 (公里/秒)", interactive=True)
+                    V2_p = gr.Number(label="V2 (公里/秒)", interactive=True)
+                    h1_p = gr.Number(label="h1 (公里)", interactive=True)
+                    length_p = gr.Number(label="測線長度 (公里)", interactive=True)
+                    n_p = gr.Slider(label="檢波器數量", minimum=2, maximum=401, step=1, value=61, interactive=True)
+                    plot_reflection_toggle_p = gr.Checkbox(label="同時顯示反射波", value=False)
             
             load_btn.click(fill_refraction_preset, inputs=[preset_choice], outputs=[V1_p, V2_p, h1_p, length_p, n_p])
             
             with gr.Row():
                 with gr.Column(scale=1):
-                    out_img_p = gr.Image(label="T-X Plot (Refraction / Combined)", type="pil")
+                    out_img_p = gr.Image(label="T-X 圖 (英文)", type="pil")
                 with gr.Column(scale=1):
                     out_info_p = gr.Markdown()
-                    out_df_p = gr.Dataframe(label="Synthetic Data")
-                    out_csv_p = gr.File(label="Download CSV")
+                    out_df_p = gr.Dataframe(label="合成資料")
+                    out_csv_p = gr.File(label="下載 CSV")
 
             run_preset_btn.click(simulate_refraction, inputs=[V1_p, V2_p, h1_p, length_p, n_p, plot_reflection_toggle_p], outputs=[out_img_p, out_info_p, out_df_p, out_csv_p])
         
-        with gr.Tab("Interactive Exercise: T-X Inversion"):
+        with gr.Tab("實作練習：走時曲線反演"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    gr.Markdown("### Problem")
-                    gr.Image("problem.jpg", label="Problem T-X Curve", show_download_button=False)
-                    gr.Markdown("The P-wave travel-time curve is shown above. Assuming the main velocity change occurs at the crust-mantle boundary, please determine: ...") # Simplified problem text
+                    gr.Markdown("### 題目")
+                    gr.Image("problem.jpg", label="題目走時曲線圖", show_download_button=False)
+                    gr.Markdown("""
+                    上圖所示為 P 波之走時曲線圖，假設地震發生於地表，橫軸是震央距離（公里），縱軸為 P 波走時（秒），如果主要的震波速度變化在地殼與地函交界，請問：
+                    1. 地殼及地函的震波速度各為多少？
+                    2. 地殼的厚度又是多少？
+                    3. 就你所得的結果推測，此為海洋板塊或是大陸板塊？
+                    """)
                 with gr.Column(scale=2):
-                    gr.Markdown("### Interactive Forward-Modeling Sandbox")
-                    gr.Markdown("Adjust the parameters to see if your modeled T-X curve matches the problem's curve!")
+                    gr.Markdown("### 互動正演沙盒")
+                    gr.Markdown("在此調整你猜測的模型參數，看看產生的走時曲線是否能與題目中的曲線吻合！")
                     with gr.Row():
-                        # UNITS: All labels and values changed to km, km/s
-                        v1_guess = gr.Slider(minimum=3.0, maximum=8.0, value=5.0, step=0.1, label="Guessed Crustal Velocity V1 (km/s)")
-                        v2_guess = gr.Slider(minimum=6.0, maximum=10.0, value=7.5, step=0.1, label="Guessed Mantle Velocity V2 (km/s)")
-                        h1_guess = gr.Slider(minimum=5.0, maximum=40.0, value=20.0, step=0.5, label="Guessed Crustal Thickness h1 (km)")
+                        v1_guess = gr.Slider(minimum=3.0, maximum=8.0, value=5.0, step=0.1, label="猜測的地殼速度 V1 (公里/秒)")
+                        v2_guess = gr.Slider(minimum=6.0, maximum=10.0, value=7.5, step=0.1, label="猜測的地函速度 V2 (公里/秒)")
+                        h1_guess = gr.Slider(minimum=5.0, maximum=40.0, value=20.0, step=0.5, label="猜測的地殼厚度 h1 (公里)")
                     
-                    plot_exercise = gr.Image(label="Your Guess (Color) vs. Problem (Dashed Black)", type="pil")
+                    plot_exercise = gr.Image(label="疊加比較圖 (英文)", type="pil")
                     feedback_exercise = gr.Markdown()
                     
-                    with gr.Accordion("Show/Hide Reference Solution", open=False):
-                        gr.Markdown("...") # Solution Markdown content
+                    with gr.Accordion("顯示/隱藏參考答案", open=False):
+                        gr.Markdown(SOLUTION_MD)
                         
             for slider in [v1_guess, v2_guess, h1_guess]:
                 slider.change(
@@ -402,7 +463,7 @@ with gr.Blocks(theme=theme, css=".markdown h2, .markdown h3 { margin-top: .6rem;
                     show_progress="hidden"
                 )
 
-    gr.Markdown("--- Provided by the **Seismology Demonstrator** ---", elem_classes=["footer-note"])
+    gr.Markdown("--- 由 **Seismology Demonstrator** 提供 ---", elem_classes=["footer-note"])
 
 if __name__ == "__main__":
     demo.launch()