import time

from typing import Dict, List

class ActiveEngineeringAI:

def __init__(self, constraints: Dict):

self.constraints = constraints

self.iteration_count = 0

self.history = []

def ingest_sensor_data(self, telemetry: Dict):

"""Processes real-time feedback from digital twins or physical sensors."""

print(f"[System] Syncing telemetry: {telemetry}")

return telemetry

def physics_reasoning_engine(self, design_data: Dict):

"""

Validates the design against structural and fluid dynamics.

In a production environment, this connects to FEA/CFD solvers.

"""

# Example: Calculating Stress/Strain or Thermal Efficiency

efficiency = design_data.get("base_efficiency", 0.85) + (self.iteration_count * 0.01)

return min(efficiency, 0.99)

def kaizen_optimizer(self, current_state: float):

"""Applies superfast iterative improvements to reach design goals."""

self.iteration_count += 1

improvement = current_state * 1.05

print(f"[Kaizen] Iteration {self.iteration_count}: Efficiency optimized to {improvement:.2f}")

return improvement

def generate_3d_manifest(self, final_specs: Dict):

"""Outputs high-definition parameters for 3D modeling and HUD visualization."""

return {

"resolution": "8K",

"render_engine": "RayTraced_Physics",

"hud_elements": ["Stress_Heatmap", "Vector_Flow", "Load_Bearing_Points"],

"specs": final_specs

}

# --- Execution Logic ---

if __name__ == "__main__":

# Define engineering constraints

initial_params = {"material": "Titanium-Aluminide", "max_temp": 1200}

ai_engineer = ActiveEngineeringAI(constraints=initial_params)

# Simulate a rapid optimization loop

current_eff = 0.70

while current_eff < 0.95:

telemetry = ai_engineer.ingest_sensor_data({"temp": 1150, "vibration": "low"})

current_eff = ai_engineer.kaizen_optimizer(current_eff)

time.sleep(0.1) # High-speed processing simulation

final_output = ai_engineer.generate_3d_manifest({"efficiency": current_eff})

print(f"\n[Final Output] Model Ready for 3D HD Rendering: {final_output}")

import abc

from typing import List, Dict

# --- Base Interface for Engineering Agents ---

class EngineeringAgent(abc.ABC):

@abc.abstractmethod

def analyze(self, design_state: Dict) -> Dict:

"""Perform domain-specific scientific reasoning."""

pass

# --- Specialized Agents ---

class StructuralAgent(EngineeringAgent):

def analyze(self, design_state: Dict):

# Calculation for Stress (Force/Area)

load = design_state.get("load_newtons", 1000)

area = design_state.get("cross_section_mm2", 50)

stress = load / area

return {"stress_mpa": stress, "status": "Stable" if stress < 200 else "Critical"}

class ThermalAgent(EngineeringAgent):

def analyze(self, design_state: Dict):

temp = design_state.get("ambient_temp", 300)

delta_t = design_state.get("heat_input", 50)

return {"final_temp_k": temp + delta_t, "thermal_expansion": 0.0012}

# --- The Active Controller (Kaizen Engine) ---

class ActiveEngineeringController:

def __init__(self):

self.agents: List[EngineeringAgent] = [StructuralAgent(), ThermalAgent()]

self.iteration_log = []

def execute_optimization_cycle(self, initial_specs: Dict, cycles: int = 5):

current_specs = initial_specs

for i in range(cycles):

print(f"\n--- Kaizen Cycle {i+1} ---")

cycle_results = {}

# Aggregate intelligence from all agents

for agent in self.agents:

report = agent.analyze(current_specs)

cycle_results.update(report)

# High-speed adjustment logic

if cycle_results.get("status") == "Critical":

current_specs["cross_section_mm2"] += 10 # Rapid reinforcement

print("[Action] Increasing material thickness for stability.")

self.iteration_log.append(cycle_results)

return current_specs, self.iteration_log

def generate_hud_manifest(self, final_state: Dict):

"""Prepares high-fidelity data for 3D HUD overlays."""

return {

"render_quality": "Ultra-HD",

"telemetry_overlay": True,

"layers": ["Wireframe", "Stress_Heatmap", "Isothermal_Lines"],

"data_points": final_state

}

# --- Execution ---

controller = ActiveEngineeringController()

specs = {"load_newtons": 5000, "cross_section_mm2": 20, "ambient_temp": 298}

optimized_design, history = controller.execute_optimization_cycle(specs)

hud_data = controller.generate_hud_manifest(optimized_design)

print("\n[AI Output] Final Optimized Design Specs:", optimized_design)

print("[HUD] Visualization Manifest Generated for 3D Rendering.")