fan

Modules

fan_torch_system module

class FanTorchSystem(nominalPowerRate=None, nominalAirFlowRate=None, c1=None, c2=None, c3=None, c4=None, f_total=None, **kwargs)

Bases: System, Module

A fan system model implemented with PyTorch for gradient-based optimization.

This model represents a fan that controls air flow rate and temperature, considering both the power consumption and the heat added to the air stream.

Parameters:

• nominalPowerRate (Optional[float]) – Nominal power rate [W]

• nominalAirFlowRate (Optional[float]) – Nominal air flow rate [m³/s]

• c1 (Optional[float]) – Constant term in power polynomial

• c2 (Optional[float]) – Linear term coefficient in power polynomial

• c3 (Optional[float]) – Quadratic term coefficient in power polynomial

• c4 (Optional[float]) – Cubic term coefficient in power polynomial

• f_total (Optional[float]) – Total fan efficiency factor (0-1)

Mathematical Formulation

The fan power is calculated using a polynomial equation:

\[P = P_{nom} \cdot \left(c_1 + c_2\frac{\dot{m}}{\dot{m}_{nom}} + c_3\left(\frac{\dot{m}}{\dot{m}_{nom}}\right)^2 + c_4\left(\frac{\dot{m}}{\dot{m}_{nom}}\right)^3\right)\]

where:

• \(P\) is the fan power [W]

• \(P_{nom}\) is the nominal power [W]

• \(\dot{m}\) is the air mass flow rate [kg/s]

• \(\dot{m}_{nom}\) is the nominal air mass flow rate [kg/s]

• \(c_1\) to \(c_4\) are polynomial coefficients that can be calibrated

The outlet air temperature is calculated considering the heat added by the fan:

\[T_{out} = T_{in} + \frac{P \cdot f_{total}}{\dot{m} \cdot c_p}\]

where:

• \(T_{out}\) is the outlet temperature [°C]

• \(T_{in}\) is the inlet temperature [°C]

• \(f_{total}\) is the fraction of power that is converted to heat and added to the air stream

• \(c_p\) is the specific heat capacity of air [J/(kg·K)]

Notes

Model Assumptions:

• Fan power follows polynomial relationship with flow rate

• All heat from fan power is added to air stream

• Constant air density and specific heat capacity

• No mechanical losses considered separately

Implementation Details:

• Uses PyTorch for gradient-based optimization

• Parameters are stored as trainable PyTorch parameters

• Includes safety checks for numerical stability

• All calculations performed in SI units

do_step(secondTime, dateTime, step_size, stepIndex)

Perform one step of the fan system simulation.

The fan power is calculated using a polynomial equation: P = P_nom * (c1 + c2*(m/m_nom) + c3*(m/m_nom)^2 + c4*(m/m_nom)^3) where: - P is the fan power - P_nom is the nominal power - m is the air flow rate - m_nom is the nominal air flow rate - c1-c4 are polynomial coefficients

The outlet air temperature is calculated considering the heat added by the fan: T_out = T_in + (P * f_total) / (m * c_p) where: - T_out is the outlet temperature - T_in is the inlet temperature - f_total is the total fan efficiency - c_p is the specific heat capacity of air

Return type:

None

initialize(start_time, end_time, step_size, simulator)

Initialize the fan system.

Return type:

None

property config

Get the configuration of the fan system.

property input: dict

Get the input ports of the fan system.

Returns:

Dictionary containing input ports:

• ”airFlowRate”: Air flow rate [m³/s]

• ”inletAirTemperature”: Inlet air temperature [°C]

Return type:

dict

property output: dict

Get the output ports of the fan system.

Returns:

Dictionary containing output ports:

• ”outletAirTemperature”: Outlet air temperature [°C]

• ”Power”: Fan power consumption [W]

Return type:

dict