| ▼ TAR 1 Rotation Gears | ||||
| ☰ | \( \theta_{\text{arc, tilt}} \) | TAR 1 Arc Angle tilt (degrees) | 64.000000 |
View Help GuidePurpose: Determine the degrees over a track arc rotation - Angle tilt (degrees) * 2
Logic: Because the track acts like a seesaw, swiveling from a downward slant to an upward slant, the total physical distance it rocks is exactly double the baseline operating angle.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\theta_{\text{arc, tilt}} = \theta_{\text{tilt}} \times 2$$ Python Logic:
v["Angle tilt (degrees)"]*2Live Evaluation: [ROUTE: STATIC/GLOBAL] 32.0000*2 = 64.0000
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| ☰ | \( \Delta\phi \) | TAR 1 Angular Displacement per Segment (rad) | 0.017185 |
View Help GuidePurpose: Angular displacement per segment for torque and energy calculations - RADIANS ( ( 2 * Angle tilt (degrees) ) / ( ( 2 * Angle tilt (degrees) ) + 1 ) )
Logic: The torque required changes constantly as the track tips. This slices the movement into radians so the simulator tracks the exact, dynamic physics curve instead of relying on a sloppy average.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\Delta\phi = \text{rad}((2 \times \theta_{\text{tilt}})/((2 \times \theta_{\text{tilt}})+1))$$ Python Logic:
RADIANS((2*v["Angle tilt (degrees)"])/((2*v["Angle tilt (degrees)"])+1))Live Evaluation: [ROUTE: STATIC/GLOBAL] RADIANS((2*32.0000)/((2*32.0000)+1)) = 0.0172
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| ☰ | \( Z_{\text{track}} \) | TAR 1 Track rotation Gear teeth |
View Help GuidePurpose: Adjustable user input to determine size of track rotation gear attached to the track - Adjustable user input
Logic: This is the final anchor point of the drivetrain. Its size determines the ultimate mechanical leverage the flywheel has to heave the massive track back and forth.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( Z_{\text{manip}} \) | TAR 1 Teeth per track manipulation | 35.555556 |
View Help GuidePurpose: Based on track arc rotation RPM to determine teeth rotated to determine gear ratio to DLLS
Logic: We aren't spinning this massive gear in full circles; we are just rocking it. This counts exactly how much of the gear face meshes with the drive pinion during one tilt cycle.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$Z_{\text{manip}} = (Z_{\text{track}}/360) \times \theta_{\text{arc, tilt}}$$ Python Logic:
(v["TAR 1 Track rotation Gear teeth"]/360)*v["TAR 1 Arc Angle tilt (degrees)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] (200.0000/360)*64.0000 = 35.5556
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| ☰ | \( C_{\text{track}} \) | TAR 1 Track rotation Gear circumference (m) | 20.000000 |
View Help GuidePurpose: Circumeference of the track rotation gear for design dimensions - Track rotation Gear teeth * GMEG Chain link (m)
Logic: Physical dimensioning. Used to ensure the gear and its driving chain/mesh perfectly fit within the facility housing constraints.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$C_{\text{track}} = Z_{\text{track}} \times L_{\text{link}}$$ Python Logic:
v["TAR 1 Track rotation Gear teeth"]*v["Chain link (m)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 200.0000*0.1000 = 20.0000
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| ☰ | \( D_{\text{track}} \) | TAR 1 Track rotation Gear diameter (m) | 6.366198 |
View Help GuidePurpose: Track rotation gear diameter for indication to height - Track rotation Gear circumference (m) / PI ( )
Logic: Critical for physical design clearancewe need to know exactly how tall this gear is to guarantee it doesn't bottom out and hit the factory floor.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$D_{\text{track}} = C_{\text{track}}/\pi$$ Python Logic:
v["TAR 1 Track rotation Gear circumference (m)"]/PI()Live Evaluation: [ROUTE: STATIC/GLOBAL] 20.0000/PI() = 6.3662
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| ☰ | \( R_{\text{track}} \) | TAR 1 Track rotation Gear radius (m) | 3.183099 |
View Help GuidePurpose: Track rotation gear radius for dimensional calculations - Track rotation Gear diameter (m) / 2
Logic: The distance from the track's center pivot to the gear teeth. A larger radius gives the drivetrain massive mechanical advantage to muscle the track around with less raw force.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$R_{\text{track}} = D_{\text{track}}/2$$ Python Logic:
v["TAR 1 Track rotation Gear diameter (m)"]/2Live Evaluation: [ROUTE: STATIC/GLOBAL] 6.3662/2 = 3.1831
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| ☰ | \( n_{\text{repos}} \) | TAR 1 Rotations per repositioning | 0.177778 |
View Help GuidePurpose: Track rotation gear rotation based on track arc rotation degree - Angle tilt (degrees) / 360
Logic: A mathematical stepping-stone to convert our degrees of tilt into standard rotational speed metrics.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{repos}} = \theta_{\text{arc, tilt}}/360$$ Python Logic:
v["TAR 1 Arc Angle tilt (degrees)"]/360Live Evaluation: [ROUTE: STATIC/GLOBAL] 64.0000/360 = 0.1778
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| ☰ | \( n_{\text{track}} \) | TAR 1 Track rotation gear (RPM) | 10.666667 |
View Help GuidePurpose: Track rotation gear operational speed during track arc rotations - Rotations per repositioning * 60
Logic: Even though it just rocks back and forth, standardizing the speed to RPM allows us to mathematically sync it with the high-speed flywheel through the gearbox.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{track}} = n_{\text{repos}} \times 60$$ Python Logic:
v["TAR 1 Rotations per repositioning"]*60Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.1778*60 = 10.6667
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| ☰ | \( I_{\text{enablers}} \) | TAR 1 Enablers moment of inertia (kg.m2) | 517,105.680277 |
View Help GuidePurpose: Defines the maximum rotational inertia contributed by the enabler train as it travels around the track center. - MAX ( IF ( Rotational Torque Cycle , Rotational Torque Enabler train moment of inertia (kg m2) ) )
Logic: Scans the Rotational Torque sheet to find the exact split-second the heavy enablers put up the maximum rotational resistance against the lifting motion.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$I_{\text{enablers}} = \text{Max Segment Enabler train Moment of inertia Rev 1 Cycle 1 (kg.m2)}$$ Python Logic:
v["Max Segment Enabler train Moment of inertia Rev 1 Cycle 1 (kg.m2)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 517,105.6803
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| ☰ | \( I_{\text{system}} \) | TAR 1 System moment of inertia (kg.m2) | 0.000000 |
View Help GuidePurpose: Defines the total inertia of the entire rotating track assembly (track structure plus enabler train mass) for subsequent inertia-matching calculations. - Track Moment of Inertia (I) + Enablers moment of inertia TAR 1 (kg.m2)
Logic: Combines the dead-weight stubbornness of the bare track with the active weight of the payload. This is the true inertial load the drivetrain must overcome.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \tau_{\text{grav, max}} \) | TAR 1 Enablers torque (Nm) | 1,162,009.344009 |
View Help GuidePurpose: Defines the maximum negative gravitational torque (load) created by the enabler train mass that the DLLS must lift. - MAX ( IF ( Rotational Torque Cycle , Rotational Torque Enabler train Absolute Gear System Torque (Nm) ) )
Logic: Scans the data to find the exact moment where the payload's weight leverages the hardest against the lift, establishing our worst-case gravity load.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\tau_{\text{grav, max}} = \tau1.1_{\text{max, seg}}$$ Python Logic:
v["MAX Segment Enabler train Absolute Gear System Torque Rev 1 Cycle 1 (Nm)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 1,162,009.3440
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| ☰ | \( \tau_{\text{total, DLLS}} \) | TAR 1 Total Peak Required DLLS Torque (Nm) | 0.000000 |
View Help GuidePurpose: Calculates the single worst-case instantaneous torque the DLLS must generate to overcome both gravitational and inertial loads. - Net Peak Flywheel Torque (Nm) + Enablers torque TAR 1 (Nm)
Logic: Combines the force needed to fight the machine's inertia with the force needed to lift the payload against gravity. Because of the drivetrain layout, the flywheel takes this massive torque punch, keeping the sensitive electric motors completely shielded.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ▼ TAR 1 Input Torque Requirement | ||||
