602560c46a
Neural Acceleration (MLP Surrogate): - Add run_nn_optimization.py with hybrid FEA/NN workflow - MLP architecture: 4-layer (64->128->128->64) with BatchNorm/Dropout - Three workflow modes: - --all: Sequential export->train->optimize->validate - --hybrid-loop: Iterative Train->NN->Validate->Retrain cycle - --turbo: Aggressive single-best validation (RECOMMENDED) - Turbo mode: 5000 NN trials + 50 FEA validations in ~12 minutes - Separate nn_study.db to avoid overloading dashboard Performance Results (bracket_pareto_3obj study): - NN prediction errors: mass 1-5%, stress 1-4%, stiffness 5-15% - Found minimum mass designs at boundary (angle~30deg, thick~30mm) - 100x speedup vs pure FEA exploration Protocol Operating System: - Add .claude/skills/ with Bootstrap, Cheatsheet, Context Loader - Add docs/protocols/ with operations (OP_01-06) and system (SYS_10-14) - Update SYS_14_NEURAL_ACCELERATION.md with MLP Turbo Mode docs NX Automation: - Add optimization_engine/hooks/ for NX CAD/CAE automation - Add study_wizard.py for guided study creation - Fix FEM mesh update: load idealized part before UpdateFemodel() New Study: - bracket_pareto_3obj: 3-objective Pareto (mass, stress, stiffness) - 167 FEA trials + 5000 NN trials completed - Demonstrates full hybrid workflow 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
73 lines
1.8 KiB
Python
73 lines
1.8 KiB
Python
"""
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Atomizer NX Open Hooks
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======================
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Direct Python hooks for NX CAD/CAE operations via NX Open API.
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This module provides a clean Python interface for manipulating NX parts
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programmatically. Each hook executes NX journals via `run_journal.exe`
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and returns structured JSON results.
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Modules
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-------
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nx_cad : CAD manipulation hooks
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- part_manager : Open, close, save parts
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- expression_manager : Get/set design parameters
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- geometry_query : Mass properties, bodies, volumes
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- feature_manager : Suppress/unsuppress features
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nx_cae : CAE/Simulation hooks (Phase 2)
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- solver_manager : BDF export, solve simulations
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Quick Start
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-----------
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>>> from optimization_engine.hooks.nx_cad import expression_manager
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>>> result = expression_manager.get_expressions("C:/model.prt")
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>>> if result["success"]:
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... for name, expr in result["data"]["expressions"].items():
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... print(f"{name} = {expr['value']}")
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>>> from optimization_engine.hooks.nx_cae import solver_manager
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>>> result = solver_manager.get_bdf_from_solution_folder("C:/model.sim")
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Requirements
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------------
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- Siemens NX 2506+ installed
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- NX_BIN_PATH environment variable (or default path)
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- Python 3.8+ with atomizer conda environment
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See Also
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--------
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- optimization_engine/hooks/README.md : Full documentation
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- docs/plans/NX_OPEN_AUTOMATION_ROADMAP.md : Development roadmap
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Version
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-------
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1.1.0 (2025-12-06) - Added nx_cae module with solver_manager
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1.0.0 (2025-12-06) - Initial release with nx_cad hooks
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"""
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from .nx_cad import (
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part_manager,
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expression_manager,
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geometry_query,
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feature_manager,
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)
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from .nx_cae import (
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solver_manager,
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)
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__all__ = [
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# CAD hooks
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'part_manager',
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'expression_manager',
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'geometry_query',
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'feature_manager',
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# CAE hooks
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'solver_manager',
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]
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__version__ = '1.1.0'
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__author__ = 'Atomizer'
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