PPolySim OS
For Engineers · Building Energy Model

Building Energy Model for a nuclear plant

Built for engineers using it for real design work. Go from concept to a running model in the browser, then scale to the cloud when needed. Simulate a nuclear plant live below — adjust the inputs and watch it respond, right in your browser.

1

Thermal Resistance

open full solver →
Composite Wall Heat TransferLive

Controls

Presets

Heat flows through a wall like current through resistors in series. Each layer's thermal resistance is its thickness over its conductivity; adding them gives the total R-value, and the heat flux is the temperature difference divided by it. Insulation, with very low conductivity, dominates the R-value — the steep temperature drop shows where it does its work.

▶ Run in Python

Data Inspector

Total R-value2.71 m²K/W
U-value0.37 W/m²K
Heat flux9.6 W/m²

Governing equation

Reading this result: The insulation layer carries the most thermal resistance, so the temperature falls most steeply across it. A total R-value of 2.71 m²K/W lets 9.6 W/m² flow for this 26°C difference.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

Solar PV SystemLive

Controls

Presets

A solar array's output is its rated power (area × efficiency at 1000 W/m²) multiplied by the peak sun hours your location receives — the equivalent full-intensity hours per day. Tilt matters too: aiming the panels near your latitude maximizes annual yield. Real systems lose a bit more to heat, wiring, and inverters.

▶ Run in Python

Data Inspector

System rating4.0 kW
Daily energy19.2 kWh
Annual energy6996 kWh
Homes powered0.7

Governing equation

Reading this result: A 4.0 kW array in 5-sun-hour sun yields about 19.2 kWh/day — roughly 0.7 average homes.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

Heat Pump COPLive

Controls

Presets

A heat pump does not make heat — it moves it, so it can deliver several kilowatts of warmth per kilowatt of electricity. The coefficient of performance is that ratio, capped by the Carnot limit T_hot/(T_hot − T_cold). The colder it gets outside, the harder the pump works and the lower the COP — but even at freezing it beats a resistance heater several times over.

▶ Run in Python

Data Inspector

COP7.74
Carnot max COP15.5
Heat per kW power7.7 kW
vs resistance heater7.7× better

Governing equation

Reading this result: At 2°C the pump delivers about 7.7 kW of heat per kW of electricity — roughly 7.7× a resistance heater — because it moves heat rather than making it.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

Levelized Cost of EnergyLive

Controls

Presets

LCOE spreads a power project's lifetime cost over every megawatt-hour it produces, letting wildly different technologies be compared fairly. It rewards high capacity factors and cheap capital, and punishes idle plants. The capital-recovery factor discounts future costs to today. It is the number that has made solar and wind the cheapest new power in most of the world.

▶ Run in Python

Data Inspector

LCOE$52/MWh
Per kWh5.2¢
Capacity factor25%

Governing equation

Reading this result: At a 25% capacity factor the plant sits idle most of the time, so its capital is spread over few MWh — that thin denominator is what pushes LCOE up to $52/MWh.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

or unlock everything with Pro →

More with Building Energy Model

Frequently asked questions

Is this good for engineers?
Yes — this version of "Building Energy Model for a nuclear plant" is framed for engineers using it for real design work. Go from concept to a running model in the browser, then scale to the cloud when needed.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.