| ☰ | \( Z_{\text{input}} \) | TAR 1 Top track rotation Gear teeth |
View Help GuidePurpose: Teeth on top track rotation gear based on gear ration between this gear and the track rotation gear
Logic: Sets the baseline size for the driving end of the final gearbox, directly dictating the mechanical leverage we have over the swiveling track.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( GR_{\text{track}} \) | TAR 1 Track rotation gear reduction ratio | 2.000000 |
View Help GuidePurpose: Gear ration between track rotation gear and final output gear of the DLLS system
Logic: Acts as our primary torque multiplier. A example a 2:1 ratio here means the drive shaft only has to push half as hard to heave the massive track, saving the system from extreme mechanical stress.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$GR_{\text{track}} = Z_{\text{track}}/Z_{\text{input}}$$ Python Logic:
v["TAR 1 Track rotation Gear teeth"]/v["TAR 1 Top track rotation Gear teeth"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 200.0000/100.0000 = 2.0000
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| ☰ | \( C_{\text{input}} \) | TAR 1 Top track rotation gear circumference (m) | 10.000000 |
View Help GuidePurpose: Based on chain link size, determine outer circumeference for cable length dimensions and overall system size
Logic: Physical dimensioning. Used to guarantee spatial clearances and ensure the connecting chain/mesh perfectly wraps the gear face.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$C_{\text{input}} = Z_{\text{input}} \times L_{\text{link}}$$ Python Logic:
v["TAR 1 Top track rotation Gear teeth"]*v["Chain link (m)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 100.0000*0.1000 = 10.0000
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| ☰ | \( D_{\text{input}} \) | TAR 1 Top track rotation gear diameter (m) | 3.183099 |
View Help GuidePurpose: Dimensional data for design purposes and overall system height - Top track rotation gear circumference (m) / PI ( )
Logic: Ensures the final stage of the drivetrain physically fits inside the gantry housing without rubbing or interference.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$D_{\text{input}} = C_{\text{input}}/\pi$$ Python Logic:
v["TAR 1 Top track rotation gear circumference (m)"]/PI()Live Evaluation: [ROUTE: STATIC/GLOBAL] 10.0000/PI() = 3.1831
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| ☰ | \( R_{\text{input}} \) | TAR 1 Top track rotation gear radius (m) | 1.591549 |
View Help GuidePurpose: Dimensional data for design purposes - Top track rotation gear diameter (m) / 2
Logic: Mathematically crucial for calculating exactly how the twisting force transfers from the DLLS gearbox, across the teeth, and into the track.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$R_{\text{input}} = D_{\text{input}}/2$$ Python Logic:
v["TAR 1 Top track rotation gear diameter (m)"]/2Live Evaluation: [ROUTE: STATIC/GLOBAL] 3.1831/2 = 1.5915
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| ☰ | \( n_{\text{lift, rot}} \) | TAR 1 Rotations per lift | 0.355556 |
View Help GuidePurpose: Top track rotation gear rotation based on gear ratio with track rotation gear - Teeth per track manipulation / Top track rotation Gear teeth
Logic: Because the drive gear is smaller than the track gear, it has to turn faster and more often. This translates the slow, rocking motion of the track into a quantifiable number of full rotations for the drivetrain.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{lift, rot}} = n_{\text{repos}} \times GR_{\text{track}}$$ Python Logic:
v["TAR 1 Rotations per repositioning"]*v["TAR 1 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.1778*2.0000 = 0.3556
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| ☰ | \( n_{\text{input}} \) | TAR 1 Top track rotation gear (RPM) | 21.333333 |
View Help GuidePurpose: Determining output speed of the DLLS final output gear - Rotations per lift * 60
Logic: Connects the slow, heavy swiveling motion of the track back to the higher-speed mechanics of the DLLS drivetrain.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{input}} = n_{\text{lift, rot}} \times 60$$ Python Logic:
v["TAR 1 Rotations per lift"]*60Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.3556*60 = 21.3333
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| ☰ | \( \tau_{\text{DLLS, input}} \) | TAR 1 DLLS Input Torque (Nm) | 0.000000 |
View Help GuidePurpose: DLLS input torque taking the gear ratio into account - Enablers torque TAR 1 (Nm) / Track rotation gear reduction ratio
Logic: This takes the massive "Final Boss" torque required to lift the track and shrinks it down using our gear ratio. This is the real-world force the flywheel must push through the gearbox.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\tau_{\text{DLLS, input}} = \tau_{\text{total, DLLS}}/GR_{\text{track}}$$ Python Logic:
v["TAR 1 Total Peak Required DLLS Torque (Nm)"]/v["TAR 1 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000/2.0000 = 0.0000
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| ☰ | \( I_{\text{reflected}} \) | TAR 1 Reflected Load Inertia (kg.m2) | 0.000000 |
View Help GuidePurpose: Quantifies the total inertia of the track and enabler assembly as 'seen' by the input shaft. This is used to size the final drive components for acceleration and dynamic stability.
Logic: Pure dynamics. Because the drive shaft spins faster through a gear reduction, the massive inertia of the track "reflects" back exponentially smaller (divided by the ratio squared).
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$I_{\text{reflected}} = \tau_{\text{total, DLLS}}/GR_{\text{track}}$$ Python Logic:
v["TAR 1 Total Peak Required DLLS Torque (Nm)"]/v["TAR 1 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000/2.0000 = 0.0000
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| ▼ TAR 1 Flywheel | ||||
| ☰ | \( W_{\text{inertial}} \) | TAR 1 Work to Rotate the Track (J) | 0.000000 |
View Help GuidePurpose: Defines the net inertial work the flywheel must supply to rotate the track structure. - Net Flywheel Energy (J)
Logic: Isolates the effort required to overcome the track's own bulk and inertia, completely separate from the heavy enablers riding inside it.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( E_{\text{grav}} \) | TAR 1 Energy Required Gravity Enablers (J) | 1,127,058.619832 |
View Help GuidePurpose: Defines the total negative gravitational work (energy) required to lift the enabler train mass during the TAR. - DLLS TAR Energy needs
Logic: Pulls data from the Rotational Torque sheet to calculate exactly how much extra work is required to heave the 24-tonne enabler mass upward during the tilt.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$E_{\text{grav}} = \text{Sum Segment Work Done by DLLS Joule Rev 2 Cycle 1 (J)}$$ Python Logic:
v["Sum Segment Work Done by DLLS Joule Rev 2 Cycle 1 (J)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 1,127,058.6198
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| ☰ | \( E_{\text{TAR, mech}} \) | TAR 1 Energy Required (J) | 1,127,058.619832 |
View Help GuidePurpose: Calculates the total minimum mechanical energy the flywheel must deliver for one complete TAR. - Net Flywheel Energy (J) + DLLS TAR Energy needs
Logic: Combines the energy needed to swing the bare track with the energy needed to lift the enablers. This defines the raw physical work the system must perform.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$E_{\text{TAR, mech}} = W_{\text{inertial}}+E_{\text{grav}}$$ Python Logic:
v["TAR 1 Work to Rotate the Track (J)"]+v["TAR 1 Energy Required Gravity Enablers (J)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000+1,127,058.6198 = 1,127,058.6198
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| ☰ | \( \eta_{\text{flywheel}} \) | TAR 1 Flywheel Inefficiency (%) |
View Help GuidePurpose: Defines the energy loss factor during the flywheel's discharge cycle (e.g., friction, windage). - Adjustable user input
Logic: No mechanical battery is perfect. This accounts for the energy that bleeds off as heat and wind drag while the heavy wheel spins.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( E_{\text{total, store}} \) | TAR 1 Total Energy Required (J) | 1,070,705.688840 |
View Help GuidePurpose: Determines the total energy the flywheel must store to account for all mechanical and efficiency losses.
