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

A Weighting

Calculates total unweighted and A-weighted sound pressure level from eight octave-band levels using fixed A-weighting corrections. The template makes the band corrections explicit so the task remains a deterministic logarithmic summation rather than a standards lookup exercise.

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

Standards

IEC 61672

Tags

a-weightingacousticsdeterministiclog-summechanical

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

8 inputs

Always given

Included directly in every task prompt.

8
Show 8 inputs

  • Level 31 5 hz

    level_31_5_hz_db

    31.5 Hz octave-band level

    0 – 140 dB

  • Level 63 hz

    level_63_hz_db

    63 Hz octave-band level

    0 – 140 dB

  • Level 125 hz

    level_125_hz_db

    125 Hz octave-band level

    0 – 140 dB

  • Level 250 hz

    level_250_hz_db

    250 Hz octave-band level

    0 – 140 dB

  • Level 500 hz

    level_500_hz_db

    500 Hz octave-band level

    0 – 140 dB

  • Level 1000 hz

    level_1000_hz_db

    1000 Hz octave-band level

    0 – 140 dB

  • Level 2000 hz

    level_2000_hz_db

    2000 Hz octave-band level

    0 – 140 dB

  • Level 4000 hz

    level_4000_hz_db

    4000 Hz octave-band level

    0 – 140 dB

Scored outputs

3 outputs

Total linear level db

total_linear_level_db

Logarithmic sum of unweighted octave-band levels

Scores if within ±3% of the reference value.

A weighted total dba

a_weighted_total_dba

Logarithmic sum after A-weighting corrections

Scores if within ±3% of the reference value.

A weighting adjustment db

a_weighting_adjustment_db

Difference between A-weighted and unweighted total levels

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 octave bands given for plant-room noise
medium:
All octave bands given across acoustic contexts
hard:
All octave bands given for environmental noise

Task bundle

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

/workspace

  • instruction.md
  • a-weighting_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 engineering acoustics.2 3## Task4 5Calculate the total unweighted and A-weighted sound pressure levels for the octave-band spectrum in {{ site_context }}.6 7## Given8 9| Octave band | Level | Unit | A-weighting correction |10| --- | ---: | --- | ---: |11| 31.5 Hz | {{ level_31_5_hz_db }} | dB | -39.4 dB |12| 63 Hz | {{ level_63_hz_db }} | dB | -26.2 dB |13| 125 Hz | {{ level_125_hz_db }} | dB | -16.1 dB |14| 250 Hz | {{ level_250_hz_db }} | dB | -8.6 dB |15| 500 Hz | {{ level_500_hz_db }} | dB | -3.2 dB |16| 1000 Hz | {{ level_1000_hz_db }} | dB | 0.0 dB |17| 2000 Hz | {{ level_2000_hz_db }} | dB | 1.2 dB |18| 4000 Hz | {{ level_4000_hz_db }} | dB | 1.0 dB |19 20## Constraints21 22- No internet access is available.23- Apply the listed A-weighting correction to each octave-band level before summing.24- Use logarithmic summation: `L_total = 10 log10(sum(10^(L_i/10)))`.25 26{% if tool_available %}27## Available Tool28 29A calculation tool is available at `/workspace/{{ meta.name }}_calc.py`. Run it with:30 31```bash32python3 /workspace/{{ meta.name }}_calc.py --help33```34 35You may use this tool to verify your calculations or compute values directly.36{% endif %}37 38## Required39 40Calculate:41 42- Total unweighted level (`total_linear_level_db`)43- Total A-weighted level (`a_weighted_total_dba`)44- A-weighting adjustment (`a_weighting_adjustment_db`)45 46## Output Format47 48Show 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:49 50```json51{52 "total_linear_level_db": <numeric_value>,53 "a_weighted_total_dba": <numeric_value>,54 "a_weighting_adjustment_db": <numeric_value>55}56```57 58Write your complete solution to `/workspace/output.md`.59

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.

Plant room noise

plant_room_noise

Plant room octave-band noise spectrum

plant-roommechanical-services-noise
Parameter ranges
level_31_5_hz_db
60 – 95
level_63_hz_db
60 – 95
level_125_hz_db
55 – 90
level_250_hz_db
50 – 85
level_500_hz_db
45 – 80
level_1000_hz_db
40 – 80
level_2000_hz_db
35 – 75
level_4000_hz_db
30 – 70

Environmental noise

environmental_noise

Environmental octave-band noise spectrum

environmental-noiseboundary-noise-assessment
Parameter ranges
level_31_5_hz_db
35 – 75
level_63_hz_db
35 – 75
level_125_hz_db
35 – 70
level_250_hz_db
35 – 70
level_500_hz_db
30 – 65
level_1000_hz_db
30 – 65
level_2000_hz_db
25 – 60
level_4000_hz_db
20 – 55

Example task

environmental-noise-environmental-noise-preview — hard difficulty, all inputs given.

Environmental octave-band noise spectrum. environmental-noise. Required outputs: total_linear_level_db, a_weighted_total_dba, a_weighting_adjustment_db

The model sees

Scenario context and visible inputs.

level_31_5_hz_db
35 to 75 dB
level_63_hz_db
35 to 75 dB
level_125_hz_db
35 to 70 dB
level_250_hz_db
35 to 70 dB
level_500_hz_db
30 to 65 dB
level_1000_hz_db
30 to 65 dB
level_2000_hz_db
25 to 60 dB
level_4000_hz_db
20 to 55 dB

Executable tool: a-weighting_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.

{
  "total_linear_level_db": <number>,
  "a_weighted_total_dba": <number>,
  "a_weighting_adjustment_db": <number>
}
  • total_linear_level_db · scored within ±3%
  • a_weighted_total_dba · scored within ±3%
  • a_weighting_adjustment_db · scored within ±3%