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

Braking Distance

Calculates train stopping distance under constant deceleration from train mass, initial speed, brake effort, adhesion limit, and track gradient. The template caps braking effort by wheel-rail adhesion and reports net deceleration, stopping distance, and stopping time.

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

Standards

AS 7520.3EN 14531-1

Tags

braking-distancedecelerationdeterministicmechanicalrolling-stock

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

5 inputs

Always given

Included directly in every task prompt.

5

  • Train mass

    train_mass_t

    Train mass

    5 – 2000 t

  • Initial speed

    initial_speed_km_h

    Initial speed before braking

    5 – 200 km/h

  • Brake effort

    brake_effort_kn

    Available braking effort

    1 – 5000 kN

  • Adhesion coefficient

    adhesion_coefficient

    Wheel-rail adhesion coefficient

    0.03 – 0.35

  • Track gradient pct

    track_gradient_pct

    Track gradient, positive for downhill in braking direction

    -5 – 5 %

Scored outputs

4 outputs

Adhesion limited brake effort kn

adhesion_limited_brake_effort_kn

Effective brake effort after adhesion limit

Scores if within ±3% of the reference value.

Net deceleration m s2

net_deceleration_m_s2

Net braking deceleration

Scores if within ±3% of the reference value.

Stopping distance

stopping_distance_m

Stopping distance

Scores if within ±3% of the reference value.

Stopping time s

stopping_time_s

Stopping time

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.

All inputs remain visible at every tier

For this template, difficulty scales through parameter and scenario ranges rather than hidden information.

easy:
All parameters given for light rail braking
medium:
All parameters given across passenger and freight braking cases
hard:
All parameters given for heavy freight braking cases

Task bundle

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

/workspace

  • instruction.md
  • braking-distance_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 mechanical engineer specializing in rolling stock braking systems.2 3## Problem4 5Calculate train stopping distance from initial speed, braking effort, adhesion limit, and track gradient.6 7## Given8 9| Parameter | Value | Unit |10|-----------|-------|------|11| Train mass | {{ train_mass_t }} | t |12| Initial speed | {{ initial_speed_km_h }} | km/h |13| Brake effort | {{ brake_effort_kn }} | kN |14| Adhesion coefficient | {{ adhesion_coefficient }} | - |15| Track gradient | {{ track_gradient_pct }} | % |16 17{% if archetype_description is defined %}18### Braking Context19 20{{ archetype_description }}21{% endif %}22 23{% if tool_available %}24## Available Tool25 26A braking distance calculation tool is available at `/workspace/{{ meta.name }}_calc.py`. Run it with:27 28```bash29python3 /workspace/{{ meta.name }}_calc.py --help30```31 32You may use this tool to verify your calculations or compute values directly.33{% endif %}34 35## Required36 37Calculate the following:38 391. Effective brake effort after adhesion limit (kN)402. Net braking deceleration (m/s2)413. Stopping distance (m)424. Stopping time (s)43 44## Constraints45 46- No internet access is available. Work from engineering knowledge and the provided tool.47- Use g = 9.81 m/s2.48- Convert mass from tonnes to kg and speed from km/h to m/s.49- Use adhesion limit = adhesion coefficient x mass x g.50- Use effective brake effort = min(brake effort, adhesion limit).51- Use gradient acceleration = g x gradient percent / 100, positive downhill.52- Use net deceleration = brake deceleration - gradient acceleration.53- Use stopping distance = initial speed^2 / (2 x net deceleration).54- Use stopping time = initial speed / net deceleration.55 56## Output Format57 58Show your step-by-step working in Markdown. At the end of your solution, include a JSON block with your final answers in exactly this format:59 60```json61{62 "adhesion_limited_brake_effort_kn": <numeric_value>,63 "net_deceleration_m_s2": <numeric_value>,64 "stopping_distance_m": <numeric_value>,65 "stopping_time_s": <numeric_value>66}67```68 69Write your complete solution to `/workspace/output.md`.70

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.

Light rail vehicle

light_rail_vehicle

Light rail vehicle braking on urban alignment

urban-light-raildepot-approach-track
Parameter ranges
train_mass_t
30 – 120
initial_speed_km_h
20 – 80
brake_effort_kn
80 – 600
adhesion_coefficient
0.08 – 0.2
track_gradient_pct
-2 – 4

Heavy freight train

heavy_freight_train

Heavy freight train braking on mainline track

regional-mainlinefreight-terminal-approach
Parameter ranges
train_mass_t
500 – 1800
initial_speed_km_h
40 – 120
brake_effort_kn
800 – 4500
adhesion_coefficient
0.06 – 0.18
track_gradient_pct
-1 – 3

Example task

regional-mainline-heavy-freight-train-preview — hard difficulty, all inputs given.

Heavy freight train braking on mainline track. regional-mainline. Required outputs: adhesion_limited_brake_effort_kn, net_deceleration_m_s2, stopping_distance_m, stopping_time_s

The model sees

Scenario context and visible inputs.

train_mass_t
500 to 1800 t
initial_speed_km_h
40 to 120 km/h
brake_effort_kn
800 to 4500 kN
adhesion_coefficient
0.06 to 0.18
track_gradient_pct
-1 to 3 %

Executable tool: braking-distance_calc.py

The model must infer

Inputs withheld at this difficulty.

Nothing. All inputs are supplied.

The model must produce

The scored JSON answer schema.

{
  "adhesion_limited_brake_effort_kn": <number>,
  "net_deceleration_m_s2": <number>,
  "stopping_distance_m": <number>,
  "stopping_time_s": <number>
}
  • adhesion_limited_brake_effort_kn · scored within ±3%
  • net_deceleration_m_s2 · scored within ±3%
  • stopping_distance_m · scored within ±3%
  • stopping_time_s · scored within ±3%