Logic: Adds the inefficiency penalty to the minimum energy requirement. This ensures the flywheel stores enough extra power to overcome its own friction and still successfully complete the lift.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$E_{\text{total, store}} = E_{\text{TAR, mech}} \times \eta_{\text{flywheel}}$$ Python Logic:
v["TAR 1 Energy Required (J)"]*v["TAR 1 Flywheel Inefficiency (%)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 1,127,058.6198*0.9500 = 1,070,705.6888
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| ☰ | \( GR_{\text{flywheel/track}} \) | TAR 1 Gear ratio | 0.000000 |
View Help GuidePurpose: Gear ration between input motor speed and top track rotation output speed - Motor speed (RPM) / Gear ratio
Logic: The flywheel spins incredibly fast to store energy, while the track swivels very slowly. This ratio dictates how the gearbox translates high-speed kinetic energy into low-speed, high-torque lifting power.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( n_{\text{flywheel}} \) | TAR 1 Flywheel Charging Speed (RPM) |
View Help GuidePurpose: (will change this as we need the flywheel faster, bear with me) - Adjustable user input
Logic: Flywheels store energy exponentially based on speed. This sets the baseline spin rate the wheel must reach before initiating the heavy track lift.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( \omega_{\text{start}} \) | TAR 1 Flywheel Radians | 0.000000 |
View Help GuidePurpose: Starting flywheel radians at start of track arc rotation - Flywheel Charging Speed (RPM) * 2* PI ( ) / 60
Logic: Converts standard RPM into radians per second so the system can run strict rotational kinetic energy calculations.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \Delta n_{\%} \) | TAR 1 Allowable Flywheel RPM Drop % |
View Help GuidePurpose: Allowable flywheel slowdown - Adjustable user input
Logic: If the flywheel drains too much speed, the system stalls. This sets a hard floor on how much RPM can be safely bled off to perform the heavy lifting without losing control.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( n_{\text{end}} \) | TAR 1 Final Flywheel RPM | 2,250.000000 |
View Help GuidePurpose: Finishing flywheel radians at end of track arc rotation - Flywheel RPM * ( 1 - Allowable Flywheel RPM Drop % )
Logic: Calculates the bottom "floor" speed based on the allowed drop percentage. The flywheel must never drop below this RPM during operation.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{end}} = n_{\text{flywheel}} \times (1-\Delta n_{\%})$$ Python Logic:
v["TAR 1 Flywheel Charging Speed (RPM)"]*(1-v["TAR 1 Allowable Flywheel RPM Drop %"])Live Evaluation: [ROUTE: STATIC/GLOBAL] 2,500.0000*(1-0.1000) = 2,250.0000
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| ☰ | \( \omega_{\text{end}} \) | TAR 1 Final Flywheel Radians | 0.000000 |
View Help GuidePurpose: Defines the angular velocity the flywheel must retain after the energy discharge. - Flywheel Radians * ( 1 - Allowable Flywheel RPM Drop % )
Logic: Required to calculate the energy deltathe exact difference in kinetic energy between the top starting speed and the bottom finishing speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{flywheel}} \) | TAR 1 Flywheel Intertia (kg m^2) | 0.000000 |
View Help GuidePurpose: Determination of flywheel inertai required to enable track arc rotation - ( 2 * Total Energy Required Rotation 1 (J) ) / ( ( Flywheel Radians )^2 - ( Final Flywheel Radian )^2 )
Logic: The master sizing calculation. It determines exactly how massive the wheel needs to be to store the required energy and release it without dropping below the target final speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \rho \) | TAR 1 Material Density kg/m3 |
View Help GuidePurpose: Adjustable density for sizing the flywheel - Adjustable user input
Logic: Translates the required inertia into actual, real-world physical dimensions (how thick and wide the metal or carbon must be).
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( D_{\text{outer}} \) | TAR 1 Outer diameter (m) |
View Help GuidePurpose: Adjustable outer size for the flywheel - Adjustable user input
Logic: Constrains the wheel's size based on the physical space available inside the DLLS housing.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( R_{\text{outer}} \) | TAR 1 Outer radius (m) | 0.000000 |
View Help GuidePurpose: Determines outer radius of the flywheel - Outer diameter (m) / 2
Logic: A fundamental geometric variable needed to map the volume and mass distribution of the spinning cylinder.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( D_{\text{inner}} \) | TAR 1 Inner diameter (m) |
View Help GuidePurpose: Adjustable inner size for the flywheel - Adjustable user input
Logic: Efficient flywheels are thick rings, not solid plates. This defines the central void so the mass is concentrated at the outer edge where it stores energy best.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( R_{\text{inner}} \) | TAR 1 Inner radius (m) | 0.000000 |
View Help GuidePurpose: Determines the inner radius of the flywheel - Inner diameter (m) / 1
Logic: Used alongside the outer radius to calculate the exact physical volume of the "doughnut" shape.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( M_{\text{flywheel}} \) | TAR 1 Flywheel weight (kg) | 0.000000 |
View Help GuidePurpose: Determining flywheel weight - ( 2 * Flywheel Intertia (kg m^2) ) / ( ( Outer radius (m) ) ^ 2 + ( Inner radius (m) ) ^ 2 )
Logic: Reverses the inertia formula to determine exactly how heavy the steel or carbon ring must be to act as a properly sized kinetic battery.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( L_{\text{width}} \) | TAR 1 Flywheel width (m) | 0.000000 |
View Help GuidePurpose: Determining flywheel width - Flywheel weight (kg) / ( Material Density kg/m3 * PI ( ) * ( ( Outer radius (m) ) ^ 2 - ( Inner radius (m) ) ^ 2 ) )
Logic: The final architectural output. It tells the machinist exactly how thick to make the ring so it hits the precise mass and inertia targets required by the system.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \tau_{\text{load, shaft}} \) | TAR 1 Load torque (Nm) | 0.000000 |
View Help GuidePurpose: Quantifies the peak torque load placed on the flywheel's output shaft during the TAR. - Top track rotation gear peak torque / Gear ratio
Logic: Takes the massive torque required to lift the track and shrinks it down through the gearbox. This is the actual twisting resistance the spinning flywheel feels as it dumps its energy.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{reflected, load}} \) | TAR 1 Reflected Load Inertia (IRL) (kg.m2) | 0.000000 |
View Help GuidePurpose: Quantifies the total inertia of the track assembly as reflected to the flywheel's output shaft. - Top track rotation gear inertia / Gear ratio ^ 2
Logic: Because the flywheel spins much faster than the track rotates, the track's massive inertia is mathematically shrunk through the gearbox (by the square of the gear ratio). This shows exactly what the flywheel is fighting against.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ▼ TAR 1 Motor sizing | ||||
| ☰ | \( t_{\text{charge}} \) | TAR 1 Charging Time (s) | 2.980769 |
View Help GuidePurpose: Time period available to charhe rotation 1 flyhweel between similar track arc rotations - Run time across GMEG track (s) - Lift Time (s)
Logic: The motors can only recharge the flywheel while the track is not actively lifting. This subtracts the lifting time from the total lap time to give us our exact recharging window.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$t_{\text{charge}} = t_{\text{run}}$$ Python Logic:
v["Run time across GMEG track (s)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 2.9808 = 2.9808
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| ☰ | \( P_{\text{avg}} \) | TAR 1 Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Average power per second needed for flyhweel charging over charging time - ( Total Energy Required Rotation 1 (J) / Charging Time (s) ) / 1000
