T-Tail HALE 02：Trim 与平衡构型¶

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这一页在上一页的几何检查基础上运行 StaticTrim。

0. 导入公共工具¶

In [1]:

import os
import sys
from pathlib import Path

os.environ.setdefault("MPLCONFIGDIR", str(Path("_sharpy_runs") / ".mplconfig"))

candidate_dirs = [
    Path.cwd(),
    Path.cwd() / "docs" / "reference-aircraft",
    Path("docs/reference-aircraft"),
]
for candidate in candidate_dirs:
    if (candidate / "ttail_hale_utils.py").exists():
        sys.path.insert(0, str(candidate.resolve()))
        break
else:
    raise FileNotFoundError("没有找到 ttail_hale_utils.py。请从仓库根目录或 docs/reference-aircraft 目录运行本 Notebook。")

import matplotlib.pyplot as plt
import numpy as np
from IPython.display import HTML, display

import ttail_hale_utils as hale

hale.configure_plots()

import os import sys from pathlib import Path os.environ.setdefault("MPLCONFIGDIR", str(Path("_sharpy_runs") / ".mplconfig")) candidate_dirs = [ Path.cwd(), Path.cwd() / "docs" / "reference-aircraft", Path("docs/reference-aircraft"), ] for candidate in candidate_dirs: if (candidate / "ttail_hale_utils.py").exists(): sys.path.insert(0, str(candidate.resolve())) break else: raise FileNotFoundError("没有找到 ttail_hale_utils.py。请从仓库根目录或 docs/reference-aircraft 目录运行本 Notebook。") import matplotlib.pyplot as plt import numpy as np from IPython.display import HTML, display import ttail_hale_utils as hale hale.configure_plots()

1. 生成模型并写入 trim 配置¶

这里的 flow 是：

BeamLoader -> AerogridLoader -> StaticTrim -> BeamLoads

StaticTrim 内部仍然会调用 StaticCoupled，但我们把输出集中在可解释的 trim 迭代表和最终构型上。

In [2]:

case_dir = hale.prepare_hale_case("02_trim", force=True)
model = hale.read_model(case_dir)

trim_config = hale.write_solver_variant(
    case_dir,
    "ttail_hale_trim.sharpy",
    ["BeamLoader", "AerogridLoader", "StaticTrim", "BeamLoads"],
)

print("trim config:", trim_config)
display(HTML(hale.html_table(hale.control_surface_summary(model))))

case_dir = hale.prepare_hale_case("02_trim", force=True) model = hale.read_model(case_dir) trim_config = hale.write_solver_variant( case_dir, "ttail_hale_trim.sharpy", ["BeamLoader", "AerogridLoader", "StaticTrim", "BeamLoads"], ) print("trim config:", trim_config) display(HTML(hale.html_table(hale.control_surface_summary(model))))

trim config: _sharpy_runs/ttail_hale_reference_aircraft/02_trim/simple_HALE/ttail_hale_trim.sharpy

control id	role	initial deflection [deg]	surfaces
0	elevator on horizontal tail	-2.0800	right horizontal tail / elevator left horizontal tail / elevator
1	rudder on vertical fin	0.0000	vertical fin / rudder

2. 运行 StaticTrim¶

求解器会调整迎角、升降舵偏角和推力，使纵向平衡残差收敛。下面保留最终数据对象，后面直接用它画 trim 后的气动网格。

In [3]:

trim_data, trim_log = hale.run_solver(trim_config)

print("structure timesteps:", len(trim_data.structure.timestep_info))
print("aero timesteps:", len(trim_data.aero.timestep_info))
print("captured solver messages:", len(trim_log))

trim_data, trim_log = hale.run_solver(trim_config) print("structure timesteps:", len(trim_data.structure.timestep_info)) print("aero timesteps:", len(trim_data.aero.timestep_info)) print("captured solver messages:", len(trim_log))

fatal: not a git repository (or any of the parent directories): .git

structure timesteps: 1
aero timesteps: 1
captured solver messages: 0

3. Trim 迭代表¶

trim_iterations.txt 中最重要的是三列残差：Fz、My、Fx。它们分别对应垂向力、俯仰力矩和轴向力/推力平衡。

In [4]:

