feat: add structural dynamics analysis

docs/validation/density_sensitivity.csv

@@ -0,0 +1,6 @@
+parameter_value,mode_1_frequency_hz
+6280.0,55.23184
+7065.0,52.07308
+7850.0,49.40086
+8635.0,47.10187
+9420.0,45.09661

docs/validation/modal_frequencies.csv

@@ -0,0 +1,11 @@
+mode,frequency_hz
+1,49.40086
+2,84.15125
+3,305.2293
+4,506.5651
+5,692.4157
+6,836.315
+7,1292.885
+8,1339.754
+9,1591.106
+10,2078.087

docs/validation/section_height_sensitivity.csv

@@ -0,0 +1,6 @@
+parameter_value,mode_1_frequency_hz
+0.032,40.01148
+0.036000000000000004,44.74873
+0.04,49.40086
+0.044000000000000004,53.97453
+0.048,58.47559

docs/validation/thickness_sensitivity.csv

@@ -0,0 +1,6 @@
+parameter_value,mode_1_frequency_hz
+0.0012000000000000001,49.76519
+0.00135,49.58304
+0.0015,49.40086
+0.0016500000000000002,49.21864
+0.0018,49.03639

docs/validation/youngs_modulus_sensitivity.csv

@@ -0,0 +1,6 @@
+parameter_value,mode_1_frequency_hz
+168000000000.0,44.18547
+189000000000.0,46.86577
+210000000000.0,49.40086
+231000000000.00003,51.81206
+252000000000.0,54.11593

scripts/run_modal_analysis.py

@@ -0,0 +1,113 @@
+import csv
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+
+from bodysimpy.analysis.modal_validation import (
+    validate_modal_response,
+)
+from bodysimpy.config.loader import load_config
+from bodysimpy.modeling.crossmember import (
+    build_crossmember_model,
+)
+
+
+def main() -> None:
+    config = load_config("configs/baseline_crossmember.yaml")
+
+    model = build_crossmember_model(config)
+
+    result = validate_modal_response(
+        model,
+        modes=10,
+    )
+
+    table_path = Path("docs/validation/modal_frequencies.csv")
+
+    table_path.parent.mkdir(
+        parents=True,
+        exist_ok=True,
+    )
+
+    with table_path.open(
+        "w",
+        encoding="utf-8",
+        newline="",
+    ) as stream:
+        writer = csv.writer(stream)
+
+        writer.writerow(
+            [
+                "mode",
+                "frequency_hz",
+            ]
+        )
+
+        for mode, frequency in enumerate(
+            result.fea_frequencies_hz,
+            start=1,
+        ):
+            writer.writerow(
+                [
+                    mode,
+                    frequency,
+                ]
+            )
+
+    modes = list(
+        range(
+            1,
+            len(result.fea_frequencies_hz) + 1,
+        )
+    )
+
+    figure_path = Path("docs/figures/modal_frequencies.png")
+
+    figure_path.parent.mkdir(
+        parents=True,
+        exist_ok=True,
+    )
+
+    plt.figure(figsize=(8, 5))
+
+    plt.plot(
+        modes,
+        result.fea_frequencies_hz,
+        marker="o",
+    )
+
+    plt.xlabel("Mode number")
+    plt.ylabel("Natural frequency [Hz]")
+    plt.title("BodySimPy Baseline Natural Frequencies")
+
+    plt.xticks(modes)
+    plt.grid(True)
+    plt.tight_layout()
+
+    plt.savefig(
+        figure_path,
+        dpi=200,
+    )
+
+    plt.close()
+
+    print()
+    print("BodySimPy Modal Analysis")
+    print("-" * 55)
+
+    for mode, frequency in enumerate(
+        result.fea_frequencies_hz,
+        start=1,
+    ):
+        print(f"Mode {mode:>2}: {frequency:>12.4f} Hz")
+
+    print()
+    print(f"Analytical mode 1: {result.analytical_mode_1_hz:.4f} Hz")
+
+    print(f"FEA mode 1:        {result.fea_mode_1_hz:.4f} Hz")
+
+    print(f"Mode-1 error:      {result.mode_1_error_percent:.4f} %")
+
+
+if __name__ == "__main__":
+    main()

scripts/run_modal_sensitivity.py

@@ -0,0 +1,145 @@
+import csv
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+
+from bodysimpy.analysis.modal_sensitivity import (
+    ModalSensitivityPoint,
+    density_sensitivity,
+    section_height_sensitivity,
+    thickness_sensitivity,
+    youngs_modulus_sensitivity,
+)
+from bodysimpy.config.loader import load_config
+from bodysimpy.modeling.crossmember import (
+    build_crossmember_model,
+)
+
+MULTIPLIERS = (
+    0.8,
+    0.9,
+    1.0,
+    1.1,
+    1.2,
+)
+
+
+def write_study(
+    *,
+    name: str,
+    x_label: str,
+    points: tuple[ModalSensitivityPoint, ...],
+    scale: float,
+) -> None:
+    csv_path = Path(f"docs/validation/{name}_sensitivity.csv")
+
+    csv_path.parent.mkdir(
+        parents=True,
+        exist_ok=True,
+    )
+
+    with csv_path.open(
+        "w",
+        encoding="utf-8",
+        newline="",
+    ) as stream:
+        writer = csv.writer(stream)
+
+        writer.writerow(
+            [
+                "parameter_value",
+                "mode_1_frequency_hz",
+            ]
+        )
+
+        for point in points:
+            writer.writerow(
+                [
+                    point.parameter_value,
+                    point.mode_1_frequency_hz,
+                ]
+            )
+
+    x_values = [point.parameter_value * scale for point in points]
+
+    frequencies = [point.mode_1_frequency_hz for point in points]
+
+    figure_path = Path(f"docs/figures/{name}_sensitivity.png")
+
+    figure_path.parent.mkdir(
+        parents=True,
+        exist_ok=True,
+    )
+
+    plt.figure(figsize=(7, 5))
+
+    plt.plot(
+        x_values,
+        frequencies,
+        marker="o",
+    )
+
+    plt.xlabel(x_label)
+    plt.ylabel("Mode-1 natural frequency [Hz]")
+
+    plt.title(f"Mode-1 Sensitivity — {name.replace('_', ' ').title()}")
+
+    plt.grid(True)
+    plt.tight_layout()
+
+    plt.savefig(
+        figure_path,
+        dpi=200,
+    )
+
+    plt.close()
+
+
+def main() -> None:
+    config = load_config("configs/baseline_crossmember.yaml")
+
+    model = build_crossmember_model(config)
+
+    write_study(
+        name="thickness",
+        x_label="Wall thickness [mm]",
+        points=thickness_sensitivity(
+            model,
+            multipliers=MULTIPLIERS,
+        ),
+        scale=1000.0,
+    )
+
+    write_study(
+        name="youngs_modulus",
+        x_label="Young's modulus [GPa]",
+        points=youngs_modulus_sensitivity(
+            model,
+            multipliers=MULTIPLIERS,
+        ),
+        scale=1e-9,
+    )
+
+    write_study(
+        name="density",
+        x_label="Density [kg/m³]",
+        points=density_sensitivity(
+            model,
+            multipliers=MULTIPLIERS,
+        ),
+        scale=1.0,
+    )
+
+    write_study(
+        name="section_height",
+        x_label="Section height [mm]",
+        points=section_height_sensitivity(
+            model,
+            multipliers=MULTIPLIERS,
+        ),
+        scale=1000.0,
+    )
+
+
+if __name__ == "__main__":
+    main()