Logic: Takes the total energy the flywheel just spent and spreads the replacement effort over the available charging time, giving us a baseline kilowatt target for the motors.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( \eta_{\text{gear, loss}} \) | TAR 1 Gear Inefficiencies (%) |
View Help GuidePurpose: System inefficiencies - Adjustable user input
Logic: Gears get hot and make noisethat is lost energy. This slider adds a realistic penalty to account for the power bleeding out of the transmission.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
|
|
| ☰ | \( P_{\text{proj, mech}} \) | TAR 1 Projected Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Average power needed taking inefficiencies into account - Average Power to Charge (kW) + ( Average Power to Charge (kW) * Gear Inefficiencies (%) )
Logic: Because the gears steal some power, the motor has to push a little harder to ensure the correct net energy actually reaches the flywheel.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( \eta_{\text{motor}} \) | TAR 1 Motor efficiency (%) |
View Help GuidePurpose: Defines the motor's baseline efficiency used to calculate power loss during the charging phase. - Adjustable user input
Logic: No electric motor converts 100% of its electricity into pure turning force. This accounts for internal copper and iron heat losses.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
|
|
| ☰ | \( P_{\text{gross, in}} \) | TAR 1 Motor Projected Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Calculates the gross electrical input power required by the motor to account for its inherent efficiency losses. - Projected Average Power to Charge (kW) + ( Projected Average Power to Charge (kW) * ( 1 - Motor efficiency (%) ) )
Logic: This is the bloated total. It factors in all the mechanical and electrical penalties so we know exactly how much raw electricity the system will demand to recharge the flywheel.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( \eta_{\text{torque, benefit}} \) | TAR 1 Startup Torque Prevention Benefit (%) |
View Help GuidePurpose: Defines the motor's baseline efficiency used to calculate power loss during the charging phase. - Adjustable user input
Logic: Starting a heavy motor from a dead stop pulls a massive spike of electricity. Because our motors are already spinning and just "topping up" the flywheel, we bypass that spike, saving a significant chunk of power.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
|
|
| ☰ | \( P_{\text{net, in}} \) | TAR 1 New Average Charging Power (kW) | 0.000000 |
View Help GuidePurpose: Defines the final, optimized net electrical power the DLLS motors will draw from the GMEG to charge the flywheel. - Projected Average Power to Charge (kW) - ( Projected Average Power to Charge (kW) * Efficiency improvement (%) )
Logic: Applies the momentum discount. This is the highly optimized, real-world kilowatt draw the system needs to keep the flywheels topped up.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( n_{\text{motor}} \) | TAR 1 Motor speed (RPM) |
View Help GuidePurpose: User inout to control input motor speed - Adjustable user input
Logic: High-efficiency industrial motors like to run at specific, high speeds. This lets us lock in a standard RPM so we can design the gearing around a motor we can actually buy.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
|
|
| ☰ | \( \omega_{\text{motor}} \) | TAR 1 Motor Angular Velocity (rad/s) | 0.000000 |
View Help GuidePurpose: Motor radians for motor torque calculations - Motor speed (RPM) * 2 * PI ( ) / 60
Logic: Converts the standard RPM into radians per second so the simulator can run dynamic torque and inertia checks.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( GR_{\text{motor}} \) | TAR 1 Motor Gear ratio | 0.000000 |
View Help GuidePurpose: Defines the gear ratio between the high-speed motors and the lower-speed flywheel shaft. - Motor speed (RPM) / Flywheel Charging Speed (RPM)
Logic: Calculates the exact gearbox ratio required to match the motor's preferred spinning speed to the flywheel's target charging speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( I_{\text{IRL}, f} \) | TAR 1 Flywheel Inertia Reflected to Motor (IRL f) | 0.000000 |
View Help GuidePurpose: Quantifies the rotational inertia of the flywheel as "seen" by the higher-speed motor shaft. - Flywheel Intertia (kg m^2) / Motor Gear ratio ^ 2
Logic: Because the motor spins at a different speed than the flywheel, the gearbox chemically shrinks the flywheel's stubbornness (divided by the ratio squared), making it much easier for the motor to spin it up.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( I_{\text{IRL}, \text{total}} \) | TAR 1 Total Reflected Load Inertia (IRL total) | 0.000000 |
View Help GuidePurpose: Defines the total effective inertia the motor bank must control and accelerate for stable operation. - Reflected Load Inertia (IRL) + Flywheel Inertia Reflected (IRL_f)
Logic: Combines the reflected stubbornness of the massive track with the reflected stubbornness of the flywheel. This is the master inertia load the motors feel on their shafts.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( \tau_{\text{motor, total}} \) | TAR 1 Torque Required from the Motor (Nm) | 0.000000 |
View Help GuidePurpose: The figure 9549 is the unit conversion constant used to directly calculate power, torque, and rotational speed when using the common engineering units of kilowatts (kW), Newton-meters (Nm), and revolutions per minute (RPM). - ( TAR 1 New Average Charging Power (kW) * 9549 ) / Motor speed (RPM)
Logic: A standard industrial engineering conversion (using the 9549 constant) that perfectly translates our required kilowatts and RPMs into raw physical torque.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( N_{\text{motors}} \) | TAR 1 Motors Bank |
View Help GuidePurpose: Defines the number of modular motors sharing the total reflected load and power requirement. - Adjustable user input
Logic: Building one giant, custom 1,000 kW motor is incredibly expensive. Splitting the load across a bank of 4 or 8 smaller, off-the-shelf motors adds redundancy and slashes build costs.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
|
|
| ☰ | \( \tau_{\text{motor, unit}} \) | TAR 1 Motor Torque (Nm) | 0.000000 |
View Help GuidePurpose: Defines the minimum continuous torque rating required for each individual modular motor. - Torque Required (Nm) / Motors Bank
Logic: Divides the total twisting load evenly across the motor bank. This is exactly what we check against the manufacturer's catalog when buying the motors.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( I_{\text{motor, unit}} \) | TAR 1 Motor Inertia (kg.m2) | 0.000000 |
View Help GuidePurpose: Defines the ideal moment of inertia for each motor to maintain dynamic stability and control. - Total Reflected Load Inertia (IRL_total) / Motors Bank
Logic: Ensures the physical load is spread out enough that no single motor gets overwhelmed and stalls under the rotational inertia.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( P_{\text{motor, unit}} \) | TAR 1 Motor Power (kW) | 0.000000 |
View Help GuidePurpose: Defines the minimum continuous electrical power rating required for each modular motor. - New Average Charging Power (kW) / Motors Bank
Logic: Divides the total electrical kilowatt load evenly across the bank. The ultimate shopping list metric for the electrical procurement team.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ▼ TAR 2 Rotation Gears | ||||
| ☰ | \( \theta_{\text{arc, tilt}} \) | TAR 2 Arc Angle tilt (degrees) | 64.000000 |
View Help GuidePurpose: Determine the degrees over a track arc rotation - Angle tilt (degrees) * 2
Logic: Because the track acts like a seesaw, swiveling from a downward slant to an upward slant, the total physical distance it rocks is exactly double the baseline operating angle.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\theta_{\text{arc, tilt}} = \theta_{\text{tilt}} \times 2$$ Python Logic:
v["Angle tilt (degrees)"]*2Live Evaluation: [ROUTE: STATIC/GLOBAL] 32.0000*2 = 64.0000
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| ☰ | \( \Delta\phi \) | TAR 2 Angular Displacement per Segment (rad) | 0.017185 |
View Help GuidePurpose: Angular displacement per segment for torque and energy calculations - RADIANS ( ( 2 * Angle tilt (degrees) ) / ( ( 2 * Angle tilt (degrees) ) + 1 ) )
Logic: The torque required changes constantly as the track tips. This slices the movement into radians so the simulator tracks the exact, dynamic physics curve instead of relying on a sloppy average.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\Delta\phi = \text{rad}((2 \times \theta_{\text{tilt}})/((2 \times \theta_{\text{tilt}})+1))$$ Python Logic:
RADIANS((2*v["Angle tilt (degrees)"])/((2*v["Angle tilt (degrees)"])+1))Live Evaluation: [ROUTE: STATIC/GLOBAL] RADIANS((2*32.0000)/((2*32.0000)+1)) = 0.0172
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| ☰ | \( Z_{\text{track}} \) | TAR 2 Track rotation Gear teeth | 200.000000 |
View Help GuidePurpose: Adjustable user input to determine size of track rotation gear attached to the track - Adjustable user input
Logic: This is the final anchor point of the drivetrain. Its size determines the ultimate mechanical leverage the flywheel has to heave the massive track back and forth.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$Z_{\text{track}} = Z_{\text{track}}$$ Python Logic:
v["TAR 1 Track rotation Gear teeth"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 200.0000 = 200.0000
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| ☰ | \( Z_{\text{manip}} \) | TAR 2 Teeth per track manipulation | 35.555556 |
View Help GuidePurpose: Based on track arc rotation RPM to determine teeth rotated to determine gear ratio to DLLS - ( Track rotation Gear teeth / 360 ) * Angle tilt (degrees)
Logic: We aren't spinning this massive gear in full circles; we are just rocking it. This counts exactly how much of the gear face meshes with the drive pinion during one tilt cycle.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$Z_{\text{manip}} = (Z_{\text{track}}/360) \times \theta_{\text{arc, tilt}}$$ Python Logic:
(v["TAR 2 Track rotation Gear teeth"]/360)*v["TAR 2 Arc Angle tilt (degrees)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] (200.0000/360)*64.0000 = 35.5556
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| ☰ | \( C_{\text{track}} \) | TAR 2 Track rotation Gear circumference (m) | 20.000000 |
View Help GuidePurpose: Circumeference of the track rotation gear for design dimensions - Track rotation Gear teeth * GMEG Chain link (m)
Logic: Physical dimensioning. Used to ensure the gear and its driving chain/mesh perfectly fit within the facility housing constraints.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$C_{\text{track}} = Z_{\text{track}} \times L_{\text{link}}$$ Python Logic:
v["TAR 2 Track rotation Gear teeth"]*v["Chain link (m)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 200.0000*0.1000 = 20.0000
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| ☰ | \( D_{\text{track}} \) | TAR 2 Track rotation Gear diameter (m) | 6.366198 |
View Help GuidePurpose: Track rotation gear diameter for indication to height - Track rotation Gear circumference (m) / PI ( )
Logic: Critical for physical design clearancewe need to know exactly how tall this gear is to guarantee it doesn't bottom out and hit the factory floor.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$D_{\text{track}} = C_{\text{track}}/\pi$$ Python Logic:
v["TAR 2 Track rotation Gear circumference (m)"]/PI()Live Evaluation: [ROUTE: STATIC/GLOBAL] 20.0000/PI() = 6.3662
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| ☰ | \( R_{\text{track}} \) | TAR 2 Track rotation Gear radius (m) | 3.183099 |
View Help GuidePurpose: Track rotation gear radius for dimensional calculations - Track rotation Gear diameter (m) / 2
Logic: The distance from the track's center pivot to the gear teeth. A larger radius gives the drivetrain massive mechanical advantage to muscle the track around with less raw force.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$R_{\text{track}} = D_{\text{track}}/2$$ Python Logic:
v["TAR 2 Track rotation Gear diameter (m)"]/2Live Evaluation: [ROUTE: STATIC/GLOBAL] 6.3662/2 = 3.1831
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| ☰ | \( n_{\text{repos}} \) | TAR 2 Rotations per repositioning | 0.177778 |
View Help GuidePurpose: Track rotation gear rotation based on track arc rotation degree - Angle tilt (degrees) / 360
Logic: A mathematical stepping-stone to convert our degrees of tilt into standard rotational speed metrics.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{repos}} = \theta_{\text{arc, tilt}}/360$$ Python Logic:
v["TAR 2 Arc Angle tilt (degrees)"]/360Live Evaluation: [ROUTE: STATIC/GLOBAL] 64.0000/360 = 0.1778
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| ☰ | \( n_{\text{track}} \) | TAR 2 Track rotation gear (RPM) | 10.666667 |
View Help GuidePurpose: Track rotation gear operational speed during track arc rotations - Rotations per repositioning * 60
Logic: Even though it just rocks back and forth, standardizing the speed to RPM allows us to mathematically sync it with the high-speed flywheel through the gearbox.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{track}} = n_{\text{repos}} \times 60$$ Python Logic:
v["TAR 2 Rotations per repositioning"]*60Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.1778*60 = 10.6667
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| ☰ | \( I_{\text{enablers}, 2} \) | TAR 2 Enablers moment of inertia (kg.m2) | 517,105.680277 |
View Help GuidePurpose: Defines the maximum rotational inertia contributed by the enabler train as it travels around the track center. - MAX ( IF ( Rotational Torque Cycle , Rotational Torque Enabler train moment of inertia (kg m2) ) )
Logic: Scans the Rotational Torque sheet to find the exact split-second the heavy enablers put up the maximum rotational resistance against the lifting motion.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$I_{\text{enablers}, 2} = \text{Max Segment Enabler train Moment of inertia Rev 1 Cycle 2 (kg.m2)}$$ Python Logic:
v["Max Segment Enabler train Moment of inertia Rev 1 Cycle 2 (kg.m2)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 517,105.6803
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| ☰ | \( I_{\text{system, 2}} \) | TAR 2 System moment of inertia (kg.m2) | 0.000000 |
View Help GuidePurpose: Defines the total inertia of the entire rotating track assembly (track structure plus enabler train mass) for subsequent inertia-matching calculations. - Track Moment of Inertia (I) + Enablers moment of inertia TAR 1 (kg.m2)
Logic: Combines the dead-weight stubbornness of the bare track with the active weight of the payload. This is the true inertial load the drivetrain must overcome.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( \tau_{\text{grav, max, 2}} \) | TAR 2 Enablers torque (Nm) | 1,162,009.344009 |
View Help GuidePurpose: Defines the maximum negative gravitational torque (load) created by the enabler train mass that the DLLS must lift. - MAX ( IF ( Rotational Torque Cycle , Rotational Torque Enabler train Absolute Gear System Torque (Nm) ) )
Logic: Scans the data to find the exact moment where the payload's weight leverages the hardest against the lift, establishing our worst-case gravity load.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\tau_{\text{grav, max, 2}} = \tau1.2_{\text{max, seg}}$$ Python Logic:
v["MAX Segment Enabler train Absolute Gear System Torque Rev 1 Cycle 2 (Nm)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 1,162,009.3440
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| ☰ | \( \tau_{\text{total, DLLS, 2}} \) | TAR 2 Total Peak Required DLLS Torque (Nm) | 0.000000 |
View Help GuidePurpose: Calculates the single worst-case instantaneous torque the DLLS must generate to overcome both gravitational and inertial loads. - Net Peak Flywheel Torque (Nm) + Enablers torque TAR 1 (Nm)