trim_rows = hale.trim_iterations(case_dir)
display(HTML(hale.html_table(trim_rows)))
hale.plot_trim_iterations(trim_rows)

final_trim = trim_rows[-1]
display(HTML(hale.html_table([final_trim])))

trim_rows = hale.trim_iterations(case_dir) display(HTML(hale.html_table(trim_rows))) hale.plot_trim_iterations(trim_rows) final_trim = trim_rows[-1] display(HTML(hale.html_table([final_trim])))

iter	alpha[deg]	elev[deg]	thrust	Fx	Fy	Fz	Mx	My	Mz
0.0000	4.3100	-2.0800	6.1600	-0.3600	-0.0000	0.8011	0.0000	-0.6942	0.0000
0.0000	7.1748	-4.9448	6.1600	-27.8570	-0.0000	280.1531	0.0000	-105.5365	0.0000
0.0000	4.3100	0.7848	6.1600	-2.5530	0.0000	38.7843	-0.0000	-377.6456	0.0000
0.0000	4.3100	-2.0800	8.1600	-2.3600	-0.0000	0.8011	0.0000	-0.6942	0.0000
1.0000	4.3018	-2.0771	5.8000	0.0660	-0.0000	-0.2783	0.0000	0.2441	0.0000
2.0000	4.3039	-2.0778	5.8558	-0.0068	-0.0000	0.0003	0.0000	0.0006	0.0000

iter	alpha[deg]	elev[deg]	thrust	Fx	Fy	Fz	Mx	My	Mz
2.0000	4.3039	-2.0778	5.8558	-0.0068	-0.0000	0.0003	0.0000	0.0006	0.0000

4. Trim 后三维构型¶

下面这张图使用 SHARPy 返回的 data.aero.timestep_info[-1].zeta 和 data.structure.timestep_info[-1].pos，不是重新画未变形输入文件。它代表 trim 求解之后的平衡构型。

In [5]:

traces = hale.aircraft_traces_from_data(trim_data, timestep=-1, opacity=0.42, suffix=" (trim)")
hale.show_plotly(
    traces,
    "Trimmed T-Tail HALE: structural beam and aerodynamic grid",
    camera={"eye": {"x": 1.55, "y": -1.9, "z": 0.85}},
)

traces = hale.aircraft_traces_from_data(trim_data, timestep=-1, opacity=0.42, suffix=" (trim)") hale.show_plotly( traces, "Trimmed T-Tail HALE: structural beam and aerodynamic grid", camera={"eye": {"x": 1.55, "y": -1.9, "z": 0.85}}, )

5. 最终载荷¶

下面把最后一个结构时间步的节点合力。

In [6]:

ts = trim_data.structure.timestep_info[-1]
total_forces = hale.timestep_total_forces(ts)
force_row = {
    "sum Fx": float(np.sum(total_forces[:, 0])),
    "sum Fy": float(np.sum(total_forces[:, 1])),
    "sum Fz": float(np.sum(total_forces[:, 2])),
    "sum Mx": float(np.sum(total_forces[:, 3])),
    "sum My": float(np.sum(total_forces[:, 4])),
    "sum Mz": float(np.sum(total_forces[:, 5])),
}
display(HTML(hale.html_table([force_row])))

ts = trim_data.structure.timestep_info[-1] total_forces = hale.timestep_total_forces(ts) force_row = { "sum Fx": float(np.sum(total_forces[:, 0])), "sum Fy": float(np.sum(total_forces[:, 1])), "sum Fz": float(np.sum(total_forces[:, 2])), "sum Mx": float(np.sum(total_forces[:, 3])), "sum My": float(np.sum(total_forces[:, 4])), "sum Mz": float(np.sum(total_forces[:, 5])), } display(HTML(hale.html_table([force_row])))

sum Fx	sum Fy	sum Fz	sum Mx	sum My	sum Mz
53.2635	7.8311	50.1438	1.3412	0.1262	-0.2752