LIVEdataset aec-bench@releasetasks 552models 18last submission … · built …
electricalwith-tool

Sports Illuminance Uniformity

Calculates reduced sports lighting performance using aggregate luminaire flux, utilisation factor, maintenance factor, and grid extrema. The template reports average horizontal illuminance, U1 and U2 uniformity ratios, and margins against target lighting class values.

with-tool: The model is given an executable Python calculator script.

Standards

AS 2560EN 12193

Tags

deterministicelectricalilluminancelightingsports-lightinguniformity

How this task is generated

One template produces many comparable benchmark tasks while keeping the scoring contract fixed.

  1. 01

    Template

    The reusable contract shown on this page.

  2. 02

    Scenario

    An archetype and site context are sampled.

  3. 03

    Difficulty tier

    Inputs may be hidden at harder tiers.

  4. 04

    Task prompt

    The model responds with the declared outputs.

Parameters

Inputs the model receives, and the outputs it is scored on.

Inputs

10 inputs

Always given

Included directly in every task prompt.

9
Show 9 inputs

  • Field length

    field_length_m

    Sports field length

    10 – 200 m

  • Field width

    field_width_m

    Sports field width

    10 – 120 m

  • Luminaire

    luminaire_count

    Number of luminaires

    4 – 300 count

  • Luminaire luminous flux

    luminaire_luminous_flux_lm

    Luminous flux per luminaire

    10000 – 250000 lm

  • Utilisation factor

    utilisation_factor

    Field utilisation factor

    0.2 – 0.8

  • Maintenance factor

    maintenance_factor

    Lighting maintenance factor

    0.5 – 0.95

  • Minimum illuminance

    minimum_illuminance_lux

    Minimum grid illuminance

    0 – 2000 lux

  • Maximum illuminance

    maximum_illuminance_lux

    Maximum grid illuminance

    1 – 5000 lux

  • Target average illuminance

    target_average_illuminance_lux

    Target average horizontal illuminance

    50 – 2000 lux

Hidden at higher difficulty

Visible in easier tasks and withheld in one or more harder tiers.

1

  • Target uniformity u2

    target_uniformity_u2

    Target U2 uniformity ratio

    Hidden at hard difficulty.

    0.1 – 0.9

Scored outputs

5 outputs

Average horizontal illuminance lux

average_horizontal_illuminance_lux

Average horizontal illuminance

Scores if within ±3% of the reference value.

Uniformity u1 min max

uniformity_u1_min_max

U1 uniformity ratio, minimum divided by maximum

Scores if within ±3% of the reference value.

Uniformity u2 min avg

uniformity_u2_min_avg

U2 uniformity ratio, minimum divided by average

Scores if within ±3% of the reference value.

Average illuminance margin pct

average_illuminance_margin_pct

Average illuminance margin against target

Scores if within ±3% of the reference value.

Uniformity u2 margin pct

uniformity_u2_margin_pct

U2 uniformity margin against target

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

Community sports field with all values visible

medium

All inputs given

Sports lighting case selected from community or stadium fields

hard

Some inputs hidden

Stadium field with target U2 embedded in context

Hidden inputs

  • Target uniformity u2target_uniformity_u2

Prompt replacement text

Use the target U2 uniformity implied by {{ archetype.description }}.

Target uniformity u2 restricted to: 0.7

Task bundle

The exact instruction and parameter contract used to generate this task, pinned to the published library source.

