Power density index w per lux m2
power_density_index_w_per_lux_m2
Power Density Index in watts per lux per square metre
Scores if within ±3% of the reference value.
LIVEdataset aec-bench@releasetasks 552models 18disciplines 5last submission … · built …
electricalwith-tool
Road Pdi Calculation
Calculates Power Density Index and specific power density for a road lighting installation from total system power, maintained illuminance, and illuminated area.
with-tool: The model is given an executable Python calculator script.
Standards
How this task is generated
One template produces many comparable benchmark tasks while keeping the scoring contract fixed.
01
Template
The reusable contract shown on this page.
02
Scenario
An archetype and site context are sampled.
03
Difficulty tier
Inputs may be hidden at harder tiers.
04
Task prompt
The model responds with the declared outputs.
Parameters
Inputs the model receives, and the outputs it is scored on.
Inputs
3 inputs
Always given
Included directly in every task prompt.
Total system power
total_system_power_w
Total installed road lighting system power
100 – 200000 WMaintained illuminance
maintained_illuminance_lux
Maintained average illuminance over the lit area
1 – 50 lux
Hidden at higher difficulty
Visible in easier tasks and withheld in one or more harder tiers.
Illuminated area
illuminated_area_m2
Illuminated road or pathway area
Hidden at hard difficulty.
100 – 100000 m2
Scored outputs
2 outputs
Specific power density w per m2
specific_power_density_w_per_m2
Installed power divided by illuminated area
Scores if within ±3% of the reference value.
Difficulty
Each template is sampled at three tiers. Harder tiers may hide inputs, forcing the model to infer them from the scenario description.
easy
All inputs given
Local road with all values visible
medium
All inputs given
Road lighting section selected from local or arterial cases
hard
Some inputs hidden
Arterial road with illuminated area embedded in context
Hidden inputs
- Illuminated area m2illuminated_area_m2
Prompt replacement text
Use the illuminated area implied by {{ archetype.description }}.
Illuminated area m2 restricted to: 12000
Task bundle
The exact instruction and parameter contract used to generate this task, pinned to the published library source.
/workspace
- instruction.md
- road-pdi-calculation_calc.py
Teal lines show Jinja input conditions, not task visibility policy. A line renders only when that input or tool is visible.
1# ABOUTME: Prompt template for road lighting Power Density Index tasks.2# ABOUTME: Presents lighting power, illuminance, and area inputs for calculation.3 4You are a senior road lighting engineer checking energy efficiency.5 6## Given7 8| Parameter | Value | Unit |9|-----------|-------|------|10| Total system power | {{ total_system_power_w }} | W |11| Maintained illuminance | {{ maintained_illuminance_lux }} | lux |12| Illuminated area | {{ illuminated_area_m2 }} | m2 |13 14## Constraints15 16- Specific power density equals total system power divided by illuminated area.17- Power Density Index equals total system power divided by maintained illuminance and illuminated area.18- Use the values exactly as given.19 20## Output Format21 22Include a JSON block with exactly these keys:23 24```json25{26 "power_density_index_w_per_lux_m2": <numeric_value>,27 "specific_power_density_w_per_m2": <numeric_value>28}29```30 31Write your complete solution to `/workspace/output.md`.32 Scenario archetypes
Each generated task is drawn from one of these realistic scenario bands.
Site contexts ground each scenario in a real locale the model can use to infer hidden values.
Local road
local_road
Local road lighting section
local-roadpedestrian-route
Parameter ranges
- total_system_power_w
- 500 – 5000
- maintained_illuminance_lux
- 3 – 15
- illuminated_area_m2
- 300 – 4000
Arterial road
arterial_road
Arterial road lighting section
arterial-roadtransport-corridor
Parameter ranges
- total_system_power_w
- 5000 – 60000
- maintained_illuminance_lux
- 10 – 35
- illuminated_area_m2
- 3000 – 40000
Example task
arterial-road-arterial-road-preview — hard difficulty, some inputs hidden.
Arterial road lighting section. arterial-road. Required outputs: power_density_index_w_per_lux_m2, specific_power_density_w_per_m2
The model sees
Scenario context and visible inputs.
- total_system_power_w
- 5000 to 60000 W
- maintained_illuminance_lux
- 10 to 35 lux
Executable tool: road-pdi-calculation_calc.py
The model must infer
Inputs withheld at this difficulty.
Illuminated area m2
illuminated_area_m2
Stand-in text in the prompt
Use the illuminated area implied by {{ archetype.description }}.
The model must produce
The scored JSON answer schema.
{
"power_density_index_w_per_lux_m2": <number>,
"specific_power_density_w_per_m2": <number>
}- power_density_index_w_per_lux_m2 · scored within ±3%
- specific_power_density_w_per_m2 · scored within ±3%