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

Escalator Capacity

Calculates escalator passenger capacity from escalator speed, step pitch, step width, and practical loading factor. The reduced method converts speed to steps per second, assigns one or two persons per step from width, then reports theoretical and practical hourly capacity.

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

Standards

AS 1735.10EN 115-1

Tags

capacitydeterministicelectricalescalatorvertical-transportation

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

4 inputs

Always given

Included directly in every task prompt.

3

  • Escalator speed

    escalator_speed_m_s

    Escalator running speed

    0.3 – 0.9 m/s

  • Step width

    step_width_mm

    Nominal step width

    500 – 1200 mm

  • Step pitch

    step_pitch_mm

    Step pitch along travel direction

    300 – 500 mm

Hidden at higher difficulty

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

1

  • Practical loading factor pct

    practical_loading_factor_pct

    Practical passenger loading factor

    Hidden at hard difficulty.

    20 – 100 %

Scored outputs

4 outputs

Steps per second

steps_per_second

Steps passing the comb per second

Scores if within ±3% of the reference value.

Persons per step

persons_per_step

Assumed persons per step from step width

Scores if within ±1% of the reference value.

Theoretical capacity persons per h

theoretical_capacity_persons_per_h

Theoretical passenger capacity

Scores if within ±3% of the reference value.

Practical capacity persons per h

practical_capacity_persons_per_h

Practical passenger capacity

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

Narrow escalator capacity

medium

All inputs given

Narrow or wide escalator

hard

Some inputs hidden

Practical loading factor hidden in site context

Hidden inputs

  • Practical loading factor pctpractical_loading_factor_pct

Prompt replacement text

Use the practical loading factor implied by {{ archetype.description }}.

Practical loading factor pct restricted to: 65

Task bundle

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

/workspace

  • instruction.md
  • escalator-capacity_calc.py

Teal lines show Jinja input conditions, not task visibility policy. A line renders only when that input or tool is visible.

1You are a senior vertical transportation engineer calculating escalator capacity.2 3## Given4 5| Parameter | Value | Unit |6|-----------|-------|------|7| Escalator speed | {{ escalator_speed_m_s }} | m/s |8| Step width | {{ step_width_mm }} | mm |9| Step pitch | {{ step_pitch_mm }} | mm |10{% if practical_loading_factor_pct is defined %}11| Practical loading factor | {{ practical_loading_factor_pct }} | % |12{% endif %}13 14## Constraints15 16- Steps per second equals escalator speed divided by step pitch in metres.17- Use 1 person per step when step width is less than 800 mm, otherwise use 2 persons per step.18- Theoretical hourly capacity equals steps per second times persons per step times 3600.19- Practical capacity equals theoretical capacity times the practical loading factor.20 21## Output Format22 23Include a JSON block with exactly these keys:24 25```json26{27 "steps_per_second": <numeric_value>,28 "persons_per_step": <numeric_value>,29 "theoretical_capacity_persons_per_h": <numeric_value>,30 "practical_capacity_persons_per_h": <numeric_value>31}32```33 34Write your complete solution to `/workspace/output.md`.35

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.

Narrow escalator

narrow_escalator

Narrow escalator with one person per step

retail-escalatorstation-secondary-access
Parameter ranges
escalator_speed_m_s
0.4 – 0.65
step_width_mm
600 – 799
step_pitch_mm
380 – 420
practical_loading_factor_pct
40 – 75

Wide escalator

wide_escalator

Wide escalator with two persons per step

rail-stationairport-terminal
Parameter ranges
escalator_speed_m_s
0.4 – 0.75
step_width_mm
800 – 1100
step_pitch_mm
380 – 420
practical_loading_factor_pct
50 – 85

Example task

rail-station-wide-escalator-preview — hard difficulty, some inputs hidden.

Wide escalator with two persons per step. rail-station. Required outputs: steps_per_second, persons_per_step, theoretical_capacity_persons_per_h, practical_capacity_persons_per_h

The model sees

Scenario context and visible inputs.

escalator_speed_m_s
0.4 to 0.75 m/s
step_width_mm
800 to 1100 mm
step_pitch_mm
380 to 420 mm

Executable tool: escalator-capacity_calc.py

The model must infer

Inputs withheld at this difficulty.

  • Practical loading factor pct

    practical_loading_factor_pct

Stand-in text in the prompt

Use the practical loading factor implied by {{ archetype.description }}.

The model must produce

The scored JSON answer schema.

{
  "steps_per_second": <number>,
  "persons_per_step": <number>,
  "theoretical_capacity_persons_per_h": <number>,
  "practical_capacity_persons_per_h": <number>
}
  • steps_per_second · scored within ±3%
  • persons_per_step · scored within ±1%
  • theoretical_capacity_persons_per_h · scored within ±3%
  • practical_capacity_persons_per_h · scored within ±3%