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active_equator_underwater_cooling.yaml
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101 lines (82 loc) · 3.63 KB
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import time
import math
class UnderwaterCoolingSystem:
def __init__(self):
# Constants for equatorial waters
self.surface_temp = 31.0 # Celsius
self.target_temp = 25.0 # Ideal operating temp for hardware
self.pump_efficiency = 0.85
self.flow_rate = 0.0 # Liters per second
def get_ambient_temp(self, depth):
"""
Simulates the equatorial thermocline.
Temperature drops exponentially with depth.
"""
return 4.0 + (self.surface_temp - 4.0) * math.exp(-0.005 * depth)
def calculate_required_flow(self, heat_load, ambient_temp):
"""
Calculates flow rate using: Q = m * Cp * ΔT
heat_load: kW
"""
specific_heat_water = 4.18 # kJ/kg°C
delta_t = self.target_temp - ambient_temp
if delta_t <= 0:
return 100.0 # Max flow if ambient is too warm
# Mass flow rate (kg/s)
m_dot = heat_load / (specific_heat_water * delta_t)
return round(m_dot, 2)
def run_monitor(self, depth, current_load):
ambient = self.get_ambient_temp(depth)
flow = self.calculate_required_flow(current_load, ambient)
print(f"--- HUD STATUS: EQUATORIAL UNDERWATER UNIT ---")
print(f"Depth: {depth}m | Ambient Temp: {ambient:.2f}°C")
print(f"Server Load: {current_load}kW")
print(f"Active Flow Rate: {flow} L/s")
print(f"Status: {'STABLE' if ambient < 15 else 'OPTIMIZING DEPTH'}")
print("-" * 40)
# Initialize system at 400m depth (Deep Sea Cooling)
system = UnderwaterCoolingSystem()
system.run_monitor(depth=400, current_load=500) # 500kW Heat Load
import numpy as np
class EquatorialDeepSeaCooler:
"""
Advanced Underwater Cooling Controller
Source Integration: gilbertalgordo/dev/thermal_management
"""
def __init__(self, target_cpu_temp=45.0):
self.target_temp = target_cpu_temp
self.seawater_density = 1025 # kg/m^3 at Equator
self.cp_seawater = 3.99 # kJ/(kg·K) - Specific heat of salt water
self.k_factor = 0.12 # Pipe friction coefficient
def calculate_thermocline_gradient(self, depth):
"""
Calculates Equatorial thermal stratification.
T(z) = T_deep + (T_surf - T_deep) * exp(-z/h)
"""
t_surf = 32.0 # Equatorial surface avg
t_deep = 4.2 # Deep ocean floor avg
h_scale = 150.0 # Depth scale factor
return t_deep + (t_surf - t_deep) * np.exp(-depth / h_scale)
def active_pump_vfd_output(self, current_temp, heat_load_kw, depth):
"""
Determines the VFD Hertz (0-60Hz) for the intake pumps.
"""
ambient_water = self.calculate_thermocline_gradient(depth)
delta_t_required = self.target_temp - ambient_water
# Mass flow rate required (kg/s)
# Q = m * Cp * dT -> m = Q / (Cp * dT)
m_dot = heat_load_kw / (self.cp_seawater * delta_t_required)
# Convert mass flow to Pump VFD Frequency
vfd_freq = min(60, (m_dot * 15.5)) # Scaled to max pump capacity
return round(vfd_freq, 2), round(ambient_water, 2)
# --- HUD DATA STREAM SIMULATION ---
system = EquatorialDeepSeaCooler()
load = 1200.0 # 1.2MW Data Center Load
depth_deployment = 450.0 # Meters below surface
freq, amb = system.active_pump_vfd_output(current_temp=55, heat_load_kw=load, depth=depth_deployment)
print(f"|--- EQUATORIAL COOLING HUD ---|")
print(f"| INTAKE DEPTH: {depth_deployment}m")
print(f"| AMBIENT TEMP: {amb}°C")
print(f"| PUMP VFD FREQ: {freq} Hz")
print(f"| STATUS: HIGH-EFFICIENCY ACTIVE")
print(f"|------------------------------|")