Logic: Combines the force needed to fight the machine's inertia with the force needed to lift the payload against gravity. Because of the drivetrain layout, the flywheel takes this massive torque punch, keeping the sensitive electric motors completely shielded.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ▼ TAR 2 Input Torque Requirement | ||||
| ☰ | \( Z_{\text{input}} \) | TAR 2 Top track rotation Gear teeth | 100.000000 |
View Help GuidePurpose: Teeth on top track rotation gear based on gear ration between this gear and the track rotation gear - Adjustable user input
Logic: Sets the baseline size for the driving end of the final gearbox, directly dictating the mechanical leverage we have over the swiveling track.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$Z_{\text{input}} = Z_{\text{input}}$$ Python Logic:
v["TAR 1 Top track rotation Gear teeth"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 100.0000 = 100.0000
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| ☰ | \( GR_{\text{track}} \) | TAR 2 Track rotation gear reduction ratio | 2.000000 |
View Help GuidePurpose: Gear ration between track rotation gear and final output gear of the DLLS system - Track rotation Gear teeth / Top track rotation Gear teeth
Logic: Acts as our primary torque multiplier. As example a 2:1 ratio here means the drive shaft only has to push half as hard to heave the massive track, saving the system from extreme mechanical stress.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$GR_{\text{track}} = Z_{\text{track}}/Z_{\text{input}}$$ Python Logic:
v["TAR 2 Track rotation Gear teeth"]/v["TAR 2 Top track rotation Gear teeth"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 200.0000/100.0000 = 2.0000
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| ☰ | \( C_{\text{input}} \) | TAR 2 Top track rotation gear circumference (m) | 10.000000 |
View Help GuidePurpose: Based on chain link size, determine outer circumeference for cable length dimensions and overall system size - Top track rotation Gear teeth * GMEG Chain link (m)
Logic: Physical dimensioning. Used to guarantee spatial clearances and ensure the connecting chain/mesh perfectly wraps the gear face.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$C_{\text{input}} = Z_{\text{input}} \times L_{\text{link}}$$ Python Logic:
v["TAR 2 Top track rotation Gear teeth"]*v["Chain link (m)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 100.0000*0.1000 = 10.0000
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| ☰ | \( D_{\text{input}} \) | TAR 2 Top track rotation gear diameter (m) | 3.183099 |
View Help GuidePurpose: Dimensional data for design purposes and overall system height - Top track rotation gear circumference (m) / PI ( )
Logic: Ensures the final stage of the drivetrain physically fits inside the gantry housing without rubbing or interference.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$D_{\text{input}} = C_{\text{input}}/\pi$$ Python Logic:
v["TAR 2 Top track rotation gear circumference (m)"]/PI()Live Evaluation: [ROUTE: STATIC/GLOBAL] 10.0000/PI() = 3.1831
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| ☰ | \( R_{\text{input}} \) | TAR 2 Top track rotation gear radius (m) | 1.591549 |
View Help GuidePurpose: Dimensional data for design purposes - Top track rotation gear diameter (m) / 2
Logic: Mathematically crucial for calculating exactly how the twisting force transfers from the DLLS gearbox, across the teeth, and into the track.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$R_{\text{input}} = D_{\text{input}}/2$$ Python Logic:
v["TAR 2 Top track rotation gear diameter (m)"]/2Live Evaluation: [ROUTE: STATIC/GLOBAL] 3.1831/2 = 1.5915
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| ☰ | \( n_{\text{lift, rot}} \) | TAR 2 Rotations per lift | 0.355556 |
View Help GuidePurpose: Top track rotation gear rotation based on gear ratio with track rotation gear - Teeth per track manipulation / Top track rotation Gear teeth
Logic: Because the drive gear is smaller than the track gear, it has to turn faster and more often. This translates the slow, rocking motion of the track into a quantifiable number of full rotations for the drivetrain.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{lift, rot}} = n_{\text{repos}} \times GR_{\text{track}}$$ Python Logic:
v["TAR 2 Rotations per repositioning"]*v["TAR 2 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.1778*2.0000 = 0.3556
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| ☰ | \( n_{\text{input}} \) | TAR 2 Top track rotation gear (RPM) | 21.333333 |
View Help GuidePurpose: Determining output speed of the DLLS final output gear - Rotations per lift * 60
Logic: Connects the slow, heavy swiveling motion of the track back to the higher-speed mechanics of the DLLS drivetrain.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$n_{\text{input}} = n_{\text{lift, rot}} \times 60$$ Python Logic:
v["TAR 2 Rotations per lift"]*60Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.3556*60 = 21.3333
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| ☰ | \( \tau_{\text{DLLS, input, 2}} \) | TAR 2 Top track rotation gear peak torque | 0.000000 |
View Help GuidePurpose: DLLS input torque taking the gear ratio into account - Enablers torque TAR 1 (Nm) / Track rotation gear reduction ratio
Logic: This takes the massive "Final Boss" torque required to lift the track and shrinks it down using our gear ratio. This is the real-world force the flywheel must push through the gearbox.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$\tau_{\text{DLLS, input, 2}} = \text{TAR 2 Total Peak Required DLLS Torque (Nm)}/GR_{\text{track}}$$ Python Logic:
v["TAR 2 Total Peak Required DLLS Torque (Nm)"]/v["TAR 2 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000/2.0000 = 0.0000
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| ☰ | \( I_{\text{reflected, 2}} \) | TAR 2 Top track rotation gear inertia | 0.000000 |
View Help GuidePurpose: Quantifies the total inertia of the track and enabler assembly as 'seen' by the input shaft. This is used to size the final drive components for acceleration and dynamic stability. - System torque TAR 1 (Nm) / Track rotation gear reduction ratio ^ 2
Logic: Pure dynamics. Because the drive shaft spins faster through a gear reduction, the massive inertia of the track "reflects" back exponentially smaller (divided by the ratio squared).
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$I_{\text{reflected, 2}} = \tau_{\text{total, DLLS, 2}}/GR_{\text{track}}$$ Python Logic:
v["TAR 2 Total Peak Required DLLS Torque (Nm)"]/v["TAR 2 Track rotation gear reduction ratio"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000/2.0000 = 0.0000
|
| ▼ TAR 2 Flywheel | ||||
| ☰ | \( W_{\text{inertial}} \) | TAR 2 Work to Rotate the Track (J) | 0.000000 |
View Help GuidePurpose: Defines the net inertial work the flywheel must supply to rotate the track structure. - Net Flywheel Energy (J)
Logic: Isolates the effort required to overcome the track's own bulk and inertia, completely separate from the heavy enablers riding inside it.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
|
| ☰ | \( E_{\text{grav, 2}} \) | TAR 2 Energy Required Gravity Enablers (J) | 935,519.370606 |
View Help GuidePurpose: Defines the total negative gravitational work (energy) required to lift the enabler train mass during the TAR. - DLLS TAR Energy needs
Logic: Pulls data from the Rotational Torque sheet to calculate exactly how much extra work is required to heave the enabler mass upward during the tilt.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$E_{\text{grav, 2}} = \text{Sum Segment Work Done by DLLS Joule Rev 1 Cycle 2 (J)}$$ Python Logic:
v["Sum Segment Work Done by DLLS Joule Rev 1 Cycle 2 (J)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000 = 935,519.3706
|
| ☰ | \( E_{\text{TAR, mech, 2}} \) | TAR 2 Energy Required (J) | 935,519.370606 |
View Help GuidePurpose: Calculates the total minimum mechanical energy the flywheel must deliver for one complete TAR.