/workspace

  • instruction.md
  • sports-illuminance-uniformity_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 sports field illuminance uniformity tasks.2# ABOUTME: Presents field, luminaire, utilisation, maintenance, and grid values.3 4You are a senior sports lighting engineer checking horizontal illuminance and uniformity.5 6## Given7 8| Parameter | Value | Unit |9|-----------|-------|------|10| Field length | {{ field_length_m }} | m |11| Field width | {{ field_width_m }} | m |12| Luminaire count | {{ luminaire_count }} | count |13| Luminaire luminous flux | {{ luminaire_luminous_flux_lm }} | lm |14| Utilisation factor | {{ utilisation_factor }} | - |15| Maintenance factor | {{ maintenance_factor }} | - |16| Minimum illuminance | {{ minimum_illuminance_lux }} | lux |17| Maximum illuminance | {{ maximum_illuminance_lux }} | lux |18| Target average illuminance | {{ target_average_illuminance_lux }} | lux |19| Target U2 uniformity | {{ target_uniformity_u2 }} | - |20 21## Constraints22 23- Field area equals length times width.24- Average horizontal illuminance equals total luminaire lumens times utilisation factor times maintenance factor divided by field area.25- U1 equals minimum illuminance divided by maximum illuminance.26- U2 equals minimum illuminance divided by average horizontal illuminance.27- Margins are percentage differences from the target average illuminance and target U2.28 29## Output Format30 31Include a JSON block with exactly these keys:32 33```json34{35 "average_horizontal_illuminance_lux": <numeric_value>,36 "uniformity_u1_min_max": <numeric_value>,37 "uniformity_u2_min_avg": <numeric_value>,38 "average_illuminance_margin_pct": <numeric_value>,39 "uniformity_u2_margin_pct": <numeric_value>40}41```42 43Write your complete solution to `/workspace/output.md`.44

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.

Community field

community_field

Community sports field lighting

community-sportfield-lighting
Parameter ranges
field_length_m
40 – 110
field_width_m
25 – 70
luminaire_count
8 – 48
luminaire_luminous_flux_lm
40000 – 160000
utilisation_factor
0.35 – 0.65
maintenance_factor
0.65 – 0.85
minimum_illuminance_lux
50 – 300
maximum_illuminance_lux
100 – 700
target_average_illuminance_lux
100 – 300
target_uniformity_u2
0.4 – 0.7

Stadium field

stadium_field

Stadium field lighting

stadiumfield-lighting
Parameter ranges
field_length_m
90 – 120
field_width_m
50 – 80
luminaire_count
40 – 240
luminaire_luminous_flux_lm
80000 – 220000
utilisation_factor
0.45 – 0.75
maintenance_factor
0.7 – 0.9
minimum_illuminance_lux
300 – 1200
maximum_illuminance_lux
600 – 2500
target_average_illuminance_lux
500 – 1500
target_uniformity_u2
0.5 – 0.8

Example task

stadium-stadium-field-preview — hard difficulty, some inputs hidden.

Stadium field lighting. stadium. Required outputs: average_horizontal_illuminance_lux, uniformity_u1_min_max, uniformity_u2_min_avg, average_illuminance_margin_pct, uniformity_u2_margin_pct

The model sees

Scenario context and visible inputs.

field_length_m
90 to 120 m
field_width_m
50 to 80 m
luminaire_count
40 to 240 count
luminaire_luminous_flux_lm
80000 to 220000 lm
utilisation_factor
0.45 to 0.75 -
maintenance_factor
0.7 to 0.9 -
minimum_illuminance_lux
300 to 1200 lux
maximum_illuminance_lux
600 to 2500 lux
target_average_illuminance_lux
500 to 1500 lux

Executable tool: sports-illuminance-uniformity_calc.py

The model must infer

Inputs withheld at this difficulty.

  • Target uniformity u2

    target_uniformity_u2

Stand-in text in the prompt

Use the target U2 uniformity implied by {{ archetype.description }}.

The model must produce

The scored JSON answer schema.

{
  "average_horizontal_illuminance_lux": <number>,
  "uniformity_u1_min_max": <number>,
  "uniformity_u2_min_avg": <number>,
  "average_illuminance_margin_pct": <number>,
  "uniformity_u2_margin_pct": <number>
}
  • average_horizontal_illuminance_lux · scored within ±3%
  • uniformity_u1_min_max · scored within ±3%
  • uniformity_u2_min_avg · scored within ±3%
  • average_illuminance_margin_pct · scored within ±3%
  • uniformity_u2_margin_pct · scored within ±3%