Logic: Combines the energy needed to swing the bare track with the energy needed to lift the enablers. This defines the raw physical work the system must perform.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$E_{\text{TAR, mech, 2}} = W_{\text{inertial}}+E_{\text{grav, 2}}$$ Python Logic:
v["TAR 2 Work to Rotate the Track (J)"]+v["TAR 2 Energy Required Gravity Enablers (J)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 0.0000+935,519.3706 = 935,519.3706
|
| ☰ | \( \eta_{\text{flywheel}} \) | TAR 2 Flywheel Inefficiency (%) |
View Help GuidePurpose: Defines the energy loss factor during the flywheel's discharge cycle (e.g., friction, windage). - Adjustable user input
Logic: No mechanical battery is perfect. This accounts for the energy that bleeds off as heat and wind drag while the heavy wheel spins.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( E_{\text{total, store, 2}} \) | TAR 2 Total Energy Required (J) | 0.000000 |
View Help GuidePurpose: Determines the total energy the flywheel must store to account for all mechanical and efficiency losses. - Energy Required TAR 1 (J) + ( Energy Required TAR 1 (J) * Flywheel Inefficiency (%) )
Logic: Adds the inefficiency penalty to the minimum energy requirement. This ensures the flywheel stores enough extra power to overcome its own friction and still successfully complete the lift.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( GR_{\text{flywheel/track}} \) | TAR 2 Gear ratio | 0.000000 |
View Help GuidePurpose: Gear ration between input motor speed and top track rotation output speed - Motor speed (RPM) / Gear ratio
Logic: The flywheel spins incredibly fast to store energy, while the track swivels very slowly. This ratio dictates how the gearbox translates high-speed kinetic energy into low-speed, high-torque lifting power.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( n_{\text{flywheel}} \) | TAR 2 Flywheel Charging Speed (RPM) |
View Help GuidePurpose: (will change this as we need the flywheel faster, bear with me) - Adjustable user input
Logic: Flywheels store energy exponentially based on speed. This sets the baseline spin rate the wheel must reach before initiating the heavy track lift.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( \omega_{\text{start}} \) | TAR 2 Flywheel Radians | 0.000000 |
View Help GuidePurpose: Starting flywheel radians at start of track arc rotation - Flywheel Charging Speed (RPM) * 2* PI ( ) / 60
Logic: Converts standard RPM into radians per second so the system can run strict rotational kinetic energy calculations.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \Delta n_{\%} \) | TAR 2 Allowable Flywheel RPM Drop % |
View Help GuidePurpose: Allowable flywheel slowdown - Adjustable user input
Logic: If the flywheel drains too much speed, the system stalls. This sets a hard floor on how much RPM can be safely bled off to perform the heavy lifting without losing control.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( n_{\text{end}} \) | TAR 2 Final Flywheel RPM | 0.000000 |
View Help GuidePurpose: Finishing flywheel radians at end of track arc rotation - Flywheel RPM * ( 1 - Allowable Flywheel RPM Drop % )
Logic: Calculates the bottom "floor" speed based on the allowed drop percentage. The flywheel must never drop below this RPM during operation.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \omega_{\text{end}} \) | TAR 2 Final Flywheel Radians | 0.000000 |
View Help GuidePurpose: Defines the angular velocity the flywheel must retain after the energy discharge. - Flywheel Radians * ( 1 - Allowable Flywheel RPM Drop % )
Logic: Required to calculate the energy deltathe exact difference in kinetic energy between the top starting speed and the bottom finishing speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{flywheel}} \) | TAR 2 Flywheel Intertia (kg m^2) | 0.000000 |
View Help GuidePurpose: Determination of flywheel inertai required to enable track arc rotation - ( 2 * Total Energy Required Rotation 1 (J) ) / ( ( Flywheel Radians )^2 - ( Final Flywheel Radian )^2 )
Logic: The master sizing calculation. It determines exactly how massive the wheel needs to be to store the required energy and release it without dropping below the target final speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \rho \) | TAR 2 Material Density kg/m3 |
View Help GuidePurpose: Adjustable density for sizing the flywheel - Adjustable user input
Logic: Translates the required inertia into actual, real-world physical dimensions (how thick and wide the metal or carbon must be).
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( D_{\text{outer}} \) | TAR 2 Outer diameter (m) |
View Help GuidePurpose: Adjustable outer size for the flywheel - Adjustable user input
Logic: Constrains the wheel's size based on the physical space available inside the DLLS housing.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( R_{\text{outer}} \) | TAR 2 Outer radius (m) | 0.000000 |
View Help GuidePurpose: Determines outer radius of the flywheel - Outer diameter (m) / 2
Logic: A fundamental geometric variable needed to map the volume and mass distribution of the spinning cylinder.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( D_{\text{inner}} \) | TAR 2 Inner diameter (m) |
View Help GuidePurpose: Adjustable inner size for the flywheel - Adjustable user input
Logic: Efficient flywheels are thick rings, not solid plates. This defines the central void so the mass is concentrated at the outer edge where it stores energy best.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( R_{\text{inner}} \) | TAR 2 Inner radius (m) | 0.000000 |
View Help GuidePurpose: Determines the inner radius of the flywheel - Inner diameter (m) / 1
Logic: Used alongside the outer radius to calculate the exact physical volume of the "doughnut" shape.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( M_{\text{flywheel}} \) | TAR 2 Flywheel weight (kg) | 0.000000 |
View Help GuidePurpose: Determining flywheel weight - ( 2 * Flywheel Intertia (kg m^2) ) / ( ( Outer radius (m) ) ^ 2 + ( Inner radius (m) ) ^ 2 )
Logic: Reverses the inertia formula to determine exactly how heavy the steel or carbon ring must be to act as a properly sized kinetic battery.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( L_{\text{width}} \) | TAR 2 Flywheel width (m) | 0.000000 |
View Help GuidePurpose: Determining flywheel width - Flywheel weight (kg) / ( Material Density kg/m3 * PI ( ) * ( ( Outer radius (m) ) ^ 2 - ( Inner radius (m) ) ^ 2 ) )
Logic: The final architectural output. It tells the machinist exactly how thick to make the ring so it hits the precise mass and inertia targets required by the system.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \tau_{\text{load, shaft}} \) | TAR 2 Load torque (Nm) | 0.000000 |
View Help GuidePurpose: Quantifies the peak torque load placed on the flywheel's output shaft during the TAR. - Top track rotation gear peak torque / Gear ratio
Logic: Takes the massive torque required to lift the track and shrinks it down through the gearbox. This is the actual twisting resistance the spinning flywheel feels as it dumps its energy.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{reflected, load, 2}} \) | TAR 2 Reflected Load Inertia (IRL) | 0.000000 |
View Help GuidePurpose: Quantifies the total inertia of the track assembly as reflected to the flywheel's output shaft. - Top track rotation gear inertia / Gear ratio ^ 2
Logic: Because the flywheel spins much faster than the track rotates, the track's massive inertia is mathematically shrunk through the gearbox (by the square of the gear ratio). This shows exactly what the flywheel is fighting against.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ▼ TAR 2 Motor sizing | ||||
| ☰ | \( t_{\text{charge}} \) | TAR 2 Charging Time (s) | 2.980769 |
View Help GuidePurpose: Time period available to charhe rotation 1 flyhweel between similar track arc rotations - Run time across GMEG track (s) - Lift Time (s)
Logic: The motors can only recharge the flywheel while the track is not actively lifting. This subtracts the lifting time from the total lap time to give us our exact recharging window.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
$$t_{\text{charge}} = t_{\text{run}}$$ Python Logic:
v["Run time across GMEG track (s)"]Live Evaluation: [ROUTE: STATIC/GLOBAL] 2.9808 = 2.9808
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| ☰ | \( P_{\text{avg}} \) | TAR 2 Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Average power per second needed for flyhweel charging over charging time - ( Total Energy Required Rotation 1 (J) / Charging Time (s) ) / 1000
Logic: Takes the total energy the flywheel just spent and spreads the replacement effort over the available charging time, giving us a baseline kilowatt target for the motors.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \eta_{\text{gear, loss}} \) | TAR 2 Gear Inefficiencies (%) |
View Help GuidePurpose: System inefficiencies - Adjustable user input
Logic: Gears get hot and make noisethat is lost energy. This slider adds a realistic penalty to account for the power bleeding out of the transmission.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( P_{\text{proj, mech}} \) | TAR 2 Projected Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Average power needed taking inefficiencies into account - Average Power to Charge (kW) + ( Average Power to Charge (kW) * Gear Inefficiencies (%) )
Logic: Because the gears steal some power, the motor has to push a little harder to ensure the correct net energy actually reaches the flywheel.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \eta_{\text{motor}} \) | TAR 2 Motor efficiency (%) |
View Help GuidePurpose: Defines the motor's baseline efficiency used to calculate power loss during the charging phase. - Adjustable user input
Logic: No electric motor converts 100% of its electricity into pure turning force. This accounts for internal copper and iron heat losses.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( P_{\text{gross, in}} \) | TAR 2 Motor Projected Average Power to Charge (kW) | 0.000000 |
View Help GuidePurpose: Calculates the gross electrical input power required by the motor to account for its inherent efficiency losses. - Projected Average Power to Charge (kW) + ( Projected Average Power to Charge (kW) * ( 1 - Motor efficiency (%) ) )
Logic: This is the bloated total. It factors in all the mechanical and electrical penalties so we know exactly how much raw electricity the system will demand to recharge the flywheel.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \eta_{\text{torque, benefit}} \) | TAR 2 Startup Torque Prevention Benefit (%) |
View Help GuidePurpose: #N/A
Logic: Starting a heavy motor from a dead stop pulls a massive spike of electricity. Because our motors are already spinning and just "topping up" the flywheel, we bypass that spike, saving a significant chunk of power.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( P_{\text{net, in, 2}} \) | TAR 2 New Average Charging Power (kW) | 0.000000 |
View Help GuidePurpose: Defines the final, optimized net electrical power the DLLS motors will draw from the GMEG to charge the flywheel. - Projected Average Power to Charge (kW) - ( Projected Average Power to Charge (kW) * Efficiency improvement (%) )
Logic: Applies the momentum discount. This is the highly optimized, real-world kilowatt draw the system needs to keep the flywheels topped up.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( n_{\text{motor}} \) | TAR 2 Motor speed (RPM) |
View Help GuidePurpose: User inout to control input motor speed - Adjustable user input
Logic: High-efficiency industrial motors like to run at specific, high speeds. This lets us lock in a standard RPM so we can design the gearing around a motor we can actually buy.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( \omega_{\text{motor}} \) | TAR 2 Motor Angular Velocity (rad/s) | 0.000000 |
View Help GuidePurpose: Motor radians for motor torque calculations - Motor speed (RPM) * 2 * PI ( ) / 60
Logic: Converts the standard RPM into radians per second so the simulator can run dynamic torque and inertia checks.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( GR_{\text{motor}} \) | TAR 2 Motor Gear ratio | 0.000000 |
View Help GuidePurpose: Defines the gear ratio between the high-speed motors and the lower-speed flywheel shaft. - Motor speed (RPM) / Flywheel Charging Speed (RPM)
Logic: Calculates the exact gearbox ratio required to match the motor's preferred spinning speed to the flywheel's target charging speed.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{IRL}, f} \) | TAR 2 Flywheel Inertia Reflected to Motor (IRL f) | 0.000000 |
View Help GuidePurpose: Quantifies the rotational inertia of the flywheel as "seen" by the higher-speed motor shaft. - Flywheel Intertia (kg m^2) / Motor Gear ratio ^ 2
Logic: Because the motor spins at a different speed than the flywheel, the gearbox chemically shrinks the flywheel's stubbornness (divided by the ratio squared), making it much easier for the motor to spin it up.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{IRL}, \text{total}} \) | TAR 2 Total Reflected Load Inertia (IRL total) | 0.000000 |
View Help GuidePurpose: Defines the total effective inertia the motor bank must control and accelerate for stable operation. - Reflected Load Inertia (IRL) + Flywheel Inertia Reflected (IRL_f)
Logic: Combines the reflected stubbornness of the massive track with the reflected stubbornness of the flywheel. This is the master inertia load the motors feel on their shafts.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( \tau_{\text{motor, total}} \) | TAR 2 Torque Required from the Motor (Nm) | 0.000000 |
View Help GuidePurpose: The figure 9549 is the unit conversion constant used to directly calculate power, torque, and rotational speed when using the common engineering units of kilowatts (kW), Newton-meters (Nm), and revolutions per minute (RPM). - ( TAR 1 New Average Charging Power (kW) * 9549 ) / Motor speed (RPM)
Logic: A standard industrial engineering conversion (using the 9549 constant) that perfectly translates our required kilowatts and RPMs into raw physical torque.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( N_{\text{motors}} \) | TAR 2 Motors Bank |
View Help GuidePurpose: Defines the number of modular motors sharing the total reflected load and power requirement. - Adjustable user input
Logic: Building one giant, custom 1,000 kW motor is incredibly expensive. Splitting the load across a bank of 4 or 8 smaller, off-the-shelf motors adds redundancy and slashes build costs.
Type: Manual Entry
Render on Grids: None
Mathematical Formula:
$$\text{User Input}$$ Python Logic:
N/ALive Evaluation: N/A (Input Variable)
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| ☰ | \( \tau_{\text{motor, unit}} \) | TAR 2 Motor Torque (Nm) | 0.000000 |
View Help GuidePurpose: Defines the minimum continuous torque rating required for each individual modular motor. - Torque Required (Nm) / Motors Bank
Logic: Divides the total twisting load evenly across the motor bank. This is exactly what we check against the manufacturer's catalog when buying the motors.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( I_{\text{motor, unit}} \) | TAR 2 Motor Inertia (kg.m2) | 0.000000 |
View Help GuidePurpose: Defines the ideal moment of inertia for each motor to maintain dynamic stability and control. - Total Reflected Load Inertia (IRL_total) / Motors Bank
Logic: Ensures the physical load is spread out enough that no single motor gets overwhelmed and stalls under the rotational inertia.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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| ☰ | \( P_{\text{motor, unit}} \) | TAR 2 Motor Power (kW) | 0.000000 |
View Help GuidePurpose: Defines the minimum continuous electrical power rating required for each modular motor. - New Average Charging Power (kW) / Motors Bank
Logic: Divides the total electrical kilowatt load evenly across the bank. The ultimate shopping list metric for the electrical procurement team.
Type: Calculated (Math Output)
Render on Grids: None
Mathematical Formula:
N/A Python Logic:
N/ALive Evaluation: N/A
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